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Connectivity in the era of the (I)IoT: about security, features and limiting factors of reconfigurable intelligent surfaces

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Discover Internet of Things 2023年第1期3卷 16页

作者： Lipps, Christoph Herbst, Jan Klingel, Steffen Franke, Lars Wolff, Alexander Rüb, Matthias Reddy, Rekha Rahm, Marco Schotten, Hans Dieter Intelligent Networks Research Group German Research Center for Artificial Intelligence Kaiserslautern67663 Germany Institute for Wireless Communication and Radio Positioning RPTU Kaiserslautern-Landau Kaiserslautern67663 Germany Department of Electrical and Computer Engineering Research Center OPTIMAS RPTU Kaiserslautern-Landau Kaiserslautern67663 Germany

What are the key drivers of the (Industrial) Internet of Things ((I)IoT)? Alongside the interconnection of the various devices, sensors, and actuators, it is above all the data collected and transmitted that is of particular significance, the (I)IoT itself is the source and recipient of various types of data. Within this, there are two main aspects that need to be considered: (i) the transmission of data with appropriate latency and reliability requirements, and (ii) the safeguarding of this data. Both requirements are taken into account during the development of the Sixth Generation (6G) Wireless Systems. This is conceived to deliver higher data rates, reduced cost deployment, and enhanced reliability while providing universal connectivity. Hence, to assist such a vast network domain, (new) 6G-enabling technologies are developed, which include Reconfigurable Intelligent Surfaces (RISs), that are capable of modifying and reconfiguring the wireless propagation channels. This work describes concepts on how security, in particular Physical Layer Security (PhySec) methods, can be supported by RISs. Furthermore, an effective impedance surface model is presented, allowing efficient simulation of beamsplitting and shaping properties of RISs. Finally, the applicability of the use cases is mentioned, with a particular focus on Visible Light communication (VLC). © The Author(s) 2023.

关键词： Internet of things

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Two-Stage Edge-Side Fault Diagnosis Method Based on Double Knowledge Distillation

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computers, Materials & Continua 2023年第9期76卷 3623-3651页

作者： Yang Yang Yuhan Long Yijing Lin Zhipeng Gao Lanlan Rui Peng Yu State Key Laboratory ofNetworking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China School of Computer Science and Engineering Nanyang Technological University639798Singapore Science and Technology on Communication Networks Laboratory The 54th Research Institute of China Electronics Technology Group CorporationShijiazhuang050051China

With the rapid development of the Internet of Things(IoT),the automation of edge-side equipment has emerged as a significant *** existing fault diagnosismethods have the characteristics of heavy computing and storage load,and most of them have computational redundancy,which is not suitable for deployment on edge devices with limited resources and *** paper proposes a novel two-stage edge-side fault diagnosis method based on double knowledge ***,we offer a clustering-based self-knowledge distillation approach(Cluster KD),which takes the mean value of the sample diagnosis results,clusters them,and takes the clustering results as the terms of the loss *** utilizes the correlations between faults of the same type to improve the accuracy of the teacher model,especially for fault categories with high ***,the double knowledge distillation framework uses ordinary knowledge distillation to build a lightweightmodel for edge-side *** propose a two-stage edge-side fault diagnosismethod(TSM)that separates fault detection and fault diagnosis into different stages:in the first stage,a fault detection model based on a denoising auto-encoder(DAE)is adopted to achieve fast fault responses;in the second stage,a diverse convolutionmodel with variance weighting(DCMVW)is used to diagnose faults in detail,extracting features frommicro andmacro *** comparison experiments conducted on two fault datasets,it is proven that the proposed method has high accuracy,low delays,and small computation,which is suitable for intelligent edge-side fault *** addition,experiments show that our approach has a smooth training process and good balance.

关键词： Fault diagnosis knowledge distillation edge-side lightweight model high similarity

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MFFLEN: Multi-Label Text Classification Based on Multi-Feature Fusion and Label Embedding

MFFLEN: Multi-Label Text Classification Based on Multi-Featu...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Gu, Qiliang Zhao, Shuo Zhang, Jianqiang Song, Gongpeng Lu, Qin Key Laboratory of Computing Power Network and Information Security Jinan China Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (纸本)9781665410205

To address the challenges associated with insufficiently extracting and utilizing features at different levels, overlooking the connection between label meanings and text, and facing problems of over-compression or information loss when extracting global information using recurrent neural networks in the field of multi-label text categorization, this paper introduces an innovative model known as MFFLEN (MultiFeature Fusion and Label Embedding Neural Network). First, a back-translated enhanced label set is constructed by back-translated splicing enhancement of the original label set. This set, together with the text, is then input into the embedding layer, which consists of the pre-trained model of bert-baseChinese, thus establishing the initial connection between the text and the labels within the same vector space. Then, to comprehensively extract multi-level semantic features, the model uses a convolutional layer to extract local features and an embedding layer to extract sentence-level features. A bidirectional attention embedded GRU (BAE-GRU) layer is used to extract hybrid finegrained features, which are then fed into the attention layer to further extract hybrid labeled features based on labeling information. Finally, these three different types of features are fused and multi-label text classification results are obtained using a classifier. The experiments proved that the MFFLEN model achieved 73.82% and 88.44% macro-F1 and 88.00% and 88.86% micro-F1 on the two datasets CAIL 2018 Small and CAIL 2018 Split, respectively, which is better than other baseline models. © 2024 IEEE.

关键词： Vector spaces

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Analog Self-Interference Cancellation By Means of a Synchronised Signal Injection

Analog Self-Interference Cancellation By Means of a Synchron...

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European Conference on Antennas and Propagation, EuCAP

作者： Sarmad Ozan Geoffrey Hilton Tommaso Cappello Mark Beach Communication Systems & Networks Research Group University of Bristol United Kingdom Department of Electrical and Computer Engineering Villanova University United States

Full-duplex communications have the potential to double the spectral efficiency. Self-interference hinders the realization of full-duplex communications, thus significant suppression needs to be achieved to enable simultaneous transmit and receive. This paper presents a digitally-assisted analog self-interference cancellation by pre-coding a cancellation waveform on an auxiliary transmitter using a modified copy of the transmitted signal. Over 30 dB self-interference cancellation has been achieved over a bandwidth of 20 MHz.

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SMGC-SBERT: A Multi-Feature Fusion Chinese Short Text Similarity Computation Model Based on Optimised SBERT

SMGC-SBERT: A Multi-Feature Fusion Chinese Short Text Simila...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Shuo Gu, Qiliang Zhang, Jianqiang Song, Gongpeng Lu, Qin Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (纸本)9781665410205

Chinese short text similarity computation stands as a pivotal task within natural language processing, garnering significant attention. However, existing models grapple with limitations in handling intricate semantic relationships, such as the challenge of discerning subtle semantic nuances in text, inadequacies in effectively integrating diverse levels of semantic information, and the struggle to capture polysemous meanings accurately. In addressing these issues, this paper introduces an innovative Chinese short text similarity computation model, SMGC-SBERT. This model addresses shortcomings of the existing models by employing a multi-module fusion strategy, thereby enabling a more precise measurement of semantic similarity between texts. Primarily, the model incorporates SAT embedding to acquire phrase-level semantic information and leverages the MS-BERT model to encode text, improving the model's comprehension of textual polysemy and obtaining richer semantic representation. Then, the fusion of module features, including multi-branch convolutional networks and mix pooling, enables the extraction of textual features from varied levels, bolstering the model's representational capacity. Additionally, to further reduce overfitting risks while improving accuracy and other performance, a multi-layer feature adjustment network is utilized for short text similarity calculation. The final resultant experimental findings showcase the superiority of the SMGC-SBERT model over other neural network models, demonstrating significant advancements across both Chinese-SNLI and CCKS2018_Task3 Chinese short text datasets. © 2024 IEEE.

关键词： Semantics

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FERI: Feature Enhancement and Relational Interaction for Image-text Matching 30

FERI: Feature Enhancement and Relational Interaction for Ima...

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30th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2024

作者： Zhang, Yu Zhang, Jianqiang Song, Gongpeng Lu, Qin Zhao, Shuo Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (纸本)9798331515966

Image-text matching is an important problem at the intersection of computer vision and natural language processing. It aims to establish the semantic link between image and text to achieve high-quality semantic alignment between the two modalities. However, the existing methods have the problem that the meaning expressed in the image or the complex narrative in the text cannot be fully understood due to insufficient feature extraction. Moreover, due to the essential modal differences between images and texts, how to effectively and accurately align the semantic contents in images and texts has become the key of research. In order to solve the above problems, this paper proposes a method based on feature enhancement and relationship interaction. When processing images, the proposed method fuses labeled features, region features and location features to represent images. When processing text, a combination of Bi-GRU and self-attention mechanism is used to represent the text. In order to further align the semantic content in images and texts accurately, this paper improves two relational interaction mechanisms by identifying connection relationships and learning association relationships. Thus, the relation enhanced embedding is obtained. Finally, it calculated the similarity of the enhanced embedding to judge the matching degree of the image and text. Extensive experiments on the public datasets Flickr30K and MSCOCO demonstrate the effectiveness of our method. © 2024 IEEE.

关键词： cross-modal retrieval feature enhancement image-text matching relationship interaction

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Event-driven bi-fidelity control for efficient and reliable robotic manipulation

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Results in Engineering 2025年 26卷

作者： Alsaade, Fawaz W. Al-zahrani, Mohammed S. Alsaadi, Fuad E. Department of Computer Science College of Computer Sciences and Information Technology King Faisal University Al-Ahsa31982 Saudi Arabia Department of Computer Networks and Communications College of Computer Sciences and Information Technology King Faisal University Al-Ahsa31982 Saudi Arabia Communication Systems and Networks Research Group Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia

This paper proposes a novel bi-fidelity control framework for robotic manipulators that integrates a high-fidelity model predictive control (MPC) scheme with a low-fidelity Long Short-Term Memory (LSTM) neural network surrogate. Unlike conventional fixed-schedule approaches, our method employs an event-triggered mechanism that dynamically selects the appropriate controller based on a real-time error metric. This mechanism ensures that the computationally intensive MPC is invoked only when the LSTM approximation deviates beyond acceptable bounds. We rigorously established the near-optimal performance and closed-loop stability of our approach via Lyapunov analysis under mild assumptions, instilling confidence in its reliability. The simulation results on a three-arm manipulator, subject to low-frequency sinusoidal and high-frequency chirp trajectories, demonstrate that the proposed approach achieves up to 80–90% reduction in MPC calls, significantly improving the accuracy of the follow-up and computational efficiency. These findings highlight the potential of integrating learning-based approximations with conventional optimization-based control to achieve reliable and time-efficient performance in complex robotic manipulation tasks. © 2025 The Authors

关键词： Predictive control systems

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Balanced Spanning Tree Protocol in Hierarchical NextGen Ethernet networks

TechRxiv

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TechRxiv 2022年

作者： Mirjalily, Ghasem Department of Electrical Engineering Computer and Communication Networks Research Group Yazd University Yazd Iran

Creation and maintenance of the spanning tree forwarding topology is an essential task in Ethernet networks. In standard Ethernet networks, Spanning Tree Protocol (STP) is responsible to do this task. In STP, some links will be disabled to provide a minimum-cost spanning tree. However, the constructed tree may be unbalanced. STP does not provide any mechanism for load balancing, results in unbalanced distribution of the traffic load and this may lead to congestion. In this paper, a new protocol named Balanced Spanning Tree Protocol (BASTP) is proposed to provide a balanced spanning tree in hierarchical topologies for using in next generation (NextGen) wired networks. Simulation results show that BASTP provides better load balancing and therefore better performance in comparison to the standard STP. © 2022, CC BY.

关键词： Ethernet

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Reconfigurable Intelligent Surfaces: A Physical Layer Security Perspective 4

Reconfigurable Intelligent Surfaces: A Physical Layer Securi...

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4th International Conference on Data Intelligence and Security, ICDIS 2022

作者： Lipps, Christoph Herbst, Jan Reddy, Rekha Franke, Lars Becker, Sven Rahm, Marco Dieter Schotten, Hans German Research Center for Artificial Intelligence Intelligent Networks Research Group KaiserslauternD-67663 Germany Institute for Wireless Communication and Radio Positioning Technische Universitt Kaiserslautern KaiserslauternD-67663 Germany Research Center OPTIMAS Technische Universit Kaiserslautern Department of Electrical and Computer Engineering KaiserslauternD-67663 Germany

ISBN: (数字)9781665459686

ISBN: (纸本)9781665459686

The conceptual design of the Sixth Generation (6G) wireless systems include, among others, Reconfigurable Intelligent Surfaces (RISs), arrays of elements that are capable of manipulating and reconfiguring the wireless propagation environment. Thereby, they are claimed to have advantages in different subjects, such as coverage, energy efficiency and localization. Therefore, this work discusses five use-cases of how RISs could contribute to Physical Layer Security (PhySec) concepts. By actively influencing the scattering, reflection and refraction characteristics of electromagnetic waves, beamforming and - splitting, as well as by adding individual information to the transmitted signals, they can increase the environmental wireless security. In addition to the description and discussion of the applicability of conceivable use-cases the RIS behaviour is demonstrated by full-wave simulations of the electric far-field. © 2022 IEEE.

关键词： Wireless networks

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Classification and evaluation of IoT brokers: A methodology

Classification and evaluation of IoT brokers: A methodology

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作者： Bertrand-Martinez, Eddas Dias Feio, Phelipe Brito Nascimento, Vagner de Kon, Fabio Abelém, Antônio GERCOM - Research Group on Networks and Multimedia Communications Federal University of Pará Belém Brazil Department of Computer Science University of São Paulo São Paulo Brazil

Since the term Internet of Things (IoT) was coined by Kevin Ashton in 1999, a number of middleware platforms have been developed to cope with important challenges such as the integration of different technologies. In this context of heterogeneous technologies, IoT message brokers become critical elements for the proper function of smart systems and wireless sensor networks (WSN) infrastructures. There are several evaluations made on IoT messaging middleware performance. Nevertheless, most of them ignore crucial aspects of the IoT context that also need to be included, such as reliability and other qualitative aspects. Thus, in this article, we propose a methodology for classification and evaluation of IoT brokers to help the scientific community and technology industry on evaluating them according to their interests, without leaving out important aspects for the context of smart environments. Our methodology bases its qualitative evaluations on the ISO/IEC 25000 (SQuaRE) set of standards and its quantitative evaluations on Jain's process for performance evaluation. We developed a case study to illustrate our proposal with 12 different open-source brokers, validating the feasibility of our methodological approach. © 2020 John Wiley & Sons, Ltd.

关键词： Middleware

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