检索结果-南通市图书馆

MDCN:Modified Dense Convolution Network Based Disease Classification in Mango Leaves

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第2期78卷 2511-2533页

作者： Chirag Chandrashekar k.P.vijayakumar k.Pradeep A.Balasundaram School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)ChennaiIndia

The most widely farmed fruit in the world is *** the production and quality of the mangoes are hampered by many *** diseases need to be effectively controlled and ***,a quick and accurate diagnosis of the disorders is *** convolutional neural networks,renowned for their independence in feature extraction,have established their value in numerous detection and classification ***,it requires large training datasets and several parameters that need careful *** proposed Modified Dense Convolutional Network(MDCN)provides a successful classification scheme for plant diseases affecting mango *** model employs the strength of pre-trained networks and modifies them for the particular context of mango leaf diseases by incorporating transfer learning *** data loader also builds mini-batches for training the models to reduce training ***,optimization approaches help increase the overall model’s efficiency and lower computing *** employed on the MangoLeafBD Dataset consists of a total of 4,000 *** the experimental results,the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

关键词： Leaf disease detection deep convolutional neural networks transfer learning optimization MangoLeafBD Dataset

SHT-based public auditing protocol with error tolerance in FDL-empowered IoVs

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Digital Communications and Networks 2024年第1期10卷 142-149页

作者： kui Zhu Yongjun ren Jian Shen Pandi vijayakumar Pradip kumar Sharma School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Peng Cheng Laboratory Shenzhen518000China Department of Computer Science and Engineering University College of Engineering TindivanamTamil Nadu604001India Department of Computing Science University of AberdeenAberdeenAB243UEUK

With the intelligentization of the Internet of Vehicles(lovs),Artificial Intelligence(Al)technology is becoming more and more essential,especially deep *** Deep Learning(FDL)is a novel distributed machine learning technology and is able to address the challenges like data security,privacy risks,and huge communication overheads from big raw data ***,FDL can only guarantee data security and privacy among multiple clients during data *** the data sets stored locally in clients are corrupted,including being tampered with and lost,the training results of the FDL in intelligent IoVs must be negatively *** this paper,we are the first to design a secure data auditing protocol to guarantee the integrity and availability of data sets in FDL-empowered ***,the cuckoo filter and reed-Solomon codes are utilized to guarantee error tolerance,including efficient corrupted data locating and *** addition,a novel data structure,Skip Hash Table(SHT)is designed to optimize data ***,we illustrate the security of the scheme with the Computational Diffie-Hellman(CDH)assumption on bilinear *** theoretical analyses and performance evaluations demonstrate the security and efficiency of our scheme for data sets in FDL-empowered IoVs.

关键词： Internet of vehicles Federated deep learning Data security Data auditing Data locating and recovery

MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第2期78卷 2593-2616页

作者： Chirag Chandrashekar Pradeep krishnadoss vijayakumar kedalu Poornachary Balasundaram Ananthakrishnan School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of TechnologyChennai600127India

Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud ***,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing *** proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution ***,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating *** study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam *** outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection *** excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage *** efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and *** simulated data indicates that the new MCWOA outpaces other methods across all *** study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

关键词： Cloud computing scheduling chimp optimization algorithm whale optimization algorithm

Covalently Bonded Ni Sites in Black Phosphorene with Electron redistribution for Efficient Metal‑Lightweighted Water Electrolysis

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano-Micro Letters 2024年第6期16卷 233-245页

作者： Wenfang Zhai Ya Chen Yaoda Liu Yuanyuan Ma Paranthaman vijayakumar Yuanbin Qin Yongquan Qu Zhengfei Dai State key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong UniversityXi’an 710049People’s Republic of China School of Chemistry and Chemical Engineering Northwestern Polytechnical UniversityXi’an 710072People’s Republic of China SSN research Centre SSN College of EngineeringChennaiTamil Nadu 603110India

The metal-lightweighted electrocatalysts for water splitting are highly desired for sustainable and economic hydrogen energy deployments,but *** this work,a low-content Ni-functionalized approach triggers the high capability of black phosphorene(BP)with hydrogen and oxygen evolution reaction(HEr/OEr)*** a facile in situ electro-exfoliation route,the ionized Ni sites are covalently functionalized in BP nanosheets with electron redistribution and controllable metal *** is found that the as-fabricated Ni-BP electrocatalysts can drive the water splitting with much enhanced HEr and OEr *** 1.0 M kOH electrolyte,the optimized 1.5 wt%Nifunctionalized BP nanosheets have readily achieved low overpotentials of 136 mV for HEr and 230 mV for OEr at 10 mA cm^(−2).Moreover,the covalently bonding between Ni and P has also strengthened the catalytic stability of the Ni-functionalized BP electrocatalyst,stably delivering the overall water splitting for 50 h at 20 mA cm^(−2).Theoretical calculations have revealed that Ni–P covalent binding can regulate the electronic structure and optimize the reaction energy barrier to improve the catalytic activity *** work confirms that Ni-functionalized BP is a suitable candidate for electrocatalytic overall water splitting,and provides effective strategies for constructing metal-lightweighted economic electrocatalysts.

关键词： Black phosphorus Water electrolysis Electrocatalyst Electron redistribution Covalent functionalization

Maximizing Solar Potential Using the Differential Grey Wolf Algorithm for PV System Optimization

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Energy Engineering 2024年第8期121卷 2129-2142页

作者： Ezhilmathi Nagarathinam Buvana Devaraju karthiyayini Jayamoorthy Padmavathi radhakrishnan Santhana Lakshmi ChandraMohan vijayakumar Perumal karthikeyan Balakrishnan Department of Electrical and Electronics Engineering Pandian Saraswathiyadav Engineering CollegeSivagangaiTamil Nadu630561India Department of Electrical and Electronics Engineering Sri Balaji Chockalingam Engineering CollegeArniTamil Nadu632317India Department of Information Science and Engineering New Horizon College of EngineeringBangalore560103India Department of Electrical and Electronics Engineering Rajalakshmi Engineering CollegeChennaiTamil Nadu602105India Department of Electrical and Electronics Engineering Sona College of TechnologySalemTamil Nadu636005India School of Electronics Engineering Vellore Institute of TechnologyChennaiTamil Nadu600127India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatoreTamil Nadu641008India

Maximum Power Point Tracking(MPPT)is crucial for maximizing the energy output of photovoltaic(PV)systems by continuously adjusting the operating point of the panels to track the point of maximum power production under changing environmental *** work proposes the design of an MPPT system for solar PV installations using the Differential Grey Wolf Optimizer(DGWO).It dynamically adjusts the parameters of the MPPT controller,specifically the duty cycle of the SEPIC converter,to efficiently track the Maximum Power Point(MPP).The proposed system aims to enhance the energy harvesting capability of solar PV systems by optimizing their performance under varying solar irradiance,temperature and shading *** results demonstrate the effectiveness of the DGWO-based MPPT system in maximizing the power output of solar PV installations compared to conventional MPPT *** research contributes to the development of advanced MPPT techniques for improving the efficiency and reliability of solar energy systems.

关键词： DGWO SEPIC converter MPPT PV module

Frequency Control Approach and Load Forecasting Assessment for Wind Systems

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第1期35卷 971-982页

作者： k.Sukanya P.vijayakumar Department of EEE Karpagam College of EngineeringCoimbatore641032India

Frequency deviation has to be controlled in power generation units when there arefluctuations in system *** several renewable energy sources,wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable *** there is a mismatch between generation and demand,the frequency deviation may arise from the actual frequency 50 Hz(in India).To mitigate the frequency deviation issue,it is necessary to develop an effective technique for better frequency control in wind energy *** this work,heuristic Fuzzy Logic Based Controller(FLC)is developed for providing an effective frequency control support by modeling the complex behavior of the system to enhance the load forecasting in wind based hybrid power *** control is applied to reduce the frequency deviation due tofluctuations and load prediction information using ANN(Artificial Neural Network)and SVM(Support Vector Machine)learning *** performance analysis of the proposed method is done with different machine learning based *** forecasting assessment is done over various climates with the aim to decrease the prediction errors and to demote the forecasting *** results show that the Mean Absolute Percentage Error(MAPE),root Mean Square Error(rMSE)and Normalized Mean Absolute Error(NMAE)values are scaled down by 41.1%,9.9%and 23.1%respectively in the proposed method while comparing with existing wavelet and BPN based approach.

关键词： Load forecasting wind power prediction fuzzy logic controller ANN SVM hybrid power systems

Application of IITM-rANS3D to free-fall water entry of prismatic and non-prismatic finite wedges

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

水动力学研究与进展B辑:英文版 2023年第3期35卷 417-430页

作者： Shaswat Saincher kshitij Srivastava r.vijayakumar V.Sriram Center for Maritime Experiments to Maritime Experience(ME2ME) Indian Institute of Technology MadrasChennaiIndia Department of Ocean Engineering Indian Institute of Technology MadrasChennaiIndia

High-speed watercraft and ships undergo coupled motions which make the front portion of the hull exit and violently re-enter *** induces short-term slamming loads that may compromise the structural integrity of the *** slamming of the bow can be modeled as straight wedges of different deadrise angles(DrAs)falling into water from different *** advent of computational fluid dynamics has allowed the problem of wedge-slamming to be simulated using the full Navier-Stokes equations thus complementing the pioneering studies based on ***,most researchers are opting to use commercial software to simulate the wedge-impact problem as it allows access to overset meshing algorithms which are robust in modeling the wedge as a moving *** boundary methods(EBMs)offer some advantages over overset meshing in that the mesh only needs to be generated once and Cartesian mesh-based solvers can be ***,the application of EBMs to wedge-impact has been limited in the literature and merits further *** this context,we investigate the applicability of the fast-fictitious-domain(FFD)based embedded boundary treatment to simulate the violent water-entry of *** extend our in-house Navier-Stokes model IITM-rANS3D to handle floating bodies through integration of a rigid-body dynamics solver and an algorithm to embed three-dimensional stereolithography(STL)geometries as solids over a Cartesian *** proposed algorithm is extensively benchmarked against variable DrA wedge-slamming experiments reported in the literature as well as constant DrA wedge-slamming experiments performed *** good agreement is reported in terms of the time-history of hydrodynamic impact pressures measured at various locations on the hull as well as the wedge motion responses thus demonstrating the suitability of FFD for simulating the coupled hydrodynamics of slamming for simplified hull geometries.

关键词： Wedge water entry slamming fast-fictitious-domain IITM-rANS3D experiments

Optimization of Cognitive Femtocell Network via Oppositional Beetle Swarm Optimization Algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第4期36卷 819-832页

作者： k.rajesh kumar M.vijayakumar Department of ECE Adhiyamaan College of EngineeringHosurTamilnaduIndia Department of EEE K.S.R.College of EngineeringTiruchengodeTamilnaduIndia

In past decades,cellular networks have raised the usage of spectrum resources due to the victory of mobile broadband *** devices create massive data than ever before,facing the way cellular networks are installed pre-sently for satisfying the increased trafﬁc *** development of a new exclusive spectrum offered to meet up the trafﬁc requirements is challenging as spectrum resources are limited,hence *** radio technology is pre-sented to increase the pool of existing spectrum resources for mobile users via Femtocells,placed on the top of the available macrocell network for sharing the same ***,the concurrent reuse of spectrum resources from Femto networks poses destructive interference on macro *** resolve this issue,this paper introduces an optimal channel allocation model using the Oppo-sitional Beetle Swarm Optimization Algorithm(OBSOA)to allocate the channel with interference avoidance.A new OBSOA is derived in this paper by the inclu-sion of opposition-based learning(OBL)in *** algorithm allocates the channels used by PUs(PUs)to the secondary users(SUs)in such a way that inter-ference is *** proposed approach is implemented in the MATrix LABoratory(MATLAB)*** performance of this proposed approach is evaluated in terms of several measures and the experimental outcome veriﬁed the superior nature of the OBSOA-based channel allocation *** mod-el has resulted in a maximum signal-to-interference-plus-noise ratio value of 86.42 dB.

关键词： Femto networks channel allocation spectrum reuse cognitive network

LSTM Based Spectrum Prediction for real-Time Spectrum Access for IoT Applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第3期35卷 2805-2819页

作者： r.Nandakumar vijayakumar Ponnusamy Aman kumar Mishra kSr Institute for Engineering and Technology Tiruchencode637215India ECE Department SRMISTChengalpattuChennai603202India

In the Internet of Things(IoT)scenario,many devices will communi-cate in the presence of the cellular network;the chances of availability of spec-trum will be very scary given the presence of large numbers of mobile users and large amounts of *** prediction is very encouraging for high trafﬁc next-generation wireless networks,where devices/machines which are part of the Cognitive radio Network(CrN)can predict the spectrum state prior to transmission to save their limited energy by avoiding unnecessarily sen-sing radio *** short-term memory(LSTM)is employed to simulta-neously predict the radio Spectrum State(rSS)for two-time slots,thereby allowing the secondary node to use the prediction result to transmit its information to achieve lower waiting time hence,enhanced performance capacity.A frame-work of spectral transmission based on the LSTM prediction is formulated,named as positive prediction and sensing-based spectrum *** proposed scheme provides an average maximum waiting time gain of 2.88 *** proposed scheme provides 0.096 bps more capacity than a conventional energy detector.

关键词： Cognitive radio network encoder-decoder LSTM waiting time capacity