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RETRACTED ARTICLE: Modified adaptive neuro fuzzy inference system based load balancing for virtual machine with security in cloud computing environment

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Journal of Ambient Intelligence and Humanized Computing 2020年第3期12卷 3869-3876页

作者： Durga Devi, T. J. b. subramani, A. Anitha, P. Department of Computer Applications K.S.R. College of Engineering Tiruchengode India Department of Computer Science M.V.Muthiah Government Arts College for Women Dindigul India

In a heterogeneous environment, computation over internet is provided by a popular paradigm called cloud computing. In a cloud heterogeneous environment, service providing has various difficulties. based on service type, difficulties differ. On cloud server, high load is produced by huge amount of request from various users for accessing various applications. security and balancing of load are major concerns. In cloud environment, NP-hard optimization problem corresponds to load balancing. Dynamic load balancing is handled by various methods. They are designed for enhancing workload distribution process between nodes. Overload avoidance, minimization of average response time, data processing time and optimum utilization of resources are the major aim of those methods. An optimal load balancing technique should improve the turnaround time and maximum CPU utilization. because of its opaqueness nature of cloud, security is a biggest challenge. According to Forbes, with introduction of General Data Protection Regulation security in cloud continue to be an issue with cloud computing. In the existing system, a fuzzy based hybrid load balancing algorithm is utilized and the results provided are not satisfactory. There are opportunities for improving CPU utilization and turnaround time and in terms of security. In this proposed research work, dynamic load balancing in a heterogeneous environment is handled by Modified Adaptive Neuro Fuzzy Inference system (MANFIs). Parameters of MANFIs are optimized by introducing Fire-fly Algorithm. security is imposed on user authentication by using the Enhanced Elliptic Curve Cryptography. This is a password-less mechanism to authenticate users. The proposed work attains satisfactory results by proper resource utilization. An experimental result shows that proposed work exhibits better performance by improving the turnaround time and maximizing the CPU utilization and providing secured access to data.

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sTRUCTURE OF bLOCKs WITH NORMAL DEFECT AND AbELIAN p' INERTIAL QUOTIENT

arXiv

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arXiv 2022年

作者： benson, David Kessar, Radha Linckelmann, Markus Institute of Mathematics Fraser Noble Building University of Aberdeen King's College AberdeenAB24 3UE United Kingdom School of Mathematics Computer Science & Engineering Department of Mathematics City University of London Northampton Square LondonEC1V 0HB United Kingdom

Let k be an algebraically closed field of prime characteristic p. Let kGe be a block of a group algebra of a finite group G, with normal defect group P and abelian p' inertial quotient L. Then we show that kGe is a matrix algebra over a quantised version of the group algebra of a semidirect product of P with a certain subgroup of L. To do this, we first examine the associated graded algebra, using a Jennings-Quillen style theorem. As an example, we calculate the associated graded of the basic algebra of the non-principal block in the case of a semidirect product of an extraspecial p-group P of exponent p and order p3 with a quaternion group of order eight with the centre acting trivially. In the case p = 3 we give explicit generators and relations for the basic algebra as a quantised version of kP. As a second example, we give explicit generators and relations in the case of a group of shape 21+4 : 31+2 in characteristic *** Codes 20C20 © 2022, CC bY-NC-ND.

关键词： Defects

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HOCHsCHILD COHOMOLOGY OF sYMMETRIC GROUPs IN LOW DEGREEs

arXiv

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arXiv 2022年

We compute the dimensions of the Hochschild cohomology of symmetric groups over prime fields in low degrees. This involves us in studying some partition identities and generating functions of the dimensions in any fix... 详细信息

关键词： Topology

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When vision Meets Touch: A Contemporary Review for visuotactile sensors from the signal Processing Perspective

arXiv

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arXiv 2024年

作者： Li, shoujie Wang, Zihan Wu, Changsheng Li, Xiang Luo, shan Fang, bin sun, Fuchun Zhang, Xiao-Ping Ding, Wenbo Tsinghua Shenzhen International Graduate School Shenzhen518055 China RISC-V International Open Source Laboratory Shenzhen518055 China Department of Materials Science and Engineering National University of Singapore Singapore117575 Singapore Centre for Robotics Research King’s College London LondonWC2R 2LS United Kingdom Department of Automation Tsinghua University Beijing100084 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Department of Computer Science and Technology Tsinghua University Beijing100084 China

Tactile sensors, which provide information about the physical properties of objects, are an essential component of robotic systems. The visuotactile sensing technology with the merits of high resolution and low cost has facilitated the development of robotics from environment exploration to dexterous operation. Over the years, several reviews on visuotactile sensors for robots have been presented, but few of them discussed the significance of signal processing methods to visuotactile sensors. Apart from ingenious hardware design, the full potential of the sensory system toward designated tasks can only be released with the appropriate signal processing methods. Therefore, this paper provides a comprehensive review of visuotactile sensors from the perspective of signal processing methods and outlooks possible future research directions for visuotactile sensors. Copyright © 2024, The Authors. All rights reserved.

关键词： signal processing

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Tomato leaf disease identification by modified inception based sequential convolution neural networks

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The Journal of Photographic science 2023年第5期71卷

作者： R. Dhanalakshmi balakrishnan K bam bahadur sinha R. Gopalakrishnan a Department of Computer Science and Engineering Indian Institute of Information Technology Tiruchirappalli Sethurapatti Tamil Nadu India b Department of Computer Science and Engineering Indian Institute of Information Technology Ranchi Jharkhand India c Department of Electrical and Electronics Engineering K.S. Rangasamy College of Technology Tiruchengode India

AbsTRACTTomato leaf disease detection has been a challenge for farmers due to the need for quick and accurate diagnosis to prevent plant contamination. Traditional approaches such as visual observation and laboratory testing have limitations such as subjectivity and reliance on human expertise. Deep Learning (DL) approaches, particularly Convolutional Neural Networks (CNN), have emerged as a solution for disease identification and classification in plants. This research proposes a new variant of an inception-based sequential network that combines the advantages of deep residual and dense networks to reduce dimensionality and enhance accuracy, information flow, and gradient. Modified input image characteristics and hyper-parameters were used to classify existing networks on the tomato dataset, with experimental findings showing that the proposed model can achieve an average identification accuracy of up to 96 percent on the tomato test dataset. The model's performance surpasses most existing leaf identification models and requires fewer computation.

关键词： Leaf disease identification convolutional neural networks inception-v3 tomato leaf disease classification diagnosis severity multi-class classification

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synergistic Impact of Magnesium Compound as a Potential Dye Additive for Organic-based sensitizer in Dsscs

SSRN

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ssRN 2022年

作者： Khan, Azlina Ahmad Abdullah, M.H. Rahman, M.A. Faizal Yusof, M. syarifah Adilah Mamat, Mohamad Hafiz bin Radzol, Afaf Md sin, N. Diyana sabani, N. Hayati banu, I.b. shameen Rusop, M. School of Electrical Engineering College of Engineering Universiti Teknologi MARA Cawangan Pulau Pinang Pulau Pinang Permatang Pauh13500 Malaysia College of Electrical Engineering Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Department of Computer and Mathematical Sciences Universiti Teknologi MARA Cawangan Pulau Pinang Pulau Pinang Permatang Pauh13500 Malaysia Universiti Malaysia Perlis Perlis Kangar01000 Malaysia Department of Physics B.S. Abdur Rahman Crescent Institute of Science & Technology Vandalur Chennai600 048 India

In this study, the dye-sensitized solar cell (DssCs) was successfully fabricated using a dye molecule sensitizer extracted from Mitragyna speciosa (Ms), while MgsO 4 salt compound served as a potent dye additive for dye treatment. The optimal amount of MgsO 4 additive that contributed to the highest power conversion efficiency, PCE was investigated. Field emission sEM, FEsEM, X-ray diffraction, XRD, Fourier transform-IR, FTIR, Uv-vis spectroscopy, current to voltage characteristics, I-v and incidence photon to current efficiency, IPCE were used to investigate the structural, optical, chemical and also the electrical properties of the DssC cells and their components. It was found that the extracted Ms dye provided evidence of the presence of chlorophyll pigment, an effective light-harvesting pigment necessary for the production of charge transfer and electricity. Also, MgsO 4 dye additive-based DssCs outperformed the untreated dye cell. At their optimal dye additive of 0.3 g (6 ml of chlorophyll dye solution), the current density, Jsc and the associated PCE of the DssC was higher at 2.08 mA/cm 2 and 0.39%, respectively. Thus, using Ms as a dye sensitizer with optimized MgsO 4 compound as the additive showed better photovoltaic effects, increased solar light absorption and enhanced photon energy utilisation. © 2022, The Authors. All rights reserved.

关键词： Magnesium compounds

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Highlighting Nerves in Images for Ultrasound Guided Regional Anesthesia 1

Highlighting Nerves in Images for Ultrasound Guided Regional...

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1st IEEE bangalore Humanitarian Technology Conference, b-HTC 2020

作者： Akkasaligar, Prema T. Koolagudi, shashidhar G. biradar, sunanda Hotagi, Poornima badiger, sharan VijayapurKaranataka586103 India Department of Computer Science and Engineering National Institute of Technology Karnataka Surathkal India Department of Medicine BLDEDU's Sri B.M.Patil Medical College and Research Centre VijayapurKarnataka India

ISBN: (纸本)9781728187945

surgery is a treatment given to the patient, when patient is having injuries in the body parts. While doing the surgery the patient will undergo pain and discomfort, to reduce the pain of patient anesthesia is given before surgery. There are many types of anesthesia procedure called local, regional and general. Local anesthesia is given to specific part of the body;general anesthesia is where the patient is completely senseless. Regional anesthesia is procedure, where anesthetist does injection near a class of nerves to numb the area of human body that requires surgery. There is difference in structure of every person. This makes doctor hard to detect nerve in internal organ. Ultrasound image provide information about structure of body which can be used for regional anesthesia. Ultrasonography is the safest method compared to the other imaging techniques like Xray, CT, and MRI;because it is not based on ionizing radiation. In this paper, we simplify the issue of detection of nerve in ultrasound image. For input, image such as ultrasound images of brachial plexus are used. Initially in preprocessing, filtering technique is used to remove noise from ultrasound image and then segmentation is carried out using active contour model. Performance of segmentation is evaluated using dice coefficient and Jaccard coefficient. The nerve location in ultrasound image is detected to help the doctors in giving regional anesthesia. © 2020 IEEE.

关键词： Median filters

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Review of meta-heuristic optimization based artificial neural networks and its applications

Review of meta-heuristic optimization based artificial neura...

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International Conference on Physics and Photonics Processes in Nano sciences 2019

作者： Devikanniga, D. vetrivel, K. badrinath, N. Department of Computer Science and Engineering Rajas Engineering College Tirunelveli TamilNadu India Department of Information Technology N.M.S.S.V.N College Madurai Tamil Nadu India Department of Computer Science and Engineering Lords Institute of Engineering and Technology Hyderabad Telangana India

There are several meta-heuristic optimization algorithms developed on inspiration from nature. Artificial neural network proves to be efficient among other machine learning techniques. The efficiency of classification and prediction is improved by optimizing artificial neural network using the meta-heuristic optimization algorithms. The review of some of these hybrid artificial neural networks that are applied for benchmark datasets and to specific real-time experiments for classification and prediction are discussed. Upcoming sections cover the current trending research topics dealing with optimized artificial neural network concepts and provide some interesting insights for researchers to use in their respective applications domains of interest. © Published under licence by IOP Publishing Ltd.

关键词： Neural networks

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Enhanced security for the authentication of Digital signature from the key generated by the CsTRNG method

Enhanced Security for the authentication of Digital Signatur...

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International Conference on smart systems and Inventive Technology (ICssIT)

作者： b.v.v.s. Prasad sridhar Mandapati b. Haritha MD.Jareena begum Computer Science Engg. Chebrolu Engineering College Guntur India R. V. R & J. C COLLEGE OF ENGINEERING Guntur India Computer Science Engg. Bapatla Women's Engineering College Bapatla India

ISBN: (数字)9781728158211

ISBN: (纸本)9781728158228

security is the most critical feature of the present e-world. Many applications are based on random number generation. In the present situation, it is very difficult to hide the data. so the key-based encryption process is suggested to keep the files secure. The protection of the data depends on the key. Key generation is more important for all cryptography applications, which is entirely dependent on randomness. As long as many designers have been able to develop many Random Number Generator-based keys. Also work is going on to make hacker data more stable. CsTRNG can be suggested in this work. One of the most commonly used technologies in the marketing field is the production of digital signatures. The generation of digital signatures can be generated using many keys that have the property of RNG. The most stable RNG is the Cryptographically secured True Random Number Generator (CsTRNG). This could generate more unexpected numbers. Work has been built on the Xilinx IsE simulator.

关键词： Digital signatures Cryptography Generators Entropy Authentication Conferences

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A survey on semantic Communications for Intelligent Wireless Networks

arXiv

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arXiv 2022年

作者： Iyer, sridhar Khanai, Rajashri Torse, Dattaprasad Pandya, Rahul Jashvantbhai Rabie, Khaled Pai, Krishna Khan, Wali Ullah Fadlullah, Zubair Department of ECE KLE Dr. M.S. Sheshgiri College of Engineering and Technology Karnataka Belagavi India Department of CSE KLE Dr. M.S. Sheshgiri College of Engineering and Technology Karnataka Belagavi India Department of EE Indian Institute of Technology-Dharwad WALMI Campus PB Road Karnataka India Department of Engineering Manchester Metropolitan University Manchester United Kingdom University of Luxembourg Luxembourg City1855 Luxembourg Department of Computer Science ATAC Building Room AT5024 Lakehead University ONP7B 5E1 Canada

With the upsurge in next-generation intelligent applications and exponentially increasing heterogeneous data traffic both, the industry and the research community have already begun conceptualizing the 6G technology. With deployment of the 6G technology, it is envisioned that the competitive edge of wireless technology will be sustained and the next decade's communication requirements will be stratified. Also, the 6G technology will aim to aid the development of a human society which is ubiquitous, intelligent, and mobile, simultaneously providing solutions to key challenges such as, coverage, capacity, providing intelligence, computing, etc. In addition, 6G technology will focus on providing the intelligent use-cases and applications using higher data-rates over the mill-meter (mm) waves and Tera-Hertz (THz) frequency. However, at higher frequencies multiple non-desired phenomena such as atmospheric absorption, blocking, etc., occur which create a bottleneck owing to resource (spectrum and energy) scarcity. Hence, following the same trend of making efforts towards reproducing at the receiver, the exact information which was sent by the transmitter, will result in a never ending need for higher bandwidth. A possible solution to such a challenge lies in semantic communications which focuses on the meaning (relevance/context) of the received data as opposed to only reproducing the correct transmitted data. This in turn will require less bandwidth, and will reduce the bottleneck due to the various undesired phenomenon. In this respect, the current article presents a detailed survey on the recent technological trends in regard to semantic communications for intelligent wireless networks. We focus on the semantic communications architecture including the model, and source and channel coding. Next, we detail the cross-layer interaction, and the various goal-oriented communication applications. We also present the overall semantic communications trends in detail, and ident

关键词： Wireless networks

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