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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Qiao, Zexin Lyu, Ling Dai, Yanpeng Cheng, Nan Shen, Xuemin Dalian Maritime University School of Information Science and Technology Dalian116026 China Xidian University School of Telecommunications Engineering Xi'an710071 China University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

ISBN: (纸本)9798350345384

The wide application of Internet of Things (IoT) technology in industrial automation promotes the emergence of industrial IoT systems, where state estimation plays a critical role in accurately tracking the state of control system and enabling informed decisions and appropriate actions. State estimation is generally performed with the sensory data delivered over IoT. Therefore, the transmission performance of sensory data plays a crucial role in the accuracy of state estimation. However, it is challenging to ensure the required transmission reliability for state estimation due to spectrum scarcity, energy limitation, and the harsh industrial radio environment. To address this issue, we propose an energy-aware sensor scheduling and opportunistic transmission scheme to balance the estimation performance and resource consumption. In particular, we define a novel performance metric, estimation error ratio, to evaluate the impact of sensor scheduling on estimation performance. Then, a spectrum and energy resources constrained minimization problem is formulated to reduce the weighted sum of estimation error and energy consumption. In order to effectively solve the non-convex problem, an estimation error ratio-based algorithm is designed to determine the scheduled sensors. Moreover, we propose an iterative method to obtain the near-optimal solution for the opportunistic transmission problem. Finally, simulation results demonstrate that the proposed scheme can effectively reduce energy consumption with the estimation accuracy guarantee. © 2023 IEEE.

关键词： Energy utilization

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Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy

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Magnetic Resonance Materials in Physics, Biology and Medicine 2024年第3期37卷 477-489页

作者： Huang, Yu-Long Lin, Yi-Ru Tsai, Shang-Yueh Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Applied Physics National Chengchi University No.64 Sec.2 ZhiNan Rd. Wenshan District Taipei 11605 Taiwan Research Center for Mind Brain and Learning National Chengchi University Taipei Taiwan

Background : Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful. Materials and methods: This study aims to investigate whether metabolite concentrations quantified using a convolutional neural network (CNN) based method, coupled with a scaling procedure that normalizes spectral signals for CNN input and linear regression, can effectively reflect variations in metabolite concentrations in IU across different brain regions with varying signal-to-noise ratios (SNR) and linewidths (LW). An error index based on standard error (SE) is proposed to indicate the confidence levels associated with metabolite predictions. In vivo MRS spectra were acquired from three brain regions of 43 subjects using a 3T system. Results: The metabolite concentrations in IU of five major metabolites, quantified using CNN and LCModel, exhibit similar ranges with Pearson’s correlation coefficients ranging from 0.24 to 0.78. The SE of the metabolites shows a positive correlation with Cramer-Rao lower bound (CRLB) (r=0.46) and absolute CRLB (r=0.81), calculated by multiplying CRLBs with the quantified metabolite content. Conclusion: In conclusion, the CNN based method with the proposed scaling procedures can be employed to quantify in vivo MRS spectra and derive metabolites concentrations in IU. The SE can be used as error index, indicating predicted uncertainties for metabolites and sharing information similar to the absolute CRLB. © The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) 2023.

关键词： Convolutional neural network Magnetic resonance spectroscopy Metabolite concentrations

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Age-Aware Dynamic Frame Slotted ALOHA for Machine-Type Communications

arXiv

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arXiv 2024年

作者： Moradian, Masoumeh Dadlani, Aresh Khonsari, Ahmad Tabassum, Hina The School of Computer Engineering K. N. Toosi University of Technology Tehran Iran The School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran The School of Electrical and Computer Engineering University of Tehran Iran The Department of Computing Science University of Alberta EdmontonABT6G 2E8 Canada The Department of Electrical and Computer Engineering Nazarbayev University Astana010000 Kazakhstan The Department of Electrical Engineering and Computer Science York University TorontoONM3J 1P3 Canada

Information aging has gained prominence in characterizing communication protocols for timely remote estimation and control applications. This work proposes an Age of Information (AoI)-aware threshold-based dynamic frame slotted ALOHA (T-DFSA) for contention resolution in random access machine-type communication networks. Unlike conventional DFSA that maximizes the throughput in each frame, the frame length and age-gain threshold in T-DFSA are determined to minimize the normalized average AoI reduction of the network in each frame. At the start of each frame in the proposed protocol, the common Access Point (AP) stores an estimate of the age-gain distribution of a typical node. Depending on the observed status of the slots, age-gains of successful nodes, and maximum available AoI, the AP adjusts its estimation in each frame. The maximum available AoI is exploited to derive the maximum possible age-gain at each frame and thus, to avoid overestimating the age-gain threshold, which may render T-DFSA unstable. Numerical results validate our theoretical analysis and demonstrate the effectiveness of the proposed T-DFSA compared to the existing optimal frame slotted ALOHA, threshold-ALOHA, and age-based thinning protocols in a considerable range of update generation rates. © 2024, CC BY.

关键词： Internet of things

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Research on the influencing factors of the spread of posts in the field of climate change - Take Sina Weibo as an example 7

Research on the influencing factors of the spread of posts i...

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7th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Li, Xue Li, Yizhuo Wu, Yande Wu, Chen Shi, Juan Cui, Ying'an Shaanxi Normal University International Business School Xi'an China China Unicom Western Innovation Research Institute Co. Ltd Software R and D Department 2 Xi'an China Xi'an University of Finance and Economics Xi'an China Xi'an University of Technology Department of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798350384437

The challenge of climate change is serious, and China attaches great importance to it and takes measures, the frequent occurrence of meteorological disasters triggers public opinion, so it is necessary to understand the formation principle, evolution process, and influencing factors of public opinion. This paper uses the LDA topic identification method to extract four main discussion topics: economic development, climate change and environment, human impact of extreme climate, and weather, and analyses the differences in discussion hotspots between different cities. The study also found that emotional attitudes towards microblog information related to climate change negatively impact its reposting, the number of words and entries on the microblog had a positive impact on its reposting, and the activity, influence, identity category, and credibility of microblog authors had a positive impact on its reposting. It provides new insights into the government's management and guidance mechanisms. © 2024 IEEE.

关键词： Sentiment analysis

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Design and Implementation of a Smart Human Posture Monitoring Device Using a Wearable Vest 7

Design and Implementation of a Smart Human Posture Monitorin...

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7th International Conference on Advances in Biomedical engineering, ICABME 2023

作者： Daou, Roy Abi Zeid Geha, Elio Aoun, Youssef Hayek, Ali Boercsoek, Josef Olmedo, Jose Javier Serrano Université la Sagesse Biomedical Engineering Department Furn El Chebbak Beirut Lebanon Mart Learning Education and Research Center Chananir Lebanon Lebanese German University Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon University of Applied Science Hamm-Lippstadt Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 Hamm59063 Germany University of Kassel Faculty of Electrical Engineering /Computer Science Department of Computer Architecture and System Programming Germany Universidad Politecnica de Madrid Lab of Bioinstrumentation and Nanomedicine Centro de Tecnologia Biomedica Spain

ISBN: (纸本)9798350325850

Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pain may manifest suddenly in some cases, it often develops gradually and persists for weeks, and in untreated cases, it can linger for years. Hence, the utilization of assistive devices such as wearable posture-monitoring vests can offer valuable assistance and guidance to users. This research paper is dedicated to the development of a system for detecting, diagnosing, and correcting poor posture, specifically leaning posture. The vest is designed to provide users with visual, auditory, and tactile cues to help them address this issue, thereby reducing the risk associated with leaning. Additionally, an integrated electrical box has been designed to consolidate all components directly onto the main board in a secure enclosure. This box also displays the daily count of instances where the user has leaned. This system is characterized by its electrical safety, portability, compactness, comfort, and affordability. A comprehensive analysis of the system's performance has been conducted with a meticulous evaluation of accuracy. Each component of the system has undergone successful testing, and the system as a whole is currently in the testing phase. The results of these tests have indicated a lack of faulty errors and have demonstrated outstanding accuracy and detection rates. Over 100 individuals of varying ages, genders, and BMI categories were involved in testing, with each person wearing the device for an average of six hours. The accuracy rate achieved was 98.85%, with an average of 54.35 instances of poor posture detected per participant. © 2023 IEEE.

关键词： Wearable technology

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An Accurate Path Tracking Algorithm for Autonomous Vehicles Based on Pure Pursuit with Systematically Designed Look-Ahead Distance and Sideslip Compensation 23

An Accurate Path Tracking Algorithm for Autonomous Vehicles ...

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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Seo, Ji Hwan Youn, Sung Hoon Kim, Jungeun Kim, Kyoung-Dae Dgist Department of Electrical Engineering and Computer Science Daegu42988 Korea Republic of Convergence Technology Development Team Autonomous a2z Anyang14067 Korea Republic of Development Team Vueron Technology Seoul06628 Korea Republic of

ISBN: (纸本)9788993215274

Pure pursuit is still being utilized as a path tracking algorithm for autonomous vehicles due to its advantages, such as robustness and easy implementation. However, using an inappropriate look-ahead distance and ignoring the effects of dynamics deteriorate the path tracking performance of pure pursuit. To improve the tracking performance, we propose a pure pursuit-based path tracking algorithm that quickly reduces tracking error and considers the sideslip by dynamics. For fast tracking error reduction, a dynamic look-ahead distance is designed as a function of speed and path curvature by analyzing the tracking error change according to the look-ahead distance. In addition, to compensate for the sideslip effect, the desired steering angle is calculated using the sideslip integrated-pure pursuit geometry. Simulation results show that the proposed algorithm significantly reduced the tracking error compared to the classical pure pursuit at a maximum 70 km/h speed. Also, the proposed method outperformed existing improved pure pursuits. © 2023 ICROS.

关键词： Autonomous vehicles

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Goal-Oriented Semantic Communication for Wireless Video Transmission via Generative AI

arXiv

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arXiv 2025年

作者： Li, Nan Deng, Yansha Niyato, Dusit Department of Engineering King’s College London strand LondonWC2R 2LS United Kingdom School of Computer Science and Engineering Nanyang Technological University Singapore

Efficient video transmission is essential for seamless communication and collaboration within the visually-driven digital landscape. To achieve low latency and high-quality video transmission over a bandwidth-constrained noisy wireless channel, we propose a stable diffusion (SD)-based goal-oriented semantic communication (GSC) framework. In this framework, we first design a semantic encoder that effectively identify the keyframes from video and extract the relevant semantic information (SI) to reduce the transmission data size. We then develop a semantic decoder to reconstruct the keyframes from the received SI and further generate the full video from the reconstructed keyframes using frame interpolation to ensure high-quality reconstruction. Recognizing the impact of wireless channel noise on SI transmission, we also propose an SD-based denoiser for GSC (SD-GSC) condition on an instantaneous channel gain to remove the channel noise from the received noisy SI under a known channel. For scenarios with an unknown channel, we further propose a parallel SD denoiser for GSC (PSD-GSC) to jointly learn the distribution of channel gains and denoise the received SI. It is shown that, with the known channel, our proposed SD-GSC outperforms state-of-the-art ADJSCC, Latent-Diff DNSC, DeepWiVe and DVST, improving Peak Signal-to-Noise Ratio (PSNR) by 69%, 58%, 33% and 38%, reducing mean squared error (MSE) by 52%, 50%, 41% and 45%, and reducing Fréchet Video Distance (FVD) by 38%, 32%, 22% and 24%, respectively. With the unknown channel, our PSD-GSC achieves a 17% improvement in PSNR, a 29% reduction in MSE, and a 19% reduction in FVD compared to MMSE equalizer-enhanced SD-GSC. These significant performance improvements demonstrate the robustness and superiority of our proposed methods in enhancing video transmission quality and efficiency under various channel conditions. Copyright © 2025, The Authors. All rights reserved.

关键词： Television transmission

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Portable comprehensive two-dimensional microgas chromatography using an integrated flowrestricted pneumatic modulator

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Microsystems & Nanoengineering 2022年第6期8卷 61-72页

作者： Xiaheng Huang Maxwell Wei-hao Li Wenzhe Zang Xiaolu Huang Anjali Devi Sivakumar Ruchi Sharma Xudong Fan Department of Biomedical Engineering University of MichiganAnn ArborMI 48109USA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA Center for Wireless Integrated MicroSensing and Systems(WIMS2) University of MichiganAnn ArborMI 48109USA Max Harry Weil Institute for Critical Care Research and InnovationUniversity of Michigan Ann ArborMI 48109USA

Two-dimensional(2D)gas chromatography(GC)provides enhanced vapor separation capabilities in contrast to conventional one-dimensional GC and is useful for the analysis of highly complex chemical *** developed a microfabricated flow-restricted pneumatic modulator(FRPM)for portable comprehensive 2D micro-GC(μGC),which enables rapid ^(2)D injection and separation without compromising the ^(1)D separation speed and eluent peak profiles.^(2)D injection characteristics such as injection peak width and peak height were fully characterized by using flow-through micro-photoionization detectors(μPIDs)at the FRPM inlet and outlet.A ^(2)D injection peak width of~25 ms could be achieved with a ^(2)D/^(1)D flow rate ratio over *** FRPM was further integrated with a 0.5-m long ^(2)D μcolumn on the same chip,and its performance was ***,we developed an automated portable comprehensive 2D μGC consisting of a 10m OV-11D μcolumn,an integrated FRPM with a built-in 0.5m polyethylene glycol ^(2)D μcolumn,and two μ*** separation of 40 volatile organic compounds in~5 min was demonstrated.A hybrid 2D contour plot was constructed by using both ^(1)D and ^(2)D chromatograms obtained with the two μPIDs at the end of the ^(1)D and ^(2)D μcolumns,which was enabled by the presence of the flow resistor in the FRPM.

关键词： flow restricted comprehensive

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Dynamics of Moral Behavior in Heterogeneous Populations of Learning Agents

arXiv

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arXiv 2024年

作者： Tennant, Elizaveta Hailes, Stephen Musolesi, Mirco Department of Computer Science University College London Gower Street LondonWC1E 6BT United Kingdom Department of Computer Science and Engineering University of Bologna Viale del Risorgimento 2 Bologna40133 Italy

Growing concerns about safety and alignment of AI systems highlight the importance of embedding moral capabilities in artificial agents: a promising solution is the use of learning from experience, i.e., Reinforcement Learning. In multi-agent (social) environments, complex population-level phenomena may emerge from interactions between individual learning agents. Many of the existing studies rely on simulated social dilemma environments to study the interactions of independent learning agents;however, they tend to ignore the moral heterogeneity that is likely to be present in societies of agents in practice. For example, at different points in time a single learning agent may face opponents who are consequentialist (i.e., focused on maximizing outcomes over time), norm-based (i.e., conforming to specific norms), or virtue-based (i.e., considering a combination of different virtues). The extent to which agents’ co-development may be impacted by such moral heterogeneity in populations is not well understood. In this paper, we present a study of the learning dynamics of morally heterogeneous populations interacting in a social dilemma setting. Using an Iterated Prisoner’s Dilemma environment with a partner selection mechanism, we investigate the extent to which the prevalence of diverse moral agents in populations affects individual agents’ learning behaviors and emergent population-level outcomes. We observe several types of non-trivial interactions between pro-social and anti-social agents, and find that certain types of moral agents are able to steer selfish agents towards more cooperative behavior. © 2024, CC BY-NC-ND.

关键词： Adversarial machine learning

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Toward Energy Efficient Multiuser IRS-Assisted URLLC Systems: A Novel Rank Relaxation Method

Toward Energy Efficient Multiuser IRS-Assisted URLLC Systems...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Jalali, Jalal Lemic, Filip Tabassum, Hina Berkvens, Rafael Famaey, Jeroen University of Antwerp - Imec IDLab Sint-Pietersvliet 7 Antwerp2000 Belgium i2Cat Foundation AI-Driven Systems Lab Barcelona Spain York University Department of Electrical Engineering and Computer Science TorontoON Canada

ISBN: (纸本)9798350370218

This paper proposes an energy efficient resource allocation design algorithm for an intelligent reflecting surface (IRS)-assisted downlink ultra-reliable low-latency communication (URLLC) network. This setup features a multi-antenna base station (BS) transmitting data traffic to a group of URLLC users with short packet lengths. We maximize the total network's energy efficiency (EE) through the optimization of active beamformers at the BS and passive beamformers (a.k.a, phase shifts) at the IRS. The main non-convex problem is divided into two sub-problems. An alternating optimization (AO) approach is then used to solve the problem. Through the use of the successive convex approximation (SCA) with a novel iterative rank relaxation method, we construct a concave-convex objective function for each sub-problem. The first sub-problem is a fractional program that is solved using the Dinkelbach method and a penalty-based approach. The second sub-problem is then solved based on semi-definite programming (SDP) and the penalty-based approach. The iterative solution gradually approaches the rank-one for both the active beamforming and unit modulus IRS phase-shift sub-problems. Our results demonstrate the efficacy of the proposed solution compared to existing benchmarks. © 2023 IEEE.

关键词： Alternating optimization (AO) intelligent re-flecting surface (IRS) semi-definite programming (SDP) ultra-reliable low-latency communication (URLLC)

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