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arXiv 2022年

作者： Khalid, Irtaza Weidner, Carrie A. Jonckheere, Edmond A. Shermer, Sophie G. Langbein, Frank C. School of Computer Science and Informatics Cardiff University CardiffCF24 4AG United Kingdom Quantum Engineering Technology Laboratories H. H. Wills Physics Laboratory Departmentof Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States Department of Physics Swansea University SwanseaSA2 8PP United Kingdom

Robustness of quantum operations or controls is important to build reliable quantum devices. The robustness-infidelity measure (RIMp) is introduced to statistically quantify in a single measure the robustness and fidelity of a controller as the p-th order Wasserstein distance between the fidelity distribution of the controller under any uncertainty and an ideal fidelity distribution. The RIMp is the p-th root of the p-th raw moment of the infidelity distribution. Using a metrization argument, we justify why RIM1 (the average infidelity) is a good practical robustness measure. Based on the RIMp, an algorithmic robustness-infidelity measure (ARIM) is developed to quantify the expected robustness and fidelity of controllers found by a control algorithm. The utility of the RIM and ARIM is demonstrated on energy landscape controllers of spin-12 networks subject to Hamiltonian uncertainty. The robustness and fidelity of individual controllers as well as the expected robustness and fidelity of controllers found by different popular quantum control algorithms are characterized. For algorithm comparisons, stochastic and non-stochastic optimization objectives are considered. Although high fidelity and robustness are often conflicting objectives, some high-fidelity, robust controllers can usually be found, irrespective of the choice of the quantum control algorithm. However, for noisy or stochastic optimization objectives, adaptive sequential decision-making approaches, such as reinforcement learning, have a cost advantage compared to standard control algorithms and, in contrast, the high infidelities obtained are more consistent with high RIM values for low noise levels. Copyright © 2022, The Authors. All rights reserved.

关键词： Controllers

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Moving Target Defense Approach for Secure Relay Selection in Vehicular Networks

SSRN

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SSRN 2023年

作者： Ghourab, Esraa M. Naser, Shimaa Muhaidat, Sami Bariah, Lina Al-Qutayri, Mahmoud Damiani, Ernesto Sofotasios, Paschalis C. Center for Cyber-PhysicalSystems DepartmentofElectricalEngineering andComputer Science Khalifa University United Arab Emirates Center for Cyber-PhysicalSystems DepartmentofElectricalEngineering andComputer Science Khalifa University UAE andwiththe DepartmentofSystems andComputer Engineering Carleton University Canada Technology Innovation Institute UAE andwiththe Center for Cyber-PhysicalSystems DepartmentofElectricalEngineering and Computer Science Khalifa University 9639Masdar City Abu Dhabi United Arab Emirates Center DepartmentofElectricalEngineering andComputer Science Khalifa University United Arab Emirates Center for Cyber-PhysicalSystems DepartmentofElectricalEngineering andComputer Science Khalifa University UAE andalso withthe Departmentof ElectricalEngineering Tampere University Finland

Ensuring the security and reliability of cooperative vehicle-to-vehicle (V2V) communications is an extremely challenging task, due to the dynamic nature of vehicular networks as well as the delay-sensitive wireless medium. In this context, the moving target defense (MTD) paradigm has been proposed to overcome the challenges of conventional solutions, based on static network services and configurations. Specifically, the MTD approach involves the dynamic altering of the network configurations to improve resilience to cyberattacks. Nevertheless, the current MTD solution for cooperative networks poses several limitations, such as they are not well-suited for highly dynamic environments;they require high synchronization modules that are resource-intensive and difficult to implement;and finally, they rely heavily on the attack-defense models, which may not always be accurate or comprehensive to use. In this paper, we propose an intelligent spatiotemporal diversification MTD scheme to defend against eavesdropping attacks in cooperative V2V networks. Specifically, we design benign random data injection patterns to meet the security and reliability requirements of the vehicular network. Our methodology involves modeling the configuration of vehicular relays and data injection patterns as a Markov decision process, followed by applying deep reinforcement learning to determine the optimal configuration. We then iteratively evaluate the intercept probability and the percentage of transmitted real data for each configuration until convergence is achieved. In order to optimize the security-real data percentage (S-RDP), we developed a two-agent framework, namely MTD-DQN-RSS and MTD-DQN-RSS-RDP. The first agent, MTD-DQN-RSS, tries to minimize the intercept probability by injecting additional fake data, which in turn reduces the overall RDP, while the second agent, MTD-DQN-RSS-RDP, attempts to inject a sufficient amount of fake data to achieve a target S-RDP. Finally, extensive sim

关键词： Iterative methods

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Deep neural networks for applying machine learning models in wireless networks

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AIP Conference Proceedings 2023年第1期2523卷

作者： G. Elangovan K. Latha S. Baggiyaraj K. V. Raghavender lDepartment School of Computing Science and Engineering VIT Bhopal University India. 2Departmentof Computer Science and Engineering Sri Sairam Engineering College Chennai Tamil Nadu India. 3Department of Information Technology Sri Ramakrishna Engineering Coimbatore Tamil Nadu India 4Department of Computer Science and Engineering G. Narayanamma Institute of Technology and Science (A) For Women Hyderabad Telangana India

Wireless networks can be designed with infrastructure-less to help enhance machine learning (ML)to meet potential requirements. This thesis explains how neural network-based data mining techniques can address different forms of wireless networking issues. We first introduce various types of Artificial Neural Networks (ANNs) with a view of wireless communication networks. Each type of artificial neural network is provided with a specific architecture and examples for design use. There are a variety of other technical alternatives to memory and circumstance. We will offer a comprehensive overview of the various forms of wireless networking discussed across multiple use cases. For each use case situation, we explain the key reason for implementing ANNs along with the related difficulties. At the same time, we include a comprehensive sample implementation besides outline everything that could be tackled through ANNs. This study highlights the advancement of ANN-based machine learning approaches responsive to the requirements of wireless communications.

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Exploratory and Predictive Analytics of User Preferences from Kaggle LEGO-Toys Datasets Using Spark ML

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IOP Conference Series: Materials science and engineering 2021年第1期1099卷

作者： Pritika Bahad Preeti Saxena Raj Kamal School of Computer Science and IT Devi Ahilya University Indore MP India Departmentof Computer Science and Engineering Prestige Institute of Engineering Management and Research Indore MP India

Apache Spark is an open-source distributed data processing framework. The paper presents a processing architecture for exploring and predicting user preferences using Apache Spark. The architecture is evaluated on LEGO-toys datasets of period 1949-2019 using the Spark Machine Learning (ML) algorithms. The large datasets analyzed consist of LEGO-toys parts, categories, themes and colour features. Spark ML algorithms are applied as (i) k-means analyses of clusters to identify commonalities in LEGO-toys themes and colours, (ii) classifications using the Support Vector Machines (SVMs), Naïve Bayes (NB) and Random Forest (RF) algorithms for theme-preference identification, and (iii) linear regression, decision tree regression, RF, and Gradient Boost for regression analyses to identify the colour-shift in user preferences. The paper elucidates the steps for analytics based on Spark. The results for exploratory and predictive analytics are presented. The evaluation metrics shows that the ensemble regression prediction is better when compared to other algorithms. The analytics give many interesting results. For example, LEGO company's products have become more colourful (children preferences exhibiting colours spectral-shift and width), diversified and multifaceted over-the-time. The architecture helps in discovering future directions for the new designs in future LEGO products. The proposed architecture can be successfully employed in the related domain to predict product and user's preferences.

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Strategic Planning for Polytechnic Information Systems with an Enterprise Architecture Planning Approach

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Journal of Physics: Conference Series 2021年第1期1845卷

作者： Tanto R Meilano D Stiawan R F Malik Politeknik Jambi Jl Lingkar Barat II Alam Barajo Jambi City Indonesia Departmentof Computer Engineering Faculty of Computer Science Universitas Sriwijaya Indonesia

Higher education institutions in implementing information systems need strategic planning, especially for Polytechnics in Indonesia. It is intended that the application of the information system is in accordance with the vision, mission and objectives of the Polytechnic. The Polytechnic information system strategic planning uses the Enterprise Architecture Planning method. The Enterprise Architecture Planning method provides an overview of data architecture, application architecture and technology architecture from the application of information systems so that the Polytechnic is not wrong in implementing information systems. The result of this research is the form or formulation of information system strategic plan which is suitable for higher education especially for Polytechnic. The information system strategic plan consists of a data architecture, there are 41 entities, while for data and application architectures there are 8 application candidates. In addition, the results of the information system strategic plan in the technology architecture section to support the Polytechnic business processes are also built.

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PRMT: Predicting Risk Factor of Obesity among Middle-Aged People Using Data Mining Techniques

PRMT: Predicting Risk Factor of Obesity among Middle-Aged Pe...

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2018 International Conference on Computational Intelligence and Data science, ICCIDS 2018

作者： Hossain, Rifat Mahmud, S.M. Hasan Hossin, Md Altab Haider Noori, Sheak Rashed Jahan, Hosney Departmentof Software Engineering Daffodil International University Dhaka1207 Bangladesh Departmentof Management Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Departmentof Computer Science and Engineering Daffodil International University Dhaka1207 Bangladesh College of Computer Science Sichuan University Chengdu610064 China

关键词： Classification (of information)

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Wireless networks in providing extraordinary quality of experience for camera consumers

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AIP Conference Proceedings 2023年第1期2523卷

作者： B. Gopi D. Sathish Kumar S. Velmurugan G. Elumalai K. Boopathy 1Department of Electronics and Communication Engineering Muthayammal Engineering College Rasipuram Tamil Nadu India. 2Departmentof Computer Science and Engineering Sri Sairam Engineering College Chennai Tamil Nadu India. 3Department of Electronics and Communication Engineering TJS Engineering College Kavaraipettai-601 206 ChennaiTamil Nadu India. 4Department of Electronics and Communication Panimalar Engineering College Chennai Tamil Nadu India. 5Department of Electrical and Electronics Engineering Aarupadai Veedu Institute of Technology Vinayaka Mission's Research Foundation Deemed to be University Paiyanoor Tamil Nadu India.

Mobile broadband users are starting to extend bandwidth demands in access networks, largely because video content has increased. In access networks, application knowledge can be used to improve the consistency of end-customer experience. In this analysis, we use client-side knowledge to achieve a superior distribution of resources to boost user Quality of Experience (QoE). As customer happiness is directly based on QoE and maximizing QuoS does not always maximize QoE, we stress the system's QoE rather than the quality of operation, as this education demonstrates. A table with client application details is stored on the SDN controller and modified every month a large application packet is sent. The table includes the latest first-person shooter (FPS) information, and all video clients have resolution information. We deliver application-aware assets distribution systems on an inactive optical Ethernet system that supports multiple accesses through wireless. Wired customers are operating video-conferencing applications via cognitive radio networks. Numerical findings indicate that the framework capable of producing up boost QoE for wired and wireless communication systems.

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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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PRMT: Predicting Risk Factor of Obesity among Middle-Aged People Using Data Mining Techniques

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Procedia computer science 2018年 132卷 1068-1076页

作者： Rifat Hossain S.M. Hasan Mahmud Md Altab Hossin Sheak Rashed Haider Noori Hosney Jahan Departmentof Software Engineering Daffodil International University Dhaka-1207 Bangladesh Departmentof Management Science and Engineering University of Electronic Science and Technology of China Chengdu-611731 China Departmentof Computer Science and Engineering Daffodil International University Dhaka-1207 Bangladesh College of Computer Science Sichuan University Chengdu-610064 China

Obesity is an anatomical condition characterized by an extreme growth of body fat. The obesity rate is increasing gradually; from prior research, obesity is the serious health disease in the globe. This study collected 259 data from specified urban and rural areas regarding different risk factor of our daily activities. The purpose of the study is to simulate the risk factor by using statistical tools (SPSS), which helpsto predict the major risk factor of obesity by testing the class level attribute according to cross-sectional study with other attributes. By analyzing the P-value (p<0.05), the outcome of this process Age (0.002), Height (0.002), Weight 0.000), Healthy lifestyle (0.000), Marital status (0.001), BMI (0.000), Economic (0.028), Sleep per day (0.011) has a significant relationship with our obesity class. This study proposed a risk mining technique (PRMT)that foretells a model to analyze the risk factor of obesity class using different data mining classifiers, using WEKA to estimate the accuracy and error measurement. The outcome of this process Naïve Bayes is the best classifier for the 10-fold cross-validation study. The proposed model collaborates to predict human factor who want to control and mitigate this major cardiovascular disease.

关键词： obesity riskmining datamining cardiovascular disease classification

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Environmentally safe layered crystal produced from hazardous chemical elements: TlPb2BrI4, a new promising detector material

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Journal of Alloys and Compounds 2022年 924卷 1页

作者： Khyzhun, O.Y. Vu, Tuan V. Parasyuk, O.V. Fedorchuk, A.O. Fochuk, P.M. Lavrentyev, A.A. Gabrelian, B.V. Levchuk, Ievgen Matt, Gebhard J. Tedde, Sandro F. Schmidt, Oliver Shrestha, Shreetu Brabec, Christoph J. Kityk, I.V. Piasecki, M. Frantsevych Institute for Problems of Materials Science National Academy of Sciences of Ukraine 3 Krzhyzhanovsky Street KyivUA-03142 Ukraine Faculty of Mechanical - Electrical and Computer Engineering School of Engineering and Technology Van Lang University Ho Chi Minh City Viet Nam Department of Inorganic and Physical Chemistry Lesya Ukrainka Volyn National University 13 Voli Avenue LutskUA-43025 Ukraine Department of Inorganic and Organic Chemistry Lviv National University of Veterinary Medicine and Biotechnologies 50 Pekarska Street Lviv79010 Ukraine Yuriy Fed'kovych Chernivtsi National University 2 Kotziubynskoho Street Chernivtsi58012 Ukraine Department of Electrical Engineering and Electronics Don State Technical University 1 Gagarin Square Rostov-on-Don344010 Russia Department of Computational Technique and Automated System Software Don State Technical University 1 Gagarin Square Rostov-on-Don344010 Russia Martensstrasse 7 Erlangen91058 Germany Siemens Healthineers Technology Center Guenther-Scharowsky-Str. 1 Erlangen91058 Germany Electrical Engineering Department Czestochowa University Technology Armii Krajowej 17 Częstochowa42217 Poland Departmentof Experimental Physics and Information-measuring Technology Lesya Ukrainka Volyn National University Voli Avenue 13 Lutsk43025 Ukraine J.Dlugosz University Częstochowa Armii Krajowej 13/15 Częstochowa42200 Poland

Exploring better Gamma, X-Ray and IR-Mid-R detectors, adequately sensitive to ambient temperatures and environmental conditions, is highly desirable. Therefore, following this path, we present detecting opportunities, based on data of experimental and theoretical investigation of the electronic and optical properties, photocurrent behavior at different bias voltages as well as the reflection for the He-Cd cw laser after irradiation by three different IR laser wavelengths, for recently grown TlPb2BrI4 single crystal with strong anisotropic, two-dimensional (2D) layered structure. The X-ray photoelectron spectroscopy brings data on binding energy values of core levels of TlPb2BrI4 for both as-grown and Ar+-ion-treated crystal surfaces as well as for elucidation of the energy distribution of the valence electronic states. In opposite to well-known IR-detector materials, TlPb2BrI4 crystal surface shows high chemical stability concerning Ar+-ion bombardment. Further, we carry out ab initio band-structure calculations to gain curves of total and partial densities of states and to elucidate the principal optical constants of TlPb2BrI4. The present studies indicate that, in spite of the fact that the TlPb2BrI4 crystal contains two very hazardous/toxic chemical elements, thallium and lead;however, it is chemically stable and reveals very low hygroscopic behavior when being exposed to environmental conditions. © 2022 Elsevier B.V.

关键词： X ray photoelectron spectroscopy

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