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Improved Control in Single Phase Inverter Grid-Tied PV System Using Modified PQ Theory

Intelligent Automation & Soft Computing 2023年第8期37卷 2441-2457页

作者： Nur Fairuz Mohamed Yusof Dahaman ishak Muhammad Ammirrul Atiqi Mohd Zainuri Muhammad Najwan Hamidi Zuhair Muhammed Alaas Mohamed Mostafa Ramadan Ahmed Faculty of Electrical Engineering&Technology Universiti Malaysia Perlis02600ArauMalaysia School of Electrical&Electronic Engineering Universiti Sains Malaysia14300Nibong TebalMalaysia Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaSelangor43600Malaysia School of Engineering Jazan UniversityJazanSaudi Arabia Faculty of Technology and Education Helwan UniversityCairoEgypt

Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic(PV)grid-connected systems *** research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total har-monic distortion(THD)even under nonlinear load applications by improving its control *** proposed system is expected to operate in both stand-alone mode and grid-connected *** stand-alone mode,the proposed controller supplies power to critical loads,alternatively during grid-connected mode provide excess energy to the utility.A modified variable step incremental conductance(VS-InCond)algorithm is designed to extract maximum power from *** the proposed inverter controller is achieved by using a modified PQ theory with double-band hysteresis current controller(PQ-DBHCC)to produce a reference current based on a decomposition of a single-phase load *** nonlinear rectifier loads often create significant distortion in the output voltage of single-phase inverters,due to excessive current harmonics in the ***,the proposed method generates a close-loop reference current for the switching scheme,hence,minimizing the inverter voltage distortion caused by the excessive grid current *** simulation findings suggest the proposed control technique can effectively yield more than 97%of power conversion efficiency while suppressing the grid current THD by less than 2%and maintaining the unity power factor at the grid *** efficacy of the proposed controller is simulated using MATLAB/Simulink.

关键词： Hysteresis current controller incremental conductance nonlinear load PQ theory single-phase inverter

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Determination of Iron Content of Three Common <i>Acacias</i>of Sudan

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American Journal of Analytical Chemistry 2015年第12期6卷 933-938页

作者： Isam Eldin Hussein Elgailani Christina Yacoub ishak Department of Chemistry Faculty of Science University of Khartoum Khartoum Sudan

The amount iron content of the extracts and samples of Acacia species was determined. Since the iron hinders the process of retanning leather, iron content is determined by wet digestion method and atomic absorption spectrophotometry. The iron contents of bark extract of Acacia nilotica, Acacia senegal and Acacia seyal were 0.0044%, 0.0040% and 0.0029% respectively. In contrast, the iron content of bark extract of the three species of Acacia had lower percentage compared to that of Mimosa (Acacia mearnsii) (0.0047%), which was imported from Kenya. The iron content presented in leaves, barks, mature and immature fruits of Acacia species were determined by the same analytical methods. Bark and mature fruits of Acacia nilotica had the highest and equal percentage (0.1450%). The percentage of iron content of leaves and bark of Acacia seyal had equal percentage (0.0750%), while the bark of Acacia senegal had much lower percentage (0.0375%).

关键词： Acacia Species Sudan Iron Content AAS

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Real Time Controller System for Lowland Tropical Greenhouse

Real Time Controller System for Lowland Tropical Greenhouse

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亚洲精细农业与计算机农业应用联合大会

作者： Wan ishak Wan Ismail Nurul Hanizah Faculty of Engineering Universiti Putra Malaysia

The environmental problem faced by the tropical countries like Malaysia is due to the high relative humidity and temperature of the outside air, which increase the ambient humidity and temperature of the greenhouse. In lowland greenhouse, it is possible that the air temperature can be decreased to the desired value by mixing with a certain amount of dried-cooled air from a cooling source The Vapor Pressure Deficit （VPD） analysis introduces an approach to develop a better basis of environment control for lowland greenhouse in Malaysia. The VPD software for the greenhouse control system was developed using the studies of VPD which can be used to identify air moisture conditions for plant production while taking into account different temperature levels. Vapor Pressure Deficit functions as a convenient indicator of the condensation potential as it quantifies how close the greenhouse air is to saturation. The concepts of VPD can be used to establish set points for temperature and relative humidity, which are two important environmental factors influencing the growth and development of greenhouse crops. The real-time controller using a PIC16f876A was developed to maintain the ideal Vapor Pressure Deficit （VPD） inside the lowland tropical greenhouse located at the Universiti Putra Malaysia. A LM35 3-pin temperature sensor was connected to a microcontroller to determine the temperature in the greenhouse for required time and period. This device can measure temperature from 2 0 C up to 100 0 C and the output voltage temperature relationship is 10mV/ 0 C. The humidity sensor that was used in this project is HH10D. It is a frequency output type sensor that can be easily integrated with user application system. Cooling is required to decrease the ambient temperature and adjust the relative humidity level inside greenhouse. Greenhouse cooling reduces plant stress caused by high leaf and air temperatures Evaporative cooling systems are used in conjunction with mechanical ventila

关键词： Greenhouse Microcontroller Vapor Pressure Deficit (VPD) Temperature Relative humidity PIC16f876A LM35 temperature sensor HH10D humidity sensor

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Forensic profiling of non-volatile organic compounds in soil using ultra-performance liquid chromatography:a pilot study

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Forensic Sciences Research 2022年第4期7卷 761-773页

作者： Loong Chuen Lee Ab Aziz ishak Ameeta A/P Nai Eyan Anas Fahmi Zakaria Nurul Syahiera Kharudin Nor Azman Mohd Noor Program of Forensic Sciences Centre for DiagnosticTherapeutic&Investigative StudiesFaculty of Health SciencesUniversiti Kebangsaan MalaysiaBangiMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiMalaysia Makmal Forensik Polis DiRaja Malaysia(PDRM) CherasMalaysia

Soil is of particular interest to the forensic community because it can be used as valuable associative evidence to link a suspect to a victim or a crime *** chromatography is a powerful analytical tool for organic compound ***,high-performance liquid chromatography(HPLC)has proven to be an efficient method for forensic soil analysis,especially in discriminating soils from proximity ***,ultra-performance liquid chromatography(UPLC),which is much more sensitive than HPLC,has never been explored in this *** study proposed a UPLC method for profiling non-volatile organic compounds in three Malaysian soils(red,brown and yellowish-brown soils).The three soils were analysed separately to assess the effects of individual chromatographic parameters:(a)elution programme(isocratic *** gradient programmes);(b)flow rate(0.1 vs.0.2 mL/min);(c)extraction solvent(acetonitrile ***)and(d)detection wavelength(230 vs.254 nm).The injection volume and total run time were set to 5μL and 35 min,***,each soil sample gave 24 different *** showed that the most desirable chromatographic parameters were(a)isocratic elution;(b)flow rate at 0.2 mL/min and(c)acetonitrile extraction *** proposed UPLC system is expected to be a feasible method for profiling non-volatile organic compounds in soil,and is more chemical-efficient than a comparable HPLC system.

关键词： Forensic sciences soil non-volatile organic compound liquid chromatography

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Earthworm Optimization with Improved SqueezeNet Enabled Facial Expression Recognition Model

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Computer Systems Science & Engineering 2023年第8期46卷 2247-2262页

作者： N.Sharmili Saud Yonbawi Sultan Alahmari E.Laxmi Lydia Mohamad Khairi ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa Computer Science and Engineering Department Gayatri Vidya Parishad College of Engineering for WomenVisakhapatnamAndhra PradeshIndia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Facial expression recognition(FER)remains a hot research area among computer vision researchers and still becomes a challenge because of high intraclass *** techniques for this problem depend on hand-crafted features,namely,LBP,SIFT,and HOG,along with that a classifier trained on a database of videos or *** execute perform well on image datasets captured in a controlled condition;however not perform well in the more challenging dataset,which has partial faces and image ***,many studies presented an endwise structure for facial expression recognition by utilizing DL ***,this study develops an earthworm optimization with an improved SqueezeNet-based FER(EWOISN-FER)*** presented EWOISN-FER model primarily applies the contrast-limited adaptive histogram equalization(CLAHE)technique as a pre-processing *** addition,the improved SqueezeNet model is exploited to derive an optimal set of feature vectors,and the hyperparameter tuning process is performed by the stochastic gradient boosting(SGB)***,EWO with sparse autoencoder(SAE)is employed for the FER process,and the EWO algorithm appropriately chooses the SAE ***-ranging experimental analysis is carried out to examine the performance of the proposed *** experimental outcomes indicate the supremacy of the presented EWOISN-FER technique.

关键词： Facial expression recognition deep learning computer vision earthworm optimization hyperparameter optimization

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Quality Improvement of Sudanese Petrodiesel Fuel by Furfural

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American Journal of Analytical Chemistry 2017年第5期8卷 355-369页

作者： Christina Yacoub ishak Elfatih A. Hassan Mohamed Ezeldin Department of Chemistry Faculty of Science University of Khartoum Khartoum Sudan Department of Chemistry Faculty of Science Sudan University of Science and Technology Khartoum Sudan Department of Chemistry Faculty of Science and Technology Omdurman Islamic University Khartoum Sudan

The main objective of this project is quality improvement of Sudanese petrodiesel fuel by the use of furfural. The Gas Chromatography Mass Spectrometry GC/MS technique was performed to analyze organic compounds for marked petrodiesel fuel before and after treatment by furfural, physicochemical characteristics of petrodiesel fuel were investigated before and after treatment according to American Society for Testing and Materials (ASTM), characteristics include: density, distillation, cloud point, viscosity, ash content, micro carbon residue, water content, flash point, colour, copper strip corrosion, sulfur content and calculated cetane number. Elements composition of petrodiesel sample has been determined by Inductively coupled plasma (ICP). The furfural showed high ability in extraction of aromatic, cyclo and branched hydrocarbons, a total of 81 organic compounds that exhibit a negative effect on quality of petrodiesel have been removed by furfural. All physicochemical characteristics of petrodiesel fuel were improved within permissible limits assigned by ASTM. The furfural has shown no effect on colour of Sudanese Petrodiesel, which cetane number has increased from 54.46 to 58.36. The concentration of Na, Mg, Ca, Fe, Al and As have been decreased after treatment by furfural, these results have led to decrease of ash content.

关键词： Sudanese Petrodiesel Furfural Khartoum Refinery

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Identification of Paddy Planted Area Using ALOS PALSAR Data

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Journal of Geographic Information System 2011年第4期3卷 351-356页

作者： Rizatus Shofiyati ishak Hanafiah Ismullah Dan Dudung Muhally Hakim Indonesian Center for Agricultural Land Resources Research and Development (ICALRD) Indonesian Ministry of Agriculture Bandung Institute of Technology (ITB)

Agricultural land has a strategic function as the primary food provider for the people of Indonesia. Various methods of agricultural production estimation, particularly food crops, provide different information. It can be a source of error in decision making. Satellite data, provides information periodically, wide coverage area, can be used as a source of information on the condition of agricultural lands and even remote areas. The advantages of SAR data that does not depend on sunlight and can penetrate of clouds and fog can fill the lack of optical data. ALOS PALSAR data has been used for analysis and ALOS AVNIR-2 is for checking of land cover visually, with acquisition date on 10 May 2007. Sampling of each rice crop growth period used several of rice field conditions in each period, on one scene data. Results showed a possibility to use soil moisture conditions derived from ALOS PALSAR for estimating rice planting area. On a scatter diagram between backscatter of ALOS PALSAR and near infrared of ALOS AVNIR-2 showed a specific pattern for each growing period of paddy. The results of the analysis produce distribution maps of the rice planting area Subang area, West Java Province. However, validation of the method used remains to be done. Remote sensing results of this study are expected to provide better information and can contribute in the planning of higher quality agricultural land.

关键词： Rice Planting Area Moisture Content ALOS PALSAR

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Hybrid Multi-Strategy Aquila Optimization with Deep Learning Driven Crop Type Classification on Hyperspectral Images

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Computer Systems Science & Engineering 2023年第10期47卷 375-391页

作者： Sultan Alahmari Saud Yonbawi Suneetha Racharla ELaxmi Lydia Mohamad Khairi ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa King Abdulaziz City for Science and Technology P.O Box 6086Riyadh 11442Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of AIML Aditya Engineering CollegeSurempallemAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed *** spatial information and spectral signatures of hyperspectral images(HSIs)present greater potential for detecting and classifying fine *** accurate classification of crop kinds utilizing hyperspectral remote sensing imaging(RSI)has become an indispensable application in the agricultural *** is significant for the prediction and growth monitoring of crop *** the deep learning(DL)techniques,Convolution Neural Network(CNN)was the best method for classifying HSI for their incredible local contextual modeling ability,enabling spectral and spatial feature *** article designs a Hybrid Multi-Strategy Aquila Optimization with a Deep Learning-Driven Crop Type Classification(HMAODL-CTC)algorithm *** proposed HMAODL-CTC model mainly intends to categorize different types of crops on *** accomplish this,the presented HMAODL-CTC model initially carries out image preprocessing to improve image *** addition,the presented HMAODL-CTC model develops dilated convolutional neural network(CNN)for feature *** hyperparameter tuning of the dilated CNN model,the HMAO algorithm is ***,the presented HMAODL-CTC model uses an extreme learning machine(ELM)model for crop type classification.A comprehensive set of simulations were performed to illustrate the enhanced performance of the presented HMAODL-CTC *** comparison studies reported the improved performance of the presented HMAODL-CTC algorithm over other compared methods.

关键词： Crop type classification hyperspectral images agricultural monitoring deep learning metaheuristics

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Phenetic Analysis of Morphological and Molecular Traits in Acanthaceae Juss

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Journal of Biosciences and Medicines 2015年第3期3卷 18-34页

作者： Usama K. Abdel-Hameed Mohamed E. Tantawy Mohamed A. Salim Magdy M. Mourad ishak F. ishak Botany Department Faculty of Science Ain Shams University Cairo Egypt

Acanthaceae has received considerable taxonomic attention at the familial, subfamilial, tribal and subtribal levels. Several different infra-familial classifications have been proposed for the Acanthaceae, but no taxonomic consensus has yet been reached. The main objective of the present study is to throw light on the phenetic relationships and to explore the contribution of morphological and molecular characters in systematics of Acanthaceae. The morphological data viz. macromorphology, stomatography, lamina architecture and ISSR profiles of 30 Egyptian acanthaceous taxa were investigated. The phenetic analysis using NTSYS-PC version 2.02 software based on 55 potentially informative morphological and molecular characters indicated that the used morphological and ISSR criteria is likely to be useful and valuable taxonomic traits. The morphological characters and ISSR aspects of all the studied species produced a phenogram that showed two series;one of them had two subseries, the first one comprised only three taxa while the second divided into two clusters, each contained two groups. The delimitation and the membership of the studied taxa clearly merit additional study using more criteria. The phenetic analysis of both morphological and molecular attributes clarified the segregation of genus Avicennia as a distinct identity away from Acanthaceae. Acanthus mollis & A. montanus are isolated in its own series that comparable to tribe Acantheae of the current taxonomic systems. The studied species of Thunbergia are gathered its own subseries that comparable to tribe Thunbergiae and Ruellia in its own group that comparable to tribe Ruellieae.

关键词： Phenetic Analysis Numerical Taxonomy Morphology ISSR Acanthaceae

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Application of Artificial Neural Network in Predicting Crop Yield： A Review

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Journal of Food Science and Engineering 2014年第1期4卷 1-9页

作者： Siti Khairunniza-Bejo Samihah Mustaffha Wan ishak Wan Ismail Department of Biological and Agricultural Engineering Faculty of Engineering Universiti Putra Malaysia Serdang 43400Selangor Malaysia

Agricultural system is very complex since it deals with large data situation which comes from a number of factors. A lot of techniques and approaches have been used to identify any interactions between factors that affecting yields with the crop performances. The application of neural network to the task of solving non-linear and complex systems is promising. This paper presents a review on the use of artificial neural network （ANN） in predicting crop yield using various crop performance factors. General overview on the application of ANN and the basic concept of neural network architecture are also presented. From the literature, it has been shown that ANN provides better interpretation of crop variability compared to the other methods.

关键词： Artificial intelligent artificial neural network crop yield prediction.

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