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The Original Method of Controlling a computer Using Distance Sensors 16

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The Original Method of Controlling a Computer Using Distance...

16th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2022

作者： Savaryn, Pavlo Strekha, Vadym Brych, Mykola Brych, Lesia Kabak, Vitalii Polishchuk, Mykola Lutsk National Technical University Department of Digital Education Technologies Lutsk Ukraine Lutsk National Technical University Department of Computer Science Lutsk Ukraine Internet of Things and Software Defined Networks Lab Lviv Polytechnic National University Lviv Ukraine Centre for International Education Lviv Polytechnic National University Lviv Ukraine Lutsk National Technical University Department of Computer Engineering and Cybersecurity Lutsk Ukraine

ISBN: (纸本)9781665468619

The article provides a brief overview of human-computer interaction methods and systems, and the research made in this area. We have designed the architecture of the system and tested a method of controlling a computer using ultrasonic distance sensors. In the course of the experiment, the following problems have been solved: obtaining and processing data from several distance sensors, data transfer to gesture recognition algorithm, uncontrolled oscillations of sensor indicators. The suggested method of controlling a computer can be used in ubiquitous computing. © 2022 IEEE.

关键词： Human computer interaction

A Novel Non- Terrestrial networks Architecture: All Optical LEO Constellations with High-Altitude Ground Stations

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A Novel Non- Terrestrial Networks Architecture: All Optical ...

IEEE International Conference on Communications Workshops, ICC

作者： Pablo G. Madoery Juan A. Fraire Jorge M. Finochietto Halim Yanikomeroglu Gunes Karabulut Kurt Department of Systems and Computer Engineering Non-Terrestrial Networks Lab Carleton University Ottawa Canada Inria INSA Lyon CITI UR3720 Villeurbanne France CONICET - Universidad Nacional de Cordoba Cordoba Argentina Department of Electrical Engineering Poly technique Montreal Poly-Grames Research Center Montreal Canada

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

The emergence of low Earth orbit (LEO) satellite mega-constellations is dynamically transforming the space sector. While free-space optical (FSO) links efficiently facilitate inter-satellite data forwarding, they suffer from atmospheric/weather conditions in the space-to-ground link. This study delves into utilizing high-altitude platform stations (HAPS) as elevated relay stations strategically positioned above terrestrial ground stations. We introduce the concept of high-altitude ground stations (HAGS), an innovative approach to enabling the development of all optical LEO satellite constellations. The first contribution is an analysis of the HAGS-based network architecture where the LEO spacecraft only hosts FSO transceivers. Secondly, we execute an extensive simulation campaign to determine the gain of HAGS, including a new equivalency model with the traditional ground station approach. Finally, we examine the research challenges of implementing HAGS-based, all optical LEO mega-constellations.

关键词： Integrated optics All-optical networks Space vehicles Satellites Uncertainty Conferences Optical buffering

Master Stability Functions in Complex networks

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arXiv 2024年

作者： Acharyya, Suman Pradhan, Priodyuti Meena, Chandrakala Complex Network Dynamics Lab Department of Mathematics Bar-Ilan University Ramat Gan5290002 Israel networks.ai Lab Department of Computer Science & Engineering Indian Institute of Information Technology Karnataka Raichur584135 India Department of Physics Indian Institute of Science Education and Research Thiruvananthapuram Kerala 695551 India

Synchronization is an emergent phenomenon in coupled dynamical networks. The Master Stability Function (MSF) is a highly elegant and powerful tool for characterizing the stability of synchronization states. However, a significant challenge lies in determining the MSF for complex dynamical networks driven by nonlinear interaction mechanisms. These mechanisms introduce additional complexity through the intricate connectivity of interacting elements within the network and the intrinsic dynamics, which are governed by nonlinear processes with diverse parameters and higher dimensionality of systems. Over the past 25 years, extensive research has focused on determining the MSF for pairwise coupled identical systems with diffusive coupling. Our literature survey highlights two significant advancements in recent years: the consideration of multilayer networks instead of single-layer networks and the extension of MSF analysis to incorporate higher-order interactions alongside pairwise interactions. In this review article, we revisit the analysis of the MSF for diffusively pairwise coupled dynamical systems and extend this framework to more general coupling schemes. Furthermore, we systematically derive the MSF for multilayer dynamical networks and single-layer coupled systems by incorporating higher-order interactions alongside pairwise interactions. The primary focus of our review is on the analytical derivation and numerical computation of the MSF for complex dynamical networks. Finally, we demonstrate the application of the MSF in data science, emphasizing its relevance and potential in this rapidly evolving field. © 2024, CC BY.

关键词： Jacobian matrices

Smart Resource Allocation Model via Artificial Intelligence in Software Defined 6G networks

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Smart Resource Allocation Model via Artificial Intelligence ...

IEEE International Conference on Communications (ICC)

作者： Ali Nouruzi Atefeh Rezaei Ata Khalili Nader Mokari Mohammad Reza Javan Eduard A. Jorswieck Halim Yanikomeroglu Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Technical University of Berlin Germany Friedrich-Alexander-University Erlangen-Nurnberg Germany Department of Electrical Engineering Shahrood University of Technology Shahrood Iran Institute of Communications Technology Technische Universität Braunschweig Braunschweig Germany Department of Systems and Computer Engineering Non-Terrestrial Networks (NTN) Lab Carleton University

In this paper, we design a new flexible smart software-defined radio access network (Soft-RAN) architecture with traffic awareness for sixth generation (6G) wireless networks. In particular, we consider a hierarchical resource allocation model for the proposed smart soft-RAN model where the software-defined network (SDN) controller is the first and foremost layer of the framework. This unit dynamically monitors the network to select a network operation type on the basis of distributed or centralized resource allocation procedures to intelligently perform decision-making. In this paper, our aim is to make the network more scalable and more flexible in terms of conflicting performance indicators such as achievable data rate, overhead, and complexity indicators. To this end, we introduce a new metric, i.e, throughput-overhead-complexity (TOC), for the proposed machine learning-based algorithm, which supports a trade-off between these performance indicators. In particular, the decision making based on TOC is solved via deep reinforcement learning (DRL) which determines an appropriate resource allocation policy. Furthermore, for the selected algorithm, we employ the soft actor-critic (SAC) method which is more accurate, scalable, and robust than other learning methods. Simulation results demonstrate that the proposed smart network achieves better performance in terms of TOC compared to fixed centralized or distributed resource management schemes that lack dynamism. Moreover, our proposed algorithm outperforms conventional learning methods employed in recent state-of-the-art network designs.

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Uplink Control Information Based Clustered Access and Discontinuous Reception Management for mMTC

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IEEE Communications Letters 2025年

作者： Wang, Shao-Di Wang, Chang-Long Wang, Hui-Ming Zhou, Feng Leung, Victor C. M. Xidian University Key Laboratory of Electronic Information Countermeasure and Simulation Technology of Ministry of Education Xi’an710071 China Xi’an Jiaotong University School of Information and Communication Engineering Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an710049 China Shenzhen MSU BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Uplink control information (UCI) and discontinuous reception (DRX) play important roles for massive machine type communication (mMTC). Despite their standalone significance, a conspicuous gap exists in comprehensively exploring the synergy between UCI and DRX concerning both energy conservation and latency reduction for mMTC. In this letter, we propose a UCI-based clustered access and DRX management (UCADM) scheme that strikes a balance between these two critical performance metrics, reducing energy usage while preserving low latency in uplink-downlink interaction for mMTC. Specifically, we present a strictly feasible solution for the proposed UCADM scheme by using the spectral radius and the constraint projection, which can effectively solve DRX switching operations as indicated by scheduling information from UCI. Simulation results confirm the effectiveness of our scheme. © 1997-2012 IEEE.

关键词： Information management

Across-Platform Detection of Malicious Cryptocurrency Transactions via Account Interaction Learning

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arXiv 2024年

作者： Che, Zheng Shen, Meng Tan, Zhehui Du, Hanbiao Zhu, Liehuang Wang, Wei Chen, Ting Zhao, Qinglin Xie, Yong The School of Computer Science Beijing Institute of Technology Beijing100081 China The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an710049 China The School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China The School of Computer Science and Engineering Macau University of Science and Technology China The School of Computer and Information Science Qinghai Institute of Technology Xining810016 China

With the rapid evolution of Web3.0, cryptocurrency has become a cornerstone of decentralized finance. While these digital assets enable efficient and borderless financial transactions, their pseudonymous nature has also attracted malicious activities such as money laundering, fraud, and other financial crimes. Effective detection of malicious transactions is crucial to maintaining the security and integrity of the Web 3.0 ecosystem. Existing malicious transaction detection methods rely on large amounts of labeled data and suffer from low generalization. label-efficient and generalizable malicious transaction detection remains a challenging task. In this paper, we propose ShadowEyes, a novel malicious transaction detection method. Specifically, We first propose a generalized graph structure named TxGraph as a representation of malicious transaction, which captures the interaction features of each malicious account and its neighbors. Then we carefully design a data augmentation method tailored to simulate the evolution of malicious transactions to generate positive pairs. To alleviate account label scarcity, we further design a graph contrastive mechanism, which enables ShadowEyes to learn discriminative features effectively from unlabeled data, thereby enhancing its detection capabilities in real-world scenarios. We conduct extensive experiments using public datasets to evaluate the performance of ShadowEyes. The results demonstrate that it outperforms state-of-the-art (SOTA) methods in four typical scenarios. Specifically, in the zero-shot learning scenario, it can achieve an F1 score of 76.98% for identifying gambling transactions, surpassing the SOTA method by 12.05%. In the scenario of across-platform malicious transaction detection, ShadowEyes maintains an F1 score of around 90%, which is 10% higher than the SOTA method. Copyright © 2024, The Authors. All rights reserved.

关键词： Decentralized finance

MV-CC: Mask Enhanced Video Model for Remote Sensing Change Caption

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arXiv 2024年

作者： Liu, Ruixun Li, Kaiyu Song, Jiayi Sun, Dongwei Cao, Xiangyong The School of Automation Xi’an Jiaotong University Xi’an710049 China The School of Software Engineering Xi’an Jiaotong University Xi’an710049 China The School of Computer Science and Technology Ministry of Education Key Lab For Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an710049 China

Remote sensing image change caption (RSICC) aims to provide natural language descriptions for bi-temporal remote sensing images. Since Change Caption (CC) task requires both spatial and temporal features, previous works follow an encoder-fusion-decoder architecture. They use an image encoder to extract spatial features and the fusion module to integrate spatial features and extract temporal features, which leads to increasingly complex manual design of the fusion module. In this paper, we introduce a novel video model-based paradigm without design of the fusion module and propose a Mask-enhanced Video model for Change Caption (MV-CC). Specifically, we use the off-the-shelf video encoder to simultaneously extract the temporal and spatial features of bi-temporal images. Furthermore, the types of changes in the CC are set based on specific task requirements, and to enable the model to better focus on the regions of interest, we employ masks obtained from the Change Detection (CD) method to explicitly guide the CC model. Experimental results demonstrate that our proposed method can obtain better performance compared with other state-of-the-art RSICC methods. The code is available at https://***/liuruixun/MV-CC. Copyright © 2024, The Authors. All rights reserved.

关键词： Change detection

SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation

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arXiv 2023年

作者： An, Xiaoqi Zhao, Lin Gong, Chen Wang, Nannan Wang, Di Yang, Jian PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology China State Key Laboratory of Integrated Services Networks Xidian University China

High-resolution representation is essential for achieving good performance in human pose estimation models. To obtain such features, existing works utilize high-resolution input images or fine-grained image tokens. However, this dense high-resolution representation brings a significant computational burden. In this paper, we address the following question: "Only sparse human keypoint locations are detected for human pose estimation, is it really necessary to describe the whole image in a dense, high-resolution manner?" Based on dynamic transformer models, we propose a framework that only uses Sparse High-resolution Representations for human Pose estimation (SHaRPose). In detail, SHaRPose consists of two stages. At the coarse stage, the relations between image regions and keypoints are dynamically mined while a coarse estimation is generated. Then, a quality predictor is applied to decide whether the coarse estimation results should be refined. At the fine stage, SHaRPose builds sparse high-resolution representations only on the regions related to the keypoints and provides refined high-precision human pose estimations. Extensive experiments demonstrate the outstanding performance of the proposed method. Specifically, compared to the state-of-the-art method ViTPose, our model SHaRPose-Base achieves 77.4 AP (+0.5 AP) on the COCO validation set and 76.7 AP (+0.5 AP) on the COCO test-dev set, and infers at a speed of 1.4× faster than ViTPose-Base. Code is available at https://***/AnxQ/sharpose. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

Microservice-Based Fog Testbed for 6G Applications

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Microservice-Based Fog Testbed for 6G Applications

International Conference on Advanced Communication Technology (ICACT)

作者： Ekaterina Kuzmina Meriem Tefikova Artem Volkov Ammar Muthanna Abdelhamied A. Ateya Andrey Koucheryavy Department of Telecommunication Networks and Data Transmission Saint-Petersburg State University of Telecommunications Saint Petersburg Russia Department of Electronics and Communications Engineering Zagazig University Zagazig Egypt EIAS Data Science Lab College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia

This paper provides a real-time fog computing model based on a microservice architecture that enables testing and modeling of eventual implementations of ultra-reliable low-latency communications (uRLLC) services. The work provides fog-based architecture for sixth-generation cellular (6G) applications, including telepresence and uRLLC. A testbed of a robot swarm was developed to prototype the proposed network architecture. Computing tasks are offloaded and handled based on a proposed microservice scheme introduced to meet the 6G requirements. Furthermore, we developed a novel migration scheme for the proposed architecture to support the mobility of end devices. The optimum server for migrating computing tasks is allocated by solving a proposed optimization problem using particle swarm optimization (PSO). All proposed algorithms were implemented in the developed prototype. The proposed work is introduced to provide an architectural foundation for testing fog-based 6G applications and services and to implement and test novel network methods in the future.

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