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Unsupervised intrusion detection system for in-vehicle communication networks

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Journal of safety science and Resilience 2024年第2期5卷 119-129页

作者： Kabilan N vinayakumar ravi v sowmya Center for Computational Engineering and Networking(CEN) Amrita School of Artificial InteligenceAmrita Vishwa VidyapeethamCoimbatoreIndia Center for Artificial Intlligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia

In-vehicle communication has been optimized day to day to keep updated of the *** area network(CAN)is used as a standard communication method because of its efficient and reliable ***,CAN is prone to several network level attacks because of its lack in security *** methods have been introduced to incorporate this in *** proposed an unsupervised method of intrusion detection for in-vehicle communication networks by combining the optimal feature extracting ability of autoencoders and more precise clustering using fuzzy C-means(FCM).The proposed method is light weight and requires less computation *** performed an extensive experiment and achieved an accuracy of 75.51%with the ML35o in-vehicle intrusion *** experimental result,the proposed method also works better for other intrusion detection problems like wireless intrusion detection datasets such as WNs-Ds with accuracy of 84.05%and network intrusion detection datasets such as KDDCup with accuracy 60.63%,UNsW_NB15 with accuracy 73.62%and Information security Center of Excellence(Iscx)with accuracy 74.83%.Overall,the proposed method outperforms the existing methods and avoids labeled datasets when training an in-vehicle intrusion detection *** results of the experiment of our proposed method performed on various intru-sion detection datasets indicate that the proposed approach is generalized and robust in detecting intrusions and can be effectively deployed in real time to monitor CAN traffic in vehicles and proactively alert during attacks.

关键词： Controlarea network Intrusiondetection Unsupervised learning Autoencoders Fuzzy C-means

Deep Learning-Based Classification of Rotten Fruits and Identification of shelf Life

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Computers, Materials & Continua 2024年第1期78卷 781-794页

作者： s.sofana Reka Ankita Bagelikar Prakash venugopal v.ravi Harimurugan Devarajan Centre for smart Grid Technologies School of Electronics EngineeringVellore Institute of TechnologyChennai600127India school of Electronics Engineering Vellore Institute of TechnologyChennai600127India Department of Electrical Engineering Dr.B R Ambedkar National Institute of TechnologyJalandharPunjab144008India

The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional *** primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to *** impact of rotten fruits can foster harmful bacteria,molds and other microorganisms that can cause food poisoning and other illnesses to the *** overall purpose of the study is to classify rotten fruits,which can affect the taste,texture,and appearance of other fresh fruits,thereby reducing their shelf *** agriculture and food industries are increasingly adopting computer vision technology to detect rotten fruits and forecast their shelf ***,this research work mainly focuses on the Convolutional Neural Network’s(CNN)deep learning model,which helps in the classification of rotten *** proposed methodology involves real-time analysis of a dataset of various types of fruits,including apples,bananas,oranges,papayas and ***,machine learningmodels such as GaussianNaïve Bayes(GNB)and random forest are used to predict the fruit’s shelf *** results obtained from the various pre-trained models for rotten fruit detection are analysed based on an accuracy score to determine the best *** comparison to other pre-trained models,the visual geometry group16(vGG16)obtained a higher accuracy score of 95%.Likewise,the random forest model delivers a better accuracy score of 88% when compared with GNB in forecasting the fruit’s shelf *** developing an accurate classification model,only fresh and safe fruits reach consumers,reducing the risks associated with contaminated ***,the proposed approach will have a significant impact on the food industry for efficient fruit distribution and also benefit customers to purchase fresh fruits.

关键词： Rotten fruit detection shelf life deep learning convolutional neural network machine learning gaussian naïve bayes random forest visual geometry group16

Exploring nitrogen reduction reaction mechanisms in electrocatalytic ammonia synthesis:A comprehensive review

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Journal of Energy Chemistry 2024年第5期92卷 681-697页

作者： Abhishek Umesh shetty ravi sankannavar school of Chemical and Materials science Indian Institute of Technology GoaFarmagudiPonda 403401GoaIndia Department of Chemical Engineering M.S.Ramaiah Institute of TechnologyMSR NagarMSRIT PostBengaluru 560054KarnatakaIndia

The electrochemical nitrogen reduction reaction(eNRR)holds significant promise as a sustainable alternative to the conventional large-scale Haber Bosch process,offering a carbon footprint-free approach for ammonia *** the process is thermodynamically feasible at ambient temperature and pressure,challenges such as the competing hydrogen evolution reaction,low nitrogen solubility in electrolytes,and the activation of inert dinitrogen(N_(2))gas adversely affect the performance of ammonia *** hurdles result in low Faradaic efficiency and low ammonia production rate,which pose obstacles to the commercialisation of the *** have been actively designing and proposing various electrocatalysts to address these issues,but challenges still need to be resolved.A key strategy in electrocatalyst design lies in understanding the underlying mechanisms that govern the success or failure of the electrocatalyst in driving the electrochemical *** mechanistic studies,we gain valuable insights into the factors affecting the reaction,enabling us to propose optimised designs to overcome the *** review aims to provide a comprehensive understanding of the various mechanisms involved in eNRR on the electrocatalyst *** delves into the various mechanisms such as dissociative,associative,Mars-van Krevelen,lithium-mediated nitrogen reduction and surface hydrogenation mechanisms of nitrogen *** unravelling the intricacies of eNRR mechanisms and exploring promising avenues,we can pave the way for more efficient and commercially viable ammonia synthesis through this sustainable electrochemical process by designing an efficient electrocatalyst.

关键词： Green ammonia synthesis Electrolysis Electrocatalysis Nitrogen reductionreaction Electrochemical reaction pathways Reactionmechanism

A functional gel polymer electrolyte based on PvDF-HFP/gelatin toward dendrite-free lithium metal batteries

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Nano Research 2024年第4期17卷 2790-2799页

作者： Xiaoyi Hu Kangli Liu shijie Zhang Guosheng shao s.ravi P.silva Peng Zhang state Center for International Cooperation on Designer Low-carbon and Environmental Materials(CDLCEM) School of Materials Science and EngineeringZhengzhou UniversityZhengzhou 450001China Zhengzhou Materials Genome Institute(ZMGI) ZhongyuanzhiguXingyang 450100China Nanoelectronics Center Advanced Technology InstituteUniversity of SurreyGuildfordGU27XHUK

The leakage of liquid electrolyte and the formation of lithium dendrites pose challenges to safety and stability of lithium metal batteries(LMBs).The appearance of gel polymer electrolyte(GPE)has obviously improved the safety of traditional ***,the limited inhibition of GPE on lithium dendrites is detrimental to the safety of ***,a kind of poly(vinylidene fluoride-co-hexafluoropropylene)(PvDF-HFP)/gelatin(GN)GPE with high ionic conductivity,high-temperature resistance,and flame-retardancy,was prepared by electrospinning and soaking *** the electrospinning network of PvDF-HFP,its affinity to liquid electrolytes,makes this GPE more beneficial to ions transport and the formation of ***,the GN with sol–gel properties,enhances the mechanical property(13.5 MPa)of HFP-GN ***,X-ray photoelectron spectroscopy(XPs)and density functional theory(DFT)suggest that the attraction of polar groups of GN to Li+can regulate the distribution of Li+and protect Li ***,the application of HFP-GN GPEs to LMBs with cathodes of LiFePO_(4) and LiCoO_(2) deliver excellent electrochemical performances:after 300 cycles,the LiFePO_(4)/HFP-GN GPE/Li battery keeps a low capacity decay rate of 0.09%at 5 C;after 400 cycles at 2 C,the LiCoO_(2)/HFP-GN GPE/Li cell retains a high capacity retention of 74%.This GPE is demonstrated for the application prospect of safe LMBs.

关键词： poly(vinylidene fluoride-co-hexafluoropropylene)(PvDF-HFP) gelatin polar groups lithium metal battery lithium dendrite

Federated Approach for Privacy-Preserving Traffic Prediction Using Graph Convolutional Network

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Journal of shanghai Jiaotong university(science) 2024年第3期29卷 509-517页

作者： LONARE savita BHRAMARAMBA ravi Pimpri Chinchwad College of Engineering Pune 411044India Department of Computer science and Engineering GITAMViskhapatnam 530045India

Existing traffic flow prediction frameworks have already achieved enormous success due to large traffic datasets and capability of deep learning ***,data privacy and security are always a challenge in every field where data need to be uploaded to the *** learning(FL)is an emerging trend for distributed training of *** primary goal of FL is to train an efficient communication model without compromising data *** traffic data have a robust spatio-temporal correlation,but various approaches proposed earlier have not considered spatial correlation of the traffic *** paper presents FL-based traffic flow prediction with spatio-temporal *** work uses a differential privacy(DP)scheme for privacy preservation of participant's *** the best of our knowledge,this is the first time that FL is used for vehicular traffic prediction while considering the spatio-temporal correlation of traffic data with DP *** proposed framework trains the data locally at the client-side with *** then uses the model aggregation mechanism federated graph convolutional network(FedGCN)at the server-side to find the average of locally trained *** results of the proposed work show that the FedGCN model accurately predicts the *** scheme at client-side helps clients to set a budget for privacy loss.

关键词： federated learning(FL) traffic flow prediction data privacy graph convolutional network(GCN) differential privacy(DP)

Kinetics of dense plasma in the field of short laser pulses:A generalized approach

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Matter and Radiation at Extremes 2024年第5期9卷 87-92页

作者： v.A.Astapenko v.s.Lisitsa Moscow Institute of Physics and Technology(National Research University) Institutskii per.9141701 DolgoprudnyiRussia National Research Centre“Kurchatov Institute ”123182 MoscowRussia National Research Nuclear University MEPhI 115409 MoscowRussia

A generalized kinetic model of atomic level populations in an optically dense plasma excited by laser pulses of arbitrary duration is formulated and *** model is based on a nonstationary expression for the probability of excitation of an atomic transition and takes into account the effects of laser pulse penetration into an optically dense medium.A universal formula for the excitation probability as a function of time and propagation length is derived and applied to the case of a Lorentzian spectral profile of an atomic transition excited by a laser pulse with a Gaussian *** features of nonstationary excitation probabilities are presented for different optical depths of the plasma,laser pulse durations,and carrier *** formulas derived here will be useful for the description of atomic populations excited by laser pulses under realistic conditions of dense plasmas.

关键词： laser excitation excited

E-voting system using cloud-based hybrid blockchain technology

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Journal of safety science and Resilience 2024年第1期5卷 102-109页

作者： Beulah Jayakumari s Lilly sheeba Maya Eapen Jani Anbarasi vinayakumar ravi A.suganya Malathy Jawahar Department of Information Technology Tagore Engineering College Chennai India school of Computer science and Engineering sRM Institute of science and Technology Ramapuram ChennaiIndia Department of Information Technology Jerusalem College of Engineering ChennaiIndia school of Computer science and Engineering vellore Institute of Technology Chennai India Center for Artificial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia Leather Process Technology Division CsIR-Central Leather Research Institute ChennaiIndia

With the invention of Internet-enabled devices,cloud and blockchain-based technologies,an online voting system can smoothly carry out election *** pandemic situations,citizens tend to develop panic about mass gatherings,which may influence the decrease in the number of *** urges a reliable,flexible,transparent,secure,and cost-effective voting *** proposed online voting system using cloud-based hybrid blockchain technology eradicates the flaws that persist in the existing voting system,and it is carried out in three phases:the registration phase,vote casting phase and vote counting phase.A timestamp-based authentication protocol with digital signature validates voters and candidates during the registration and vote casting *** smart contracts,third-party interventions are eliminated,and the transactions are secured in the blockchain ***,to provide accurate voting results,the practical Byzantine fault tolerance(PBFT)consensus mechanism is adopted to ensure that the vote has not been modified or ***,the overall performance of the proposed system is significantly better than that of the existing *** performance was analyzed based on authentication delay,vote alteration,response time,and latency.

关键词： E-voting Cloud Blockchain smart contract Consensus mechanism

An Interactive Operating Demand Response Approach for Hybrid Power systems Integrating Renewable Energy sources

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Protection and Control of Modern Power systems 2024年第3期9卷 174-194页

作者： Abhishek saxena ravi shankar IEEE the Department of Electrical Engineering National Institute of Technology PatnaIndia

The increased deployment of renewable energy in existing power networks has jeopardized rotational inertia,resulting in system degradation and *** address the issue,this paper proposes a demand response strategy for ensuring the future reliability of the electrical power *** addition,a modified fuzzy logic control topology-based two-degree-of-freedom(fractional order proportional integral)-tilt derivative controller is designed to regulate the frequency within a demand response framework of a hybrid two-area deregulated power *** test system includes thermal power plants,renewable energy sources(such as wind,parabolic trough solar thermal plant,biogas),and electric vehicle *** adaptively tune the controller’s coefficients,a quasi-opposition-based harris hawks optimization(QOHHO)algorithm is *** effectiveness of this algorithm is compared to other optimization algorithms,and the stability of the system is *** results demonstrate that the designed control algorithm significantly enhances system frequency stability in various scenarios,including uncertainties,physical constraints,and high penetration of renewables,compared to existing ***,an experimental assessment through OPAL-RT is conducted to verify the practicality of the proposed strategy,considering source and load intermittencies.

关键词： Area control error demand response energy storage vertically integrated utility

Conformally symmetric wormhole solutions supported by non-commutative geometry in f(Q,T)gravity

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Communications in Theoretical Physics 2024年第2期76卷 111-124页

作者： Chaitra Chooda Chalavadi v venkatesha N s Kavya s v Divya Rashmi Department of P.G.studies and Research in Mathematics Kuvempu UniversityShankaraghattaShivamogga 577451KarnatakaIndia Department of Mathematics Vidyavardhaka College of EngineeringMysuru—570002India

This paper investigates wormhole solutions within the framework of extended symmetric teleparallel gravity,incorporating non-commutative geometry,and conformal *** achieve this,we examine the linear wormhole model with anisotropic fluid under Gaussian and Lorentzian *** primary objective is to derive wormhole solutions while considering the influence of the shape function on model parameters under Gaussian and Lorentzian *** resulting shape function satisfies all the necessary conditions for a traversable ***,we analyze the characteristics of the energy conditions and provide a detailed graphical discussion of the matter contents via energy ***,we explore the effect of anisotropy under Gaussian and Lorentzian ***,we present our conclusions based on the obtained results.

关键词： traversable wormhole f(Q T)gravity energy conditions non-commutative geometry conformal motion