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An Optimal Framework for SDN Based on Deep Neural Network

computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Novel Bendable Mnxca(0.90−X)Ni0.10fe2o4 Substrate Based Symmetrical Metamaterial Absorber for Rf Energy Harvesting Application to Achieve Sustainable Development Goals

SSRN

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SSRN 2024年

作者： Hasan, Mohammad Shakibul Islam, Mohammad Tariqul Ouda, Mohammad Alenezi, Abdulmajeed M. Soliman, Mohamed S. Samsuzzaman, Md. Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Electrical Engineering Technology College of Engineering & Technology University of Doha for Science and Technology Doha24449 Qatar Department of Electrical Engineering Faculty of Engineering Islamic University of Madinah Madinah41411 Saudi Arabia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh

This article presents a bendable substrate MnxCa(0.90−x)Ni0.10Fe2O4 based metamaterial absorber for RF energy harvesting from Wifi frequency of 5 GHz to the achievement of the Sustainable Development Goals. The bendable metamaterial absorber (BMMA) energy harvester unit cell constructed with the physical dimension of 21 × 21 *** proposed unit cell consist of cross sign shaped resonator surrounded by circular ring resonator is located middle portion and boundary split outer ring resonator. Based on the simulation findings, the proposed BMMA energy harvester provides maximum energy harvesting efficiency of 99.42% at 5 GHz. Due to the symmetrical design, the energy harvester unit cell shows excellent angle insensitive up to 90 degrees for incident angle and polarization angle. The proposed BMMA exhibits single negative properties, and it shows excellent harvesting efficiency for various bending conditions. The lightweight, flexibility of the structure indicate that MnxCa(0.90−x)Ni0.10Fe2O4 based bendable metamaterial absorber energy harvester have significant potential for RF energy harvesting application from wifi frequency of 5 GHz and it achieve Sustainable Development Goals (SDGs), specially alignment with SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities),and SDG 13 (Climate Action). © 2024, The Authors. All rights reserved.

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FDD based Cell-free massive MIMO with angular reciprocity over rician fading channels

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Telecommunication systems 2025年第3期88卷 1-18页

作者： Hassan, Beenish Baig, Sobia Aslam, Saad Tahzeeb, Shahab Hasan, Syed Faraz Department of Electrical Engineering The Islamia University of Bahawalpur Bahawalpur Pakistan Electrical Engineering Department College of Engineering Qassim University Unaizah Saudi Arabia School of Computing and Artificial Intelligence Faculty of Engineering and Technology Sunway University Selangor Malaysia Department of Computer and Information Systems Engineering NED University of Engineering and Technology Karachi Pakistan Directorate of Research Services University of New England Armidale Australia

We present a combined angle reciprocity and Rician K factor based feedback for up/downlink scenarios using MMSE estimator for frequency division duplex (FDD) based massive Multiple Input Multiple Output (MIMO) system. It considers phase variation for spatially correlated Rician fading channel and also takes into account the phase shift in the line-of-sight component of Rician channel that is incurred due to user mobility and/or phase noise. The cell-free massive MIMO system has largely been implemented in the context of time division duplex (TDD) systems. However, FDD is still prevalent in communication standards and therefore, it is essential to assess its performance for FDD based channel estimation schemes in a typical cell-free massive MIMO environment. To begin with, we present an analysis of estimation schemes including the minimum mean square error (MMSE), linear MMSE (LMMSE), and least-square (LS) in terms of their spectral efficiency, using prior channel knowledge at the access points. We also present an angle-based beamforming technique that combines the quantized channel feedback based on Rician K factor with angle reciprocity-based channel estimates. The multipath channel estimation for MMSE and LMMSE schemes is also presented and simulation results are provided that show the superior performance of proposed angle and feedback MMSE over the LMMSE and theoretical MMSE schemes. Numerical simulations of the overall system confirm that the combined angular reciprocity and feedback-based MMSE estimates perform better with a value of $$12.6\%$$ for spectral efficiency and $$27\%$$ for energy efficiency, thus, producing an overall improved system performance compared to the conventional FDD based estimation schemes.

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Carbon Nanotubes Enhancement of Fiber Bragg Grating Surface Plasmon Resonance Sensor 25

Carbon Nanotubes Enhancement of Fiber Bragg Grating Surface ...

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25th International Electronics Symposium, IES 2023

作者： Thirunavakkarasu, Punithavathi Khan, Abdul Ali Shabaneh, Arafat Saidin, Norazlina Bte Sulaiman, Muhammad Syahnizam Noor, Ahmad Shukri Muhammad Universiti Kuala Lumpur Communication Technology Section British Malaysia Institute Gombak Malaysia Palastine Technical University-Kadoorie Department of Telecommunication Technology Engineering Tulkrarm Palestine International Islamic University Malaysia Department of Electrical and Computer Engineering Kuala Lumpur Malaysia Universiti Putra Malaysia Faculty of Engineering Department of Cmputer and Communication Systems Engineering Selangor Malaysia

ISBN: (纸本)9798350314731

In this research, a telecommunication standard fiber Bragg grating is sputtered with a 45 nm gold film to obtain surface plasmon resonance. Carbon nanotubes are deposited over the gold layer for sensitivity enhancement due to its unique chemical and optical properties. The developed sensor is interrogated with a broad-spectrum light source and spectrophotometer setup in the visible region and the sensing performance is analyzed. The sensor showed high sensitivity of 526 nm/RIU which was more than 4 time higher than a sensor without the carbon nanotubes enhancement. This shows great promise in the application of CNTs and possibly other sensitive nanomaterials as sensing enhancements of future sensing using optical fibers. © 2023 IEEE.

关键词： Surface plasmon resonance

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology 33

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Bogacki, P. Dlugosz, M. Talaska, T. Dlugosz, R. Aptiv Services Poland Kraków30-399 Poland Agh University of Science and Technology Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications Kraków30-059 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350347760

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock. © 2023 IEEE.

关键词： Pixels

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Fine-grained Intent Classification in the Legal Domain

Fine-grained Intent Classification in the Legal Domain

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2022 Workshop on Scientific Document Understanding, SDU 2022

作者： Mullick, Ankan Nandy, Abhilash Kapadnis, Manav Nitin Patnaik, Sohan Raghav, R. Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Electrical Engineering Indian Institute of Technology Kharagpur India Department of Mechanical Engineering Indian Institute of Technology Kharagpur India Department of Industrial and Systems Engineering Indian Institute of Technology Kharagpur India

A law practitioner has to go through a lot of long legal case proceedings. To understand the motivation behind the actions of different parties/individuals in a legal case, it is essential that the parts of the document that express an intent corresponding to the case be clearly understood. In this paper, we introduce a dataset of 93 legal documents, belonging to the case categories of either Murder, Land Dispute, Robbery, or Corruption, where phrases expressing intent same as the category of the document are annotated. Also, we annotate fine-grained intents for each such phrase to enable a deeper understanding of the case for a reader. Finally, we analyze the performance of several transformer-based models in automating the process of extracting intent phrases (both at a coarse and a fine-grained level), and classifying a document into one of the possible 4 categories, and observe that, our dataset is challenging, especially in the case of fine-grained intent classification. © 2021 Copyright for this paper by its authors.

关键词： Classification (of information)

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Transforming engineering Education Using Generative AI and Digital Twin Technologies

arXiv

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arXiv 2024年

作者： Lin, Yu-Zheng Alhamadah, Ahmed Hussain J. Redondo, Matthew William Patel, Karan Himanshu Ghimire, Sujan Latibari, Banafsheh Saber Salehi, Soheil Satam, Pratik Department of Electrical and Computer Engineering University of Arizona TucsonAZ85721 United States Department of Systems and Industrial Engineering University of Arizona TucsonAZ85721 United States

Digital twin technology, traditionally used in industry, is increasingly recognized for its potential to enhance educational experiences. This study investigates the application of industrial digital twins (DTs) in education, focusing on how DT models of varying fidelity can support different stages of Bloom’s taxonomy in the cognitive domain. We align Bloom’s six cognitive stages with educational levels: undergraduate studies for"Remember" and"Understand," master’s level for"Apply" and"Analyze," and doctoral level for"Evaluate" and"Create." Low-fidelity DTs aid essential knowledge acquisition and skill training, providing a low-risk environment for grasping fundamental concepts. Medium-fidelity DTs offer more detailed and dynamic simulations, enhancing application skills and problem-solving. High-fidelity DTs support advanced learners by replicating physical phenomena, allowing for innovative design and complex experiments. Within this framework, large language models (LLMs) serve as mentors, assessing progress, filling knowledge gaps, and assisting with DT interactions, parameter setting, and debugging. We evaluate the educational impact using the Kirkpatrick Model, examining how each DT model’s fidelity influences learning outcomes. This framework helps educators make informed decisions on integrating DTs and LLMs to meet specific learning objectives. © 2024, CC BY-NC-ND.

关键词： Knowledge acquisition

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Composite Distributed Learning and Synchronization of Nonlinear Multi-Agent systems with Complete Uncertain Dynamics

Composite Distributed Learning and Synchronization of Nonlin...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Emadodin Jandaghi Dalton L. Stein Adam Hoburg Paolo Stegagno Mingxi Zhou Chengzhi Yuan Department of Mechanical Industrial and Systems Engineering Kingston RI USA Department of Electrical Computer and Biomedical Engineering Kingston RI USA Graduate School of Oceanography Kingston RI USA

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

This paper addresses the problem of composite synchronization and learning control in a network of multiagent robotic manipulator systems with heterogeneous nonlinear uncertainties under a leader-follower framework. A novel two-layer distributed adaptive learning control strategy is introduced, comprising a first-layer distributed cooperative estimator and a second-layer decentralized deterministic learning controller. The first layer is to facilitate each robotic agent’s estimation of the leader’s information. The second layer is responsible for both controlling individual robot agents to track desired reference trajectories and accurately identifying/learning their nonlinear uncertain dynamics. The proposed distributed learning control scheme represents an advancement in the existing literature due to its ability to manage robotic agents with completely uncertain dynamics including uncertain mass matrices. This allows the robotic control to be environment-independent which can be used in various settings, from underwater to space where identifying system dynamics parameters is challenging. The stability and parameter convergence of the closed-loop system are rigorously analyzed using the Lyapunov method. Numerical simulations validate the effectiveness of the proposed scheme.

关键词： Adaptive learning computer aided instruction Uncertainty System dynamics Distance learning Aerospace electronics Nonlinear dynamical systems

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Performance Comparison of the Invasive Weed Optimization K-Means Algorithm with Particle Swarm Optimization K-Means for Banking Data

Performance Comparison of the Invasive Weed Optimization K-M...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Ni Luh Gede Pivin Suwirmayanti I Ketut Gede Darma Putra Made Sudarma I Made Sukarsa Emy Setyaningsih Department of Computer Systems Faculty of Informatics and Computer Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia Department of Information Technology Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Electrical Engineering Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Computer Systems Engineering Faculty of Applied Science Universitas AKPRIND Indonesia Yogyakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

Banking produces extensive and diverse data, so a clustering process is needed to understand customer behavior patterns and transactions more effectively. This clustering has been widely utilized with the K-Means algorithm due to its simplicity and efficiency. However, this algorithm is limited in determining the optimal cluster center, affecting the accuracy of the clustering results. This study proposes applying two metaheuristic algorithms, Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO), as additional solutions combined with K-Means. These two algorithms were chosen because of their ability to find global solutions and convergence speed to handle large and complex banking data. The results show the superiority of IWOKM compared to PSOKM in terms of SSE and DBI. From the SSE value, IWOKM produces a lower value (3029.77), which indicates that this method is better at minimizing clustering errors and producing more accurate clustering than PSOKM (80007.09). From the DBI value, IWOKM also produces a better value (1.6684) than PSOKM (1.6782), which shows that the clusters produced by IWOKM are more compact and more separated. However, in terms of computation time, PSOKM is more efficient, with a faster average computation time. Although IWOKM produces better clustering quality, PSOKM offers advantages in terms of processing speed. This finding confirms that the selection of the IWO algorithm is more appropriate for use on datasets with characteristics such as the German Credit Dataset.

关键词： Accuracy Consumer behavior Metaheuristics Clustering algorithms Banking Computational efficiency Particle swarm optimization Intelligent systems Cybernetics Convergence

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Architecture Open Workspace Concept for Prescriptive Model of Digital Twin 9

Architecture Open Workspace Concept for Prescriptive Model o...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Supangkat, Suhono Harso Supangkat, Suhono Harso Leksono, Edi Ramelan, Agus Latifah, Ayu School of Electrical and Informatics Engineering Bandung Institute of Technology Bandung Indonesia Engineering Physics Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia Electrical Engineering Departement Universitas Sebelas Maret Solo Indonesia Department of Computer Science Institut Teknologi Garut Garut Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

The workspace is a portion of a structure that can currently apply a smart building system adaption for more ideal design outcomes. Millions of hours are reportedly wasted each year as a result of the harmful effects that poor environmental quality has on workers' productivity and health, according to the findings of several studies. Therefore, a centralized approach is required to be able to give quick and accurate information. This may be accomplished via digital twin technology, which will result in a workspace design that is more ideal in the future. The major goal of this research is to create a digital twin prescriptive model in a physical workspace environment that can create a strategic space design plan and be flexible enough to react to changes in the physical environment, which will improve user comfort and productivity. A life cycle model was employed as the study methodology, which begins with the identification of the model's requirements and ends with its maintenance. This model is employed to offer suggestions for preventative and remedial activities on actual things. © 2022 IEEE.

关键词： Productivity

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