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An asymmetrical multilevel inverter with minimum voltage stress and fewer components for photovoltaic renewable-energy system

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CLEAN ENERGY 2024年第1期8卷 1-22页

作者： memon, rabail Mahar, Mukhtiar Ahmed Larik, Abdul Sattar Shah, Syed Asif Ali Mehran Univ Engn & Technol Dept Elect Engn Jamshoro Pakistan

The enhanced power quality provided by multilevel inverters (MLIs) has made them more appropriate for medium- and high-power applications, including photovoltaic systems. Nevertheless, a prevalent limitation involves the necessity for numerous switches and increased voltage stress across these switches, consequently increasing the overall system cost. To address these challenges, a new 17-level asymmetrical MLI with fewer components and low voltage stress is proposed for the photovoltaic system. This innovative MLI configuration has four direct current (DC) sources and 10 switches. Based on the trinary sequence, the proposed topology uses photovoltaics with boost converters and fuzzy logic controllers as its DC sources. Mathematical equations are used to calculate crucial parameters for this proposed design, including total standing voltage per unit (TSVPU), cost function per level (CF/L), component count per level (CC/L) and voltage stress across the switches. The comparison is conducted by considering switches, DC sources, TSVPU, CF/L, gate driver circuits and CC/L with other existing MLI topologies. The analysis is carried out under various conditions, encompassing different levels of irradiance, variable loads and modulation indices. To reduce the total harmonic distortion of the suggested topology, the phase opposition disposition approach has been incorporated. The suggested framework is simulated in MATLAB (R)/Simulink (R). The results indicate that the proposed topology achieves a well-distributed stress profile across the switches and has CC/L of 1.23, TSVPU of 5 and CF/L of 4.58 and 5.76 with weight coefficients of 0.5 and 1.5, respectively. These values are notably superior to those of existing MLI topologies. Simulation results demonstrate that the proposed topology maintains a consistent output at varying irradiance levels with FLCs and exhibits robust performance under variable loads and diverse modulation indices. Furthermore, the total harmonic disto

关键词： asymmetrical multilevel inverter photovoltaic system renewable energy component count per level cost function per level total standing voltage per unit phase opposition disposition technique CONVERTER TOPOLOGY REDUCED NUMBER IMPLEMENTATION PERFORMANCE CONNECTION REDUCTION DESIGN SINGLE

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Benchmarking YOLOv5 models for improved human detection in search and rescue missions

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Journal of Electronic Science and Technology 2024年第1期22卷 70-80页

作者： Namat Bachir Qurban Ali memon Electrical Engineering Department College of EngineeringUnited Arab Emirates UniversityAl Ain15551United Arab Emirates

Drone or unmanned aerial vehicle(UAV)technology has undergone significant *** technology allows UAV to carry out a wide range of tasks with an increasing level of sophistication,since drones can cover a large area with ***,the increasing number of computer vision applications utilizing deep learning provides a unique insight into such *** primary target in UAV-based detection applications is humans,yet aerial recordings are not included in the massive datasets used to train object detectors,which makes it necessary to gather the model data from such *** only look once(YOLO)version 4,RetinaNet,faster region-based convolutional neural network(R-CNN),and cascade R-CNN are several well-known detectors that have been studied in the past using a variety of datasets to replicate rescue ***,we used the search and rescue(SAR)dataset to train the you only look once version 5(YOLOv5)algorithm to validate its speed,accuracy,and low false detection *** comparison to YOLOv4 and R-CNN,the highest mean average accuracy of 96.9%is obtained by *** comparison,experimental findings utilizing the SAR and the human rescue imaging database on land(HERIDAL)datasets are *** results show that the YOLOv5-based approach is the most successful human detection model for SAR missions.

关键词： Unmanned aerial vehicle(UAV) Search and rescue(SAR) You look only once(YOLO)model You only look once version 5 (YOLOv5)

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Development of Sustainable Wireless Resource model through Shrewd Neural Network

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Data Intelligence 2024年第3期6卷 649-665页

作者： Shahzad Ashraf Furqan memon Fouzia Akram Zeeshan Rasheed Shahzad Sarwar Bhattit Innam Ullah NFC Institute of Engineering and Technology Multan Pakistan DHA Suffa University Karachi Pakistan Mir Chakar Khan Rind University Sibi Pakistan Emerson University Multan Pakistan Gachon University Seongnam 13120Republic of Korea

Due to an increasing number of wireless spectrums,the network components are tangling with multiple frequencies and the result create hindrance in resource management *** resource management process,data leakage is one of the sensitive enigma that requires an astute *** all these issues,a sustainable wireless resource management proposal(DSWR-SNN)has been developed by incorporating a shrewd Neural *** resources are managed by testing performance of each network component connected wirelessly through dataset testing which matches the results from the dataset *** performance of the proposed DSWR-SNN method has been compared with state of the art studies Hopfield Neural Network(HNN),Radio Resource Management(RRM),and Deep Q-Network(DQN),and results are evaluated by conducting simulation using Python with TensorFlow based on Bandwidth Utilization,Duplicate Packet Handling,Data Leakage,and Energy *** result illustrates the marvelous performance of the proposed method and effective in addressing the challenges of resource allocation in wireless communication systems.

关键词： Neural network Sustainable resources Dataset testing Dataset corpus,Data leakage

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A review:Health benefits and physicochemical characteristics of blended vegetable oils

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Grain & Oil Science and Technology 2024年第2期7卷 113-123页

作者： Hina Daud memon Sarfaraz Ahmed Mahesar Sirajuddin Huseyin Kara Syed Tufail Hussain Sherazi Mohammad Younis Talpur National Centre of Excellence in Analytical Chemistry University of SindhJamshoro 76080Pakistan International Center for Chemical and Biological Sciences HEJ Research Institute of ChemistryUniversity of KarachiKarachi 75270Pakistan Department of Chemistry Faculty of ScienceSelcuk UniversityKonya 42075Turkey Dr.M.A.Kazi Institute of Chemistry University of SindhJamshoro 76080Pakistan

Oil blending is the method of choice used worldwide to improve oxidative stability and nutritional *** is no such edible oil/fat that meets all the recommendations from the health point of *** fatty acid composition of vegetable oils decides the fate of the *** single oil is unable to provide a balanced amount of fatty acids(FAs)required/recommended on a daily intake *** oils/fats is an appropriate procedure of physically mixing multiple oils in suitable proportions which may provide functional lipids with improved antioxidant potential and desirable physical and chemical *** review piled up the accessible data on the blending of diverse oils/fats in the combination of binary,ternary,quaternary,or other types of oils into a single blended *** can be found very convincing towards appropriate FA profile,enhancement in physicochemical characteristics,and augmented stability for the period of storage or when used as cooking/frying processes which could ultimately serve as an effectual dietary intervention towards the health protectiveness.

关键词： Vegetable oil Oil blending Physicochemical properties Nutritional benefits

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Research on Iron Loss of Switched Reluctance Starter/Generator for Energy Storage

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Protection and Control of Modern Power Systems 2024年第4期9卷 147-159页

作者： Hao Chen Xing Wang Yongqiang Liu Vuong Dang Quoc Wenju Yan Muhammad Saqib Antonino Musolino Guanjun Wang Yong Qi Ali Asghar memon Alexandros G.Paspatis the Shenzhen Research Institute China University of Mining and TechnologyShenzhen 515100China the School of Electrical Engineering China University of Mining and TechnologyXuzhou 221116China Xinjiang Institute of Engineering Urumqi 830000China the International Joint Research Center of Central and Eastern European Countries on New Energy EV Technology and Equipment Xuzhou 221008China the International Cooperation Joint Laboratory of New Energy Power Generation and EVs of Jiangsu Province Colleges and Universities Xuzhou 221008China the Xuzhou Key Laboratory of New Energy EV Technology and Equipment Xuzhou 221008China the the School of Electrical Engineering China University of Mining and Tech-nologyXuzhou 221116China the Laboratory of High Performance Electric Machines(HiPems) Hanoi VN 10000Viet Nam the University of Engineering and Technology Lahore 54890Pakistan the Department of Energy Pisa Uni-versity of PisaPisa IT 56126Italy the Wuxi Inspection and Testing Certification Research Institute Wuxi 214000China the Nanjing University of Science&Tech-nology Nanjing 210094China the Mehran University of Engi-neering&Technology Jamshoro PK 76062Sindh the National Technical University of Athens Zografou GR 15780Attica

In order to better realize the energy recovery and storage of hybrid EVs(HEVs),a switched reluctance starter/generator(SRS/G)with both starting and power generation functions is investigated in this ***,the iron loss of SRS/G is mainly studied to reduce the motor loss and improve the power generation ***,the energy storage of hybrid EVs can be effectively ***,a magnetic flux density(MFD)waveforms solution method is proposed to solve the difficulty in calculating the iron loss of the SRS/*** with the commonly used finite element method,the proposed solution method has the advantages of simple,fast and small computational ***,considering the different operating conditions of SRS/G,the iron loss models for both the time-domain and frequency-domain are *** addition,the calculation formula of the variable coefficient Bertotti three-term loss separation is *** the hysteresis loss coefficient,the Steinmetz coefficient and the stray loss coefficient are respectively fitted by the Fourier fitting *** method is also applied to solve the iron loss of SRS/***,through an experimental verification,it is indicated that the development of proposed method has high accuracy.

关键词： Switched reluctance starter/generator energy storage iron loss finite element method magnetic flux density(MFD)

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Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

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Intelligent Automation & Soft Computing 2024年第3期39卷 545-566页

作者： Asad Raza Shahzad memon Muhammad Ali Nizamani Mahmood Hussain Shah Dr.AHS Bukhari Postgraduate Centre of Information and Communication Technology Faculty of Engineering and TechnologyUniversity of SindhJamshoro76060Pakistan Newcastle Business School Northumbria UniversityNewcastleNE1UK

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven ***,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the *** signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging ***,there is the need for an IDS which can learn from data and detect new *** Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking *** this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta *** proposed DSNN model was trained and evaluated with the next-generation dataset,TON_*** pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE ***,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble *** experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML *** addition,the model proposed for IDS has been compared with similar *** proposed DSNN achieved better performance metrics than the other *** proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

关键词： Industrial internet of things smart industrial environment cyber-attacks convolutional neural network ensemble learning

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Evaluation of the fishery status for King Soldier Bream Argyrops spinifer in Pakistan using the software CEDA and ASPIC

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Chinese Journal of Oceanology and Limnology 2015年第4期33卷 966-973页

作者： Aamir Mahmood memon 刘群 Khadim Hussain memon Wazir Ali BALOCH Asfandyar memon Abdul BASET College of Fisheries Ocean University of China Sindh Fisheries Department Marine Fisheries Department Fish Harbor west wharf Karachi 74000 Pakistan Department of Fresh Water Biology and Fisheries University of Sindh Department of Economics Management and Quantitative Methods Via Conservatorio7 Universita Degli Studi Di Milano

Catch and effort data were analyzed to estimate the maximum sustainable yield （MSY） of King Soldier Bream, Argyrops spinifer （Forsskal, 1775, Family： Sparidae）, and to evaluate the present status of the fish stocks exploited in Pakistani waters. The catch and effort data for the 25-years period 1985-2009 were analyzed using two computer software packages, CEDA （catch and effort data analysis） and ASPIC （a surplus production model incorporating covariates）. The maximum catch of 3 458 t was observed in 1988 and the minimum catch of 1 324 t in 2005, while the average annual catch ofA. spinifer over the 25 years was 2 500 t. The surplus production models of Fox, Schaefer, and Pella Tomlinson under three error assumptions of normal, log-normal and gamma are in the CEDA package and the two surplus models of Fox and logistic are in the ASPIC package. In CEDA, the MSY was estimated by applying the initial proportion （IP） of 0.8, because the starting catch was approximately 80% of the maximum catch. Except for gamma, because gamma showed maximization failures, the estimated results of MSY using CEDA with the Fox surplus production model and two error assumptions, were 1 692.08 t （R^2=0.572） and 1 694.09 t （R^2=0.606）, respectively, and from the Schaefer and the Pella Tomlinson models with two error assumptions were 2 390.95 t （R^2=0.563）, and 2 380.06 t （R^2=0.605）, respectively. The MSY estimated by the Fox model was conservatively compared to the Schaefer and Pella Tomlinson models. The MSY values from Schaefer and Pella Tomlinson models were the same. The computed values of MSY using the ASPIC computer software program with the two surplus production models of Fox and logistic were 1 498 t （R^2=0.917）, and 2 488 t （R^2=0.897） respectively. The estimated values of MSY using CEDA were about 1 700-2 400 t and the values from ASPIC were 1 500-2 500 t. The estimates output by the CEDA and the ASPIC packages indicate that the stock is overfished, and needs some effective manage

关键词： stock assessment Argyrops spinifer maximum sustainable yield catch and effort data analysis (CEDA) a surplus production model incorporating covariates (ASPIC) Pakistan

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Hyperledger Fabric Blockchain: Secure and Efficient Solution for Electronic Health Records

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Computers, Materials & Continua 2021年第8期68卷 2377-2397页

作者： Mueen Uddin M.S.memon Irfana memon Imtiaz Ali Jamshed memon Maha Abdelhaq Raed Alsaqour Faculty of Science Universiti Brunei DarusslamGadongBE1410Negara Brunei Darussalam CSE Department QUESTNawabshahPakistan School of Computing and Mathematics Ulster UniversityJordanstown CampusNewtownabbeyBT370QBUK Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic UniversityRiyadh93499Saudi Arabia

Background:Electronic Health Record(EHR)systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients ***,the existing EHR systems mostly lack in providing appropriate security,entrusted access control and handling privacy and secrecy issues and challenges in current hospital ***:To solve this delicate problem,we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR ***:In our EHR blockchain system,Peer nodes from various organizations(stakeholders)create a ledger network,where channels are created to enable secure and private communication between different stakeholders on the ledger *** patients and other stakeholders are identified and registered on the network by unique digital certificates issued by membership service provider(MSP)component of the fabric ***:We created and implemented different Chaincodes to handle the business logic for executing separate EHR transactions on the *** proposed fabric architecture provides a secure,transparent and immutable mechanism to store,share and exchange EHRs in a peer-to-peer network of different healthcare *** ensures interoperability,scalability and availability in adapting the existing EHRs for strengthening and providing an effective and secure method to integrate and manage patient records among medical institutions in the healthcare ecosystem.

关键词： Electronic health records blockchain hyperledger fabric patient data privacy private permissioned blockchain healthcare ecosystem

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Fault Detection and Identification Using Deep Learning Algorithms in Induction Motors

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Computer Modeling in Engineering & Sciences 2022年第11期133卷 435-470页

作者： Majid Hussain Tayab Din memon Imtiaz Hussain Zubair Ahmed memon Dileep Kumar Department of Electronic Engineering Quaid-e-Awam University of Engineering Science and TechnologyNawabshah67480Pakistan NCRA Condition Monitoring Systems Lab Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Design and Creative Technology Torrens University AustraliaMelbourneAustralia Department of Electronics and Power Engineering Pakistan Navy Engineering College NUSTKarachi75350Pakistan

Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to avoiding plant disturbances and ***,Motor Current Signature Analysis(MCSA)is widely reported as a condition monitoring technique in the detection and identification of individual andmultiple Induction Motor(IM)***,checking the fault detection and classification with deep learning models and its comparison among them selves or conventional approaches is rarely reported in the ***,in this work,wepresent the detection and identification of induction motor faults with MCSA and three Deep Learning(DL)models namely MLP,LSTM,and ***,we have developed the model of Squirrel Cage induction motor in MATLAB and simulated it for single phasing and stator winding faults(SWF)using Fast Fourier Transform(FFT),Short Time Fourier Transform(STFT),and Continuous Wavelet Transform(CWT)to detect and identify the healthy and unhealthy conditions with phase to ground,single phasing and in multiple fault conditions using Motor Current Signature *** faults impact on stator current is presented in the time and frequency domain(i.e.,power spectrum).The simulation results show that the scalogram has shown good results in time-frequency analysis for fault and showing its impact on the energy of current during individual fault and multiple fault *** is further investigated with three deep learning models(i.e.,MLP,LSTM,and 1D-CNN)for checking the fault detection and identification(i.e.,classification)improvement in a three-phase induction *** simulating the three-phase induction motor in various healthy and unhealthy conditions in MATLAB,we have collected current signature data in the time domain,labeled them accordingly and created the 50 thousand samples dataset for DL *** the DL models are trained and validated with a suitable number of architecture *** simulation,the multiclass confusion

关键词： Condition monitoring motor fault diagnosis stator winding faults deep learning signal processing

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Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

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Computers, Materials & Continua 2023年第5期75卷 2461-2477页

作者： Tarique Rafique memon Tayab Din memon Imtiaz Hussain Kalwar Bhawani Shankar Chowdhry NCRA-HHCMS Lab Mehran University of Engineering&Technology Jamshoro76062Pakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience&Technology Nawabshah67480Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourneVIC 3000Australia Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronics and Power Engineering Pakistan Navy Engineering CollegeNUST Karachi75350Pakistan

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each *** this purpose,a proper condition monitoring system is essential to avoid accidents and heavy ***,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy ***,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway *** proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition *** contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy *** works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black *** have used the multiprocessing technique to overcome the massive processing and memory *** embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/*** functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faul

关键词： Railway track surface faults condition monitoring system fault detection contour detection deep learning image processing rail wheel impact

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