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User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains

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Computer systems science & Engineering 2022年第8期42卷 605-618页

作者： s.Godfrey Winster A.siva Kumar R.ramesh Department of Computer science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyChengalpattu603203India Department of Information Technology Sri Sai Ram Engineering CollegeChennai600044India Department of Electronics and Communication Engineering Saveetha Engineering CollegeChennai602105India

Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner.The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation(RMI).The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user.Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service.To improve the performance in data security,the block chains are used for securing the data in the cloud environment.However,the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud.In this paper,an efficient user centric block level Attribute Based Encryption(UCBL-ABE)scheme is presented to provide the efficient security of cloud data in cloud environment.The proposed approach performs data transaction by employing the block chain.The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust(DLAT).Based on DLAT,the user access has been restricted in the cloud environment.The proposed protocol is implemented in real time using Java programming language and uses IBM cloud.The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.

关键词： Cloud blockchain data security ABE block-level

Fuzzy-Based secure Clustering with Routing Technique for VANETs

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Computer systems science & Engineering 2022年第10期43卷 291-304页

作者： T.s.Balaji s.srinivasan s.Prasanna Bharathi B.ramesh saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Electronics and Communication Engineering College of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Electronics and Communication Engineering SRM Institute of Science and Technology600026ChennaiIndia Department of Civil Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India

Due to the advanced developments in communication technologies,Internet of vehicles and vehicular adhoc networks(VANET)offers numerous opportunities for effectively managing transportation problems.On the other,the cloud environment needs to disseminate the emergency message to the vehicles which are consistently distributed on the roadway so that every vehicle gets the messages from closer vehicles in a straightforward way.To resolve this issue,clustering and routing techniques can be designed using computational intelligence approaches.With this motivation,this paper presents a new type-2 fuzzy sets based clustering with metaheuristic optimization based routing(T2FsCMOR)technique for secure communication in VANET.The T2FsC-MOR technique aims to elect CHs and optimal routes for secure intercluster data transmission in VANET.The proposed model involves T2FsC technique for the selection of CHs and construction of clusters.The T2FsC technique uses different parameters namely traveling speed(Ts),link quality(LQ),trust factor(TF),inter-vehicle distance(IVD),and neighboring node count(NCC).The inclusion of trust factor helps to select the proper cluster heads(CHs)for secure data dissemination process.Moreover,trust aware seagull optimization based routing(TAsGOR)approach was derived for the optimal selection of routes in VANET.In order to validate the enhanced performance of proposed technique,the set of simulations take place and the outcomes are examined interms of different measures.The experimental outcomes highlighted the improved performance of the proposed model over the other state of art techniques with a higher throughput of 98%.

关键词： VANET security clustering routing fuzzy logic systems metaheuristic algorithms

Recognition and classification of paddy leaf diseases using Optimized Deep Neural network with Jaya algorithm

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Information Processing in Agriculture 2020年第2期7卷 249-260页

作者： s.ramesh D.Vydeki Electronics and Communication Engineering Department VIT UniversityChennai 600127India

In the agriculture field,one of the recent research topics is recognition and classification of diseases from the leaf images of a plant.The recognition of agricultural plant diseases by utilizing the image processing techniques will minimize the reliance on the farmers to protect the agricultural products.In this paper,Recognition and Classification of Paddy Leaf Diseases using Optimized Deep Neural Network with Jaya Algorithm is proposed.For the image acquisition the images of rice plant leaves are directly captured from the farm field for normal,bacterial blight,brown spot,sheath rot and blast diseases.In pre-processing,for the background removal the RGB images are converted into HsV images and based on the hue and saturation parts binary images are extracted to split the diseased and non-diseased part.For the segmentation of diseased portion,normal portion and background a clustering method is used.Classification of diseases is carried out by using Optimized Deep Neural Network with Jaya Optimization Algorithm(DNN_JOA).In order to precise the stability of this approach a feedback loop is generated in the post processing step.The experimental results are evaluated and compared with ANN,DAE and DNN.The proposed method achieved high accuracy of 98.9%for the blast affected,95.78%for the bacterial blight,92%for the sheath rot,94%for the brown spot and 90.57%for the normal leaf image.

关键词： Paddy leaf diseases Optimized Deep Neural Network Jaya optimization algorithm K-means clustering Color features Texture features

Binder-free heterostructure(g-C3N4/PPy) based thin film on semi-flexible nickel foam via hybrid spray technique for energy storage application

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Progress in Natural science:Materials International 2020年第3期30卷 298-307页

作者： Navaneethan Duraisamy Prabhu s ramesh R Kavitha Kandiah Department of Chemistry J.K.K.Nataraja College of Arts and Science Komarapalayam 2. Department of Physics Periyar University Department of Microbiology Periyar University Center for New and Renewable Energy Department of Physics Periyar University

A semi-flexible binder-free graphitic carbon nitride(g-CN) intercalated polypyrrole(PPy) nanocomposite thin film was prepared via hybrid electrospray technique. A homogeneous thin film was achieved by the controlled spray process. A deposited thin film illustrated the amorphous nature of composite with high surface purity and good chemical composition. The surface analysis confirmed the smoother surface with well-defined distinct phases of g-CNand PPy matrix in the composite thin film. The electrochemical studies exhibited that a maximum areal capacity of the thin film was achieved to be 289.6 mF/cm~2 at a current density of 0.4 mA/cm~2,which is higher than that of pristine PPy(194.8 mF/cm~2). The heterostructure electrode illustrated that the life cycles of 99% could be up to 10,000 cycles with low resistance due to the synergetic effect of g-CNand PPy matrix with strong material adhesion(hybrid spray process) on the surface. A binder-free heterostructure thin film will play a significant role in the energy storage application.

关键词： Polypyrrole G-C 3 N 4 Heterostructure spray Thin film Electrochemical study

Hybrid Deep Learning-Improved BAT Optimization Algorithm for soil Classification Using Hyperspectral Features

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Computer systems science & Engineering 2023年第4期45卷 579-594页

作者： s.Prasanna Bharathi s.srinivasan G.Chamundeeswari B.ramesh saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105TamilnaduIndia Department of Electronics and Communication Engineering College of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India

Now a days,Remote sensing(Rs)techniques are used for earth observation and for detection of soil types with high accuracy and better reliability.This technique provides perspective view of spatial resolution and aids in instantaneous measurement of soil’s minerals and its characteristics.There are a few challenges that is present in soil classification using image enhancement such as,locating and plotting soil boundaries,slopes,hazardous areas,drainage condition,land use,vegetation etc.There are some traditional approaches which involves few drawbacks such as,manual involvement which results in inaccuracy due to human interference,time consuming,inconsistent prediction etc.To overcome these draw backs and to improve the predictive analysis of soil characteristics,we propose a Hybrid Deep Learning improved BAT optimization algorithm(HDIB)for soil classification using remote sensing hyperspectral features.In HDIB,we propose a spontaneous BAT optimization algorithm for feature extraction of both spectral-spatial features by choosing pure pixels from the Hyper spectral(Hs)image.spectral-spatial vector as training illustrations is attained by merging spatial and spectral vector by means of priority stacking methodology.Then,a recurring Deep Learning(DL)Neural Network(NN)is used for classifying the Hs images,considering the datasets of Pavia University,salinas and Tamil Nadu Hill scene,which in turn improves the reliability of classification.Finally,the performance of the proposed HDIB based soil classifier is compared and analyzed with existing methodologies like single Layer Perceptron(sLP),Convolutional Neural Networks(CNN)and Deep Metric Learning(DML)and it shows an improved classification accuracy of 99.87%,98.34%and 99.9%for Tamil Nadu Hills dataset,Pavia University and salinas scene datasets respectively.

关键词： HDIB bat optimization algorithm recurrent deep learning neural network convolutional neural network single layer perceptron hyperspectral images deep metric learning

导电纤维材料在高柔性可穿戴超级电容器中的研究进展

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新型炭材料（中英文） 2023年第2期38卷 211-229页

作者： Nujud Badawi M Namrata Agrawal syed Farooq Adil s ramesh K ramesh shahid Bashir Centre for Ionics University of Malaya Department of PhysicsFaculty of ScienceUniversiti MalayaKuala Lumpur 50603Malaysia University of Hafr Al-Batin College of ScienceHafer Al-Batin 39921Saudi Arabia swami shraddhanand College University of DelhiDelhiIndia Department of Chemistry College of ScienceKing Saud UniversityRiyadhKingdom of Saudi Arabia Department of Physics/saveetha school of Engineering Saveetha University(SIMATS)ChennaiIndia Higher Institution Centre of Excellence(HICoE) UM Power Energy Dedicated Advanced Centre(UMPEDAC)Universiti MalayaJalan Pantai Baharu59990 Kuala LumpurMalaysia

采用纤维材料制备的超级电容器因柔韧性好、质量轻、能量密度高等优点,成为人们关注的电化学储能器件。目前,他们已广泛应用在信息传感、数据计算和通信等电子系统中。这些基于纤维材料的超级电容器(sCs)拥有比标准的平行平板电容器和... 详细信息

采用纤维材料制备的超级电容器因柔韧性好、质量轻、能量密度高等优点,成为人们关注的电化学储能器件。目前,他们已广泛应用在信息传感、数据计算和通信等电子系统中。这些基于纤维材料的超级电容器(sCs)拥有比标准的平行平板电容器和电池具有更高的功率密度,因而再电子纺织品中大量使用。本文详细阐述了碳纳米管(CNTs)、石墨烯和聚(3,4-乙烯二氧噻吩):聚(苯乙烯磺酸)(PEDOT:Pss)的组成、纺丝和制备条件对可穿戴储能装置电化学性能的影响。

关键词：纺织基超级电容器智能织物柔性系统储能

Analysis of Melting Heat Transport in a Cross Flow Direction:A Comparative study

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Communications in Theoretical Physics 2018年第12期69卷 777-784页

作者： G.K.ramesh s.A.shehzad Department of Mathematics K.L.E'S J.T.College Department of Mathematics COMSATS Institute of Information Technology

An incompressible three-dimensional laminar flow in a cross flow direction is described in this work. The term of melting and viscous dissipation is incorporated in the mathematical modeling of present flow problem. The flow expressions are converted into dimensionless equations, which are solved with help of Runge-Kutta scheme. Impact of the emerging parameters on the non-dimensional velocities and temperature and friction-factors and local Nusselt number are examined. The convergence analysis is found for ε sis is made between the obtained results and published data for limiting case. It is explored at the surface that the melting parameter retards the liquid temperature while it enhances the fluid velocity.

关键词： melting effect cross flow moving plate viscous heating numerical solution

Closed-Form solutions of stress Intensity Factors for semi-elliptical surface Cracks in a Cylindrical Bar Under Pure Tension

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Acta Mechanica solida sinica 2022年第2期35卷 344-356页

作者： M.K.Ramezani s.ramesh J.Purbolaksono R.Das Centre of Advanced Manufacturing and Materials Processing Department of Mechanical EngineeringFaculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Department of Mechanical Engineering University of PertaminaJakarta 12220Indonesia sir Lawrence Wackett Aerospace Research Centre School of EngineeringRMIT UniversityMelbourneVI 3000Australia

In this work,the stress intensity factors(sIFs)for a wide range of semi-elliptical surface cracks with different inclination angles in a cylindrical bar subjected to pure tension were investigated numerically.The main parameters considered to evaluate the sIFs were the crack size ratio(a/d),the crack aspect ratio(a/c),and the crack inclination angle(0).The dual-boundary element met hod implemented in software BEAsY was used to compute the sIF values for cracks.Furt her more,the general closed-form solutions were proposed to evaluate the corresponding sIFs for Mode I,Mode II and Mode III types of fracture through curve fitting approaches.These solutions can provide accurate and reliable values of stress intensity factors for a crack on a cylindrical bar under pure tension in a rapid way compared to those obtained using computational models.In addition,these results can be used as inputs for failure studies and life evaluations of cracked cylinder under working conditions.

关键词： stress intensity factor surface crack solid cylinder Closed-form solution Dual-boundary element method

Investigation of dry sliding wear properties of multi-directional forged Mg-Zn alloys

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Journal of Magnesium and Alloys 2019年第3期7卷 444-455页

作者： s.ramesh Gajanan Anne H.shivananda Nayaka sandeep sahu M.R.ramesh Department of Mechanical Engineering National Institute of Technology KarnatakaSurathkal 575025India Department of Mechanical Engineering Shri Madhwa Vadiraja Institute of Technology and ManagementUdupiKarnataka 574115India Department of Materials science and Engineering Indian Institute of Technology KanpurKanpur 208016India

Effect of multi-directional forging(MDF)on wear properties of Mg-Zn alloys(with 2,4,and 6wt%Zn)is investigated.Dry sliding wear test was performed using pin on disk machine on MDF processed and homogenized samples.Wear behavior of samples was analyzed at loads of ION and 20 N,with sliding distances of 2000m and 4000m,at a sliding velocity of 3m/s.Microstructures of worn samples were observed under scanning electron microscopy(sEM),energy dispersive spectroscopy(EDs),and x-ray diffraction(XRD)and the results were analyzed.Mechanical properties were evaluated using microhardness test.After 5 passes of MDF,the average grain size was found to be 30±4p m,22±3 pm,and 18±3 pm,in Mg-2%Zn,Mg-4%Zn,and Mg-6%Zn alloys,respectively,with significant improvement in hardness in all cases.Wear resistance was improved after MDF processing,as well as,with increment in Zn content in Mg alloy.However,it decreased when the load and the sliding distance increased.Worn surface exhibited ploughing,delamination,plastic deformation,and wear debris along sliding direction,and abrasive wear was found to be the main mechanism.

关键词： Multi-directional forging Mg-Zn alloy Microhardness Wear Coefficient of friction