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Discrete RKZD (Reciprocal-Kind Zhang Dynamics) Algorithm Solving Time-Independent Linear Matrix-Vector Equation (TILMVE) Simplified from Time-Dependent Situation 42

Discrete RKZD (Reciprocal-Kind Zhang Dynamics) Algorithm Sol...

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42nd Chinese Control Conference, CCC 2023

作者： Zhang, Yunong Lu, Ji Mao, Mingzhi Li, Shuai School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China School of Software Engineering Sun Yat-sen University Zhuhai519082 China University of Oulu Faculty of Information Technology and Electrical Engineering Oulu90570 Finland

ISBN: (纸本)9789887581543

We present a continuous reciprocal-kind Zhang dynamics (RKZD) model for solving the time-dependent linear matrixvector equation. On the basis of the model, we deduce its simplified form for solving the time-independent linear matrix-vector equation (TILMVE). Subsequently, for more efficient computation and easier implementation in digital hardware, we utilize Euler forward difference formula (EFDF) to discretize the continuous RKZD model, resulting in a discrete RKZD algorithm. Finally, numerical experimental results attest to the feasibility and high effectiveness of the discrete RKZD algorithm for solving TILMVE. Comparisons with the discrete gradient neural network (or termed discrete gradient dynamics), Jacobi iteration, as well as Gauss-Seidel iteration highlight the superior convergence properties of the discrete RKZD algorithm. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Computational efficiency

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Intersection of Artificial Intelligence, Data Science, and Cutting-Edge Technologies: From Concepts to Applications in Smart Environment 1

Intersection of Artificial Intelligence, Data Science, and C...

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Yousef Farhaoui Tutut Herawan Agbotiname Lucky Imoize Ahmad El Allaoui

ISBN: (数字)9783031883040

ISBN: (纸本)9783031883033

This book explores the integration of AI, data science, and emerging technologies to create innovative, practical solutions for smart environments. This book offers a comprehensive framework that combines theoretical concepts with real-world applications, focusing on how these technologies intersect to transform various domains such as healthcare, urban planning, and sustainable development. The book's novel approach emphasizes interdisciplinary methods and problem-solving in dynamic, data-driven environments, with case studies illustrating practical impacts and advancements in smart city infrastructure, IoT, and predictive analytics. It is designed for researchers, practitioners, and advanced students interested in AI and data science applications within smart systems, as well as professionals seeking actionable insights to apply these technologies in complex environments.

关键词： Computational Intelligence Data engineering Artificial Intelligence

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Integrity verification architecture (IVA) based security framework for windows operating system

Integrity verification architecture (IVA) based security fra...

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11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom-2012

作者： Isa, Mohd Anuar Mat Hashim, Habibah Manan, Jamalul-Lail Ab Mahmod, Ramlan Othman, Hanunah Faculty of Electrical Engineering 40450 UiTM Shah Alam Selangor Malaysia Advanced Analysis and Modeling Cluster MIMOS Berhad Technology Park Malaysia 57000 Bukit Jalil Kuala Lumpur Malaysia Faculty of Computer Science and Information Technology 43400 UPM Serdang Selangor Malaysia

ISBN: (纸本)9780769547459

Windows Operating System (WinOS) emerged in the market for the past few decades to provide the solution for various platforms that range from desktop computer, server to sophisticated computing systems such as grid computer. The evolution of the design of operating systems continues to fulfill the needs of diverse applications that run on various platforms or hardware. Recently, a new element was introduced to provide trust enhancement on platforms using Trusted Computing. In this paper, we discuss an implementation of Trusted Computing in providing a mechanism to check whether hardware, software or application running on a platform "behaves as expected" without need for further validation. We further propose a new Integrity Verification Architecture (IVA) based Security Framework to protect user data privacy. Our proposed security framework focuses on providing platform integrity verification and self-healing in Windows Operating Systems via IVA. © 2012 IEEE.

关键词： Trusted computing

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Investigating the Benefits of Adopting Secure Shell (SSH) in Wireless Network Security

Investigating the Benefits of Adopting Secure Shell (SSH) in...

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2023 IEEE International Conference on Paradigm Shift in information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Gavathri, C. Patil, Vivek D. Singh, Dhiraj Kumar Kumar, Ritesh Narmadha, T. Kalra, Hitesh Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Electrical Engineering Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka 562112 India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350329773

cozy Shell is an encrypted network protocol that has become increasingly popular in network security. Using SSH, organizations can defend their wireless networks from community penetration and malicious interest. SSH affords encryption for statistics transfers, thus stopping records robbery and interception of better-level protocols, which includes statistics confidentiality, integrity, and authentication. Similarly, complex SSH configurations can offer defense in opposition to assaults such as phishing, malware dissemination, and man-in-the-middle attacks. This paper will examine the feasibility and effectiveness of SSH for use in Wi-FiWi-Fi network safety. It will discuss the benefits of SSH for defensive a Wi-FiWi-Fi network and the demanding situations related to its implementation. Additionally, the paper will become aware of the metrics used to degree the overall performance of an SSH-blanketed community and suggest a secure framework for SSH implementation. In the end, this paper will explore the potential for further research within the region of wireless network protection using SSH. © 2023 IEEE.

关键词： Authentication

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Cost-Effective and Dynamic Migration for Microservices in Hybrid Cloud-Edge Systems

Cost-Effective and Dynamic Migration for Microservices in Hy...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Zhai, Jiahui Bi, Jing Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Southern Methodist University Dept. of Computer Science Lyle School of Engineering DallasTX United States

ISBN: (纸本)9798350337020

Mobile edge computing (MEC), as a promising paradigm, delivers computation and storage capacities at the edge of the network. It supports delay-sensitive services for mobile users (MUs). However, dynamic and stochastic characteristics of MEC networks necessitate constant migration of installed services across edge servers to keep up with the mobility of MUs. As a result, the cost of maintaining the network increases significantly. Existing studies of MEC rarely consider the cost of service migration due to MU mobility. To minimize the long-term cost for microservices in a hybrid cloudedge system comprising of MUs, small base stations (SBSs), and a cloud data center (CDC), the total cost minimization is formulated as a constrained mixed-integer nonlinear program. To solve it, this work designs a novel meta-heuristic optimization algorithm called Multi-swarm Grey-wolf-optimizer based on Genetic-learning (MGG), which effectively combines strong local search capabilities of grey wolf optimizer with superior global search capabilities of genetic algorithm. MGG simultaneously optimizes service request routing among MUs, SBSs, and CDC, CPU speeds of SBSs, service deployment of SBSs, service migration cost of SBSs, as well as MUs' transmission power and channel bandwidth allocation. Simulation results with Google cluster trace demonstrate that MGG outperforms several state-of-the-art peers with respect to the overall cost of the hybrid system. © 2023 IEEE.

关键词： genetic algorithm grey wolf optimizer Mobile edge computing resource allocation service migration

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Assessment of MODIS land surface temperature data against ground meteorological data for the west coast of Peninsular Malaysia 40

Assessment of MODIS land surface temperature data against gr...

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40th Asian Conference on Remote Sensing: Progress of Remote Sensing technology for Smart Future, ACRS 2019

作者： Bahari, Nurul Iman Saiful Muharam, Farrah Melissa Zulkafli, Zed Mazlan, Norida Husin, Nor Azura Serdang43400 Malaysia Universiti Putra Malaysia UPM Faculty of Agriculture Serdang43400 Malaysia Universiti Putra Malaysia UPM Faculty of Engineering Serdang43400 Malaysia Universiti Putra Malaysia UPM Faculty of Computer Science and Information Technology Serdang43400 Malaysia

Land surface temperature is one of the remote sensing products extracted from MODIS satellites. MODIS MOD11A1 provides land surface temperature data (Ts) on a daily basis at 1km spatial resolution. Although the Ts are freely available, the data suffers from missing values and unknown accuracy especially for tropical region such as Peninsular Malaysia. The weather in the tropics is mainly characterised with high rainfall intensity, high cloud cover and moderate temperature. The Ts for tropical regions is highly contaminated with cloud cover resulting in most part of the data being discarded even before they can be made ready for end-users. Therefore, this study was conducted with the objective to assess the accuracy of Ts in comparison to ground air temperature data (Ta) acquired from network of meteorological stations across west coast of Peninsular Malaysia. Daily Ta from 26 stations distributed were compared statistically against MODIS MOD11A1 Ts from 2012 to 2016. The MODIS-extracted Ts were compared with the pixel where the Ta from the ground meteorological stations were obtained. The performance of Ts in comparison to Ta analysis were quantified using measures such as root mean square error (RMSE) and correlation coefficient (r). The results illustrated were as follows: RMSE= 1.7 °C to 5.6 °C, and r = 0.1 to 0.6. The slightly high RMSE and low r values indicated that bias correction is necessary prior to the usage of MODIS MOD11A1 Ts. © 2020 40th Asian Conference on Remote Sensing, ACRS 2019: "Progress of Remote Sensing technology for Smart Future". All rights reserved.

关键词： Tropics

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Anomaly-Based Intrusion DetectionModel Using Deep Learning for IoT Networks

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computer Modeling in engineering & Sciences 2024年第10期141卷 823-845页

作者： Muaadh A.Alsoufi Maheyzah Md Siraj Fuad A.Ghaleb Muna Al-Razgan Mahfoudh Saeed Al-Asaly Taha Alfakih Faisal Saeed Faculty of Computing Universiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia DAAI Research Group College of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11345Saudi Arabia

The rapid growth of Internet of Things(IoT)devices has brought numerous benefits to the interconnected ***,the ubiquitous nature of IoT networks exposes them to various security threats,including anomaly intrusion *** addition,IoT devices generate a high volume of unstructured *** intrusion detection systems often struggle to cope with the unique characteristics of IoT networks,such as resource constraints and heterogeneous data *** the unpredictable nature of network technologies and diverse intrusion methods,conventional machine-learning approaches seem to lack *** numerous research domains,deep learning techniques have demonstrated their capability to precisely detect *** study designs and enhances a novel anomaly-based intrusion detection system(AIDS)for IoT ***,a Sparse Autoencoder(SAE)is applied to reduce the high dimension and get a significant data representation by calculating the reconstructed ***,the Convolutional Neural Network(CNN)technique is employed to create a binary classification *** proposed SAE-CNN approach is validated using the Bot-IoT *** proposed models exceed the performance of the existing deep learning approach in the literature with an accuracy of 99.9%,precision of 99.9%,recall of 100%,F1 of 99.9%,False Positive Rate(FPR)of 0.0003,and True Positive Rate(TPR)of *** addition,alternative metrics,such as training and testing durations,indicated that SAE-CNN performs better.

关键词： IoT anomaly intrusion detection deep learning sparse autoencoder convolutional neural network

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Simulated Evolution and Learning 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Xiaodong Li Michael Kirley Mengjie Zhang David Green Vic Ciesielski Hussein Abbass Zbigniew Michalewicz Tim Hendtlass Kalyanmoy Deb Kay Chen Tan Jürgen Branke Yuhui Shi

ISBN: (数字)9783540896944

ISBN: (纸本)9783540896937

This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.

关键词： Programming Techniques Computation by Abstract Devices Artificial Intelligence Simulation and Modeling User Interfaces and Human computer Interaction Discrete Mathematics in computer Science

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An Intelligent Prediction Model for Target Protein Identification in Hepatic Carcinoma Using Novel Graph Theory and ANN Model

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computer Modeling in engineering & Sciences 2022年第10期133卷 31-46页

作者： G.Naveen Sundar Stalin Selvaraj D.Narmadha K.Martin Sagayam A.Amir Anton Jone Ayman A.Aly Dac-Nhuong Le Computer Science and Engineering Karunya Institute of Technology and SciencesCoimbatore641114India Centre for Nanotechnology&Advanced Biomaterials(CeNTAB) School of Chemical&BiotechnologySASTRA Deemed to be UniversityThanjavur613401India Department of ECE Karunya Institute of Technology and SciencesCoimbatore641114India Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Institute of Research and Development Duy Tan UniversityDanang550000Vietnam Faculty of Information Technology Duy Tan UniversityDanang550000Vietnam

Hepatocellular carcinoma(HCC)is one major cause of cancer-related mortality around the ***,at advanced stages of HCC,systematic treatment options are currently *** a result,new pharmacological targetsmust be discovered regularly,and then tailored medicines against HCC must be *** this research,we used biomarkers of HCC to collect the protein interaction network related to ***,DC(Degree Centrality)was employed to assess the importance of each *** an improved Graph Coloring algorithm was used to rank the target proteins according to the interaction with the primary target protein after assessing the top ranked proteins related to ***,physio-chemical proteins are used to evaluate the outcome of the top ranked *** proposed graph theory and machine learning techniques have been compared with six existing *** the proposed approach,16 proteins have been identified as potential therapeutic drug targets for Hepatic *** is observable that the proposed method gives remarkable performance than the existing centrality measures in terms of Accuracy,Precision,Recall,Sensitivity,Specificity and F-measure.

关键词： Drug target detection hepatic carcinoma degree centrality graph coloring artificial neural network model

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A Study of Cantilever Beam Vibration Wireless Transmission System

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Procedia engineering 2011年 14卷 1300-1306页

作者： Guangxiang Yang WenHui Duan Hua Liang School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China Faculty of Mechanical Engineering Monash University Australia

ZigBee is a wireless communication technology which based on IEEE 802.15.4 protocol, communicating within short distance and with low power. ZigBee is applied in cantilever beam vibration measurement system in this paper, and the old wired transmission system are substituted by IEEE 802.15.4, software and sensor circuit are designed, reliable data transmission method and half byte compression algorithm are analyzed, and also provide basis and data analyzing solution for dynamics model of cantilever beam which using piezoelectric transducer. Experimental results show that with wireless ZigBee transmission solution and compression algorithm, the acquisition data of 150 bytes per second can be achieved, which will improve the quality of vibration analysis.

关键词： ZigBee Piezoelectric Transducer Compression Algorithm Cantilever Beam

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