With the emergence of electric vehicles in the transport sector, concerns over charging infrastructure were raised. The charging infrastructure is mainly used for powering electric vehicles, like how the gas stations work. Recently, alternative options such as solar, wind, etc., were suggested for developing charging stations. In this paper, a solar power charging station is modeled and analyzed. An off-grid system is considered for the EV load, and the simulation is carried out. Results of this study include the power generation potential, supply, and load mismatch relationships. In addition, analysis is extended considering the weather parameter influence on power produced. We believe this study could be useful for planning EV charging stations.
Keywords: Electric vehicles, Charging stations, Solar for EVs, Off-grid charging infrastructure, HOMER tool, PV plant feasibility.

Compact hand fan shaped monopole with microstrip line feed is presented for super wide band applications. Bandwidth (1.8GHz – 31.1GHz) is achieved by diverging the ends of microstrip line feed linearly towards the rectangular patch, a modification in the ground plane and an elongated slit in the ground plane asymmetrically with respect to the strip line. Ansoft HFSS software is used for simulating the monopole and measurements after fabrication are done using Anritsu MS2038C vector network analyzer. The maximum peak gain of the monopole is 6.5dB. The E-plane patterns are approximately directional and H-plane patterns are approximately omni directional. So, the monopole can be used as a super wide band antenna which is eco friendly. The measured S11 (upto 18GHz) are promising with the simulated results.
Keywords: Compact, Monopole, Super wide band, Wide band applications.

Process mining is used to promote the business and production in organization through raw data pre-processing, relevant data usage by feature selections, mining methods, technique, simulations, validation and testing and sustainable manufacturing. Process analysis is vital role to convert prototype into product. Main problem in manufacturing industries are migrating between business and IT perspective and hard to automate with green manufacturing. Also achieving computerized clarifications from high-level production representation and analyzing the implementation of processes from a technical data and a business perception is widely difficult task. Continues evaluation of process mining and performance monitoring in components levels are very essential benchmark in large scale industries. Data mining is one of the recent approaches to improve the performance of the output and business. This research promotes the business and product output with sustainable manufacturing of the car manufacturing industries with the help of machine learning algorithm. It mined the information about motor vehicles and also controls the fuel usage with green engineering by proposed model and the manufactures may select the model of the car based on the customer usage point through clustering concept.
Keywords: Green Manufacturing, Data Mining, Machine Learning, Process Analysis, Classification and WEKA

The research aims to propose a green infrastructure design that allows us the connectivity in the Pantanos de Villa Wildlife Refuge located in the district of Chorrillos - Lima. This proposal aims to improve the connectivity of the ecological area through bike paths and eco-friendly spaces in order to have a greater interest of visitors and tourists, to also contribute to the conservation of this natural area by taking advantage of the appreciation of the landscape since it serves as rest of migratory birds, this area is a natural reserve that allows the nesting and transit of migratory and resident birds. With this proposal, we can improve the landscape of the area and increase the flow of visitors to the Pantanos de Villa Wildlife Refuge.
Keywords: Connectivity, Green design, wetland, bike line, eco friendly

Need for energy is increasing day by day and the use of clean fuel is becoming important. Everyone needs a clean environment and is an important concern. The energy source used conventionally is not nonrenewable. Use and extraction of such energy source increase pollution and also have a damaging effect on the environment. Increasing urbanization, increase the demand and also increase the emission from the conventional fuels which created a demand for an efficient and alternative energy source. The production process of energy should be developed which can cater to the demand for environmentally safe, renewable and sustainable. To meet the growing demand, renewable energy should have cost-competitive and economical. The transportation sector plays a major role in the consumption of crude oil. Which is almost 1/3rd of the total crude oil. Thus transportation is the major contributor to greenhouse gas emission. Demand for fuel is anticipated to rise by 40% because of the transportation sector in a period of 2010-2040. There are a lot of advantages of using biodiesel, but from a sustainability point of view, it was not advisable to produce biodiesel from food crops. Generation of biodiesel from used or waste cooking oil is a good idea as it does not pose any threat to the food crops. This paper gives a review of the use and characteristics of waste cooking oil biodiesel used in a compression ignition engine.
Keywords: Waste cooking oil, Biodiesel, NOx, CO, HC.

Medical diagnosis plays an important role in determining bone fracture disorders. In this research work osteoporosis disease diagnosis investigation can be performed through 11-bit pulsed s-transform coded thermal wave imaging. In addition to that the realization of osteoporosis disease diagnosis is established. The bone fracture, damage percentage, density and area are calculated by this implementation with MATLAB 2015b software. These numerical values are constrained with earlier methods. The final output performance measures such as density variance signal to noise ratio and thermal properties are deliberate. It is known that the approach proposed is outperforming the experimental results and competing with current technology.SNR is 136.4dB, sensitivity 99.95%, predictivity 99.935%, true positive rate 99.91% has been attained.
Keywords: 11-bit barker code, pulsed s-transform, thermal image, osteoporosis.

A larger chuck of microarray data sets are generated with the fast forward by high-throughput technologies. Where analysis of microarray will allow scientists to understand a disease more effectively at the molecular level. Nowadays, the analysis of microarray data has been a vital contribution to the detection and treatment of illness. Other processes of microarray data investigation on microarray data classification. However, the microarray data classification is still challenging due to its high-dimensionality. Lots of techniques are involved in feature selection in place to resolve the high dimensionality for microarray data classification. Search space enhanced Modified Whale Optimization Algorithm (SMWOA) was an effective feature selection method to select the most discriminative features from microarray data. SMWOA is inspired from the hunting behavior of humpback whales and it achieved a better trade-off between local exploitation and global exploration by using a self-adaptive control parameter. However, it may get sure in a part of the Pareto-optimal problem since multiple objectives are used in SMWOA. To overcome this problem and give development an better final subset of features, an Ensemble of Multi-objective Search space enhanced Modified Whale Optimization Algorithmic method (EMSMWOA) is planned in this paper. Initially, an evidential reasoning approach is introduced to choose optimal solution from the Pareto-optimal set by setting various decision solutions based on specificity, sensitivity, Area Under Curve (AUC) and relative distance. It returns a final subset of features for microarray data classification. Furthermore, an ensemble algorithm is proposed to generate a better final feature subset. In the ensemble algorithm, multiple SMWOA is initialized with various population sizes and different maximum iteration numbers. In each SMWOA, an evidential reasoning approach is processed and selects optimal features for data classification. The selected features from multiple SMWOA are combined based on feature-class and feature-feature mutual information. Thus, the EMSMWOA picks up a stable feature subset which improves the accuracy classification. The preferred features are processed in Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naïve Bayes (NB) and Artificial Neural Network (ANN) for tumor detection.
Keywords: Microarray data, Search space enhanced Modified Whale Optimization Algorithm, evidential reasoning approach, ensemble algorithm, Ensemble of Multi-objective Search space enhanced Modified Whale Optimization Algorithm.

Blockchain technology can be used in almost all fields due to its strengths such as symmetric encryption, openness, immutability, and the decentralised data network. Currently, an intelligent medical infrastructure with a blockchain computer system and healthcare processes offers openness, simple and rapid connectivity, protection, efficiency, etc. Healthcare is a development that encompasses manufacturing processes like IoT, IoT, computational engineering, quantum computing, big data, cloud technology, edging, etc. The purpose of this project is to create an intelligent health infrastructure which is illustrated through Blockchain's and healthcare's convergence and interoperability in the sense of basic healthcare. Health procedures used for data accessibility are aimed at validating these processes via methods and algorithms for numerical computation. It's implemented in the network of Ethereum and related programming languages and techniques like solidity, web3.js and Athena etc the blockchain is implemented. In addition, this report prepares a comparative survey of state-of-the-art smart health care programmes focused on blockchain. The whole analysis contains methods, implementations, criteria, performance, future directions etc. A list of predominantly Electronic Health Record (EHR), Telemedicine or Digital Personal Records (DPR) groups, institutions and enterprises is drawn up and contextual research surrounding the use of blockchain technologies for their operations. This research investigates optimisation algorithms for trends in healthcare and increases the efficiency of open blockchain-based technologies for the intelligent healthcare system. In addition, the proposed framework for accelerating confidence building and payment processes prepares intelligent contracts and strategies. In order to test the methodology presented, the thesis envisaged simulation and execution. Effects of the simulation suggest that the appropriate gas value (indicating block size and expenses) is within the established limits for Gas Etherum's network. The device suggested is active since the use of the block is over 80%. The smart contract is less than 20 seconds immediately executed. In a method that demonstrates a competitive health care market, a good number (mean 4 by simulation period) is created. Although simulation and deployment errors of 0.55 to 4.24 percent exist, they do not impact device output overall because simulated and real data differences (acceptance of state-of-the-art) are marginal.
Keywords: 

Attitudes towards safety refer to the mental predisposition of workforce to respond either proactively or reactively on the organisational safety belief, safety objective and safety plan. The safety attitudes not only tend to influence the choice of actions of the workforce but also their immediate responses to the imminent challenges faced by them at workplace. Risk perception refers to the subjective judgement made by the workforce with regard to their work place hazards and severity potentials. The safety attitudes and safety perceptions of workforce about their sustainable work environments form the safety climate at workplace. Safety climate is the measure of the safety culture prevailing at the organisational level. No iota of doubt that the sustainable organisations strive hard to protect its people at workplace and its stakeholders. Striking balance between the safety of people and prfitability perceptions influence the behaviour at workplace. The positive safety attitudes and safety perceptions lead to safe work behaviour. Similarly, the negative attitudes and perceptions may lead to at risk behaviour at workplace which in turn culminates in accidents at workplace. The primary goal of this research is to ascertain the sustainability by measuring the safety attitudes and perceptions prevailing among the workforce involved at construction sites. In addition to the perceptions of workers the data for their personal experience with workplace accidents and primary causes for such accidents also collected. The accident data was compared with previous studies. The current study revealed that lack of concentration, irresponsible actions, reckless behaviour, lack of safety training and poor safety perceptions among the workforce are the primary reasons for the accidents. Improving safety climate at construction job sites is the need of the hour to inculcate the sustainable safety culture
Keywords: Construction, Sustainability, Attitudes, Perceptions, Behaviour, Safety Climate, Environment

In the present world, generation of power is vital to meet the requirements and the growing demands of the end users but at the same time losses in the transmission line, optimization and planning of power systems is also equally indispensable. Therefore, keeping the voltage levels within the appropriate limit is a difficult job. The Crow Search Algorithm (CSA) is used in this paper to define the size of UPFC as well as to enhance the stability of the system. The CSA is a modern, effective solution that relies on the smart behaviour of crows. In the present scenario CSA is used to tackle several complex problems of engineering optimization where it has proven its reliability and flexibility. Moreover this algorithm emphasizes on reducing the transmission line's actual power losses and preserving voltage stability. In this paperCSA will accomplish this by choosing 125 percent, 150 percent, 175 percent and 200 percent over load cases on the IEEE 30 bus systemthe result reveals that CSA surpasses other meta-heuristic algorithms by doing well. Hence CSA turns into a viable technique to recognize UPFC size and position.
Keywords: CSA, UPFC, FACTS, Power system stability, Optimal Location.

This research aims to identify degraded areas due to changes in vegetation cover and land productivity in high Andean terrestrial ecosystems in a prioritized area of the upper watershed of the Huaura River, Department of Lima, which allows its categorization as a starting point to seek the appropriate recovery of these ecosystems, For this purpose, satellite information was used to recognize degraded areas in high Andean terrestrial ecosystems, which are reliable and applicable to our national territory. To identify degraded areas, pixels with a negative trend in the time series with a confidence value of 95% and a P-value lower than 0 were considered. 05, as results were 7 the ecosystems analyzed and a degradation was generated until the moment of 8,916.7 has that corresponds to the 5.01% of the area occupied by these spaces of life; in addition the studied degradation corresponded to the 3.19% of the territory of the high basin of river Huaura.
Keywords: degraded areas, vegetation cover, productivity, ecosystems,Land

[1] Minagri. “Principales cuencas hidrográficas a nivel nacional”, 2015. Available online : https://www.minagri.gob.pe/portal/54-sectoragrario/cuencas-e-hidrografia/372-principales-cuencas-a-nivel-nacional [2] Ibarra J, Román R, Gutierrez K, Gaxiola J, Arias V, Bautista M. Cambio en la cobertura y uso de suelo en el norte de Jalisco, “México: Un análisis del futuro, en un contexto de cambio climático”, Revista Ambiente e Agua, p. 111-128, 2011. [3] Patiño J, León Pelaez J, Montes L:HL. “Propuesta Metodológica para comparar el efecto de diferentes coberturas vegetales en la regulación de cauales en cuencas hidrográficas”, Aplicación en la microcuenca de la quebrada La Murciélago, Antioquía. Avances en Recursos Hidráulicos, 2007. [4] Minam. Mapa Nacional de Ecosistemas del perú. Lima, 2019, Available online: https://sinia.minam.gob.pe/mapas/mapa-nacional-ecosistemasperu [5] Murillo A. “Análisis De Cambios De Cobertura Y Uso Actual De La Tierra Con Imágenes Satelitales Del Distrito De Llacanora, Periodo 2001-2016”,Cajamarca, 2017, Available Online: http://repositorio.unc.edu.pe/handle/UNC/1687 [6] Ledezma J, García M. “Cambio de Cobertura de la Tierra en el área de influencia del proyecto de interconexión entre Pucallpa y Cruzeiro do Sul, Perú”, Pucallpa, 2015, Available Online: https://www.conservationstrategy.org/sites/default/files/fieldfiles/Complement_to_PUCALLPA_final.pdf [7] Vlek P, Le Q, Tamene L. “Assessment of land degradation, its possible causes and threat to food security in Sub-Saharan Africa”, CRC Press, Economics of Land Degradation, pp.57-86, 2010. [8] Yengoh G, Dent D, Olsson L, Tengberg A, Turkey C. “The Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales: a review of the current status, future trends, and practical considerations, Lund University Centre for Sustainability Studies, 2015. Available online: https://www.stapgef.org/sites/default/files/stap/wpcontent/uploads/2015/05/Final-report-The-use-of-NDVI-to-assess-landdegradation-G.-Yengoh-et-al..pdf [9] Hoekstra J, Eklundh L, Seaquist J, Smith B, Ardo J, Olsson L, et al. Confronting a biome crisis: global disparities of habitat loss and protection. In.: Ecol Left, 2005. [10] Ramos, L, Esenarro, D, Rodriguez C. and Lagos J, “Recovery of public spaces for the conservation of green areasin Tablada Lurin”, IOP Conf. Series: Materials Science and Engineering, Vol. 910, 2020. [11] Nájera G, Bojorquez J, Vilchez F. “Cobertura del terreno y uso del suelo de la reserva ecológica sierra de San Juan, Nayarit. En: Reunión De”, Reunión de Investigación y Desarrollo Tecnológico, 2000. [12] Reyes H, Aguilar M, Aguirre J, Trejo I. “Cambios en la cobierta vegetal y uso de suelo en el área del proyecto Pujal-Coy”, In. San Luis Potosí: Investigaciones Geográficas, 2006. [13] Marquez A. “Cambio de uso de suelo y el desarrollo turístico en Bahía de Banderas”, Ciencia UANI. 2008. [14] Gonzáles A, Bojorquez J, Nájera O, García J, Madueño A, Flores F. “Regionalización ecológica de la llanura costera norte de Nayarit, México”, Investigaciones Geográficas, 2009. [15] Kendall M. “Rank Correlation Methods”, 4th edition London: Charles Griffin, 1975. [16] Gilbert R. “Statistical Methods for Environmental Pollution Monitoring”, Van Nostrand Reinhold Company New York,1987, Available online: https://www.osti.gov/servlets/purl/7037501/ [17] Esenarro D, Cabello F, Amaya P, and Vargas C. “Camping Area and Dock with Viewpoint to Promote Sustainable Ecotourist in the Ticcllacocha Lagoon, Tanta-Peru”, International Journal of Environmental Science and Development, Vol. 11, 2020. [18]Available Online: http://www.millenniumassessment.org/documents/document.356.aspx.pdf. [19] Dominati EJ, Patterson M, Mackay A. “A framework for classifying and quantifying the natural capital and ecosystem services of soils”, Ecological Economics, Vol. 69, pp. 1858-1868, 2010. [20] Esenarro D, Escate I, Anco L, Tassara C, and Rodriguez C. “Proposal for an Ecological Research Center for the Recovery and Revaluation of Biodiversity in the Town of Quichas-Lima, Peru”, International Journal of Environmental Science and Development, , Vol. 11, no. 4, pp.212-216, 2020. [21] Inaigem. “Informe de la situación de los glaciales y Ecosistemas de Montaña Perú”, Instituto Nacional de Investigación en Glaciares y Ecosistemas de Montaña, 2017. Available online: https://www.inaigem.gob.pe/wp-content/uploads/2019/04/InterioresInforme-anual-2017.pdf [22] MINAM. “Diversidad biológica”, 6th ed. Lima; 2019. [23] Jara P. ,“Efectos del cambio de la cobertura vegetal y del uso de la tierra sobre la cantidad y calidad de materia orgánica del suelo en ecosistemas alto-andinos de ecuador”, Salamanca: Universidad de Salamanca, 2018. [24] León A. “Reserva de Carbono en bofedales y su relación con la florística y condición del pastizal Lima”, 2016. [25] Cerrón J, Castillo J. BV, Peralvo M, Mathez S. “Relación entre árboles, cobertura y uso de la tierra y servicios hidrológicos en los Andes Tropicales”, Una síntesis del conocimiento. LimaCentro Internacional de Investigación Agroforestal, 2019. [26] Esenarro D, Rodriguez C, Huachaca K, Cachay B & Aylas C. “Classification and Characterization of the Sustainable Wetland Bello Horizonte”, Test Engineering & Management, pp.13453– 13458, 2020.

Existence of Internet of Things (IoT) is due to spread of smart devices throughout world. Enormous amount of data from IoT enabled devices are getting generated in real time. Real time data originates from IoT enabled devices build knowledge database and magnifies the wisdom in the society. Application of IoT is in areas like homes, agriculture, transport, health, security & safety. Green IoT based agriculture makes life easy for farmers. It is being used in controlled environment farming like greenhouse farming, open field farming, livestock breeding, aquaculture& in aquaponics. Use of IoT technology will certainly enrich the quality of human life.
Keywords: Internet of Things; IoT, Smart home, Smart transport, Smart health, Green IoT, Security & safety, Big Data.

Knowledge sharing activities, argued to be able to enhance organisational efficiency and gain competitive advantage for Malaysian power utility firms, are also not effectively induced. How Malaysia's energy sector should be encouraged to use a digital hub to inculcate information sharing practises is still a significant research topic. This paper suggests and explores the techniques included in the flow process, from the brainstorming of knowledge-sharing activity predictors within a Malaysian power utility corporation to the review of raw data to the study of human behaviour in detail. This paper aims to address a pilot study using a few main aspects of the research method, including, sample size determination, questionnaire and survey distribution configuration, estimation of data collection and response rate, data interpretation, and ultimately, outcomes and analysis. For the questionnaires, multiple variables have been chosen as the suggested variables. Via an online portal and hardcopy delivery, the questionnaires were distributed in following reasons. Two samples of questionnaires were developed for the purpose of this paper; one for the consumers and the other for the employees of power utility companies serving as respondents. In order to classify information sharing behaviour patterns of respondents, future research will try to concentrate on various views held on data processing using other statistical instruments and methodsto study the relevant factors suggested in the questionnaire. In order to obtain strong arguments for each attribute defined in the questionnaires, this pilot study requires data analysis using a distinct statistical model that enables a normality test and a chi square test. The findings of this pilot study have shown that a virtual network, including a digital hub, needs to be built to inculcate information-sharing behaviour that could boost human skills, knowledge and competency in the energy sector.
Keywords: Knowledge sharing, digital hub, energy sector, pilot study

The main objective is to design a rectangular microstrip patch antenna integrated with Electromagnetic Bandgap structure to reduce return loss with operating frequency of 5.2GHz. To overcome various limitations of patch antennas such as constrict bandwidth, low gain, excitation of surface waves we proposed the EBG concept. Using this configuration, we obtained 83.88% as patch antenna return loss bandwidth at operating frequency range of 3 to 7 GHz. The EBG structure is designed on FR4 substrate which has a dielectric constant of 4.4 and thickness of 1.6mm. The proposed design has reduced the return loss from -24dB to -36dB by integrating the rectangular microstrip patch antenna with EBG. The Antenna parameters such as return loss, polar chart, field directivity, field gain and radiation efficiencies, 3 D radiation pattern has been analyzed by High frequency structure simulator (HFSS).
Keywords: WiFi, Bandwidth, Return loss, Radiation pattern, EBG, FR4, Frequency.

Defect free material characterization without diminishing its future utility has attained the importance and thus, demands a suitable non-destructive testing method. Active infrared thermography becoming a prominent non-destructive testing method to get the depth resolvable subsurface details by imposing a band of low frequencies over the test objects. This work presents a novel analytical model for 3-D heat diffusion equation using greens function based approach to get the temperature response. Further the obtained thermal response has been processed using recently introduced chirp z based post processing modality to get the detail visualization of subsurface details. Later the proposed mathematical model has been experimentally validated by conducting experiment over a carbon fiber reinforced polymer and the results are compared in terms of detection, signal to noise ratio and full width at half maxima.
Keywords: Active infrared thermography, 3-D heat equation, Greens function, Chirp Z transform and Quadratic frequency modulated thermal wave imaging.

Glass Fibre-Reinforced Polymer (GFRP) rebarsare nowadays used in construction industries because of good corrosion resistance and tensile strength properties they possess. The objective of the current research was to estimate ultimate shear capacity of concrete beams provided with GFRP rebars and conventional steel as reinforcement, using a sustainable method.In this case, shear reinforcement is eliminated to avoid flexural failure. Earlier research results show that ultimate shear capacity of concrete beams reinforced with FRP rebars is lesser than the estimated values using available standards for steel reinforcement. Hence the current study includes the re-evaluation of ultimate shear capacity of simply supported concrete beams reinforced with longitudinal GFRP and conventional steel rebars (omitting shear reinforcing bars) under four-point loading. Fifty-six numerical models of concrete beams have been developed during the simulation process. Analysis of all these beams have been executedbyapplysing Finite Element Analysis (FEA) software. The parameters varied in this numerical study are shear span to effective depth ratio, yield strength of conventional steel, compressive strength of concrete and diameter and arrangement of GFRP rebar in concrete beams. The observations such as ultimate load and load versus concrete and steel and GFRP reinforcement strain behavior are included in this paper. The shear strength of concrete beams under consideration was computed and compared with the estimations as per availablestandards. The estimations based on equations suggested by previous researchers (as available in literature) was also included, for comparison purpose.
Keywords: Finite Element Analysis; Shear strength; Concrete Beams; GFRPrebars

IoT is a network used to interrelate multiple things including mechanical and computer machines. It passes data to a computer interface over the networks without the help of humans or computers. This enables control of various parameters, including electrical, physical and environmental parameters. One of most important parameters to be monitored in IOT is electrical power consumption. There are many power monitoring devices have been proposed in literature but they are lack in adequate security measures and security. The consumed electricity amount is also a parameter to be measured. To do this we need power meter which is much expensive.Thus, in this proposed work we adopt a basic portable low-cost power monitoring system with Wi-Fi capabilities. Different test results are provided to demonstrate the proposed work feasibility also IoT powered power monitoring system for calculating consumed electricity and secure data transmission via Wi-Fi module to the Blynk server (Cloud server). A Blynk application was developed for simulation purpose and hardware implementation. It is an in build app used
Keywords: Energy meter, IOT, Blynkk cloud, Voltage, Current. for a project using multiple widgets and this app this app gives us to create amazing interfaces.

Wind power is a pollution-free, sustainable, indigenous, and renewable source of energy. The principle of wind power is to convert the kinetic energy of the wind into electrical energy using a turbine and a generator. India has 125 billion populations, which is 17.5% of the total world inhabitants. Presently, India is the second most densely inhabited country in the world. Indian economy is the second fastest economy in the world. The population of India is continuously increasing. Therefore, the demand for energy resources is also increasing to fulfil the energy requirement of people. The renewable sources and wind energy is a great source for developing countries, such as India, to fulfil energy demands. Wind energy does not emit any greenhouse gases. It is the most valuable and environmentally friendly energy source. It has not any type of limitation of material for generating energy and is available without any cost. This paper presents the potential, technical growth and policies of various renewable energy sources in the last two decades.
Keywords: Energy Sources, Renewable Energy, Solar Energy, Wind Energy, Wind Policies.

This paper is intended to detect any sort of object, including non-metallic objects buried under the earth, by means of a radar device. In the military, this sort of device can be used to detect explosives hidden under the earth. For this reason, ground penetrating radar (GPR) is used. The technique used to image the subsurface using radar pulses is GPR. This approach uses electromagnetic waves from microwave bands. The object embedded under the surface of the ground is detected within the X-band frequency spectrum (8-12GHz). Radar is intended for a project in which the horn antenna is known to be an antenna that transmits and receives. Depending on the dielectric properties, various types of artifacts such as aluminum sheet, plastic sheet, glass plate, etc. have also been observed. Images are generated using MATLAB using these dispersing matrices. For signal processing, the A-scan and B- scan techniques are used. The aim of this paper is to explore the variations of GPR signals for various objects. Results shows clear discrimination between soil and the object buried.
Keywords: GPR, Microwaves, Soil moisture, X-Band, Radar, MATLAB.

Currently in Malaysia, the price of imported red chilli is cheaper compared to local red chilli. Local farmer needs to be more efficient in the production and one of the ways is to detect the plant diseases. The most significant indicator of a sick plant is by observing the leaf. The leaf will wilt, curled up, spotted yellowish or easily fall to the ground. Different sickness leads to different symptoms on the leaf and occasionally there can be more than one disease affecting the plant. Farmers need to exactly identify the type of disease in order to treat the disease either to use fertilizer, pesticides or simply kill the plant. With so many diseases that can infect a plant, disease detection became harder. One way to overcome this problem is to semi-automate the process using modern technique such as deep learning. Deep learning is a method to extract useful pattern from data with as little human effort involved as possible. In this work, Convolutional Neural Network (CNN) is deployed for image-based red chilli disease detection. The result have shown that 97% accuracy has been achieved in the detection of healthy, crumpled, and yellow leaf.
Keywords: Disease detection, Chilli plant, Convolution Neural Networks.

The topic of this article is the problem of far-range non-active (passive) tracking of a target through a stationary multi-static sonar location. This challenge seems difficult enough. In our case, the observations accessible first are the bearings towards the target with the Doppler change of the signal obtained induced by the motion of the target relative to the sonar. The tracking initiation problem is discussed in the sense of Doppler-Bearing Tracking for a single target that appears/disappears (DBT). At present, in nonlinear contexts, the particle filtering (PF) algorithm has found growing use in many areas. An improved combination of the PF algorithm along with the Extended Kalman Filter (PF-EKF) to fix degeneracy deficiencies is suggested in this research. The position of the underwater-moving-target and target motion parameters such as range, direction and velocity need to be accurately determined in a situation in which autonomous underwater vehicles (AUVs) perform tasks. It finds that by simulating iteration operations in Matlab, the proposed algorithm provides greater accuracy in convergence times.
Keywords: 

Plant disease detection prevails as one of the crucial issues in agricultural sector despite colossal research works performed to eliminate this problem encountered by farmers all over the world. Machine Learning, a subfield of artificial intelligence practice, allows computers to use a massive amount of data to train and teach themselves to make predictions, as opposed to a static system. With the help of big data, industrial 4.0 revolution, and high-performance Graphical Processing Unit (GPU), the issues as mentioned earlier has become an ideal case to solve. This paper reviews type of common diseases appeared in tomato plant, technology evolution employed to detect the diseases of tomato plant and the core concept of its detection using machine learning, the concise comparison of each of the existing architecture for image-based classification in determining whether the plants is healthy or affected by diseases, the vital analysis for different methods, and the key challenges faced by the endless problem faced by farmers.
Keywords: Tomato disease detection, Machine Learning, Deep Learning, Neural Network, Artificial Intelligence, Agriculture Technology.

[1]Available online : http://www.fao.org/3/a-i6583e.pdf. [2]JA Lucas. “Plant Pathology and Plant Pathogens”, 4th Edition Blackwell, 2020. [3]T Kozai, “LED lighting for Urban Agriculture”, pp.3-18, 2016. [4]T Kozai, G Niu and M Takagaki, “Plant factory: an indoor vertical farming system for efficient quality food production”, Academic Press, Elsevier, 2019. [5]RG Taketani, MD Lanconi, VN Kavamura, A Durrer, FD Andreote and IS Melo. “Dry season constrains bacterial phylogenetic diversity in a semi-arid rhizosphere system”, Microbial Ecology, Vol. 73, pp. 153-161, 2017. [6]KS Karthika, I Rashmi and MS Parvathi.“Biological Functions, Uptake and Transport of Essential Nutrients in Relation to Plant Growth”, Plant Nutrients and Abiotic Stress Tolerance, pp. 1-49, 2018. [7]G Polder, PM Blok, H De Villiers, JM Van de Wolf and Kamp.“Potato Virus Y detection in seed potatoes using deep learning on hyperspectral images”, Frontiers in Plant Science, Vol. 10, 2019. [8]F Martinelli, R Scalenghe, S Davino, S Panno, G Scuderi, P Ruisi, P Villa, D Stroppian, M Boschetti, LR Goulart, CE Davis and AM Dandekar. “Advanced methods of plant disease detection- A review”, Agronomy for Sustainable Development, pp. 1-25, 2014. [9]Available online: http://jmc.stanford.edu/artificial-intelligence/what-is-ai/index.html. [10]K Kersting.“Machine Learning and Artificial Intelligence: Two Fellow Travelers on the Quest for Intelligent Behaviour in Machines”, Frontiers in Big Data, pp. 1-6, 2018. [11]M Ray, A. Ray, S Dash, A. Mishra, KG Achary, S Nayak and S Singh.“Fungal disease detection in plants: Traditional assays, novel diagnostic techniques and biosensors”, Biosensors and Bioelectronics, Vol. 87, pp.708-723, 2017. [12]A Camargo and JS Smith.“Image pattern classification for the identification of disease causing agents in plants”, Computers and Electronics in Agriculture, Vol. 66, pp. 121-125, 2009. [13]M Neumann, L Hallau, B Klatt, K Kersting and C Bauckhage. “Erosion Band Features for Cell Phone Image Based Plant Disease Classification”, 22nd International Conference on Pattern Recognition, pp. 3315-3320, 2014. [14]CP Wijekoon, PH Goodwin and T Hsiang.“Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software, Journal of Microbiological Methods, Vol. 74, pp. 94-101, 2008. [15]E Bauriegel, A. Giebel, M Geyer, U Schmidt and WB Herppich. “Early detection of Fusarium infection in wheat using hyper-spectral imaging”, Computers and Electronics in Agriculture, Vol. 75, pp. 304-312, 2008 [16]C Bravo, D Moshou, J West, A McCartney and H Ramon. “Early Disease Detection in Wheat Fields using Spectral Reflectance, Biosystems Engineering, Vol. 84, pp. 137-145, 2003. [17]W Huang, DW Lamb, Z Niu, Y Zhang, L Liu and J Wang.“Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging”, Precision Agriculture, Vol.8, pp. 187-197, 2007. [18]D Moshou, C Bravo, J West, S Wahlen, A McCartney and H Ramon.“Detection of ‘yellow rust’ in wheat using reflectance measurements and neural networks”, Computers and Electronics in Agriculture, Vol. 44, pp. 173-188, 2004. [19]X Wang, M Zhang, J Zhu and S Geng. “Spectral prediction of Phytophthorainfestans infection on tomatoes using artificial neural network (ANN)”, International Journal of Remote Sensing, Vol. 29, pp. 1693-1706, 2008. [20]S Bergsträsser, D Fanourakis, S Schmittgen, MP Cendrero-Mateo, M Jansen, H Scharr and U Rascher.“HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance- transmittance imaging”, Plant Methods, Vol. 11, 2015. [21]AK Mahlein, U Steiner, C Hillnhütter, HW Dehne and EC Oerke.“Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases” Plant Methods, Vol. 8, 2012. [22]K Steddom, MW Bredehoeft, M Khan and CM Rush.“Comparison of Visual and Multispectral Radiometric Disease Evaluations of Cercospora Leaf Spot of Sugar Beet”, Plant Disease, Vol. 89, pp. 153-158, 2007. [23]C Hillnhütter, AK Mahlein, RA Sikora and EC Oerke, “Remote sensing to detect plant stress induced by Heteroderaschachtii and Rhizoctoniasolani in sugar beet fields”, Field Crops Research, Vol. 122, pp. 70-77, 2011. [24]R Laudien, G Bareth, R Doluschitz. “Analysis of hyperspectral field data for detection of sugar beet diseases”, EFITA Conference, pp. 375-381, 2003. [25]S Delalieux, J Aardt, W Keulemans, E Schrevens and P. Coppin.“Detection of biotic stress (Venturiainaequalis) in apple trees using hyperspectral data: Non-parametric statistical approaches and physiological implications”, European Journal of Agronomy, Vol. 27, pp. 130-143, 2007. [26]M Wahabzada, A. Mahlein, C Bauckhage, U Steiner, E-C Oerke and K Kersting. “Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants”, Scientific Reports, Vol. 6, 2016. [27]M Kuska, M Wahabzada, M Leucker, H-W Dehne, K Kersting, E-C Oerke, U Steiner and A-K Mahlein.“Hyperspectralphenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions”, Plant Methods, Vol. 11, 2015. [28]A. Apan, A. Held, S Phinn and J Markley. “Detecting sugarcane ‘orange rust’ disease using EO-1 Hyperion hyperspectral imagery”, International Journal of Remote Sensing, Vol. 22, pp.489-498, 2004. [29]L Chaerle, D Hagenbeek, E De Bruyne, R Valcke and D. Van Der Straeten. “Thermal and Chlorophyll-Fluorescence Imaging Distinguish Plant-Pathogen Interactions at an Early Stage”, Plant and Cell Physiology, Vol. 45, pp. 887-896, 2004. [30]E-C Oerke, U Steiner, H-W Dehne and M Lindenthal. “Thermal imaging of cucumber leaves affected by downy mildew and environmental conditions”, Journal of Experimental Botany, Vol. 57, pp. 2121-2132, 2006. [31]CA Berdugo, R Zito, S Paulus and AK Mahlein.“Fusion of sensor data for the detection and differentiation of plant diseases in cucumber”, Plant Pathalogy, Vol. 63, pp. 1344-1356, 2014. [32]E-C Oerke, P Fröhling and U Steiner.“Thermographic assessment of scab disease on apple leaves”, Precision Agriculture, Vol. 13, pp. 600-715, 2011.[33]SG Caro,” Infection and spread of Peronosporasparsa on Rosa sp. (Berk.) - a microscopic and a thermographic approach", Dissertation, University of Bonn, Lincoln University Digital Thesis, Germany,2014. [34]K Bürling, M Hunsche and G Noga.“Use of blue–green and chlorophyll fluorescence measurements for differentiation between nitrogen deficiency and pathogen infection in winter wheat”, Journal of Plant Physiology, Vol. 168, pp. 1641-1648, 2011. [35]C Römer, K Bürling, M Hunsche, T Rump, G Noga and L Plümer. “Robust fitting of fluorescence spectra for pre-symptomatic wheat leaf rust detection with Support Vector Machines”, Computers and Electronics in Agriculture, Vol. 79, pp. 180-188, 2011. [36]S Konanz, L Kocsányi and C Buschmann.“Advanced Multi-Color Fluorescence Imaging System for Detection of Biotic and Abiotic Stresses in Leaves”, Agriculture, Vol. 4, pp. 79-95, 2014. [37]L Chaerle, D Hagenbeek, E De Bruyne and D Van Der Straeten.“Chlorophyll fluorescence imaging for disease-resistance screening of sugar beet”, Plant Cell, Tissue and Organ Culture, Vol. 91, pp. 97-106, 2007. [38]CR Muniz, FCO Freire, FMP Viana, JE Cardoso, CAF Sousa, MIF Guedes, R van der Schoor and H Jalink. “cashew seedlings during interactions with the fungus Lasiodiplodiatheobromae using chlorophyll fluorescence imaging, Photosynthetica, Vol. 52, pp.529-537, 2014. [39]M Patil, G Langar, P Jain and N Panchal.“Tomato leaf disease detection using artificial intelligence and machine learning”, International Journal of Advance Scientific Research and Engineering Trends, Vol. 5, 2020. [40]GK Sandhu and R Kaur.“Plant disease detection technique: A review”, International Conference on Automation, Computational and Technology Management (ICACTM), pp. 34-38, 2009. [41]U Khan and AOberoi. “Plant disease detection technique: A review”, International Journal of Computer Science and Mobile Computing, Vol.8, pp. 59-68, 2019. [42]AK Dey, M Sharma and MR Meshram.“Image processing based leaf rot disease, detection of betel vine (piper betleL.)”, Procedia Computer Science, Vol. 85, pp. 748-754, 2016. [43]M Sardogan, ATuncer and Y Ozen. “Plant leaf disease detection and classification based on CNN with LVQ algorithm”, 3rd International Conference on Computer Science and Engineering (UBMK), Sarajevo, pp. 382-385, 2018. [44]K Balaji and K Kavanya. “Medical image analysis with Deep Neural Networks”, Deep Learning and Parallel Computing Environment for Bioengineering Systems, Academic Press, pp. 75-97, 2019. [45]P Gavali and S Banu. “Deep Convolutional Neural Network for image classification on CUDA platform”, Deep Learning and Parallel Computing Environment for Bioengineering Systems, Academic Press, pp. 99-122, 2019. [46]V Tümen, ÖF Söylemezand and B Ergen.“Facial emotion recognition on a dataset using convolutional neural network”, International Artificial Intelligence and Data Processing Symposium (IDAP), pp. 1-5, 2017. [47]H Durmuş, EO Güneş and M Kırcı. “Disease detection on the leaves of the tomato plants by using deep learning”, IEEE 6th International Conference on Agro-Geoinformatics, pp. 1-5, 2017. [48]RG de Luna, EP Dadios and AA Bandala.“Automated Image Capturing System for Deep Learning-based Tomato Plant Leaf Disease Detection and Recognition”, IEEE Region 10 Conference, pp. 1414-1419, 2018. [49]J Shijie, J Peiyi, H Siping and S Haibo.“Automatic detection of tomato diseases and pests based on leaf images”, Chinese Automation Congress (CAC), pp. 2537-2510, 2017. [50]SP Mohanty, DP Hughes and M Salathé.“Using Deep Learning for image-based plant disease detection”, Frontiers in Plant Science, 2016. [51]P Tm, A. Pranathi, K SaiAshritha, NB Chittaragi and SG Koolagudi.“Tomato Leaf Disease Detection Using Convolutional Neural Networks”, Eleventh International Conference on Contemporary Computing (ICC), pp. 1-5, 2018. [52]A Fuentes, S Yoon, SC Kim and DS Park.“A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition”, Sensors in Agriculture, Vol. 17, 2017. [53]H Sabrol and S Kumar. “Plant Leaf Disease Detection Using Adaptive Neuro-Fuzzy Classification”, Advances in Computer Vision, pp. 434-443,2019.

In general, the operation of Vocoders is based on modeling of speech waveform’s segment (or frame) on the order of 20 milliseconds. The parameters of speech model are determined, quantized, coded, and transmitted through the communication channel. To synthesize speech, the transmitted values are decoded, reconstructed, and used at the receiver. It is in this context, we provide a basic feasible solution by name Intelligent Pause Detection Protocol (IPDP) which would ensure performance enhancement of vocoders used in mobile communications. In this paper, we make an attempt to analyze IPDP protocol enabled Vocoders with the other commonly used Vocoders using Wire Shark simulator.
Keywords: Vocoders, Wire shark, Protocols, Communication channel.

[1] J. P. Campbell, Jr., “Speaker Recognition: A Tutorial”, Proceedings of The IEEE, Vol.85, no.9, pp.1437-1462, 1997. [2] Koji Kitayama, MasatakaGoto, Katunobu Itou and Tetsunori Kobayashi, “Speech Starter: Noise-Robust Endpoint Detection by Using Filled Pauses”, 8th European Conference on Speech Communication and Technology, Eurospeech,pp. 1237-1240, 2003. [3] S. E. Bou-Ghazale and K. Assaleh, “A robust endpoint detection of speech for noisy environments with application to automatic speech recognition”,IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP, Vol. 4, 2002, pp. 3808–3811,2002. [4] A. Martin, D. Charlet, and L. Mauuary, “Robust speech / non-speech detection using LDA applied to MFCC”,IEEE International Conference on Acoustics, Speech, and Signal Processing,2001. [5] K. Ishizaka and J.L Flanagan, “Synthesis of voiced Sounds from a Two-Mass Model of the Vocal Chords”, Bell System Technical J., Vol. 50, no.6,pp. 1233-1268, 1972. [6] Atal, B. Rabiner, L., “A pattern recognition approach to voiced-unvoiced-silence classification with applications to speech recognition”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 24 , no. 3 , pp.201 – 212, 1976. [7] D. G. Childers, M. Hand, J. M. Larar, “ Silent and Voiced/Unvoied/ Mixed Excitation(Four-Way), Classification of Speech”, IEEE Transaction on ASSP,, Speech, and Signal Processing, Vol. 37, no.11, pp. 1771-1774, 1989. [8] Mark Greenwood and Andrew KInghorn, “SUVing: Automatic Silence/Unvoiced/Voiced Classification of Speech'', Presented at the university of Sheffield. [9] Richard. O. Duda, Peter E. Hart, David G. Strok, “Pattern Classification”, A Wiley-interscience publication, John Wiley & Sons, Inc, Second Edition, 2001. [10]Sarma, V.; Venugopal, D., “Studies on pattern recognition approach to voiced-unvoiced-silence classification”, Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '78. , Vol. 3, pp. 1 – 4, 1978. [11] L. R. Rabiner and R.W. Schafer, “Digital Processing of Speech Signals”, First Edition, Chapter- 4, Pearson Education, Prentice-Hall. [12]Available online: http://cslu.ece.ogi.edu/nsel/data/SpEAR_technic al.html. [13]J. L. Flanagan, “Speech Analysis, Synthesis, and Perception”, 2nd ed., Springer-Verlag, New York, 1972. [14]L. R. Rabiner and B. H. Juang, “Fundamentals of speech recognition,” 1st Indian Reprint, Pearson Education., [15]R Chinna Rao, Elizabath Rani, S Srinivasa Rao, “Basic Frame work of Vocoders for Speech Processing”, Soft Computing and Signal Processing,2019.

Nonlinear Kalman Filtering is a well-established field in applied probability and control systems which plays an important role in many practical applications such as target tracking. In this project, nonlinear Kalman filtering algorithm named Extended Kalman Filter (EKF) is presented to estimate the location of the target using bearing and Doppler-frequency measurements. The tracking using bearing and doppler-frequency measurements are popularly known as Doppler-Bearing tracking. Here the measurements, that is, bearings and doppler-frequency, are considered to be corrupted with Gaussian noise. Target Motion Analysis (TMA) using bearing together with doppler-frequency measurements are explored. In this project, TMA is carried out using and EKF. Range, course and speed parameters are proposed in the EKF state vector to obtain the convergence of solution fast. Finally, the results of one scenario in Monte-Carlo simulation are presented.
Keywords: 

[1]L. Badriasl and K. Dogancay. “Three-dimensional target motion analysis using azimuth/elevation angles”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 50, no. 4, pp. 3178-3194, 2014. [2]Qihu Li., “Digital Sonar Design in Underwater Acoustics”, Springer Science and Business Media LLC, 2012. [3]G. Isbitiren and O. B. Akan, “Three-Dimensional Underwater Target Tracking With Acoustic Sensor Networks”, IEEE Transactions on Vehicular Technology, Vol. 60, no. 8, pp. 3897-3906, 2011. [4]Dan Simon. “Optimal State Estimation: Kalman, H and nonlinear Approximations”, Wiley, 2006. [5]MahendraMallick, Vikram Krishnamurthy and Ba-NguVo.“Integrated Tracking, Classification, and Sensor Management”, Wiley, 2013. [6]Jahan K., KoteswaraRao S., “Extended Kalman filter for bearings-only tracking”, International Journal of Engineering and Advanced Technology, Vol. 8, no. 6, pp. 637-640, 2019. [7]H. Chen, C. Han and F. Lian. “Three-dimensional target motion analysis using angle-only measurements”, IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC), pp. 1-6, 2013. [8]Jahan, Kausar; Sanagapallea, Koteswara R., “Fusion of Angle Measurements from Hull Mounted and Towed Array Sensors”, Department of Electronic and Communication Engineering, Vol. 11, No. 9, 2020. [9]Buch, J. R., Kakad, Y. P., &Amengonu, Y. H., “Performance Comparison of Extended Kalman Filter and Unscented Kalman Filter for the Control Moment Gyroscope Inverted Pendulum”, 25th International Conference on Systems Engineering (ICSEng), 2017. [10]IenkaranArasaratnam and Simon Haykin, “Cubature Kalman Filters”, IEEE Transactions on Automatic Control, Vol. 54, No. 6, pp.1254-1269, 2009. [11]BabuSreeHarsha P., VenkataRatnam D., “Fuzzy logic-based adaptive extended kalman filter algorithm for GNSS receiver”, Defence Science Journal, Vol. 68, no. 6, pp. 560- 565, 2018. [12]BrankoRistic, SanjeevArulampalam and Neil Gordon, “Beyond the Kalman Filter: Particle Filters for Tracking Applications”, 7 Artech House, 2004. [13]JunhaiLuo, Yanping Chen, Zhiyan Wang, Man Wu, Yang Yang. “Improved Cubature KalmanFilter for Target Tracking in Underwater Wireless Sensor Networks”, IEEE 23rd International Conference on Information Fusion, 2020. [14]Xu, J., Xu, M., & Zhou, X., “The bearing only target tracking of UUV based on cubature Kalman Filter with noise estimator”, 36th Chinese Control Conference (CCC), 2017. [15]SyamantakDatta Guptaet.al, “Comparison of Angle-only Filtering Algorithms in 3D Using EKF, UKF, PF, PFF, and Ensemble KF”, 18th International Conference on Information Fusion, pp. 6-9, 2015. [16]Omkar Lakshmi Jagan, B., KoteswaraRao, S., “Underwater surveillance in non-Gaussian noisy environment”, Measurement and Control, Vol. 53, no. 1-2, pp. 250-261, 2020.

The purpose of this project is to decrease the chance of the large fire hazard from occurring due to unreliable existing fire alarm systems. Existing fire alarms have proven to be unreliable at times due to faulty or flawed systems. Our main purpose is to improve the existing fire alarms with new technology such as MICA2 device which contains several sensor nodes that are capable of reading several variables that can be processed to find the point which fire is present which will analyze the image to read the pattern of the fire to further improve the capability of detecting fire. With this device, a new and improved system can be produced. The new system will be an Internet-of-Things-based system (or IOT-based) that will allow firefighters or any person with authority to determine the presence of fire by looking at a warning display. The warning can be viewed on any device that is capable of connecting to the internet.
Keywords: Internet of thing, Sensor Network, MICA2 Sensor,PostgreSQL.

[1]S Vijayalakshmi and S Muruganand.“Internet of Things technology for fire monitoring system”, International Research Journal of Engineering and Technology (IRJET),Vol: 04, no. 06, 2017. [2]S Tiwari and S Bandopadhaya.“IoT Based Fire Alarm and Monitoring System”,3rd International Conference on Trends in Electronics and Informatics ,2019. [3]S Sundar, P Vinothkumar, D Murthy and Kumar. Engineering Unit Conversion for Process Parameters”,Indian journal of science and technology,Vol. 9, no.11, pp.1-4, 2016. [4]K Sujatha, NP Bhavani, TK Reddy and KR Kumar.“Internet of Things for Flame Monitoring Power Station Boilers”,IEEE Trends in Industrial Measurement and Automation (TIMA),2017. [5]K Sujatha, NP Bhavani and R Ponmagal.“Impact of NOx emissions on Climate and Monitoring using Smart Sensor Technology”,International Conference on Communication and Signal Processing (ICCSP), 2017. [6]B Stojkoska and D Davcev.“Web Interface for Habitat Monitoring using Wireless Sensor Network”,Wireless and Mobile Communications, International Conference,2009. [7]BR Stojkoska. “Data Compression for Energy Efficient IoT Solutions”,Telfor,2017. [8]W Si, M Hashemi, L Xin, D Starobinski and A Trachtenberg. TeaCP: a Toolkit for Evaluation and Analysis of Collection Protocols in Wireless Sensor Networks”, IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS 2013),2013. [9]C Seiber, D Nowlin, B Laldowski and ME Tolentino.“Tracking Hazardous Aerial Plumes using IoT Enabled Drone Swarms”,IEEE 4th World Forum on Internet of Things (WF-IoT), 2018. [10]F Saeed, A Paul, A Rehman, WH Hong and H Seo. “IoT-Based Intelligent Modeling of Smart Home Environment for Fire Prevention and Safety”,J. Sens. Actuator Netw.,Vol. 7, no.1, 2018. [11]NF Raun. Smart Environment using Internet of things(IOTS). India. [12]K Padmanabh, L Malhotra, AM Reddy V, A Kumar, S Kumar V and S Paul. “MOJO: A Middleware that Converts Sensor Nodes into Java Objects”, Computer Communications and Networks (ICCCN),IEEE Xplore, 2010. [13]WO Oduola, N Okafor, O Omotere and L Qian.“Experimental Study of Hierarchical Software Defined Radio Controlled Wireless Sensor Network”, IEEE Trends in Industrial Measurement and Automation (TIMA,2017. [14]K Muhammad, S Khan, M Elhoseny, SH Ahmed and SW Baik.“Efficient Fire Detection for Uncertain Surveillance Environment”, IEEE Transactions on Industrial Informatics, Vol. 15, no. 5,pp. 3113 - 3122 2019. [15]A Moon, A Dar, UI Khan and N Shah. Test Bed For Real-Time Monitoring of Water Quality Using Wireless Sensor Networks, [16]J Lim and K Wong. Wireless Sensor Networks: ThePotential Use of Received Signal Strength in Power Transmission Control for the MICA2, Vol.01, no.2,pp.9-13, Engineering e-Transaction, University of Malaya 2006. [17]WL Lee, ADatta and R Cardell-Oliver. Network Management in Wireless Sensor NetworksConference: to appear in Handbook on Mobile Ad Hoc and Pervasive Communications, American Scientific Publishers, 2006. [18]H Larthani, AZrelli and T Ezzedine. On The Detection of Disasters: Optical Sensors and IoT Technologies”,Conference: International Conference on Internet of Things, Embedded Systems and Communications (IINTEC),2018. [19]Available online: http://users.cis.fiu.edu/~iyengar/publication/C-(2009)%20-%20Application%20of%20Sensor%20Networks%20for%20Monitoring%20of%20Rice%20Plants%20A%20Case%20Study%20-%20%5BSymposium%20on%20Innovations%5D.pdf.pdf [20]RK Kodali and S Yerroju.“IoT Based Smart Emergency Response System for Fire Hazards”,IEEE 3rd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), 2017. [21]M Khadem, G Stamatescu and V Sgarciu. Wireless Measurement Node for Dust Sensor Integration”,Sensorcomm, The Sixth International Conference on Sensor Technologies and Applications, 2012. [22]Kaliski. “TinyOS Laboratory Development”, Thesis, California Polytechnic State University,Sensor networks, 2005. [23]AImteaj, T Rahman, MK Hossain, MS Alam and S Ahmad. “An IoT based Fire Alarming and Authentication System for Workhouse using Raspberry Pi 3”,IEEE International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017. [24]V Gokul and S Tadepalli.“Implementation of Smart Infrastructure and NonInvasive Wearable for Real Time Tracking and Early Identification of Diseases in Cattle Farming using IoT”,IEEE International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2017. [25]S Duangsuwan, ATakarn and P Jamjareegulgarn. “A Development on Air Pollution Detection Sensors based on NB-IoT Network for Smart Cities”,IEEE 18th International Symposium on Communications and Information Technologies (ISCIT),2018.

Data clustering is a significant technique used in distinct fields for measuring the similarity present among the data which is useful in day to day life applications.Clustering is theprocess where the dataset will be divided into number of groups of same data points. However, in few instances it would undergo the problem of overlapping because many features may not be ready to capture necessary information in order to separate clusters. In order to overcome the limitations, theEnhanced K-Means Clustering (EKMC) method is proposed for data clustering.To perform classification on highly imbalanced datasets, the proposedEKMC algorithm is used by computingthe distance metrics between the two different data points. Therefore, in the proposed method, an improvised KMC known as an Enhanced KMC overcomes the problem occurred in KMC for disease detection. The KMC has the specialty of producing acceptable results however, it fails to provide good results as the data consists of outliers the spread density data points across the space is different. This differences shows reduction in CPU and memory requirements. K-means clustering algorithm can be significantly improved by using a better initialization technique such as Davies–Bouldin Index (DBI). DBI computes the ratio between the cluster distances and the between cluster distances thereby calculates average of overall clusters. The EKMC performs various iterations sequentially and in each iteration KMC computes the distances among the data points and the centers which consume more time, also expensive due to their huge UCI repository datasets. In order to overcome the problem, the EKMC is computed in the next iteration which uses the values obtained in the previous nearest cluster based on the distance. This results are evaluated and the proposed method achieves accuracy of 96.71% when compared with the existing KMC method.
Keywords: Data clustering, Davies–Bouldin Index, Enhanced K-Means Clustering, Imbalanced, Overlapping.

[1] R. Venkatesh, C. Balasubramanian, M. Kaliappan, “Development of Big Data Predictive Analytics Model for Disease Prediction using Machine Learning Technique”,Journal of medical systems, Vol. 43, no. 8, pp. 272, 2019. [2] M.J. Sousa, A.M. Pesqueira, C. Lemos, M. Sousa, A. Rocha, “Decision-making based on big data analytics for people management in healthcare organizations”, Journal of medical systems, Vol. 43, no. 9, pp. 290, 2019. [3] V. Tang, P.K.Y. Siu, K.L. Choy, H.Y. Lam, G.T.S. Ho, C.K.M. Lee, Y.P. Tsang, “An adaptive clinical decision support system for serving the elderly with chronic diseases in healthcare industry”, Expert Systems, Vol. 36, no. 2, pp. e12369, 2019. [4] O. Inan, M.S. Uzer, “A Method of Classification Performance Improvement via a Strategy of Clustering-Based Data Elimination Integrated with k-Fold Cross-Validation”, Arabian Journal for Science and Engineering, 2020. [5] M.S. Amin, Y.K. Chiam, K.D. Varathan, “Identification of significant features and data mining techniques in predicting heart disease”, Telematics and Informatics, Vol. 36, pp. 82-93, 2020. [6] L. Ali, A. Rahman, A. Khan, M. Zhou, A. Javeed, J.A. Khan, “An Automated Diagnostic System for Heart Disease Prediction Based on ${\chi^{2}} $ Statistical Model and Optimally Configured Deep Neural Network”, IEEE Access, Vol. 7, pp.34938-34945, 2019. [7] K. Mittal, G. Aggarwal, P. Mahajan, “Performance study of K-nearest neighbor classifier and K-means clustering for predicting the diagnostic accuracy”, International Journal of Information Technology, Vol. 11, No. 3, pp. 535-540, 2019. [8] T. Tang, S. Chen, M. Zhao, W. Huang, J. Luo, “Very large-scale data classification based on K-means clustering and multi-kernel SVM”, Soft Computing, Vol. 23, No. 11, pp. 3793-3801, 2019. [9] K. Mittal, G. Aggarwal, P. Mahajan, “Performance study of K-nearest neighbor classifier and K-means clustering for predicting the diagnostic accuracy”, International Journal of Information Technology, Vol. 11, no. 3, pp. 535-540, 2019. [10] N. Han, S. Qiao, G. Yuan, P. Huang, D. Liu, K. Yue, “A novel Chinese herbal medicine clustering algorithm via artificial bee colony optimization”, Artificial Intelligence in Medicine, Vol. 101, pp. 101760, 2019. [11] C. Zhu, C.U. Idemudia, W. Feng, “Improved logistic regression model for diabetes prediction by integrating PCA and K-means techniques”, Informatics in Medicine Unlocked, Vol. 17, pp. 100179, 2019. [12] C.Y. Lin, “A reversible privacy-preserving clustering technique based on k-means algorithm”, Applied Soft Computing, Vol. 87, pp.105995, 2020. [13] H. Gürüler, “A novel diagnosis system for Parkinson’s disease using complex-valued artificial neural network with k-means clustering feature weighting method”, Neural Computing and Applications, Vol. 28, no. 7, pp. 1657-1666, 2019. [14] T.L. Le, T.T. Huynh, L.Y. Lin, C.M. Lin, F. Chao, “A K-means Interval Type-2 Fuzzy Neural Network for Medical Diagnosis”, International Journal of Fuzzy Systems, Vol. 21, no. 7, pp. 2258-2269, 2019. [15] Newman, D. J., Hettich, S., Blake, C. L. S., &Merz, C. J., “UCI repository of machine learning database”, Irvine, CA: University of California, 1988.

Automatic defect detection enabled with machine learning based processing techniques is the recent trend in thermal wave imaging based non-destructive testing. In this context, automatic defect detection can be regarded as a classification problem, distinguishing defective and non-defective regions using the respective thermal profiles of a test sample. This article introduces and analyses a deep neural network autoencoder for automatic defect detection in quadratic frequency modulated thermal wave imaging. The proposed methodology is validated experimentally on the thermal response of carbon fiber reinforced polymer specimen with flat-bottom holes at different depths. Machine learning assessment metrics suggest that the proposed autoencoder provides automatic defect detection in composite samples.
Keywords: Automatic defect detection, Autoencoder, Carbon fiber reinforced polymer, and Quadratic frequency modulated thermal wave imaging.

[1]X P V Maldague, “Theory and Practice of Infrared Thermography for Nondestructive Testing”, John Wiley& Son, New York , 2001. [2]. Trétout, H., D. David, J. Y. Marin, M. Dessendre, M. Court, and I. Avena's-Payan. “An evaluation of artificial neural networks applied to infrared thermography inspection of composite aerospace structures”, Review of Progress in Quantitative Nondestructive Evaluation, pp. 827-834, 1995. [3].Yanpeng Cao, Yafei Dong, Yanlong Cao, Jiangxin Yang, Michael Ying Yang. “Two-stream convolutional neural network for non-destructive subsurface defect detection via similarity comparison of lock-in thermography signals”, NDT&E International, Vol. 112, 2020, [4.]Mulaveesala, Ravibabu, and SuneetTuli. “Theory of frequency modulated thermal wave imaging for nondestructive subsurface defect detection”, Applied Physics Letters, no. 19, 2006. [5.]Subbarao, GhaliVenkata, and RavibabuMulaveesala. “Quadratic frequency modulated thermal wave imaging for non-destructive testing”, Progress In Electromagnetics Research, Vol. 26, pp. 11-22, 2012. [6.]Ghali, V. S., S. S. B. Panda, and R. Mulaveesala. “Barker coded thermal wave imaging for defect detection in carbon fibre-reinforced plastics”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 53, no. 11, pp. 621-624, 2011. [7]Mulaveesala, Ravibabu, GhaliVenkataSubbarao, and MuniyappaAmarnath. “Matched excitation for thermal nondestructive testing of carbon fiber reinforced plastic materials”, Thermosense: Thermal Infrared Applications XXXIV, Vol. 8354, 2012. [8.]Benítez, Hernán D., HumbertoLoaiza, Eduardo Caicedo, Clemente Ibarra-Castanedo, AbdelHakimBendada, and Xavier Maldague. “Defect characterization in infrared non-destructive testing with learning machines”, NDT & E International, Vol. 42, no. 7, pp. 630-643, 2009. [9]Yousefi, Bardia, DavoodKalhor, Rubén UsamentiagaFernández, Lei Lei, Clemente Ibarra Castanedo, and Xavier PV Maldague.“Application of Deep Learning in Infrared Non-Destructive Testing”, Quantitative Infra-Red Thermography (QIRT), 2018. [10]NumanSaeed, Nelson King, Zafar Said, Mohammed A. Omar. “Automatic defects detection in CFRP thermograms, using convolutional neural networks and transfer learning”, Infrared Physics and Technology, Vol. 102, 2019. [11]Luo, Qin, Bin Gao, WaiLok Woo, and Yang Yang. “Temporal and spatial deep learning network for infrared thermal defect detection”, NDT & E International, Vol. 108, 2019. [12].Dudek, Grzegorz, and Sebastian Dudzik. “Classification Tree for Material Defect Detection Using Active Thermography”, International Conference on Information Systems Architecture and Technology, pp. 118-127, 2017. [13]Fang, Qiang, and Xavier Maldague.“A method of defect depth estimation for simulated infrared thermography data with deep learning”, Applied Sciences, Vol. 10, no. 19, 2020. [14]Wang, Qiang, Qiuhan Liu, Ruicong Xia, Guangyuan Li, JianguoGao, Hongbin Zhou, and Boyan Zhao. “Defect Depth Determination in Laser Infrared Thermography Based on LSTM-RNN”, IEEE Access, Vol. 8, pp. 153385-153393, 2020. [15]Liu, Kaixin, Yingjie Li, Jianguo Yang, Yi Liu, and Yuan Yao.“Generative Principal Component Thermography for Enhanced Defect Detection and Analysis”, IEEE Transactions on Instrumentation and Measurement, 2020. [16]Erazo-Aux, Jorge, HumbertoLoaiza-Correa, Andres David Restrepo-Giron, Clemente Ibarra-Castanedo, and Xavier Maldague.“Thermal imaging dataset from composite material academic samples inspected by pulsed thermography”, Data in brief, Vol. 32, 2020. [17]A. Vijaya Lakshmi, V. Gopitilak, Muzammil M. Parvez, S.K. Subhani, V.S. Ghali. “Artificial neural networks based quantitative evaluation of subsurface anomalies in quadratic frequency modulated thermal wave imaging”, Infrared Physics and Technology, Vol. 97, pp. 108–115, 2019. [18]Lakshmi, A. Vijaya, V. S. Ghali, SkSubhani, and Naik R. Baloji. “Automated quantitative subsurface evaluation of fiber reinforced polymers”, Infrared Physics & Technology, Vol.110 2020. [19]Xie, J.; Xu, C.; Chen, G.; Huang,W., “Improving visibility of rear surface cracks during inductive thermography of metal plates using Autoencoder”, Infrared Physics Technology, Vol. 91, pp. 233–242, 2018. [20]Xu, Changhang, Jing Xie, Changwei Wu, LemeiGao, Guoming Chen, and Gangbing Song. “Enhancing the visibility of delamination during pulsed thermography of carbon fiber-reinforced plates using a stacked autoencoder”, Sensors, Vol. 18, no. 9, 2018. [21]Munir, Mohsin, Muhammad Ali Chattha, Andreas Dengel, and Sheraz Ahmed."A Comparative Analysis of Traditional and Deep Learning-based Anomaly Detection Methods for Streaming Data”, 18th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 561-566, 2019. [22]Available online: https://towardsdatascience.com/auto-encoder-what-is-it-and-what-is-it-used-for-part-1-3e5c6f017726 [23] Amarbayasgalan, T., Jargalsaikhan, B., &Ryu, K. H. “Unsupervised novelty detection using deep autoencoders with density based clustering.” Applied Sciences, Vol. 8, no. 9. 2018.

There is an excellent deal of procedures proposed by different scientists to forestall DDoS attacks on a cloud infrastructure. In this paper, we put forward another system against DDoS within the cloud that uses Threat Intelligence strategies and a positive thanks to affecting distinguish traffic conduct irregularities. We utilize a trundle Based methodology for preventing DDoS within the cloud condition. This system is responsive and utilizes the resource flexibility of the cloud. The purpose of this strategy is to spare the best number of favorable clients from the attack through rearranging. It indicated that we will spare a perfect level of favorable clients from the progressing attacks after certain trundles. To acknowledge the attack on every server, an indicator is conveyed that utilizes an entropy-based methodology for detecting DDoS. An interesting deviation in entropy speaks to the DDoS attack. A progression of investigations was performed and therefore the outcomes show that this system can effectively distinguish and relieve DDoS attacks from an assortment of known and obscure sources. So in our work, we've taken an attempt to detect and prevention of DDoS on cloud infrastructure.
Keywords: Cloud, attack detection, Entropy, Botnets, Virtualization, flooding, DDoS attack.

The characteristic of Cold-Formed Steel (CFS) is its thinness, but it is also a disadvantage because it is more susceptible to buckling. The efforts to improve CFS performance were carried with a variety of research and extended into the joint area. The motivation of the previous researcher's in the connection area was due to limited information in EC3 for gusset plate connections. This paper presents the proposed gusset plate joint combination with flange web cleat angle, which is an innovation from other research, and it was chosen because it can produce extra advantageous in terms of resistance and stiffness. The Isolated Joint Test (IJT) and Sub-assemblage Frame Test (SAFT) were conducted so that the influence of connection could be identified. Four specimens for each procedure and the results showed that the influence of beam dimensions and connection components significantly increased the joint performance, 21% for moment resistance and 47% for stiffness respectively. The experimental results show that the joint deformation has happened without any failure on the gusset plates, angles and bolts, indicating bearing failure around bolt holes due to the thin plate of the CFS. However, the connection contribution is only a quarter of the ultimate connection capacity in terms of mid-span behaviour. The increment in load capacity, which was not exceeding 1 kN, is mainly controlled by the beam's lateral-torsional buckling. Therefore, the composite beam application is more recommended for CFS so that it can be applied as the primary structure.
Keywords: Cold-formed steel, sub-assemblage, gusset plate, web cleat connection, load capacity.

In this modern day and age, data is arguably the most valuable asset. Specifically, the piece of information which could be transformed into an entity of economic value has a greater need to be protected. During this era of digital upgrading in every domain, the area of electrical energy is not spared either. The conventional electrical grid systems have become smarter with the implementation of smart grid (SG) technologies, along with its own risks and limitations. The prominent challenge here is to discover and apply the correct methods and technologies to safeguard the data that gets accumulated in every node of the SG networks. This paper focuses on the protection of data collected at the Advanced Metering Infrastructure (AMI) of the SGs. The data that becomes available in the smart meters of AMI needs to be encrypted before any communication steps are initialized. Currently, many proven algorithms, and appropriate key management solutions have been suggested to establish end-to-end secure communication for smart grid. Here in this paper, the standard encryption algorithms which are commonly used in AMIs are analysed. Also, the challenges in implementing the encryption algorithms in AMI are investigated with the focus on secure key management. The current standards in implementing the encryption techniques in AMI are also briefly studied.
Keywords: Smart Grid; Cyber Security; Advanced Metering Infrastructure; Encryption techniques; Key Management Systems; Lightweight KMS Solutions.

The primary advantage of using prefabricated concrete in a building is enhancing building completion speed. Renovation works are then carried out, introducing opening to the wall to provide new access. Without the option of providing opening on the precast load-bearing wall, this would cause a significant impact on structural integrity. This paper presents numerical modelling of the precast wall panel with opening. The ultimate load of the precast wall panel is evaluated where the slenderness of the panel, the aspect ratio and the opening ratio are taking into consideration. The ultimate load capacity of the wall with an opening (Nu,o) which was derived from the numerical analysis using Finite Element Model is compared with design equations for the precast wall in the ACI 318-14, AS3600-2009 and EN1992-1-1. The proposed design equations by other researchers are compared as well. It is found that the relationship between geometry properties and ultimate load are determined under the specified condition. When buckling type failure is imminent, a non-linear relationship can be observed which significantly reduce the ultimate load. On the other hand, under bending type failure, a linear relationship can be observed. It is observed that the code design equations are not applicable in determining the ultimate load of the wall with opening where the mean values of the differences are 9.79, 1.39 and 2.12 respectively observed. The value of Nu,o from the numerical model found a good comparison with the proposed equation from other researchers with a mean difference 0.15.
Keywords: Precast wall with opening; ultimate load capacity; slenderness ratio, aspect ratio; opening ratio.

The wireless sensor network is the key deciding element in communication, the 4G and 5G LTE communication models are offering many applications such as data accessing, and data rate controlling, multimedia and live streaming applications. Therefore, an advanced wireless sensor network designing and its development is compulsory to provide the above applications. The wireless sensor networks are dynamic in nature, so that they can change their behavior with little time. Due to time-variant action, internal and external factors cannot be predictable. WSN facing power constrains issue, node failure, and homogeneity node accessing and node scalability problems. Moreover WSN network challenging following key parameters such as the high bandwidth, high energy consumption, QOS, cross layer communication and physical channel. The lifespan of the sensor network, Maximum usage of resources and system are the main limitations of the earlier method. The existed architecture and optimization models cannot solve the above limitations and significant problems. In this research work addressing the machine learning-based WSN node localization technique, the node localization is a complex problem due to more number of elements to be estimated between sensor nodes. In this paper, node localization, objective function, mean-average error in localization, anchor node density and estimated position parameters are analyzed with various methodologies. At final proposed an advanced localization technique with machine learning model for future generations.
Keywords: WSN, node localization, sensor nodes, machine learning.

3, no. 4, pp. 360–371, 2006.

Conventional load modeling methodologies consist of two existing approaches, which are the component based approach and the measurement based approach. The measurement based approach offers several advantages and can overcome certain limitations resulted from component based approach implementation. By using the measurement based approach, the load model parameters can be estimated using power system disturbance records. Automated disturbance record collection can be performed by utilizing IEC 61850, i.e. the international communication standard for substation and power utility automation. This paper presents the design and development of automated load modeling system utilizing IEC 61850 file transfer service. The system architecture was designed based on the centralized disturbance record concentrator for distributed recording devices. The system was developed to perform event triggered disturbance record acquisition, where IEC 61850 file transfer service was utilized for automatic disturbance record retrieval. The proposed system was tested to automatically retrieve disturbance records from three multivendor IEC 61850 compliant relays. It was found that the root directory for each relay are not standardized eventhough the communication is standardized according to IEC 61850. The proposed system was then tested and verified by simulating actual disturbance measurements into the relays. The system was able to automatically retrieve the disturbance records and perform a fairly accurate curve fit to the actual disturbance measurements based on the automatically generated load model parameters. The results are encouraging for the actual implementation and deployment of actual substations.
Keywords: Load Modeling; IEC 61850, File Transfer, Dynamic Model, Parameter Estimation.

Water is the elixir for agricultural process as the entire procedure relies merely on that. Optimization and effective usage of water in agriculture is an essential phenomenon. Wide varieties of automatic irrigation systems exists in practice but none of them proved to be efficient in terms of cost, technology adopted and fixing the loopholes which is evident from the current literature. Efficiency should be achieved in all the aforementioned levels for enhancing the agricultural productivity. Drip emitters with sensors helps in proper water distribution of agricultural crops which in turn prevents the water wastage and soil degradation. It joins hand with the emerging technology Internet of Things to enable smart tracking and solving the irrigation related issues. Hence the major focus is to assist the farmers for irrigation by applying organized procedures for getting the details regarding amount of water to be dispersed, issues in the water dispersion and water inlet flows. Effective automatic irrigation is the needy solution in today’s scenario as agriculture is the backbone in spite of the growth and advancement of any other processes. Our system attempts to fix the loopholes in the existing ones by tracking the water pressure in the dispersion pumps and checking the inlet, outlet flows. It eradicates the agricultural overhead with a complete user friendly interface. The interrelated computing devices manage the ability of data transfer over a network with minimized human intervention. Low cost is achieved in the irrigation process with the help of drip emitter connected to the semi-submersible water pump. Experimental test bed is done with the water pumps and sensors for validating its accuracy and effectiveness
Keywords: IoT, smart irrigation, soil moisture prediction, microcontroller, rain water sensor

Floods are recurrently appearing in the headings of local, national and international mass media. Flood as a geo-hazard challenge in many populated territory on the planet. People are trying to mitigate and find ways to minimize damages. Among the initiatives are flood mitigation plans. These tactics can be classify into two categorihich is (a) structural flood mitigation is where physical structures are constructed or modified to reduce the impact of flooding on individual properties or whole catchments, and (b) non-structural flood mitigation can be considered as a lot of moderation as well as adjustment estimates that don't utilize customary basic flood safeguard measures. The tricky situation in handling flood challenges is the multi-layered information that need to be deciphered by the hydrologists in the decision making. To deal with the flood occasions requires to a noteworthy degree a decent plan and development of a flood control system, and taking appropriate measures for flood relief including non-basic measures, flood determining, cautioning and moderation plans. This paper looks at the evacuation route selection through multi-criteria decision-making. The Analytical Hierarchy Process (AHP) technique is utilized to choose the best evacuation route over variance weighting of different criteria and sub-criteria. A learning-driven expert-based GIS model for Kelantan river basin was developed with three design parameters, i.e. accessibility, technical and safety. The model successfully predicted the best route for evacuation centres in Kelantan. In common, the developed model were reasonably accurate. The resultant maps would be useful for regional flood mitigation planning.
Keywords: Analytic hierarchy process (AHP), route selection, multi-criteria decision-making, geographical information system (GIS).

Submerged remote wireless data exchange correspondence systems and its applications are developing quickly related to underwater. The communication in the mode of acoustic is spreading effect of submerged remote data interchanges influenced by communication path varieties, and effects of Doppler move. The submerged communication path, examining an overabundance & postpone limits turns into a basic assignment. Stochastic Network Calculus (SNC) has offered an exquisite numerical result for surveying momentum arranges execution particularly considered with submerged correspondence. The SNC is a generally new proposition, that expanding deployment activity of different frameworks. It have built up a submerged acoustic remote channel exposed to MAC layer design in an underwater Channel with fading effects. The determined stochastic network calculus to ensures that the defer prerequisites, infringement prospects, delay occurrences with bound values, and flow of packets in the acoustic channel.
Keywords: Underwater Acoustic Wireless Communication, Delay, Backlog, Stochastic Network Calculus, Fading.

In this analysis, catalytic air gasification of the rice husk was investigated to optimise the composition of hydrogen and syngas using a thermogravimetric analyser coupled with a mass spectrometer. The fixed bed reactor is then used as a pilot plant to determine the practicality of the optimal parameters obtained for upscaling from the thermogravimetric analyzer test. The catalyst used is coal bottom ash chosen and obtained from a nearby power plant based on a previous analysis. The findings from the thermogravimetric analyser test showed that at reaction temperature of 900oC, rice husk particle size of 250 μm, catalyst quantities of 10%, and air to biomass ratio of 1.25 were the optimum input parameters for syngas formulation to obtain product gas with 73.8% of syngas composition. 76.2% of the composition of syngas is derived from a fixed bed reactor, 3.25% more than the previous test. In addition, 84.1% of the gaseous substance yield, including syngas and CH4, was obtained using the coal bottom ash catalyst in catalytic air gasification. This demonstrated the promise of coal bottom ash in catalytic gasification as a replacement for industrial catalysts. Finally, to determine the effect of temperature, particle size, air to biomass ratio, and coal bottom ash loading on the production of H2 and syngas, the main component analysis was applied. Production of H2 tends to be extremely sensitive to the temperature of the reaction. Meanwhile, there was a positive association between particle size, air to biomass ratio and catalyst loading with CO2 and CH4, but a negative correlation with H2.
Keywords: Catalytic air gasification, Optimization, Syngas production, thermogravimetric analyser, fixed bed reactor.

In India, Paddy is the most imperative crops, and they are prone to numerous diseases, say, bacterial blight, rice blast, brown spot, et cetera. All the methodologies that were previously developed are less accurate and do not focus on detecting the stages. This paper proposed a paddy leaves disease classification and stages identification with the aid of SR-DCNN. This proposed method comprises totally ‘7’ phases. Initially, the Image Acquisition (IA) process is carried out, and then, the ICLAHE enhances the contrast. Following the preprocessing, the CoK-means method clusters that image into disease affected leave and normal leaves. After that, the LoO method segment the disease affected part as of the disease leaves, and the features are extracted as of that segmented part. After Feature Extraction (FE), the features are selected utilizing the SAF-ACO algorithm. Then, these selected features are inputted to the SR-DCNN, which classifies the image as bacterial blight, rice blast, brown spot, leaf smut, and sheath blight. Lastly, the distance is gauged between the classified disease input of the images and query images utilizing Euclidean distance, which is employed to distinguish the disease’s stages. In an experimental appraisal, the proposed work attains better accuracy than the prevailing methodologies.When contrasted to other classifiers, the proposed SR-DCNN classifier attains 98.95% accuracy in disease detection.
Keywords: Improved Contrast Limited Adaptive Histogram Equalization (ICLAHE), Covariance based K-means (COK-means), Logarithmic Otsu (LAO), Speed and Aggregation factor-Ant Colony Optimization (SAF-ACO) and Softmax and rectifier based Deep Convolutional Neural Network (SR-DCNN).

[1] A.D. Nidhis, Chandrapati Naga VenkataPardhu, K. Charishma Reddy, K. Deepa, “Cluster based paddy leaf disease detection, classification and diagnosis in crop health monitoring unit”, Computer Aided Intervention and Diagnostics in Clinical and Medical Images, Springer, Cham, Vol. 31, pp. 281-291, 2019. [2] S. Ramesh, “Rice blast disease detection and classification using machine learning algorithm”, In 2nd International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE), IEEE, Ghaziabad, India, pp. 255-259, 2018. [3] K. Sukhvir, P. Shreelekha, G. Shivani, “Plants disease identification and classification through leaf images: A survey”, Archives of Computational Methods in Engineering, Vol. 26, No. 2, pp. 507-530, 2019. [4] P. Jitesh Shah, B. Harshadkumar. Prajapati, K. VipulDabhi, “A survey on detection and classification of rice plant diseases”, IEEE International Conference on Current Trends in Advanced Computing (ICCTAC), IEEE, Bangalore, India, pp. 1-8. 2016. [5] Y. Ghazaala, K. Asit Das, A. Ghosal, “A hierarchical stratagem for rice leaf disease distinction”, In International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), IEEE,Kannur, India, pp. 1177-1183, 2017. [6] M. Suresha, K.N. Shreekanth, B.V. Thirumalesh., “Recognition of diseases in paddy leaves using knn classifier”, 2nd International Conference for Convergence in Technology (I2CT), IEEE, Mumbai, India, pp. 663-666, 2017. [7] SrdjanSladojevic, Marko Arsenovic, AndrasAnderla, DubravkoCulibrk, DarkoStefanovic, “Deep neural networks based recognition of plant diseases by leaf image classification”, Computational intelligence and neuroscience, 2016. [8] FarhanaTazmimPinki, NipaKhatun, SM Mohidul Islam, “Content based paddy leaf disease recognition and remedy prediction using support vector machine”, 20th International Conference of Computer and Information Technology (ICCIT), IEEE, Dhaka, Bangladesh, pp. 1-5. 2017. [9] Taohidul Islam, Manish Sah, SudiptoBaral, RudraRoyChoudhury, “A faster technique on rice disease detectionusing image processing of affected area in agro-field”, Second International Conference on Inventive Communication and Computational Technologies (ICICCT), IEEE, Coimbatore, India, pp. 62-66, 2018. [10]R.P. Narmadha, G. Arulvadivu, “Detection and measurement of paddy leaf disease symptoms using image processing”, International Conference on Computer Communication and Informatics (ICCCI), IEEE,Coimbatore, India, pp. 1-4. 2017. [11]A. Amrita Joshi, B.D. Jadhav, “Monitoring and controlling rice diseases using Image processing techniques”, International Conference on Computing, Analytics and Security Trends (CAST), IEEE,Pune, India, pp. 471-476, 2016. [12]Johanna Albetis, Sylvie Duthoit, Fabio Guttler, Anne Jacquin, Michel Goulard, HervéPoilvé, Jean-Baptiste Féret, Gérard Dedieu, “Detection of Flavescencedorée grapevine disease using unmanned aerial vehicle (UAV) multispectral imagery”, Remote Sensing, Vol. 9, No. 4, pp. 308, 2017. [13]SavitaSabale P. and Chhaya R. Jadhav, “Hyperspectral image classification methods in remote sensing-a review”, International Conference on Computing Communication Control and Automation, IEEE,Pune, India, pp. 679-683, 2015. [14]Muhammad Jaleed Khan, Hamid Saeed Khan, AdeelYousaf, KhurramKhurshid, and Asad Abbas, “Modern trends in hyperspectral image analysis: A review”, IEEE Access, Vol. 6, pp. 14118-14129, 2018. [15]Stefan Thomas, Matheus Thomas Kuska, David Bohnenkamp, Anna Brugger, Elias Alisaac, MirwaesWahabzada, Jan Behmann, and Anne-KatrinMahlein, “Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective”, Journal of Plant Diseases and Protection, Vol. 125, No. 1, pp. 5-20, 2018. [15]S. Ramesh, D. Vydeki, “Recognition and classification of paddy leaf diseases using Optimized Deep Neural network with Jaya algorithm”, Information Processing in Agriculture, Vol. 7, No. 2, pp. 249--260, 2019. [16] SantanPhadikar, Jaya Sil, Asit Kumar Das, “Rice diseases classification using feature selection and rule generation techniques”, Computers and electronics in agriculture, Vol. 90, pp. 76-85, 2013. [18]S. Shampa, and K. Asit Das, “Particle swarm optimization based incremental classifier design for rice disease prediction”, Computers and Electronics in Agriculture, Vol. 140, pp. 443-451, 2017. [19]B. HarshadkumarPrajapati, P. Jitesh Shah, and K. VipulDabhi, “Detection and classification of rice plant diseases”, Intelligent Decision Technologies, Vol. 11, No. 3, pp. 357-373, 2017. [20]Z. Guoxiong, Z. Wenzhuo, C. Aibin, H. Mingfang, M. Xueshuo, “Rapid detection of rice disease based on FCM-KM and faster R-CNN fusion”, IEEE Access, vol. 7, pp. 143190-143206, 2019. [21]M.G. Sánchez, V. Miramontes-Varo., J.A Chocoteco., V. Vidal, “Identification and Classification of Botrytis Disease in Pomegranate with Machine Learning” Advances in Intelligent Systems and Computing, Springer, Cham, Vol 1229, 2020. [22]D. Qiang, C. Xi, Q. Yan, Z. Youhua, Agricultural Pest Super-Resolution and Identification with Attention Enhanced Residual and Dense Fusion Generative and Adversarial Network, IEEE Access, Vol. 8, pp. 81943-81959, 2020. [23]S. Vijai, S. Namita, S. Shikha, A review of imaging techniques for plant disease detection, Artificial Intelligence in Agriculture, Vol. 4, pp. 229-242, 2020.

In order to avoid the risk of drinking contaminated water, the information of drinking water quality must be available in real time. This paper presents the design and development of a real time monitoring system of drinking water quality using Internet of Thing (IoT). Several sensors IoT water sensors are used to measure and validate the water quality parameter values. These parameters include pH, turbidity and oxidation-reduction potential (ORP). The sensors are connected through an Arduino UNO controller. The Arduino UNO controller reads and sends sensor parameter values to an android mobile application which displays the measurements and concludes whether the quality of the water is safe to be drinkable or not.
Keywords: Arduino UNO, real time water quality, Internet of Thing, water quality assessment, monitoring

Agriculture is the backbone of the Indian economy, but farmers face so many problems during the period of cultivation. Sometimes they lose their crop at the ending stage due to the impact of unseasonal heavy rains and air. This problem can be avoided by using a crop protection system. For the implementation of the crop protection system, rain and Flex sensors are used to detect the signal when heavy rainfall and high air force have occurred. Anyone of the sensors output signal is above the thresh hold value, and then this value activates the mechanical arrangement of the protection system through Arduino. This protection system protects the cultivated fields with a dome shape, and the collected rainwater is drained to the well through pipelines.
Keywords: Rain sensor, Flex sensor, Arduino and protection system.

Research design on the toxicity of Sodium Dodecyl Urea (SDU) and Sodium Dodecyl Sulphides (SDS) copper nanofluid on kinetics of methane hydrate formation was studied. The experiments were done using stainless steel stirred reactor at 5.1 MPa pressure and 274.15 K temperature. Completion time was reported to describe overall formation kinetic. The consequences exposed that SDS and nanofluid reduced the completion time significantly. Among all samples 0.05wt% copper nanoparticles suspended in The 0.03 weight percent SDS solution achieved the average formation of methane hydrate in shortest time. Nanofluid contains 0.01wt% and 0.1wt% copper nanoparticles do not enhance the hydrate formation in compare to 0.03 wt% SDS solution.
Keywords: methane hydrate, copper nanoparticle, hydrates formation, completion time, Sodium Dodecyl Sulphides

WSN is a collection of sensors, which senses critical information related to military, opponent tracking, patient health details etc. These sensed critical and private data will be collected and aggregated by aggregators and forward it to the base station. Due to the involvement of sensitive data, there is a demand for secure transmission and privacy preserving data aggregation. In this paper, we propose a light weight, secure, multi party, privacy preserving data aggregation scheme, in which one or more sensors share their private data with aggregator securely without revealing the original content. The aggregators also perform the aggregation operation without knowing the original content.
Keywords: Privacy preserving, Data Aggregation, WSN.

In Malaysian universities, energy wastage tends to occur mainly due to inefficient use of energy and lack of information among institutions occupancy. Most of the energy consumption is contributed from the operation of HVAC and lighting system. However, the energy consumption remains the same during final exam week and semester break even though the occupancy in the college is low. It is mainly due to the lack of ignorance and awareness in managing the use of electrical energy in dwellings. Connected with the hike in electricity bills to the University, therefore it is important that swift actions can be taken to reduce the bills via energy efficiency measures. This paper highlights preliminary results of the electrical energy consumption for 3 blocks in College of Engineering (COE), Universiti Tenaga Nasional (UNITEN). This paper also identifies potential areas of energy saving in those blocks. Finally, suggestions on the ways to improve electrical energy usage in those buildings. This study indicates that by implementing no cost initiatives into COE buildings, the university can potentially save up to 11.9% of its monthly electrical bills by switching off lightings for one hour.
Keywords: Electrical Energy Consumption, University Building, Energy Saving, Energy Efficiency, Electricity bills.

This paper is aim to presenting Wind Energy conversion System. In this article, we focus on the technique used in the converter. We discuss on the wind turbine modelling introduced in this work. There is new circuit topologies PMSG with rising focus aimed towards Wind Turbine manufacturing. The output of the PMSG is Three Phase Sinusoidal Waveform. The all topology simulate in the MATLAB Simulink environment.
Keywords: PMSG, Wind Turbine, Controlled Rectifier, Uncontrolled Rectifier, Sinusoidal Pulse Width Modulation, Space Vector Controlled technique

Microwave-assisted extraction coupled with for the extraction of polycyclic aromatic hydrocarbons (PAHs) in vegetables, dispersive liquid-liquid microextraction (MAE-DLLME) is already advanced. The analyses were segregated and detected using the ionic detector for gas-chromatography-flame (GC-FID). In this study, microwave-assisted pre-treatment was used to solve the problem of matrix interferences. The parameters affecting the MAE-DLLME performance have been developed and optimized in a previous work. Pre-treatment was done by heating the sample with acetone under 200 W of microwave power for 1.5 minutes and followed by DLLME extraction using 30 uL of 1-bromo-3-methylbutane as extraction solvent and 800 uL of acetone as dispersive solvent for one minute extraction time. Analytical parameters, such as sensitivity, detection limits (LOD), quantification limits (LOQ), relative extraction recovery (ER) and relative standard deviation (RSD), were already compared in this work with those obtained from modified DLLME and conventional DLLME techniques. MAE-DLLME showed the highest sensitivity, lowest LOD and LOQ values, the best related extraction recovery with the low RSD compared to the modified DLLME and the conventional DLLME. The MAE pre-treatment has improved the overall analytical performances of MAE-DLLME by eliminating the matrix interferences.
Keywords: Microwave-assisted extraction, dispersive liquid-liquid micro extraction, polycyclic aromatic hydrocarbons, vegetable, detection limits

At present, computers have been in agriculture for the automation of different applications. The expert and decision support system is used for taking the critical decision about crop yield and measures for plant protection. It is a tedious process for farmers to predict the cultivated area manually when it is enormous in acres. The proposed scheme presents a result of frequently watching the cultivated region and offers automatic disease discovery using data mining techniques. For example, data mining techniques help to detect or forecast crops diseases, manufacture, and loss. The disease patterns are used to recognize diseases. Generally, the classification rules and relationships are used for acquiring knowledge from empirical data of diverse dataset. This paper explores what Classification rule and prediction can do in the agricultural domain. This paper goal to detect classification rules for the Indian Banana, Paddy and Sugarcane using the Linear Discriminant Analysis (LDA) algorithm. It is compared with standard machine learning and neural network algorithms for example artificial neural network, Support vector machine and Decision Tree.
Keywords: Data Mining, Paddy Crop, Diseases, Classification, Expert System, Agriculture

A large amount of energy can be saved by developing a smart street lighting system which essentially assuage the problem of power consumption and reduction of carbon footprint. The conventional process involves higher energy consumption because of longer and unnecessary operating hours of the street lights based on night hours. However, by controlling the intensity of the street lights based on the movement of traffic in the street saves a great deal of energy. In this research, a smart system for operating the street lights is developed for controlling brightness of the light bulb based on the motion of the movement of the vehicle. In this research, a prototype for smart street light system is developed based on the solar PV panel, battery, light dependent resistor (LDR), passive infrared sensors (PIR) and battery charge controller. Moreover, the control system is designed based on Arduino UNO as the microcontroller which provide the necessary pulse width modulated signal to control the light intensity. The research has been conducted based on four different simulation scenarios where the operating time and traffic condition is varied. In this study, the developed smart street lighting system is able to save up to 50% of energy than the conventional system per day during light traffic condition.
Keywords: Solar Powered LED, Energy Utilization, Vehicle Motion Detection, Street Lighting, Prototype.

In this study, a novel ducted blade with varying width is proposed for wind energy application. The proposed wind blade is designed, fabricated, and used to develop a vertical axis wind turbine (VAWT). Here, VAWT with 2,3 and 4 blade configurations are modeled, fabricated and tested experimentally in subsonic wind tunnel. Based on the experiments conducted, the performance of three VAWT models for varying wind speed is analyzed. It is revealed that the ducted VAWT with a 3-blade configuration outperforms the other two configurations.
Keywords: varying blade width; ducted blade; VAWT; subsonic wind tunnel testing; VAWT performance

Raman fiber laser in C-band region has undeniable potential in optical communication systems due to the low attenuation at this wavelength band for signal processing and data transmission. Therefore, the extensive investigation for Raman fiber laser in terms of continuous wave and pulse regimes have been sought-after among the engineers and researchers. However, a simple design of the Raman fiber laser is always the merit to minimize the design complexity of the laser system. The main objective of this research work is to propose a simple design of Raman fiber laser which is designed with continuous wave operation. A unidirectional ring laser cavity is tailored by integrating an optical isolator within the Raman fiber laser configuration. The optical spectrum, power development, and the pulse validation for the Raman fiber laser will be thoroughly conducted in this work. The experimental result is expected with the absence of the pulse operation due to the continuous wave laser regime of the proposed Raman fiber laser scheme. The success of this work will contribute to a simple yet flexible design to a C-band Raman fiber laser for optical communication system.
Keywords: Raman Fiber Laser, Unidirectional Ring Laser Cavity, Continuous Wave, Ultra-long Fiber Laser,Power

Recent trend changes have created opportunities to achieve numerous technological innovations including the use of distributed generation (DG) to achieve different advantages. A precise evaluation of energy losses is expanding rapidly when DG is connected to the electricity sector due to developments such as increased competition and real time pricing. Nevertheless, non-optimal DG installation either in the form of DG locations and sizing will lead to possible under-compensation or over-compensation phenomena. The integrated clustering resulted from the pre-developed Embedded Meta Evolutionary Programming–Firefly Algorithm (EMEFA) has been used to ensure the optimum allocation and placement of DG. The study also considers the different types of DG. The aim of the technique is to consider the computational time of the optimization process for DG planning in achieving the minimal total loss. Two test systems have been used as test specimens to achieve the efficacy of the proposed technique. In this study, the techniques proposed were used to establish the DG size and the appropriate place for DG planning. The results for total losses and minimum voltage for the system were recorded from the simulation. The result in this study will be compared with the ranking identification technique to ensure the capability of this technique. The power system planner can adopt the suitable sizes and locations from the obtained result for the planning of utility in term of economic and geographical consideration.
Keywords: Distributed generation, DG Planning, Evolutionary Programming, Firefly Algorithm, Loss Minimization.

This article presents the Hybrid Renewable Energy System project plan (HRES) representation for high rise building in Malaysia. A building has been for this study since it signifies a distinctive load profile for many high-rise buildings in Malaysia. A techno-economic investigation has been performed to establish the possibility of PV, and battery system installation to reduce network dependence. The methodology started with information collection of load summary and solar resources at the selected location. Then, HOMER software was used by the analysis of hybrid financial and technological analysis configurations. Sensitivity examination was conducted to analyze system presentation under load and grid price changes. Results of analyses includes net present cost (NPC), energy cost (COE) and environmental pollution (CO2). This feasibility findings shows that the grid-only communication has the most promising results with the lowest NPC, preceded by the PV and battery grid system.
Keywords: Renewable Energy System, Solar PV, HOMER, Techno-economic Analysis, High Rise Building

Nowadays it is necessary to develop modern technologies for self-sustaining intelligent power buildings containing these devices through the use of several mobile devices – the main sources for energy use with the popularity of DC voltage appliances such as LEDs, computers and laptops. These smart office buildings are the next generation of smart cities. This article suggests a novel topology system in the DC Nano grid, keeping these points in mind. The Nano-Grid PV system is used in small-scale structures to maximise grid efficiency and to reduce power plant emissions. DC nano-grid has promising research platforms for integration with small buildings/offices and the use of new DC appliances in recent studies to increase the number of smart homes and create a clean environment, due to its high efficiency, simple architecture, low cost and ease of control. The foremost objective of our proposed model is to improve the efficiency of the traditional solar system. In this work, we construct the DC Nano grid which works on sharing basis between solar PV systems and utility grid with DC loads. Solar energy is given the predominance and the system will take the required power proportion from the utility grid if the solar power is not enough. This is done by linearly adding the power from the SPV system and the Utility. Thus we can reduce the usage of utility supply and maximise the utilization of the solar power, thus reducing the cost and improving efficiency.
Keywords: DC Nano grid, DC voltage, Maximum power point tracker, solar panel, Zeta converter.

Recent advancement of High Voltage Direct-Current (HVDC) transmission based on alternate arm converter (AAC) draws the attention of researchers due to their unique structure. It is a hybrid converter as the characteristics of this converter varies among the modular multilevel converter (MMC), due to the existence of H-bridge cells, and the two-level converter, in the sort of director switches in every arm of the converter. AAC presents the improved fault tolerant characteristics compare to traditional voltage source converter (VSC). It has gained much popularity in HVDC transmission because of its robustness against fault, ability of generating superior ac voltage compares to the dc terminal voltage. At this point energy balance between the ac and dc terminal is equal. Therefore, the significant contribution of this paper is to analyze the performance of AAC model under normal condition and fault condition which proves the robustness of AAC converter against the faulty situation. Both AC and DC faults are considered in this study. Simulation is performed in Matlab/ Simulink environment.
Keywords: Alternate arm converter, Energy Balance, H-bridge Cells, High Voltage Direct-Current, High Voltage Direct-Current

Vector based Routing protocol for very less power and dissipation network problems occurs due to the energy unbalancing problem in the RPL (Routing Protocol for Low Power and Lossy Networks), where this issue can be solved by a heterogeneous algebraic ring based communication network domain along with identical kind of communication based ring domain network, probably to stay away from the energy holes in the wireless sensor networks. Several routing algorithms based on maintenance methods are studied to solve Energy Efficient Heterogeneous Ring Clustering (E2HRC) routing protocol in wireless sensor networks, and several experimental methods also described the comparison studies against RPL and E2HRC RPL. Based on constructive equilibrium conditions towards the wireless sensor and communication based networks according to the expected energy consumption are achieved, by descending their nodes and this restrict the messages through the energy consumption. This article reveals the E2HRC related studies and describes how to overcome the barriers of energy holes in wireless sensor network according to the recent techniques.
Keywords: E2HRC, RPL, Multihop, Nodes, WSN, Routing protocol, Energy hole, sensor nodes, equilibrium.

Fibre Reinforced Polymer (FRP) mixtures are widely used in construction fields, such as repair, restoration, reinforcement and new construction, properties like high corrosion resistance, electrical insulation characteristics low thermal conductivity, high strength, and , high strength-weight ratio. Therefore, like their metal equivalents, these composites are not isotropic, that provides more difficult design and development methods for interact about an economical design that could maintain every types of loads. Therefore, this paper aimed to study and enhance a design of a transmission tower cross arm made of Glass Fiber Reinforced Polymer (GFRP) carrying a 275 kV cable by developing a numerical model of a GFRP cross arm. The results showed that stresses developed in the composites were within the safe range. In addition, the cross arm was shown to be governed by the serviceability requirement and it was safe against multiple failure criteria such as fibers and delamination failure. Furthermore, the results showed that the total deformation was reduced by 14.2% by adding 1-meter GFRP sleeves to all members near the cable and by 20.7% if Carbon Fiber Reinforced Polymer (CFRP) sleeves were used.
Keywords: GFRP, Failure Criteria, Numerical Modeling, Total Deformation, Delamination Failure.

Main Outfall Drain (MOD) is important project established in 1950 in Iraq. MOD suffers from the sedimentation. Six developed formulas in previous studies (Van Rijin 1984 b, Bagnold 1966, Khassaf et al 2005, Al-Kizwini et al 2007, Jasem 2012 and Maatooq et al., 2016) were used to estimate the sedimentary load in MOD at Al Nasiriya City. An evaluation of six current formulas were presented to estimate the suspended sediment load, two of these formulas are global and four of them are local, based on field data obtained at sections in Main Outfall Drain at Al Nasiriya, which are characterized with silt, clay and sand particles are formed deposition that are traveled through MOD. Although there are deviations in the results for some formulas between the measured and calculated values, a limited number of formulas gave reasonably accepTable values. It was found according to graphical and statistical comparison that Maatooq et al., 2016 and Al-Kizwini et al, 2007 are more suitable than other adopted formulas to represent the suspended load in MOD in Al Nasiriya City.
Keywords: Suspended sediment, transport formulas, Main Outfall Drain.

The aim for this paper is to optimize the water quality indicator which is the sewage effluent from aeration process in Wastewater Treatment Plant (WWTP) process by using hybrid Artificial Immune System (AIS) algorithm. The effluents are including dissolved oxygen (DO) and other effluents such as biochemical oxygen demand (CBOD), concentration of suspended solids (TSS), dissolved phosphorous (TDP) and suspended phosphorous (TSP). The proposed algorithms will be applied into model of aeration process in practical of WWTP process in this paper. The proposed AIS algorithms are named as Transform of Artificial Immune System (TRANSAIS) and Cross Three Parents of Artificial Immune System (X3PAIS). The two models are tested under the similar condition such as generation number, size of population, rate of cloning process, rate of mutation process, crossover rate and stopping condition. The concentration of the effluents will affect the water quality and energy consumption during WWTP process. The optimize indicators results from this paper will be used in the next research to optimize the energy consumption in WWTP process.
Keywords: Aeration Process, Artificial Immune System, Genetic Algorithm, Optimization, Wastewater Treatment Plant Process

he recent orientation in transportation development is based on the criteria of sustainability especially in developed high-income countries and they depended in transportation development on the green engineering. Iraq is one of countries that based on the traditional orientation in transport development where other conditions assist in applying this orientation such as security issues and environmental conditions. One of the major factors contribute to more efficient and safe transportation traffic system is accessibility management. This research study the spatial and temporal variation of travel speed and developed a travel speed model using statistical SPSS software (ver.21). It can observed that the distribution of travel speed at region I and region II with different land uses for 2016,2017,2018 and 2019 years respectively. The average travel speed increased significantly at 2018 and 2019 for region I and the distribution of travel speed for region II is skewed to the right, which indicated that the maximum travel speed, and most of drivers’ exhibit greater speed than its mean value. Also a negative effect on average travel speed for region I and II is observed and a reduction of 11% and 7% are obtained for region I and II. The transportation accessibility management resulted in an increase of 45% and 49% for travel speed at 2018 and 2019 years respectively. This provided that the access management increased and maintained the desired speed with reduced delays. This research demonstrated the effectiveness of travel speed model on two component, access points and mixed land use using linear multiple regressions model. A travel speed model with correlation coefficients R and R2 of 0.827 and 0.685 respectively is obtained. The verification of the regression model is based on the correlation coefficient (R2) of 0.789 between the observed travel speed and estimated travel speed as the goodness of fit of the predicted model.
Keywords: Travel Speed, Access Points, Arterial, Accessibility Management, Sustainability, Green Engineering, Multiple Regression.

The current research aims to examine the feasibility of production of biodiesel with non-edible mixed oils, Ceiba Pentandra Oil (CPO) and Rice Bran Oil (RBO).Several blends of CPO and RBO, ranging from 10:90 to 50:50% w/w were put under evaluation. The transesterification process variables of CP50RB50 as the suitable blend using exposure surface methodology, they were enhanced (RSM). The proportion of methanol to gasoline, the time of reaction and the concentration of the catalyst were both the key process parameters tested.An response surface transesterification process conditions such as KOH catalyst concentration are preferable: 0.83 percentage wt, methanol to oil ratio: 55.36%, reacted for 18.58 min18.58 min, with methyl ester yield of 98.7 %. The result indicates that the CP50RB50 methyl ester properties satisfy the biodiesel requirements as laid in standards, ASTM D6751 and EN 14214.
Keywords: Biodiesel, Ceibapentandra, rice bran, mix oil, optimization, RSM

Al- Gharraf River is one of the Tigris River branches, it is flowing within Wasit and Dhi Qar Governorates. The river's total length is 230 km. It is the main source of water for the cities along it extends. So, the quality of the river needs to be monitored continuously. Accordingly, a water quality model was developed by implementing HEC-RAS software to predict the values of some water quality parameters along Al-Gharraf River during different seasons. The water quality model was calibrated and validated using collected data from previous studies.In the first 58 km of the river and during high flow or wet season, the Carbonaceous Biochemical Oxygen Demand is bounded between 8 to 10 mg/l which was considered acceptable, but these values were increased during the low flow or dry season to 11 and 15 mg/l and it was not within the standard. While the values of Carbonaceous Biochemical Oxygen Demand for the lower part of the river (from 58 to 230)km ranged between 11 to 24 mg/l during the wet season and 15 to 27 mg/l during the low discharge season or dry season, for both seasons the Carbonaceous Biochemical Oxygen Demand levels in the lower part of the river were not within the suitable range. The values of Dissolved Oxygen ranged from 7 to 8.2 mg/l during the high flow season and 7 to 6 mg/l in low flow season. While the values of Nitrate are 4.1 to 4.78 mg/l during the high flow period and 5.1 to 7.5 mg/l during the low flow period. Moreover, the values of Phosphate are ranged from 0.13 to 0.62 mg/l during the high flow period and 0.2 to 0.72 mg/l during the low flow period. In general, the values of Dissolved Oxygen, Nitrate, and Phosphate were within the allowable limits in all seasons.
Keywords: HEC-RAS Simulation, Water quality, Gharraf River, CBOD, DO, NO3, PO4.

Agency for Standardization and Quality Control, Standard No, (417) 2nd modification, drinking water, 2009.

The power system is facing new challenges with anticipated higher penetration of Renewable Energy (RE) resources. Among others, Solar Power, other RE resources such as mini hydro, biomass, biogas and Battery Energy Storage System (BESS) is gaining popularity in terms of deployment. Virtual Power Plant (VPP) is relatively new concept of combining RE resources including BESS to serve as one power plant and able to be controlled by an aggregator system. VPP enhanced by BESS is capable in serving few utility and customers challenges. It has been identified that BESS can serve few applications such as to cut peak demand, energy arbitrage, spinning reserve, frequency regulation, and reducing the intermittency of renewable resources. It is foreseen that the role of BESS can be crucial with a higher increase of RE penetration of power system. This paper will cover technical and non-technical requirements for BESS and VPP development.
Keywords: Renewable Energy, Virtual Power Plant (VPP), Battery Energy Storage System (BESS),

Chaos Shift Keying (CSK) is the main notion in this paper. CSK is the critical point of a Frequency-division multiplexing (FDM) system with a nonlinear satellite transponder. The effectiveness of the chaos in the security of satellite transmission with Quadrature Phase Shift Keying (QPSK) modulation at a symbol of 8MSymbols/second can be taken for consideration in this paper. The given information to transmit is decomposed into four combinations. We use four chaotic attractors to permute each data: quadratic map, Bernoulli’s map, logistic map, tent map so the main idea of CSK system is to alternate the transmitted information between these four attractors in the goal to have a secured communication without any interception.
Keywords: Chaos, Chaotic maps, CSK, Satellite, and numerical transmission.

The design of next Vehicular Ad-hoc Network (VANET) in various technologies will offer seamless connectivity across different coverage. However, VANET's vertical handover (VHO) decision in seamless connectivity is a huge challenge caused by the network topology complexity. Furthermore, the conventional scheme only uses a received signal strength as a metric value, which shows a lack of appropriate handover metrics that is more suitable in horizontal handover compared to VHO. This study aims to design an intelligent network to minimize the handover delay and latency, and packet loss in the heterogeneous Vehicle-to-Infrastructure (V2I) wireless networks. The proposed intelligent-based scheme uses Fuzzy Logic (FL) that generates multiple attributes parameters using the information context of vertical handover decision in the V2I heterogeneous wireless networks. This study uses a network simulator as the mobility traffic network and vehicular mobility traffic generator to perform a topology in a realistic VANET mobility scenario via Wi-Fi, WiMAX, and LTE networks technologies. The proposed intelligent scheme shows an improvement in the QoS handover over the conventional (RSS-based) scheme with an average QoS increased of 21%, 20%, and 13% in delay, latency and packet loss, while Media Independent Handover based (MIH-based) scheme with 12.2%, 11%, and 7% respectively. The proposed scheme assists the mobile user enhanced the QoS handover during the vehicles’ movement without degrading the performance of ongoing applications.
Keywords: Vehicle-to-Infrastructure, Fuzzy logic, Received signal strength, Vertical handover decision, Media independent handover

Internet of Things (IoT) and cloud computing are two connected areas that rely on each other from which physicians track and assist remote patients. Successful treatment of diseases includes a model equipped with IoT for the identification of diseases. Computer-aided diagnostics are becoming more popular in all fields of pharmaceuticals, including ophthalmology, with the improvement of image recognition and effective machine learning techniques. This approach continue to offer systematic and effective large-scale testing of a range of picture methods to help medical professionals in the identification of diseases. Subsequently, the optic nerve is the maximum vital component of the retinal fundus picture for the diagnosis of glaucoma. This article suggests a two-phase structure that initially recognises and separates the optic disc and ultimately categorises it into glaucoma or stable. The initial step will focus on the RCNN (Regions with Convolutional Neural Network) and will be accountable for defining and isolating the optical nerve head from the retinal fundus signal. At the same time, deep learning strategies are used in the second process to categorise the mined disc into glaucoma or stable. In addition, a rule-based semi-automatic ground truth generation approach is also developed that provides important interpretations to train the RCNN-based model for automatic disc localization. Area under the Receiver Operational Characteristic Curve is achieved for the classification of glaucoma equivalent to 0.874, which reflects a relative improvement of 2.7% over the recent results already observed for the classification of the ORIGA data set. For data sets without pre-determined test and training splits and with class disparity, the experimental assessment of the classification of glaucoma on ORIGA reveals that the exposure of AUC (Area Under the Curve) alone does not disclose an accurate picture of the performance of the classifier and calls for additional performance tests to validate the effects.
Keywords: IoT, Area Under the Curve, Regions with Convolutional Neural Network, Automatic Detection of Glaucoma Disease, Deep Learning Techniques.

Infrastructure asset management is one of the major concerns in Tenaga Nasional Berhad (TNB). Failure of any transmission tower would cause disruption in power supply affecting a huge area, huge economic losses to TNB, and danger to maintenance workers and the public. Thus, efficient maintenance and management system for transmission towers is crucial. To monitor the transmission towers and lines condition, a group of researchers and engineers in TNB have embarked on a research to formulate a systematic framework to determine indicator statuses of power transmission lines and a web-based system to monitor the transmission lines and cables conditions based on the statuses. The system is known as TNB Transmission Line and Cables Health Index (LCHI). In LCHI, the elements to determine condition of transmission lines and cables are insulator, conductor, spacer/damper, mid-span joint, tower footing resistance, right of way, ground clearance, slope condition, bracing and crossarm, cross-linked polyethylene cable and oil-filled cable. These elements can be classified into three components: electrical/mechanical, surrounding environment and structural. This paper explains the health index determination framework and the evolutionary prototyping approach adopted to develop the system. Also, it explains the process flow, components and elements used to determine health index of the transmission lines and cables. This is followed by explanation on the context and main features of LCHI system. In the energy sector generally, the system plays an important role in prioritizing maintenance, refurbishing or replacing transmission towers to avoid power supply disruption.
Keywords: Transmission lines, transmission towers, transmission cables, health index, condition rating.

VANETS are treated as one of the greater well-known technologies for enhancing the efficiency and protection of modern transportation schemes. The issue in SCRP (stable CDS-based routing protocol) computes the end-toend delay for the entire routing path before sending a data message. To overcome this issue, we proposed E-BDSC (extended bi-directional stable communication) protocol with timer based Broadcast Storm Suppression Algorithm. This protocol broadcast the HELLO packets to find the link quality ratio is used to permit/restrict nodes depends upon the link as becoming the next rely node for forwarding the alert message and also it reduces the unwanted flooding of message leading to broadcast storm problem. Our analytical and experimental results show that the link quality between the source and destination has been increased with decrease in unwanted flooding/bandwidth, message loss and E2E Delay.
Keywords: ACNL List, Alert message, Bandwidth, BSSA, duty cycle, Endto-End delay, HELLO Packets, Link Quality Ratio

Advance technologies in today’s world gradually developing and bringing many innovative products and findings. One of the improving technologies of all time are energy harvesting. With a massive amount of external sources, energy harvesting can be a prominent and alternative solution to provide power supply without batteries in a more cost effective at the same time environment friendly way. In this paper, a new method of harvesting electric field under 275kV transmission line is applied by using innovative design of non-contact electric field energy harvester (EFEH). Seven significant design parameters such as the capacitance of the harvester, the material and thickness of harvester and the surface nature of the harvester are examined and improved step by step ensuring an efficient, cost effective and less complaicated EFEH design. ANSYS Maxwell software is used to simulate, analyse and compare the electric field captured on each designs. In order to support the electric field simulations of all the harvester designs, EFEH prototypes are built and tested under a 275kV electrical transmission lines surroundings. A maximum of 14.5V of AC voltage from the harvester and 7uW of output power is recorded from the most efficient EFEH design using a simple half wave rectifier 10uF capacitor in filter. The proposed EFEH can be implemented to energize low powered sensors that are used to monitor conditions of electrical transmission lines and the vicinity surrounding the tower especially in areas that cannot be easily accessed by people.
Keywords: Power transmission line; Capacitance; Electric field; Electric field energy harvesting; Non-contact.

This paper introduces renewable fed power system for the unbalanced loads like induction loads because of the pollution level created due to the CO2, CO and other toxic gases that got out from the non-grid power generating stations (i.e.) diesel and coal plant etc. For the utilization of the renewable the wind turbine system is used along with the MP point tracking system is designed in addition with closed loop control scheme. The MP point tracking system is used to get the high performance source utilization from the wind turbine. For the non-linear load utilization the load side inverter is designed with the rated power rating. The PMSG motor is the rotor side motor and it its designed by the vertically aligned wind arrangement scheme. By implementing the above statements the power factor is improved unity with variable rotor speed conditions.
Keywords: MP Point Tracking Control, PMSG, Grid, Non Linear Load, WES.

Grid tied system with non-transformer inverter is implemented in wide range of PV applications due to their benefits of high efficient and lower investment. More over the use of non-transformer inverters have isolation from main system addressing specific problems with constant voltage on the PV panels. In order to eliminate the leakage current and non-isolated grid synced system eliminates the high frequency with negative PV terminal to mains commutating on the frequency. The proposed model has 4 power switches. The inverter has an ability to achieve the shape controlled PWM for the MP-Point tracking from the PV panel arrays.
Keywords: Transformer less Grid Tie Inverter, Photovoltaic, Power Factor, Maximum Power Point Tracking.

Ultrasonic non-destructive techniques have been successfully used for assessment of internal damage in concrete structures for a long time. The conventional ultrasonic pulse velocity test is a linear method and not sensitive to micro-cracks or early age defects. This research focuses on nonlinear ultrasonic technique based on third harmonic generation. In this paper concrete specimens were subjected to compressive loading and ultrasonic evaluation was done in several steps. Ultrasonic signals were analysed both in time and frequency domains. The amplitude of fundamental and third harmonics was measured and nonlinear ultrasonic parameter was obtained. The experimental results show that nonlinear ultrasonic parameter increases with increasing level of internal micro-cracks. The results also suggest that nonlinear ultrasonic method based on third harmonic generation is more sensitive and accurate in monitoring micro-structural change in concrete than ultrasonic pulse velocity technique.
Keywords: Concrete, Micro-cracks, Nonlinear ultrasonic, Harmonics

Generally, in an open air environment placing of the large sensor networks randomly can result a small coverage. Therefore for these sensor networks, coverage factor is playing as a significant role for the improvement of performance which reflecting the monitoring quality of a sensor array. The deployment of sensor nodes also plays an important role in Wireless sensor networks (WSN) because of the collective information preset at each sensor node. A review of placing and monitoring of sensor nodes in the wireless sensor networks is presented in this paper with the two algorithms which maximize the coverage area and optimize the localization of audio in wireless sensor networks. Firstly, a generalized harmony search algorithm is reviewed which is a metaheuristic algorithm for solving optimization quandaries to amend the coverage of wireless sensor networks. Secondly, a Virtual Force Algorithm (VFA) is described as a coverage optimization algorithm for a wireless sensor network in the surveillance area.The simulation results for the both algorithms are illustrated that the Harmony search algorithm outperforms than existing algorithms, where as VFA algorithm shows an improved optimization effect on uniformity and coverage rate the sensor nodes that optimize the network coverage of wireless sensors than other algorithms
Keywords: Wireless sensor networks, maximum coverage area, Harmony Search Algorithm and Virtual Force algorithm

Aviation is one of the high value-added and well-regulated industry. During the design and manufacturing phase, the aircraft manufacturing companies are focusing on the follow-on-support stage. A commercial aircraft's lifespan is about 35 years depending on the operation conditions. When an airline operation company pays 1 unit to purchase an aircraft, support operations are approximately three times the initial purchase price. In other words, 4 units will be paid totally at the end of the life cycle by the airliner company. In this study, the relationship between the manufacturing and maintenance phase is investigated. It has been found that even a tiny difference that has been done during the manufacturing phase has vital importance on Life Cycle Cost (LCC).
Keywords: Aircraft Maintenance, Intervals, Maintenance Phases, Aircraft Life Cycle, Airborne

Design reliability requirements are growing rapidly to cope with design complexity and process challenges. Common design specifications are qualified against process corners, known as PVT (process, voltage, and temperature), are getting more complex. Bias, bandgap, circuit is one of the critical building blocks which compensates for both supply fluctuations and temperature variations. In these bias circuits, the incorporated temperature compensation techniques are usually based on first or second order approximations which reduce the temperature validity range. Beyond this validity range, the biasing reference voltage gets dominated by nonlinearities and becomes temperature dependent. The impact of these nonlinearities is amplified by the effect of thermal gradient across the chip which causes both soft and hard silicon failures. This work proposes an on-chip temperature sensing and holding mechanism that extends the bias temperature compensation validity range by keeping the chip in thermal equilibrium and avoiding thermal gradient and skewness. This work leverages a geometrical-based thermal symmetry and gradient verification approach that allows even placement and distribution of thermal heaters in low voltage (LV) areas to compensate for hot regions across the chip. The flow has been implemented on a voltage regulator test chip and demonstrated reliability improvements.
Keywords: thermal equilibrium, biasing validity range, thermal gradient, heaters.