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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Zhizongkai Wang Hanfei Wang Zhongji Wang Yilin Xiao Yunzhi Zhao Xiaowen Li Xufeng Chen Lin Gao Fen Hou Jianwei Huang School of Electronics and Information Engineering and the Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Harbin Institute of Technology Shenzhen Guangdong P.R. China School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network and CSIJRI Joint Research Centre on Smart Energy Storage The Chinese University of Hong Kong Shenzhen Guangdong P.R. China Department of Electrical and Computer Engineering State Key Laboratory of IoT for Smart City University of Macau Macau SAR P.R. China Huawei Technologies P.R. China

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

The rapid advancement of information and communication technology (ICT) has made the industry a significant contributor to global carbon emissions. As the foundation of ICT, next-generation mobile communication networks aim to be more powerful and energy-efficient. However, optimizing energy efficiency in real networks is challenging due to large-scale, multi-layer control variables and the dynamic environment. This paper addresses the energy efficiency optimization problem from a network perspective by controlling cross-layer variables including both cell activation status and cell priority, to minimize overall network energy consumption while ensuring user quality-of-experience, which poses an NP-hard mixed-integer nonlinear programming problem. To tackle this, we propose a non-cooperative game where each cell acts as a player, optimizing its activation status and reference signal transmission power (determining its priority). We show that the game is a potential game, guaranteeing the existence of Nash equilibrium and the convergence of simple distributed algorithms towards Nash equilibrium. We further show that the Nash equilibrium points of the game can (but not always) reach the global optimal energy efficiency. Simulation results show that our proposed method can reduce the total system cost (including both energy consumption cost and user experience loss) by up to 28% compared to existing methods in the literature. Moreover, the performance loss of our proposed method, compared to the global optimal solution, is less than 13.7%. In summary, this work offers a realistic network model, introduces a novel game-based method, and provides extensive performance evaluation, making a significant contribution to both industry and academia.

关键词： Industries Energy consumption Costs Simulation Games Nash equilibrium Energy efficiency Information and communication technology Distributed algorithms Optimization

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An Intelligent Age of Information Based Self-Energized Uav-Assisted Wireless Communication System

SSRN

引用

SSRN 2022年

作者： Jeganathan, Anandpushparaj Dhayabaran, Balaji Jayakody, Dushantha Nalin K. Muthuchidambaranathan, P. Ranchagodage Don, Sanjaya Arunapriya National Institute of Technology Tiruchirappalli India Department of Electronics and Communication Engineering National Institute of Technology Tiruchirappalli620015 India Senior Member Technical Staff Baseband Algorithm Development Team Saankhya Labs Private Limited Bengaluru560001 India Centro de Investigaçä em Tecnologias - Autónoma TechLab Universidade Autónoma de Lisboa Portugal School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk Russia Centre for Telecommunication Research School of Engineering Sri Lanka Technological Campus Padukka10500 Sri Lanka

Internet-of-things (IoT) is an enabling technology in the fourth generation industrial revolution. An unified performance metric named age of information (AoI) is introduced to quantify the freshness of data and its applications. Thus, this paper study the combination of AoI and full-duplex enabled unmanned aerial vehicle (FD-UAV) as a promising solution to improve latency and spectrum efficiency of a wireless powered sensor network. A sensor node (SN), located ina transport infrastructure, harvests energy from radio frequency signals transmitted by the FD-UAV. This uses to transmit real time sensor observations to the data sink via FD-UAV. The SN generates an update after replenished the battery and transmits by using the harvested energy. A closed-form expression for average AoI (AAoI) is derived as a function of time allocated for energy harvesting (EH). The optimal time allocation for EH that maximizes the freshness of data update is identified. Deep learning algorithms such as Long-Short Term Memory (LSTM) is used to predict the AAoI. Simulation results demonstrate the usefulness performance bounds in-terms of freshness of data updates. © 2022, The Authors. All rights reserved.

关键词： Sensor nodes

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Novel Smart N95 Filtering Facepiece Respirator with Real-time Adaptive Fit Functionality and Wireless Humidity Monitoring for Enhanced Wearable Comfort

arXiv

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arXiv 2023年

作者： Kwon, Kangkyu Lee, Yoon Jae Jung, Yeongju Soltis, Ira Choi, Chanyeong Na, Yewon Romero, Lissette Kim, Myung Chul Rodeheaver, Nathan Kim, Hodam Lloyd, Michael S. Zhuang, Ziqing King, William Xu, Susan Ko, Seung-Hwan Lee, Jinwoo Yeo, Woon-Hong School of Electrical and Computer Engineering College of Engineering Georgia Institute of Technology AtlantaGA30332 United States Center for Human-Centric Interfaces and Nanoengineering Institute for Electronics and Nanotechnology Georgia Institute of Technology AtlantaGA30332 United States Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332 United States School of Industrial Design Georgia Institute of Technology AtlantaGA30332 United States Division of Cardiology Emory University School of Medicine AtlantaGA30322 United States National Institute for Occupational Safety and Health National Personal Protective Technology Laboratory PittsburghPA15236 United States Seoul National University Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Department of Mechanical Robotics and Energy Engineering Dongguk University 30 Pildongro 1-gil Jung-gu Seoul04620 Korea Republic of Wallace H. Coulter Department of Biomedical Engineering Parker H. Petit Institute for Bioengineering and Biosciences Neural Engineering Center Institute for Materials Institute for Robotics and Intelligent Machines Georgia Institute of Technology AtlantaGA30332 United States

The widespread emergence of the COVID-19 pandemic has transformed our lifestyle, and facial respirators have become an essential part of daily life. Nevertheless, the current respirators possess several limitations such as poor respirator fit because they are incapable of covering diverse human facial sizes and shapes, potentially diminishing the effect of wearing respirators. In addition, the current facial respirators do not inform the user of the air quality within the smart facepiece respirator in case of continuous long-term use. Here, we demonstrate the novel smart N-95 filtering facepiece respirator that incorporates the humidity sensor and pressure sensory feedback-enabled self-fit adjusting functionality for the effective performance of the facial respirator to prevent the transmission of airborne pathogens. The laser-induced graphene (LIG) constitutes the humidity sensor, and the pressure sensor array based on the dielectric elastomeric sponge monitors the respirator contact on the user’s face, providing the sensory information for a closed-loop feedback mechanism. As a result of the self-fit adjusting mode along with elastomeric lining, the fit factor is increased by 3.20 and 5 times at average and maximum respectively. We expect that the experimental proof-of-concept of this work will offer viable solutions to the current commercial respirators to address the *** Codes 92C55 Copyright © 2023, The Authors. All rights reserved.

关键词： Graphene

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Preliminary Evaluation of Recommended Airline Exercises for Optimal Calf Muscle Pump Activity

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European Journal of Vascular and Endovascular Surgery 2006年第3期32卷 340-340页

作者： K.J. O'Donovan T. Bajd P.A. Grace D.T. O'Keeffe G.M. Lyons Biomedical Electronics Laboratory Department of Electronic and Computer Engineering University of Limerick Limerick Ireland Laboratory of Robotics and Biomedical Engineering Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia Vascular Imaging Laboratory Department of Vascular Surgery Mid-Western Regional Hospital Limerick Ireland

Objectives A preliminary study to investigate which of the recommended airline exercises for DVT prevention produce optimal calf muscle pump activity. Methods Four subjects were instructed to carry out ten lower leg exercises based on those recommended by airlines for DVT prevention. An EMG sensor was used to record calf muscle activity and a motion analysis system was used to ensure the exercise was conducted correctly. Results Statistical analysis showed significant differences in the level of calf muscle pump activity induced by the different exercises. Heel rise foot pumps were shown to induce highest levels of activity while many exercises did not induce any significant calf muscle activity at all. Conclusion These findings indicate that a further, more detailed examination of the exercises recommended to passengers for DVT prevention on long distance flights should be conducted to determine the potential benefit to the health and safety of the passenger.

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Robot ontologies for sensor- and Image-guided surgery

Robot ontologies for sensor- and Image-guided surgery

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International Workshop on Robot Sensing (ROSE)

作者： Tamás Haidegger Marcos Barreto Paulo J. S. Goncalves Maki K. Habib S. Veera Ragavan Howard Li Alberto Vaccarella Roberta Perrone Edson Prestes Austrian Center for Medical Innov. and Techn. (ACMIT) Wiener Neustadt Austria UFBA Distributed Systems Laboratory (LaSiD) Brazil IDMEC Center of Intelligent Systems Portugal The American University in Cairo Cairo Egypt Monash University Selangor Malaysia Dept. of Electrical and Computer Engineering University of New Brunswick Canada Dept. of Electronics Information and Bioengineering (DEIB) NearLab Medical Robotics Milan Italy UFRGS Instituto de Informática Brazil

Robots and robotics are becoming more complex and flexible, due to technological advancement, improved sensing capabilities and machine intelligence. Service robots target a wide range of applications, relying on advanced Human-Robot Interaction. Medical robotics is becoming a leading application area within, and the number of surgical, rehabilitation and hospital assistance robots is rising rapidly. However, the complexity of the medical environment has been a major barrier, preventing a wider use of robotic technology, thus mostly teleoperated, human-in-the-loop control solutions emerged so far. Providing smarter and better medical robots requires a systematic approach in describing and translating human processes for the robots. It is believed that ontologies can bridge human cognitive understanding and robotic reasoning (machine intelligence). Besides, ontologies serve as a tool and method to assess the added value robotic technology brings into the medical environment. The purpose of this paper is to identify relevant ontology research in medical robotic, and to review the state-of-the-art. It focuses on the surgical domain, fundamental terminology and interactions are described for two example applications in neurosurgery and orthopaedics.

关键词： Robot sensing systems Surgery Lead Ontologies Biomedical optical imaging

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Mitigation Methods of Reducing DDOS Attack Frequency on Blockchain

Mitigation Methods of Reducing DDOS Attack Frequency on Bloc...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： R. Sathees Kumar Phanikanth Chintamaneni Madarapu Naresh Kumar Ankita Joshi Bajila Swathi Joshuva Arockia Dhanraj Department of CSE Narasaraopeta Institute of Technology JNTUK University Narasaraopet Andhra Pradesh Department Of CSE Koneru Lakshmaiah Education Foundation Scientist B National Informatics Centre Ministry of Electronics and Information Technology (MEITY) New Delhi National Informatics Centre Ministry of Electronics and Information Technology (MEITY) New Delhi Uttaranchal Institute of Technology Uttaranchal University India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Padur Chennai India

A serious risk to genuine organization demands is a distributed denial of service (DDoS) attack. The main DDoS attack was archived in 1996, however, from that point forward, their intricacy and refinement have consistently expanded. A 2 TBps attack on a crucial foundation, including the monetary area, was accounted for in August 2020 during the Coronavirus pandemic. In the accompanying two years, it is anticipated that the number of attacks would twofold, stretching around 15 million. Since its beginning, many relief plans have been made, however, the intricacy is rising, requiring modern arrangements in view of new innovation. A potential and common-sense method for DDoS relief is blockchain. The point of the review is to give an exhaustive examination of the fundamental and intrinsic properties of blockchain, including their decentralization, inside and outer trust lessness, unchanging nature, honesty, obscurity, and evidence, which have demonstrated to be a fantastic contender for battling this destructive cyber threat.

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Development of Microcontroller-Based Manipulator Arm: A Trilemma Problem-Solving Framework for robotics and STEM Education in Nigerian Schools

Development of Microcontroller-Based Manipulator Arm: A Tril...

引用

Technologies Applied to electronics Teaching (TAEE)

作者： Mbadiwe S. Benyeogor Tobore L. Igbigbi Olusegun I. Lawal Udoh T. Akpan Andrew O. Benyeogor Nnaemeka M. Mbachu Kosisochukwu P. Nnoli Muhammad S. Aliero Adeboye Olatunbosun Institute of Physics University of Münster Münster Germany Department of Public Utilities City of Cleveland Ohio State USA Advanced Aerospace Engines Lab. Nat. Space Research & Dev. Agency Oka Akoko Ondo State Nigeria Dept. Mechatronics Engineering Lagos State Univ. of Sc. & Tech. Ikorodu Lagos State Nigeria CTE Computer Science & Robotics International Leadership of Texas Aggieland Texas USA Dept. Comp. Sc. & Electrical Engineering Constructor University Bremen Germany ICT Department Kebbi State Univ. of Sc. & Tech Aliero Nigeria Dept. Electrical & Electronics Engineering Ajayi Crowther University Oyo Town Oyo State Nigeria

ISBN: (数字)9798350348675

ISBN: (纸本)9798350348682

Advances in microprocessor technology and software engineering have resulted in the development of sophisticated robots that are used in modern society as assistive automata for production, security, and farming, among other things. To sustain the development of robots, robotics education should be included in school curricula (i.e., teaching and learning process). However, schools in many developing nations, such as Nigeria, are unable to adapt to this trend due to personnel, technological, infrastructural, and fiscal limitations. To address this problem, a low-cost robotic manipulator arm with real-time control algorithms and a human-robot interface that allows it to be controlled by a microcomputer is developed. This includes its functional model, geometry of link movement, mechanical design, control circuitries, and a Teraterm-based human-robot interface (HRI). Furthermore, an encryption method was developed that maps selected control keys to actuation functions in manipulator chains. We also explored how this robotic manipulator may be used as a teaching tool, particularly for teaching three major industrial technologies: machine-making, electronics, and computing. Our manipulator arm has undergone both unit and system tests and has been used for classroom teaching. Results of its applicability assessment show that our system could aid the teaching of robotics and STEM subjects in schools, as a way to solve the trilemma of harmonizing the concept of machines, electronic control, and computation in multidisciplinary domains.

关键词： Service robots Educational robots Education Manipulators Real-time systems Production facilities Security

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Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement

arXiv

引用

arXiv 2021年

作者： Luo, Hongming Zhou, Fei Liao, Guangsen Qiu, Guoping College of Electronics and Information Engineering Shenzhen University China Peng Cheng Laboratory Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen China Shenzhen Key Laboratory of Digital Creative Technology China Shenzhen Institute for Artificial Intelligence and Robotics for Society Shenzhen China School of Computer Science University of Nottingham NottinghamNG8 1BB United Kingdom Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication Guangdong Shenzhen China

In real-world applications, such as sharing photos on social media platforms, images are always not only sub-sampled but also heavily compressed thus often containing various artefacts. Simple methods for enhancing the resolution of such images will exacerbate the artefacts, rendering them visually objectionable. In spite of its high practical values, super-resolving compressed images is not well studied in the literature. In this paper, we propose a novel compressed image super resolution (CISR) framework based on parallel and series integration of artefacts removal and resolution enhancement. Based on a mathematical inference model for estimating a clean low-resolution (LR) image and a clean high-resolution (HR) image from a down-sampled and compressed observation, we have designed a CISR architecture consisting of two deep neural network modules: the artefacts removal module (ARM) and the resolution enhancement module (REM). The ARM and the REM work in parallel with both taking the compressed LR image as their inputs, at the same time they also work in series with the REM taking the output of the ARM as one of its inputs and the ARM taking the output of the REM as its other input. A technique called unfolding is introduced to recursively suppress the compression artefacts and restore the image resolution. A unique feature of our CISR system is that it exploits the parallel and series connections between the ARM and the REM, and recursive optimization to reduce the model's dependency on specific types of degradation thus making it possible to train a single model to super-resolve images compressed by different methods to different qualities. Experiments are conducted on a mixture of JPEG and WebP compressed images without assuming apriori compression type and compression quality factor. To demonstrate our technique's real-world application value, we have also applied the trained models directly to restore social media images which have undergone scaling and compre

关键词： Deep neural networks

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Probabilistic learning vector quantization on manifold of symmetric positive definite matrices

arXiv

引用

arXiv 2021年

作者： Sonna, Fengzhen Tang Feng, Haifeng Tino, Peter Si, Bailu Ji, Daxiong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China School of computer Science University of Birmingham BirminghamB15 2TT United Kingdom School of Systems Science Beijing Normal University Beijing100875 China Institute of Marine Electronics and Intelligent Systems Ocean College Zhejiang University Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of Education Zhoushan316021 China

In this paper, we develop a new classification method for manifold-valued data in the framework of probabilistic learning vector quantization. In many classification scenarios, the data can be naturally represented by symmetric positive definite matrices, which are inherently points that live on a curved Riemannian manifold. Due to the non-Euclidean geometry of Riemannian manifolds, traditional Euclidean machine learning algorithms yield poor results on such data. In this paper, we generalize the probabilistic learning vector quantization algorithm for data points living on the manifold of symmetric positive definite matrices equipped with Riemannian natural metric (affine-invariant metric). By exploiting the induced Riemannian distance, we derive the probabilistic learning Riemannian space quantization algorithm, obtaining the learning rule through Riemannian gradient descent. Empirical investigations on synthetic data, image data, and motor imagery EEG data demonstrate the superior performance of the proposed method. © 2021, CC BY-NC-SA.

关键词： Learning algorithms

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Extreme ecosystem studies in the deep OCEan: Technological developments EXOCET/D

Extreme ecosystem studies in the deep OCEan: Technological d...

引用

The Fourteenth International Offshore and Polar engineering Conference - ISOPE 2004

作者： Sarradin, P.-M. Sarrazin, J. Cadiou, J.F. Olu, K. Desbruyères, D. Rigaud, V. Drogou, J.F. Lecornu, F. Rolin, J.F. Vuillemin, R. Cambon-Bonavita, M.A. Sauter, E. Von Juterzenka, K. Boetius, A. Serrão Santos, R. Colaço, A. Pascoal, A. Oliveira, P. Shillito, B. Zal, F. Schultz, A. Taylor, P. Lane, D. Loke, R.E. Du Buf, H. Waldmann, C. Cormack, A. Sanfilippo, L. Masson, M. Ifremer DRO/EP Plouzané and La Seyne sur Mer France DNIS Plouzané and La Seyne sur Mer France TMSI Plouzané and La Seyne sur Mer France DRV/VP Plouzané and La Seyne sur Mer France AWI Dept. Geosystem and Project Group Deep-Sea Research Bremerhaven Germany Project Group AUV Payload Development and Deep-Sea Gradients Bremerhaven Germany Geosystem Paleoenvironment from Marine Sediments Bremerhaven Germany University of the Azores Horta Portugal Dept. of Electrical Engineering Institute for Systems and Robotics Instituto Superior Técnico Lisbon Portugal UMR CNRS 7138 Systématique Adaptation et Evolution Université Pierre et Marie Curie Paris France Equipe Ecophysiologie Station Biologique Roscoff France School of Earth Ocean and Planetary Sciences Cardiff University Cardiff United Kingdom Dept. Electrical Electronic and Computer Engineering Heriot-Watt University Edinburgh United Kingdom Dept. of Electronics and Computer Science Vision Laboratory University of Algarve Faro Portugal University of Bremen FB5/MARUM Bremen Germany SeeByte Ltd Edinburgh United Kingdom Systea Srl Anagni Italy CAPSUM Technologie GmbH Trittau Germany

The general objective of EXOCET/D is to develop, implement and test specific instruments aimed at exploring, describing, quantifying and monitoring biodiversity in deep-sea fragmented habitats as well as at identifying links between community structure and environmental dynamics. Onboard experimental devices will complement the approach, enabling experiments on species physiology. The EXOCET/D working fields include: video and acoustic imagery, in situ analysis of physico-chemical factors, quantitative sampling of macro- and micro-organisms, in vivo experiments, integration of multidisciplinary data, implementation on European deep-submersibles and a final phase of technical and scientific validation. Copyright © 2004 by The International Society of Offshore and Polar Engineers.

关键词： Submersibles

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