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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Piotr Oziablo Dorota Mozyrska Mariusz Matusiak Faculty of Computer Science Bialystok University of Technology Wiejska 45A Poland Faculty of Electrical Electronics Computer Science and Control Engineering Lodz University of Technology Lodz Poland

ISBN: (纸本)9781665476881

In the paper, there is presented a MATLAB Toolbox that allows simulation and parameter tuning of closed-loop systems with fractional-variable-order digital PID (FVOPID) controllers. The proposed toolbox provides MATLAB Simulink blocks of FVOPID based on two different implementations of Grünwald-Letnikov fractional-variable-order operator. An additional part of the toolbox is an application with a GUI interface which primary purpose is to simulate and find the optimal tuning parameters of FVOPID for a given closed-loop system. The tuning process, in this case, can be performed employing different optimization methods set to minimize an objective function according to the selected integral criterion. The paper describes the internal architecture (design) of the toolbox and its functionalities.

关键词： Software packages Optimization methods Programming Linear programming Calculus Closed loop systems Tuning

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Web Data Management Platform Integrating Encryption Algorithms 13

Web Data Management Platform Integrating Encryption Algorith...

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13th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2021

作者： Dinca, Alexandru Angelescu, Nicoleta Popescu, Dan University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Valahia University of Targoviste Faculty of Electrical Engineering Electronics and Information Technology Targoviste Romania

ISBN: (纸本)9781665425346

The development area of web technologies has gained great popularity due to the power with which these new technologies can manage resources and due to developers or experts of various types who can build applications and scale them according to the needs of different application areas or companies which use these types of applications. In this paper we present a modern web platform for data management that includes current web technologies and security standards that ensure the integrity of data in the information flow of the application. © 2021 IEEE.

关键词： Information management

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A Dynamic SDN-based Privacy-Preserving Approach for Smart City Using Trust Technique 9

A Dynamic SDN-based Privacy-Preserving Approach for Smart Ci...

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9th Iranian Joint Congress on Fuzzy and Intelligent Systems, CFIS 2022

作者： Alzubi, Jafar A. Movassagh, AliAkbar Gheisari, Mehdi Najafabadi, Hamid Esmaeili Abbasi, Aaqif Afzaal Liu, Yang Pingmei, Zhou Izadpanahkakhk, Mahdieh Najafabadi, AmirHossein Pourishaban Al-Balqa Applied University Faculty of Engineering Salt Jordan Tehran University of Medical Sciences School of Medicine Department of Medical Physics and Biomedical Engineering Tehran Iran Islamic Azad University Young Researchers and Elite Club Parand Branch Parand Iran University of Calgary Canada Foundation University Department of Software Engineering Islamabad44000 Pakistan Harbin Institute of Technology Department of Computer Science and Technology Shenzhen China Shenzhen BKD Company Shenzhen China La Sapienza University DIET Department Rome Italy University of Yazd Department of Electrical and Computer Engineering Yazd Iran

ISBN: (纸本)9781665478724

A smart city is an Internet-based application of things that automates city management with no need for human interference. Exchanging data via devices obviate some challenges in intelligent cities. In a smart city, Internet-of-Things (IoT) devices may detect sensitive data, posing a risk of privacy violation and system harm. We discover that existing solutions are either too expensive or ineffective at limiting unintended disclosure of sensitive data to build a dependable, smart city. The fact that they create static surroundings is the fundamental reason behind this. Software-Defined Networking (SDN) technology has recently evolved to configure the network for performance and monitoring improvement. This study offers a work-in-progress that uses the SDN to protect the privacy of IoT devices by creating a dynamic SDN-based privacy-preserving ecology. The mechanism of the SDN controller performs under the nodes' mutual trust;it chooses various routes from the IoT device to the Cloud space destination dependent on the level of confidence. The packet is re-routed if the SDN controller identifies a device that does not trust its neighbor. Then it instructs the owner to deliver data over a different path. To demonstrate its improved performance, we are currently evaluating it from the perspective of overhead criteria in the future. © 2022 IEEE.

关键词： Smart city

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Consistent and Asymptotically Efficient Localization from Range-Difference Measurements

arXiv

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arXiv 2023年

作者： Zeng, Guangyang Mu, Biqiang Shi, Ling Chen, Jiming Wu, Junfeng The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen China The Department of Automation University of Science and Technology of China Hefei China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

We consider signal source localization from range-difference measurements. First, we give some readily-checked conditions on measurement noises and sensor deployment to guarantee the asymptotic identifiability of the model and show the consistency and asymptotic normality of the maximum likelihood (ML) estimator. Then, we devise an estimator that owns the same asymptotic property as the ML one. Specifically, we prove that the negative log-likelihood function converges to a function, which has a unique minimum and positive definite Hessian at the true source's position. Hence, it is promising to execute local iterations, e.g., the Gauss-Newton (GN) algorithm, following a consistent estimate. The main issue involved is obtaining a preliminary consistent estimate. To this aim, we construct a linear least-squares problem via algebraic operation and constraint relaxation and obtain a closed-form solution. We then focus on deriving and eliminating the bias of the linear least-squares estimator, which yields an asymptotically unbiased (thus consistent) estimate. Noting that the bias is a function of the noise variance, we further devise a consistent noise variance estimator that involves 3-order polynomial rooting. Based on the preliminary consistent location estimate, a one-step GN iteration suffices to achieve the same asymptotic property as the ML estimator. Simulation results demonstrate the superiority of our proposed algorithm in the large sample case. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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Capability-based IoT access control using blockchain

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Digital Communications and Networks 2021年第4期7卷 463-469页

作者： Yue Liu Qinghua Lu Shiping Chen Qiang Qu Hugo’Connor Kim-Kwang Raymond Choo He Zhang School of Computer Science and Engineering University of New South WalesAustralia Data61 CSIROAustralia Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesChina Department of Information Systems and Cyber Security University of Texas at San AntonioUSA Software Institute Nanjing UniversityChina

Internet of Things(IoT)devices facilitate intelligent service delivery in a broad range of settings,such as smart offices,homes and ***,the existing IoT access control solutions are mainly based on conventional identity management schemes and use centralized *** are knowm security and privacy limitations with such schemes and architectures,such as the single-point failure or surveillance(e.g.,device tracking).Hence,in this paper,we present an architecture for capability-based IoT access control utilizing the blockchain and decentralized identifiers to manage the identity and access control for IoT ***,we propose a protocol to provide a systematic view of system interactions,to improve *** also implement a proof-of-concept prototype of the proposed approach and evaluate the prototype using a real-world use *** evaluation results show that the proposed solution is feasible,secure,and scalable.

关键词： Blockchain Internet of things Capability-based access control Identity management Architecture design

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scIAC: clustering scATAC-seq data based on Student’s t-distribution similarity imputation and denoising autoencoder

scIAC: clustering scATAC-seq data based on Student’s t-dist...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Wei Lan Jin Ye Xun Sun Xiaoshu Zhu Qingfeng Chen Yi Pan School of computer electronic and information and Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Nanning China School of computer electronic and information Guangxi University Nanning China School of Computer Science and Engineering Yulin Normal University Yulin China School of Computer Science and Control Engineering Shenzhen Institute of Advanced Technology Shenzhen China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Assay of single cell transposase-accessible chromatin with high-throughput sequencing (scATAC-seq) have enabled massively profiling of the chromatin accessibility landscape at the single-cell level. The essential step in analyzing scATAC-seq data is to cluster the cells into different clusters and utilize the clustering information in the subsequent downstream analysis. However, there are some challenges in the clustering analysis of scATAC-seq data. For example, scATAC-seq data are often high-dimensional and extremely sparse, as well as featuring high loss rate or noise. In this study, we proposed the scIAC to address these challenges of scATACseq data. In particular, scIAC combines the Student’s t-distribution similarity imputation and the denoising autoencoder based on the Zero-inflated Negative Binomial (ZINB) distribution. The Student’s t-distribution similarity imputation is used to solve the problem of high sparsity and high loss rate. The denoising autoencoder is employ to extract features which are useful for clustering and to reduce data noises. In addition, the self-training soft K-means and pairwise constraints are utilized in the clustering phase to enhance clustering performance. The experimental validation on several datasets shows that the proposed method performed better than other state-of-the-art methods. In conclusion, scIAC is an effective method to accurately cluster and identify cell types in scATAC-seq data.

关键词： Sequential analysis Runtime Clustering methods Noise reduction Neural networks Feature extraction Data models

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A Multifunctional Reflectarray Antenna for Sub-THz Applications

A Multifunctional Reflectarray Antenna for Sub-THz Applicati...

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

作者： Xingxing Yang Botao Feng Xiao Ding Wenzhe Gu Sanshan Sun Kwok L. Chung College of Electronics and Information Engineering Shenzhen University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China School of Computer Science and Engineering Huizhou University Huizhou China College of Physics and Electronic Engineering Sichuan Normal University Sichuan China School of Computer Science and Engineering Huizhou University Huizhou P. R. China

In this paper, a reflection element sensitive to polarization direction is proposed, which can independently control the phase of incident wave in dual polarized directions. Then, a reflectarray including the proposed 7×7 elements is designed to offer dual-polarized deflection. The results show that the reflectarray achieves a -15° beam deflection with an X-axis polarized incident wave. In contrast, it realizes a +15° beam deflection with a Y-–axis polarized wave. In addition, the cross polarization (X-pol) level is less than -20 dB, and the gain of the array is higher than that of the waveguide feed by 8 dBi. Therefore, significant gain enhancement can be successfully obtained.

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A Beam-Scanning Reflectarray with the Weighted Average Phase Compensation for the150-160 GHz Communications

A Beam-Scanning Reflectarray with the Weighted Average Phase...

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

作者： Zhengdong Zhou Botao Feng Xiao Ding Li Deng Wenzhe Gu Kwok L. Chung College of Electronics and Information Engineering Shenzhen University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China College of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China School of Computer Science and Engineering Huizhou University Huizhou China School of Computer Science and Engineering Huizhou University Huizhou P. R. China

In this paper, a 15×15 beam scanning reflectarray operating in 150–160 GHz is proposed. The element consists of 3-layer patches conducted with metal vias. The proposed weighted average phase compensation method is used to obtain stable beam and low gain variations during the beam scanning process. Furthermore, the comparisons of radiation between normal phase compensation and weighted average phase are given to verify the effectiveness of the method. Results show that a large scanning angle of ±50° and a maximum gain of 18.7 dBi with gain variations less than 1.8 dB can be achieved, and hence the proposed antenna array is suitable for future 6G communication system.

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MISROBÆRTA: TRANSFORMERS VERSUS MISINFORMATION

arXiv

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arXiv 2023年

作者： Truicǎ, Ciprian-Octavian Apostol, Elena-Simona Department of Information Technology Uppsala University Uppsala Sweden Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

Misinformation is considered a threat to our democratic values and principles. The spread of such content on social media polarizes society and undermines public discourse by distorting public perceptions and generating social unrest while lacking the rigor of traditional journalism. Transformers and transfer learning proved to be state-of-the-art methods for multiple wellknown natural language processing tasks. In this paper, we propose MisRoBÆRTa, a novel transformer-based deep neural ensemble architecture for misinformation detection. MisRoBÆRTa takes advantage of two state-of-the art transformers, i.e., BART and RoBERTa, to improve the performance of discriminating between real news and different types of fake news. We also benchmarked and evaluated the performances of multiple transformers on the task of misinformation detection. For training and testing, we used a large real-world news articles dataset (i.e., 100,000 records) labeled with 10 classes, thus addressing two shortcomings in the current research: (1) increasing the size of the dataset from small to large, and (2) moving the focus of fake news detection from binary classification to multi-class classification. For this dataset, we manually verified the content of the news articles to ensure that they were correctly labeled. The experimental results show that the accuracy of transformers on the misinformation detection problem was significantly influenced by the method employed to learn the context, dataset size, and vocabulary dimension. We observe empirically that the best accuracy performance among the classification models that use only one transformer is obtained by BART, while DistilRoBERTa obtains the best accuracy in the least amount of time required for fine-tuning and training. However, the proposed MisRoBÆRTa outperforms the other transformer models in the task of misinformation detection. To arrive at this conclusion, we performed ample ablation and sensitivity testing with MisRoBÆRTa on t

关键词： Large dataset

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Feedback Stability Under Mixed Gain and Phase Uncertainty

arXiv

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arXiv 2024年

作者： Liang, Jiajin Zhao, Di Qiu, Li The Googol Technology Guangdong Shenzhen China The Department of Control Science and Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

In this study, we investigate the robust feedback stability problem for multiple-input-multiple-output linear time-invariant systems involving sectored-disk uncertainty, namely, dynamic uncertainty subject to simultaneous gain and phase constraints. This problem is thereby called a sectored-disk problem. Employing a frequency-wise analysis approach, we derive a fundamental static matrix problem that serves as a key component in addressing the feedback stability. The study of this matrix problem heavily relies on the Davis-Wielandt (DW) shells of matrices, providing a profound insight into matrices subjected to simultaneous gain and phase constraints. This understanding is pivotal for establishing a less conservative sufficient condition for the matrix sectored-disk problem, from which we formulate several robust feedback stability conditions against sectored-disk uncertainty. Finally, several conditions based on linear matrix inequalities are developed for efficient computation and verification of feedback robust stability against sectored-disk uncertainty. Copyright © 2024, The Authors. All rights reserved.

关键词： Linear time-invariant system

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