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MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

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Computers, Materials & Continua 2024年第3期78卷 3489-3510页

作者： Rashmi Sharma Ashok Pal nitin mittal Lalit Kumar Sreypov Van Yunyoung Nam Mohamed Abouhawwash Department of Mathematics Chandigarh UniversityGharuanMohali140413India Deaprtment of Industry 4.0 Shri Vishwakarma Skill UniversityPalwal121102India Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Computational Mathematics Science and Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI 48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated *** uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective *** hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge *** evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been *** proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and *** primary objective of developing this hybrid approach has been achieved *** proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

关键词： Multi-objective optimization genetic algorithm ant lion optimizer metaheuristic

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Deep Learning-Based Mask Identification System Using ResNet Transfer Learning Architecture

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Computer Systems Science & Engineering 2024年第2期48卷 341-362页

作者： Arpit Jain Nageswara Rao Moparthi A.Swathi Yogesh Kumar Sharma nitin mittal Ahmed Alhussen Zamil S.Alzamil MohdAnul Haq Department of Computer Science and Engineering KoneruLakshmaiah Education FoundationVaddeswaram522302India Department of Computer Science and Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Recently,the coronavirus disease 2019 has shown excellent attention in the global community regarding health and the *** Health Organization(WHO)and many others advised controlling Corona Virus Disease in *** limited treatment resources,medical resources,and unawareness of immunity is an essential horizon to *** all resources,wearing a mask is the primary non-pharmaceutical intervention to stop the spreading of the virus caused by Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2)*** countries made masks mandatory to prevent *** such enforcement,automatic and effective face detection systems are *** study presents a face mask identification approach for static photos and real-time movies that distinguishes between images with and without *** contribute to society,we worked on mask detection of an individual to adhere to the rule and provide awareness to the public or *** paper aims to get detection accuracy using transfer learning from Residual Neural Network 50(ResNet-50)architecture and works on detection *** experiment is tested with other popular pre-trained models such as Deep Convolutional Neural Networks(AlexNet),Residual Neural Networks(ResNet),and Visual Geometry Group Networks(VGG-Net)advanced *** proposed system generates an accuracy of 98.4%when modeled using Residual Neural Network 50(ResNet-50).Also,the precision and recall values are proved as better when compared to the existing *** outstanding work also can be used in video surveillance applications.

关键词： Transfer learning depth analysis convolutional neural networks(CNN) COVID-19

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Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

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Computers, Materials & Continua 2023年第5期75卷 3189-3201页

作者： Shakti Raj Chopra Parulpreet Singh Ahmed Alhussen nitin mittal MohdAnul Haq School of Electronics and Electrical Engineering Lovely Professional UniversityPhagwaraPunjab144411India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia University Centre for Research and Development Chandigarh UniversityMohaliPunjab140413India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Many extensive UAV communication networks have used UAV cooperative *** networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base *** only is coverage maximization,but also better connectivity,a fundamental design challenge that must be *** number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)*** bands,however,have become overcrowded as the number of systems that use them *** Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this *** a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV *** paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient *** maximization,power control,and enhanced connection quality are the three steps of the proposed *** satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).

关键词： UAV networks multi-UAV coverage energy-efficient FER SNR

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Optimization of Cognitive Radio System Using Self-Learning Salp Swarm Algorithm

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Computers, Materials & Continua 2022年第2期70卷 3821-3835页

作者： nitin mittal Harbinder Singh Vikas mittal Shubham Mahajan Amit Kant Pandit Mehedi Masud Mohammed Baz Mohamed Abouhawwash Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India School of VLSI Design and Embedded Systems National Institute of TechnologyKurukshetra136119India School of Electronics&Communication Engineering Shri Mata Vaishno Devi UniversityKatra182320India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityTaif21994Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

CognitiveRadio(CR)has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral *** improve the overall performance of the CR systemit is extremely important to adapt or reconfigure the *** Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter *** meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches,the performance of these algorithms is investigated in order to design an efficient CR system that is able to adapt the transmitting parameters to effectively reduce power consumption,bit error rate and adjacent interference of the channel,while maximized secondary user ***-Learning Salp Swarm Algorithm(SLSSA)is a recent meta-heuristic algorithm that is the enhanced version of SSA inspired by the swarming behavior of *** this work,the parametric adaption of CR system is performed by SLSSA and the simulation results show that SLSSA has high accuracy,stability and outperforms other competitive algorithms formaximizing the throughput of secondary *** results obtained with SLSSA are also shown to be extremely satisfactory and need fewer iterations to converge compared to the competitive methods.

关键词： Cognitive radio meta-heuristic algorithm cognitive decision engine salp swarm algorithm

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A Novel Hybrid Tunicate Swarm Naked Mole-Rat Algorithm for Image Segmentation and Numerical Optimization

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Computers, Materials & Continua 2022年第5期71卷 3445-3462页

作者： Supreet Singh nitin mittal Urvinder Singh Rohit Salgotra Atef Zaguia Dilbag Singh Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Electronics&Communication Engineering TIETPatiala147004India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Electrical Engineering and Computer Science Gwangju Institute of Science and TechnologyGwangju61005Korea

This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm(TSNMRA)which uses hybridization concept of tunicate swarm algorithm(TSA)and naked mole-rat algorithm(NMRA).This newly developed algorithm uses the characteristics of both algorithms(TSA and NMRA)and enhance the exploration abilities of *** from the hybridization concept,important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing(sa)mutation operator and there is no need to define its value *** evaluating the working capabilities of proposed TSNMRA,it is tested for 100-digit challenge(CEC 2019)test problems and real multi-level image segmentation *** the results obtained for CEC 2019 test problems,it can be seen that proposed TSNMRA performs well as compared to original TSA and *** case of image segmentation problem,comparison of TSNMRA is performed with multi-threshold electro magnetism-like optimization(MTEMO),particle swarm optimization(PSO),genetic algorithm(GA),bacterial foraging(BF)and found superior results for TSNMRA.

关键词： Optimization NMRA TSA image segmentation thresholding

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Deep Learning and SVM-Based Approach for Indian Licence Plate Character Recognition

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Computers, Materials & Continua 2023年第1期74卷 881-895页

作者： nitin Sharma Mohd Anul Haq Pawan Kumar Dahiya B.R.Marwah Reema Lalit nitin mittal Ismail Keshta Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Electronics&Communication Engineering DCRUST Murthal131039India Department of Transportation Engineering IITKanpur208016Uttar PradeshIndia Department of Computer Science Applications PIETSmalkha132102India Skill Faculty of Science and Technology Shri Vishwakarma Skill UniversityPalwal121102India Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia

Every developing country relies on transportation,and there has been an exponential expansion in the development of various sorts of vehicles with various configurations,which is a major component strengthening the automobile *** is a developing country with increasing road traffic,which has resulted in challenges such as increased road accidents and traffic oversight *** the lack of a parametric technique for accurate vehicle recognition,which is a major worry in terms of reliability,high traffic density also leads to mayhem at checkpoints and toll plazas.A system that combines an intelligent domain approach with more sustainability indices is a better way to handle traffic density and transparency *** Automatic Licence Plate Recognition(ALPR)system is one of the components of the intelligent transportation system for traffic *** study is based on a comprehensive and detailed literature evaluation in the field of *** major goal of this study is to create an automatic pattern recognition system with various combinations and higher accuracy in order to increase the reliability and accuracy of identifying digits and alphabets on a car *** research is founded on the idea that image processing opens up a diverse environment with allied fields when employing distinct soft techniques for *** properties of characters are employed to recognise the Indian licence plate in this *** licence plate recognition,more than 200 images were analysed with various parameters and soft computing techniques were *** comparison to neural networks,a hybrid technique using a Convolution Neural Network(CNN)and a Support Vector Machine(SVM)classifier has a 98.45%efficiency.

关键词： Intelligent transportation system automatic license plate recognition system neural network random forest convolutional neural network support vector machine

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Non-Negative Minimum Volume Factorization (NMVF) for Hyperspectral Images (HSI) Unmixing: A Hybrid Approach

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Computers, Materials & Continua 2022年第11期73卷 3705-3720页

作者： Kriti Mahajan Urvashi Garg nitin mittal Yunyoung Nam Byeong-Gwon Kang Mohamed Abouhawwash Department of Computer Science and Engineering Chandigarh UniversityPunjab140413India Skill Faculty of Science and Technology Shri Vishwakarma Skill UniversityPalwal121102India Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI48824USA

Spectral unmixing is essential for exploitation of remotely senseddata of Hyperspectral Images (HSI). It amounts to the identification of a position of spectral signatures that are pure and therefore called end members andtheir matching fractional, draft rules abundances for every pixel in HSI. Thispaper aims to unmix hyperspectral data using the minimal volume methodof elementary scrutiny. Moreover, the problem of optimization is solved bythe implementation of the sequence of small problems that are constrainedquadratically. The hard constraint in the final step for the abundance fractionis then replaced with a loss function of hinge type that accounts for outlinersand noise. Existing algorithms focus on estimating the endmembers (Ems)enumeration in a sight, discerning of spectral signs of EMs, besides assessmentof fractional profusion for every EM in every pixel of a sight. Nevertheless, allthe stages are performed by only a few algorithms in the process of hyperspectral unmixing. Therefore, the Non-negative Minimum Volume Factorization(NMVF) algorithm is further extended by fusing it with the nonnegativematrix of robust collaborative factorization that aims to perform all the threeunmixing chain steps for hyperspectral images. The major contributions ofthis article are in this manner: (A) it performs Simplex analysis of minimum volume for hyperspectral images with unsupervised linear unmixing isemployed. (B) The simplex analysis method is configured with an exaggeratedform of the elementary which is delivered by vertical component analysis(VCA). (C) The inflating factor is chosen carefully inactivating the constraintsin a large majority for relating to the source fractions abundance that speedsup the algorithm. (D) The final step is making simplex analysis method robustto outliners as well as noise that replaces the profusion element positivity hardrestraint by a hinge kind soft restraint, preserving the local minima havinggood quality. (E) The matrix factorizati

关键词： Hyperspectral Imaging minimum volume simplex source separation end member extraction non-negative minimum volume factorization(NMVF) endmembers(EMs)

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Design and Analysis of Graphene Based Tunnel Field Effect Transistor with Various Ambipolar Reducing Techniques

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Computers, Materials & Continua 2023年第7期76卷 1309-1320页

作者： Puneet Kumar Mishra Amrita Rai nitin Sharma Kanika Sharma nitin mittal Mohd Anul Haq Ilyas Khan ElSayed M.Tag El Din Department of Electronics and Communication Engineering G L Bajaj Institute of Technology and ManegmentGretear NoidaIndia Department of Electronics and Communication Engineering Chandigarh UnievrsityMohaliPunjabIndia Department of Electronics and Communication Engineering NITTTRChandigarhIndia University Center of Research&Development Chandigarh UniversityMohali121102India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah University11952Al-MajmaahSaudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

The fundamental advantages of carbon-based graphene material,such as its high tunnelling probability,symmetric band structure(linear dependence of the energy band on the wave direction),low effective mass,and characteristics of its 2D atomic layers,are the main focus of this research *** impact of channel thickness,gate under-lap,asymmetric source/drain doping method,workfunction of gate contact,and High-K material on Graphene-based Tunnel Field Effect Transistor(TFET)is analyzed with 20 nm *** modelling and electrical characteristic performance have been simulated using the Atlas device simulator of SILVACO TCAD with user-defined material syntax for the newly included graphene material in comparison to silicon carbide(SiC).The simulation results in significant suppression of ambipolar current to voltage characteristics of TFET and modelled device exhibits a significant improvement in subthreshold swing(0.0159 V/decade),the ratio of Ion/Ioff(1000),and threshold voltage(-0.2 V with highly doped p-type source and 0.2 V with highly doped n-type drain)with power supply of 0.5 V,which make it useful for low power digital applications.

关键词： Graphene tunnel field effect transistor(TFET) band to band tunnelling subthreshold swing

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Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

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Intelligent Automation & Soft Computing 2023年第9期37卷 3159-3177页

作者： nitin mittal Rohit Salgotra Abhishek Sharma Sandeep Kaur SSAskar Mohamed Abouhawwash University Center for Research and Development Chandigarh UniversityMohaliPunjab140413India Faculty of Physics and Applied Computer Science AGH University of Science&TechnologyKrakowPoland Faculty of Information Technology Middle East UniversityAmman11813Jordan Department of Computer Engineering and Applications GLA UniversityMathura281406India Department of Computer Engineering&Technology Guru Nanak Dev UniversityAmritsarPunjab143005India Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Department of Computational Mathematics Science and EngineeringCollege of EngineeringMichigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt

The optimization of cognitive radio(CR)system using an enhanced firefly algorithm(EFA)is presented in this *** Firefly algorithm(FA)is a nature-inspired algorithm based on the unique light-flashing behavior of *** has already proved its competence in various optimization prob-lems,but it suffers from slow convergence *** improve the convergence performance of FA,a new variant named EFA is *** effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions,and simulation results show its superior performance compared to biogeography-based optimization(BBO),bat algorithm,artificial bee colony,and *** an application of this algorithm to real-world problems,EFA is also applied to optimize the CR *** is a revolutionary technique that uses a dynamic spectrum allocation strategy to solve the spectrum scarcity ***,it requires optimization to meet specific performance *** results obtained by EFA in CR system optimization are compared with results in the literature of BBO,simulated annealing,and genetic *** results further prove that the proposed algorithm is highly efficient and provides superior results.

关键词： Firefly algorithm cognitive radio bit error rate genetic algorithm simulated annealing biogeography-based optimization

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Multilayer Neural Network Based Speech Emotion Recognition for Smart Assistance

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Computers, Materials & Continua 2023年第1期74卷 1523-1540页

作者： Sandeep Kumar MohdAnul Haq Arpit Jain C.Andy Jason Nageswara Rao Moparthi nitin mittal Zamil S.Alzamil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAP522502India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Computer Science and Engineering Teerthanker Mahaveer UniversityMoradabadUttar Pradesh244001India Department of Electronics and Communication Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia

Day by day,biometric-based systems play a vital role in our daily *** paper proposed an intelligent assistant intended to identify emotions via voice message.A biometric system has been developed to detect human emotions based on voice recognition and control a few electronic peripherals for alert *** proposed smart assistant aims to provide a support to the people through buzzer and light emitting diodes(LED)alert signals and it also keep track of the places like households,hospitals and remote areas,*** proposed approach is able to detect seven emotions:worry,surprise,neutral,sadness,happiness,hate and *** key elements for the implementation of speech emotion recognition are voice processing,and once the emotion is recognized,the machine interface automatically detects the actions by buzzer and *** proposed system is trained and tested on various benchmark datasets,i.e.,Ryerson Audio-Visual Database of Emotional Speech and Song(RAVDESS)database,Acoustic-Phonetic Continuous Speech Corpus(TIMIT)database,Emotional Speech database(Emo-DB)database and evaluated based on various parameters,i.e.,accuracy,error rate,and *** comparing with existing technologies,the proposed algorithm gave a better error rate and less *** rate and time is decreased by 19.79%,5.13 *** the RAVDEES dataset,15.77%,0.01 s for the Emo-DB dataset and 14.88%,3.62 for the TIMIT *** proposed model shows better accuracy of 81.02%for the RAVDEES dataset,84.23%for the TIMIT dataset and 85.12%for the Emo-DB dataset compared to Gaussian Mixture Modeling(GMM)and Support Vector Machine(SVM)Model.

关键词： Speech emotion recognition classifier implementation feature extraction and selection smart assistance

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