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Design of a 2-DOF-PID controller using an improved sine-cosine algorithm for load frequency control of a three-area system with nonlinearities

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Protection and Control of Modern Power Systems 2022年第1期7卷 490-507页

作者： Neelesh Kumar Gupta Manoj Kumar Kar arun Kumar Singh Department of Electrical Engineering NIT JamshedpurJamshedpurJharkhand 831014India

This paper proposes an improved sine-cosine algorithm(ISCA)based 2-DOF-PID controller for load frequency control.A three-area test system is built for study,while some physical constraints(nonlinearities)are considered for the investigation of a realistic power *** proposed method is used as the parameter optimizer of the LFC control-ler in different *** 2-DOF-PID controllers are used because of their capability of fast disturbance rejection without significant increase of overshoot in set-point *** 2-DOF-PID controllers’efficacy is observed by examining the responses with the outcomes obtained with PID and FOPID *** simulation results with the suggested scheme are correlated with some of the existing algorithms,such as SCA,SSA,ALO,and PSO in three dif-ferent scenarios,i.e.,a disturbance in two areas,in three areas,and in the presence of physical *** addition,the study is extended to a four-area power *** analysis is performed using the Wilcoxon Sign Rank Test(WSRT)on 20 independent *** confirms the supremacy of the proposed method.

关键词： 2-DOF-PID FOPID Load frequency control WSRT Statistical analysis Improved sine-cosine algorithm

Effect of hydroalcoholic leaf extract of Cassia fistula *** typeⅡcollagen-induced arthritis in rats

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Asian Pacific Journal of Tropical Biomedicine 2023年第5期13卷 195-204页

作者： Vineet Mehta Priyanka Nagu arun Parashar Manjusha Chaudhary Department of Pharmacology Govt.College of PharmacyRohruShimlaHimachal Pradesh 171207India Department of Pharmaceutics Govt.College of PharmacyRohruShimlaHimachal Pradesh 171207India School of Pharmaceutical Sciences Shoolini UniversitySolan Himachal Pradesh 173229India Institute of Pharmaceutical Sciences Kurukshetra UniversityKurukshetraHaryana 136119India

Objective:To explore the effect of Cassia fistula on collagenⅡ-induced arthritis in ***:The effect of 250 and 500 mg/kg chloroform and hydroalcoholic extract of Cassia fistula leaf on collagenⅡ-induced arthritis was investigated by evaluating paw volume,arthritis index,spleen index,and biochemical *** analysis and docking study were also ***:A dose-dependent reduction in paw volume,arthritic index,and spleen index was observed following oral administration of the chloroform and hydroalcoholic *** with Cassia fistula extracts reduced tumor necrosis factor-α,interleukin(IL)-1β,IL-6,prostaglandin E_(2),aspartate aminotransferase,alanine aminotransferase,total leucocyte count,and erythrocyte sedimentation rate while increasing IL-10 *** addition,Cassia fistula extracts improved joint architecture,and prevented cartilage and bone *** analysis demonstrated that the physcion,1-octacosanol,5,3’,4’-trihydroxy-6-methoxy-7-O-α-Lrhamnopyranosyl-(1,2)-O-β-D-galactopyranoside and scopoletin may be responsible for the anti-arthritic effect of Cassia ***:Cassia fistula suppresses the progression of collagenⅡ-induced arthritis by lowering the inflammatory factors,decreasing paw volume and arthritic index,and alleviating joint ***,further studies are required to confirm the bioactive molecule responsible for the anti-arthritic potential of Cassia fistula.

关键词： Cassia fistula Rheumatoid arthritis CollagenⅡ Inflammatory cytokines Docking

Forecasting the Municipal Solid Waste Using GSO-XGBoost Model

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Intelligent Automation & Soft Computing 2023年第7期37卷 301-320页

作者： Vaishnavi Jayaraman arun Raj Lakshminarayanan Saravanan Parthasarathy ASuganthy B.S.Abdur Rahman Crescent Institute of Science and Technology GST RoadVandalurChennai600048Tamil NaduIndia Pondicherry University Chinna KalapetKalapetPuducherry605014India

Waste production rises in tandem with population growth and increased *** indecorous disposal of waste paves the way for huge disaster named as climate *** National Environment Agency(NEA)of Singapore oversees the sustainable management of waste across the *** three main contributors to the solid waste of Singapore are paper and cardboard(P&C),plastic,and food ***,they have a negligible rate of *** this study,Machine Learning techniques were utilized to forecast the amount of garbage also known as waste *** waste audit would aid the authorities to plan their waste *** applied models were k-nearest neighbors,Support Vector Regressor,ExtraTrees,CatBoost,and *** XGBoost model with its default parameters performed better with a lower Mean Absolute Percentage Error(MAPE)of 8.3093(P&C waste),8.3217(plastic waste),and 6.9495(food waste).However,Grid Search Optimization(GSO)was used to enhance the parameters of the XGBoost model,increasing its ***,the optimized XGBoost algorithm performs the best for P&C,plastics,and food waste with MAPE of 4.9349,6.7967,and 5.9626,*** proposed GSO-XGBoost model yields better results than the other employed models in predicting municipal solid waste.

关键词： Waste management municipal solid waste grid search optimization XGBoost machine learning sustainability

A comprehensive survey on security issues in vehicle-to-grid networks

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Journal of Control and Decision 2023年第2期10卷 150-159页

作者： arun Sekar Rajasekaran Maria Azees Fadi Al-Turjman Department of Electronics and Communication Engineering GMR Institute of TechnologyRajamIndia Artificial Intelligence Engineering Department. Research Center for AI and IoTAI and Robotics InstituteNear East UniversityMersin 10Turkey

Vehicle to grid(V2G)is the most hopeful approach to transfer energy as well as information in the bidirectional way.V2G network is formed by electric vehicles which connect with smart metres for information and energy transfer in a wireless *** though many security preserving schemes developed in V2G networks,they were prone to enormous number of security breaches.A countless deal of works has been done towards it,but security mechanisms in V2G networks are not *** survey work provides a summary about the V2G network characteristics,significance,security services and the security ***,this work offers a summary of some foremost security attacks on various security services such as accessibility,confidentiality,authentication,integrity and non-repudiation and the related countermeasures to make the V2G communications more protected.

关键词： Authentication confidentiality integrity privacy security

Adaptive Sub-Threshold Voltage Level Control for Voltage Deviate-Domino Circuits

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Intelligent Automation & Soft Computing 2023年第2期35卷 1767-1781页

作者： C.arun Prasath C.Gowri Shankar Department of Electronics and Communication Engineering Mahendra Engineering CollegeNamakkal637503India Department of Electrical and Electronics Engineering KSR College of EngineeringTiruchengode637215India

Leakage power and propagation delay are two signiﬁcant issues found in sub-micron technology-based Complementary Metal-Oxide-Semiconductor(CMOS)-based Very Large-Scale Integration(VLSI)circuit *** Channel Metal Oxide Semiconductor(PMOS)has been replaced by Negative Channel Metal Oxide Semiconductor(NMOS)in recent years,with low dimen-sion-switching changes in order to shape the mirror of voltage *** is used to reduce stacking leakage as well as total *** Logic Cir-cuit is a powerful and versatile digital programmer that gained popularity in recent *** this study regarding Adaptive Sub Threshold Voltage Level Control Pro-blem,the researchers intend to solve the contention issues,reduce power dissipa-tion,and increase the noise immunity by proposing Adaptive Sub Threshold Voltage Level Control(ASVLC)-based domino *** efﬁciency and effec-tiveness of the domino circuit are demonstrated through simulation *** suggested system makes use of high-speed broad fan-gate circuits,occupies mini-mum space,and consumes meagre amount of *** proposed circuit was validated in Cadence simulation tool at a supply voltage of 1V,frequency of 100 MHz,and an operating temperature of 27°C with 64 input OR *** per the simulation results,the suggested Domino Gate reduced the power dissipa-tion by 17.58 percent and improved the noise immunity by 1.21 times in compar-ison with standard domino logic circuits.

关键词： Domino logic power consumption ﬁgure of merit adaptive sub-threshold voltage level wide fan-in gates

Optimal Algorithms for Load Balancing in Optical Burst Switching Networks

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Computer Systems Science & Engineering 2022年第8期42卷 739-749页

作者： K.arun Kumar V.R.Venkatasubramani S.Rajaram Research Scholar Department of ICEAnna UniversityChennai600025India Department of ECE Thiagarajar College of EngineeringMadurai625015India

Data packet drop can happen in Optical Burst-Switched(OBS)when two data bursts are competing on the same ***,many techniques have been developed to solve this problem but they do not consider the ***,it is necessary to balance the load system in the OBS *** Ant Colony Optimization(ACO)technique can be applied to determine the straight and the safest ***,the ACO technique raises both power utilization as well as the execution *** this study,Cuckoo Search(CS)and ACO methods based approach is proposed to avoid the congestion and load balancing in the OBS *** strategy evaluates the intensity of hotspot data and then launches the congestion rate optimization process that depends on their load *** congestion rate optimization represents the available bandwidth,data distribution rate,queue size,and access rate,and also these factors are optimized through the CS *** fitness utility in the CS technique adjusts the distribution rate in the OBS network,and the proposed ACO technique solves the energy utilization *** simulation results proved that the presented strategy evades both the end-to-end delay as well as the possibility of packet drop.

关键词： Ant colony optimization cuckoo search optical burst-switched load balancing congestion control

Facial Emotion Recognition Using Swarm Optimized Multi-Dimensional DeepNets with Losses Calculated by Cross Entropy Function

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Computer Systems Science & Engineering 2023年第9期46卷 3285-3301页

作者： A.N.arun P.Maheswaravenkatesh T.Jayasankar Department of Computer Science&Engineering Sri Venkateswara Institute of Science and TechnologyTiruvallurTamilnaduIndia Department of Electronics and Communication Engineering Anna UniversityTrichyTamilnaduIndia

The human face forms a canvas wherein various non-verbal expressions are *** expressional cues and verbal communication represent the accurate perception of the actual *** many cases,a person may present an outward expression that might differ fromthe genuine emotion or the feeling that the person *** when people try to hide these emotions,the real emotions that are internally felt might reflect as facial expressions in the form of micro *** micro expressions cannot be masked and reflect the actual emotional state of a person under *** expressions are on display for a tiny time frame,making it difficult for a typical person to spot and recognize *** necessitates a place for Machine Learning,where machines can be trained to look for these micro expressions and categorize them once they are on *** study’s primary purpose is to spot and correctly classify these micro expressions,which are very difficult for a casual observer to *** research improves upon the accuracy of the recognition by using a novel learning technique that not only captures and recognizes multimodal facial micro expressions but also has features for aligning,cropping,and superimposing these feature frames to produce highly accurate and consistent results.A modified variant of the deep learning architecture of Convolutional Neural Networks combined with the swarm-based optimality technique of the Artificial Bee Colony Algorithm is proposed to effectively get an accuracy of more than 85%in identifying and classifying these micro expressions in contrast to other algorithms that have relatively less *** of the main aspects of processing these expressions from video or live feeds is aligning the frames homographically and identifying these concise bursts of micro expressions,which significantly increases the accuracy of the *** proposed swarm-based technique handles this in the research to precisely alig

关键词： Facial micro expression recognition deep learning CNN artificial bee colony

DSAFF-Net:A Backbone Network Based on Mask R-CNN for Small Object Detection

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Computers, Materials & Continua 2023年第2期74卷 3405-3419页

作者： Jian Peng Yifang Zhao Dengyong Zhang Feng Li arun Kumar Sangaiah Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computing Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India

Recently,object detection based on convolutional neural networks(CNNs)has developed *** backbone networks for basic feature extraction are an important component of the whole detection ***,we present a new feature extraction strategy in this paper,which name is *** this strategy,we design:1)a sandwich attention feature fusion module(SAFF module).Its purpose is to enhance the semantic information of shallow features and resolution of deep features,which is beneficial to small object detection after feature fusion.2)to add a new stage called D-block to alleviate the disadvantages of decreasing spatial resolution when the pooling layer increases the receptive *** method proposed in the new stage replaces the original method of obtaining the P6 feature map and uses the result as the input of the regional proposal network(RPN).In the experimental phase,we use the new strategy to extract *** experiment takes the public dataset of Microsoft Common Objects in Context(MS COCO)object detection and the dataset of Corona Virus Disease 2019(COVID-19)image classification as the experimental object *** results show that the average recognition accuracy of COVID-19 in the classification dataset is improved to 98.163%,and small object detection in object detection tasks is improved by 4.0%.

关键词： Small object detection classification RPN MS COCO COVID-19

Breast Mammogram Analysis and Classification Using Deep Convolution Neural Network

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Computer Systems Science & Engineering 2022年第10期43卷 275-289页

作者： V.Ulagamuthalvi G.Kulanthaivel A.Balasundaram arun Kumar Sivaraman Department of Computer Science and Engineering Sathyabama UniversityChennai600119India Department of Electrical Electronics and Communication EngineeringNITTTRChennai600113India Centre for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)Chennai600127India School of Computer Science and Engineering Vellore Institute of Technology(VIT)Chennai600127India

One of the fast-growing disease affecting women’s health seriously is breast *** is highly essential to identify and detect breast cancer in the earlier *** paper used a novel advanced methodology than machine learning algorithms such as Deep learning algorithms to classify breast cancer *** learning algorithms are fully automatic in learning,extracting,and classifying the features and are highly suitable for any image,from natural to medical *** methods focused on using various conventional and machine learning methods for processing natural and medical *** is inadequate for the image where the coarse structure matters *** of the input images are downscaled,where it is impossible to fetch all the hidden details to reach accuracy in *** deep learning algorithms are high efficiency,fully automatic,have more learning capability using more hidden layers,fetch as much as possible hidden information from the input images,and provide an accurate *** this paper uses AlexNet from a deep convolution neural network for classifying breast cancer in mammogram *** performance of the proposed convolution network structure is evaluated by comparing it with the existing algorithms.

关键词： Medical image processing deep learning convolution neural network breast cancer feature extraction classification