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Frequency reconfigurable monopole antenna

AIP Conference Proceedings 2022年第1期2519卷

作者： K. Periyarselvam N. C Sendhilkumar C. Malarvizhi R. Ganesan 1Department of Electronics and Communication Engineering GRT Institute of Engineering and Technology Tiruvallur Tamil Nadu India 2Department of Electronics and Communication Engineering Sri Indu College of Engineering & Technology Sheriguda Telangana India 3Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India 4Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India

The proposal is for a compact and novel shaped frequency-reconfigurable Monopole antenna with a large tuning band. Depending on the switching states, the recommended antenna works in single band modes. In the modelling context, lumped components are utilised to offer variable capacitance, which is responsible for frequency settings. The built antenna’s tuning capacity has been discovered to be between 2.1 and 5.2 GHz. For all resonant bands, the proposed antenna has a VSWR of 1.3. The High Frequency Structure Simulator is used to test the proposed antenna’s far field and scattering characteristics (HFSS). The developed antenna may be readily integrated into modern communication devices such as smart phones, laptops, and other portable electronic equipment due to its small size and inexpensive cost. To verify the simulation findings, a model of the proposed antenna is created and monitored using PIN diode switches. The measured and anticipated results for the recommended reconfigurable antenna are satisfactory.

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HAWK: Rapid Android malware detection through heterogeneous graph attention networks

arXiv

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arXiv 2021年

作者： Hei, Yiming Yang, Renyu Peng, Hao Wang, Lihong Xu, Xiaolin Liu, Jianwei Liu, Hong Xu, Jie Sun, Lichao The School of Cyber Science and Technology Beihang University Beijing100083 China The School of Computing University of Leeds LeedsLS2 9JT United Kingdom The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The School of Computer Science and Software Engineering East China Normal University Shanghai Trusted Industrial Control Platform Co. Ltd. Shanghai200062 China The Department of Computer Science and Engineering Lehigh University Bethlehem United States

Android is undergoing unprecedented malicious threats daily, but the existing methods for malware detection often fail to cope with evolving camouflage in malware. To address this issue, we present HAWK, a new malware detection framework for evolutionary Android applications. We model Android entities and behavioural relationships as a heterogeneous information network (HIN), exploiting its rich semantic meta-structures for specifying implicit higher-order relationships. An incremental learning model is created to handle the applications that manifest dynamically, without the need for re-constructing the whole HIN and the subsequent embedding model. The model can pinpoint rapidly the proximity between a new application and existing in-sample applications and aggregate their numerical embeddings under various semantics. Our experiments examine more than 80,860 malicious and 100,375 benign applications developed over a period of seven years, showing that HAWK achieves the highest detection accuracy against baselines and takes only 3.5ms on average to detect an out-of-sample application, with the accelerated training time of 50x faster than the existing approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Android (operating system)

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Energy management in electric vehicle using machine learning

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AIP Conference Proceedings 2023年第1期2523卷

作者： T. G. Arul K. Vijay Kumar Usman K. S. Mohideen J. A. M. Rexie L. Chitra. 1Department of MechanicalEngineering St.Mary's Engineering College Hyderabad Telangana India. 2Department of Mechanical Engineering Malla Reddy College of Engineering Hyderabad Telangana India. 3Department of Management Studies Sri Sairam Engineering College Chennai Tamil Nadu India. 4Departmentof Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India. 5Department of Electrical and Electronics Engineering AarupadaiVeedu Institute of Technology Vinayaka Mission's Research Foundation Deemed to be University Paiyanoor Tamil Nadu India.

In power system, the energy which is fed to the grid control and management is accomplished using various architectures system. The variation in the control and manage systems are based on the performance and features as well as the overall cost. HEVs were really high increased air and oil emissions control. HEVs of different designs are becoming increasingly common, as they can achieve high fuel savings and mitigate emissions through multiple storage systems. The most powerful approach is the battery-driven *** article examines the management of energy issue with the minimisation of the operating costs of the HEVs for hybrid electric vehicles (HEVs). The energy management strategy and hybrid performance enhancement are the key to ensuring the system functions properly. The battery energy is managed using the proposed GA approach based on reinforcement learning (RL) which is originated from the ML. The results are obtained and verified successfully.

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Erratum: “Understanding the interplay of surface structure and work function in oxides: A case study on SrTiO3” [APL Mater. 8, 071110 (2020)]

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APL Materials 2021年第1期9卷

作者： Tianyu Ma Ryan Jacobs John Booske Dane Morgan 1Department of Materials Science and Engineering University of Wisconsin-Madison Madison Wisconsin 53706 USA 2Department of Electrical and Computer Engineering University of Wisconsin-Madison Madison Wisconsin 53706 USA

Since the publication of the original article,1 we found that some of the DFT-calculated work functions in Tables II and III in the original article were incorr

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High-speed CMOS-free purely spintronic asynchronous recurrent neural network

APL Machine Learning

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APL Machine Learning 2023年第1期1卷

作者： Pranav O. Mathews Christian B. Duffee Abel Thayil Ty E. Stovall Christopher H. Bennett Felipe Garcia-Sanchez Matthew J. Marinella Jean Anne C. Incorvia Naimul Hassan Xuan Hu Joseph S. Friedman 1School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia 30332 USA 2Department of Electrical and Computer Engineering The University of Texas at Dallas Richardson Texas 75080 USA 3Laboratoire de Physique de la Matière Condensée Ecole Polytechnique CNRS IP Paris Palaiseau 91128 France 4Sandia National Laboratories Albuquerque New Mexico 87185 USA 5Departamento de Física Aplicada Universidad de Salamanca Salamanca 37008 Spain 6School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA 7Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA

The exceptional capabilities of the human brain provide inspiration for artificially intelligent hardware that mimics both the function and the structure of neurobiology. In particular, the recent development of nanodevices with biomimetic characteristics promises to enable the development of neuromorphic architectures with exceptional computational efficiency. In this work, we propose biomimetic neurons comprised of domain wall-magnetic tunnel junctions that can be integrated into the first trainable CMOS-free recurrent neural network with biomimetic components. This paper demonstrates the computational effectiveness of this system for benchmark tasks and its superior computational efficiency relative to alternative approaches for recurrent neural networks.

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Estimation of climate change impact on the flood of Kickapoo River at La Farge

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AIP Conference Proceedings 2022年第1期2463卷

作者： Sivapragasam C. Saravanan P. Balamurali S. 1Center for Water Technology Kalasalingam Academy of Research and Education Srivilliputtur-626126 India 2Department of Civil Engineering Kalasalingam Academy of Research and Education Srivilliputtur-626126 India 3Department of Computer Applications Kalasalingam Academy of Research and Education Srivilliputtur-626126 India

Predicting the impact of climate change in a particular river is necessary to adapt and mitigate the future floods. In this study the climate change impact on Kickapoo River is estimated using the rainfall forcing of RCP 4.5 scenario. Towards this a new methodology is framed to simulate discharge in the river using Artificial Neural Network which uses the knowledge of predictability of the time series as well. Four different bias correction methods, including an ANN based bias correction method is evaluated to reduce the biases in the rainfall forcing series obtained from Global Circulation Model and the best out of the four applied to bias correct the whole series. Simulation of discharge is done till the year 2099. It is found the Kickapoo River flow may likely go low in future due to climate change.

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Scheduling task and offloading process based on KNN and NB algorithm on cloud

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AIP Conference Proceedings 2021年第1期2387卷

作者： J. Premalatha K. Sathya Vani Rajasekar S. E. Dharani S. Harivarshini R. Keerthana 1Department of Information Technology Kongu Engineering College Erode Tamilnadu India - 638060 2Department of Computer Technology-UG Kongu Engineering College Erode Tamilnadu India - 638060 3Department of Computer Science and Engineering Kongu Engineering College Erode Tamilnadu India - 638060

Cloud Computing is quickly developing and a lot more cloud suppliers are arising. This project says how the incoming tasks are scheduled in the cloud. In this paper, presenting a classifier algorithmic technique that integrates the K-Nearest Neighbor(KNN) algorithm with the Naive Bayes algorithm. Calculation offloading innovation offers a feasible arrangement by offloading some calculation serious assignments of the K-Nearest Neighbor algorithm and the Naive Bayes algorithm to edges or distant mists that are furnished with adequate assets. However, the offloading process might lead to excessive delays and thus seriously affect the user experience. To address this significant issue, we first respect the average response time of multi-task parallel scheduling as our streamlining objective. Finally, the K-Nearest Neighbor and Naive Bayes algorithm based applications are proposed to solve the problem. Offloading a task means how the task is scheduled in Virtual Machine, first, the task is separated into types(small, medium, large and extra-large) after that it sees which Virtual Machine is available to load the task. Suppose, if the incoming task is too-large then we have to offload it by separating the task into subtask as 6 operations (split, combine, merge, demerge, promote and demote). To avoid the burden in the Virtual Machine, We analyze the above operations by using the K-Nearest Neighbour (KNN) algorithm with the Naive Bayes algorithm and then scheduled in the Virtual Machine. We want to show that the K-Nearest Neighbour (KNN) algorithm with the Naive Bayes algorithm shows better performance than Deep Neural Network(DNN).

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Online food court payment processing using blockchain

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AIP Conference Proceedings 2021年第1期2387卷

作者： J. Premalatha K. Sathya Vani Rajasekar S. Nishanth S. Ramesh Kumar M. Praveena 1Department of Information Technology Kongu Engineering College Erode Tamilnadu India - 638060 2Department of Computer Technology UG Kongu Engineering College Erode Tamilnadu India - 638060 3Department of Computer Science and Engineering Kongu Engineering College Erode Tamilnadu India - 638060

It is a web-based application designed commonly for use in Food & beverage based enterprises. These applications tackle the issues of Manual Labour cost in the food court bringing about a rapid expansion in the Overall business Model. It also provides the proprietor of the restaurant to administer and make modifications as per the stip-ulations in their restaurant. The consumer can order their food by accessing the application through their mobile browser in an optimized manner. The retailer can easily complete the order in time, as there will be a streamlined check-in for the availability of ingredients. In this paper, let's exemplify the overall description and generalized soft-ware requirements specification of the entire systematic structure designed for use in different food courts. Our appli-cation will impart the restaurant employees to manage their online cuisines and keep track of all the orders placed by their consumers. Furthermore, the Customer can make Payment using the Existing Payment Gateways as well as they can go for blockchain-based Payment Methodologies. Eventually, this idea is projected to reduce the overheads of Payment gateways and improvise Data security in a precise manner.

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Development of a fuzzy authentication system for the automated line devices of a distributed internet of things using a hash-resistant algorithm

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AIP Conference Proceedings 2023年第1期2700卷

作者： A. L. Zolkin T. G. Aygumov A. N. Losev E. V. Alexandrova 1Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara 443010 Russia 2Department of computer engineering software and automated systems Dagestan State Technical University Makhachkala 367000 Russia 3Department of Applied Informatics Russian State Agrarian University - Moscow Timiryazev Agricultural Academy Moscow 127550 Russia 4Department of Information Technologies and Mathematics Orel State Agrarian University named after N.V. Parakhin Orel 302019 Russia

The cybernetic essence of the data extraction process at the level of end nodes (intermediate links of the information exchange path) is considered in the article. Authors consider and generalize the context-oriented problem of control action transferring to a specific activation point (transfer perceptron (response node)).The authors consider the subject area - distributed response networks. The role of addictive technologies in the process of formation of a complex control action or command and their transmitting is indicated. A simulation balance model is being developed for a routing model in the spatial field of an industrial computer network. It implements the method of filtering and disaggregation of automated technological process control lines according to a group criterion (by the method of sets determination).The introduction of hardware control of the model of the authentication system of automated line devices using the method of data multiplexing and the apparatus of fuzzy mathematics is given, formalized and considered, taking into account the use of a cryptographic flow limiter (unidirectional hash function, which has an integrated address controlled impact).Authors generalize a probabilistic model for calculation of the efficiency and expediency of the functioning of this system for a four-loop motion control line. Calculation of the standard deviation and variance for the emulating output of the considered perceptron is given. In conclusion, a block diagram of the developed device is presented.

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An Efficient Evolutionary Algorithm for High-Speed Train Rescheduling Under a Partial Station Blockage

SSRN

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SSRN 2023年

作者： Wang, Rongsheng Zhang, Qi Dai, Xuewu Yuan, Zhiming Zhang, Tao Ding, Shuxin Jin, Yaochu China Academy of Railway Sciences Corporation Limited Beijing100081 China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Train Operation Control Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing100081 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Faculty of Technology Bielefeld University BielefeldD-33615 Germany Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

This paper investigates the high-speed train rescheduling (HSTR) problem under a partial station blockage and proposes an efficient problem-specific strengthen elitist genetic algorithm (PS-SEGA) for HSTR. An HSTR model that is subject to train operation constraints is established to minimize the total train delay. The PS-SEGA framework consists of the following main steps. Firstly, a permutation-based encoding method is developed to define an efficient search space based on a train departure sequence. A decoding method is employed to output the rescheduled timetable and objective value based on the departure sequence. Moreover, a hybrid initialization method involving an efficient heuristic strategy (EHS) is put forward to accelerate the convergence speed of Evolutionary algorithms (EAs). Using problem-specific knowledge, EHS generates an efficient and feasible solution for the initial population. Finally, a restart strategy is presented to maintain genetic diversity. Compared with other advanced EAs and their improved variants also using the PS-SEGA framework, experimental results demonstrate the effectiveness of the proposed PS-SEGA for addressing HSTR scenarios under the partial station blockage. As for the scenarios that CPLEX can not obtain optimal solutions within 10 minutes, PS-SEGA can all provide quasi-optimal solutions in real-time. Furthermore, compared with the other two strategies (i.e., First-Scheduled-First-Served and EHS), PS-SEGA can find the best departure sequence that can output the timetable with a quasi-optimal solution. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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