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International Conference on Intelligent Transportation

作者： Zhitong He Lingxi Li Department of Electrical and Computer Engineering Transportation and Autonomous Systems Institute (TASI) Indiana University-Purdue University Indianapolis Indianapolis Indiana USA

The number of shared micro-mobility services such as electric scooters (e-scooters) has an increasing trend due to the advantages of high efficiency and low cost in short-range travel in urban areas. However, due to the unique characteristics of moving behavior, it is commonly seen that e-scooters may share the road with other motor vehicles. The lack of protection may lead to severe injury for e-scooter riders. The scenario where an e-scooter crosses an intersection or makes a lane change while interacting with an approaching vehicle was commonly seen in real-life traffic data. Such scenarios are hazardous because the intention and behavior of the e-scooter may vary significantly based on the traffic environment conditions. Furthermore, some other vehicles may occlude the presence of the moving e-scooter, which can result in an unexpected collision. In this paper, we propose a simulation platform to mimic the interactions between vehicles and e-scooters. Several traffic scenarios are studied via qualitative and quantitative analysis. The proposed framework is shown to be valuable and efficient for the general risk analysis for vehicle and e-scooter interactions (VEI).

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Irregular Honeycomb Network: Revolutionizing k-Coverage in Spatial Wireless Sensor Networks

Irregular Honeycomb Network: Revolutionizing k-Coverage in S...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Dakshanya Maddala Habib M. Ammari Department of Electrical Engineering and Computer Science Frank H. Dotterweich College of Engineering Wireless Sensor and Mobile Autonomous Networks (WiSeMAN) Research Lab Texas A&M University-Kingsville Kingsville Texas USA

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Sensor deployment, and in particular coverage, is a fundamental component in the design and development of wireless sensor networks. Achieving coverage (or 1-coverage) in three-dimensional (or spatial) wireless sensor networks (WSNs), which requires that every point in a spatial field of interest (FoI), is an open challenging problem. In particular, the problem of k-coverage in spatial WSNs, where every point in a spatial FoI is k-covered (or covered by at least k sensors at the same time), is even more challenging. In this paper, we investigate the problem of connected k-coverage in spatial WSNs, where a spatial FoI is k-covered while all the sensors participating in this k-coverage process are connected to each other. Our study aims at producing an energy-efficient and optimized protocol, which helps achieve connected k-coverage in spatial WSNs with a minimum number of sensors, thus, extending the network lifespan. Precisely, this study is based on convex polyhedral space fillers that help establish an irregular hexagonal prism tessellation referred to as Irregular Honeycomb Network (IHN), which serves as a medium to achieve k-coverage in spatial WSNs. First, we propose a randomly distributed sensor placement strategy, which is designed to guarantee full k-coverage of a spatial FoI. To this end, we tile a spatial FoI with irregular hexagonal prisms, known as space fillers, which are adjacent to each other without any gaps or overlaps. Second, we exploit this tiling strategy to guarantee k-coverage of a spatial FoI. Then, we compute the spatial sensor density (i.e., number of sensors per unit volume) to k-cover a spatial FoI. Third, we determine the necessary relationship between the sensors’ communication and sensing ranges to ensure network connectivity. We corroborate our analysis with various simulation results.

关键词： Wireless communication Wireless sensor networks Sensor placement Protocols Simulation Stochastic processes Energy efficiency

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Investigating Role of Renewable Resources Including Wind Turbines in Energy Hub by Considering Simultaneous Demand for Electricity, Heating and Cooling

Investigating Role of Renewable Resources Including Wind Tur...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Daryoush Tavangar Rizi Mohammad Hassan Nazari Ali Maleki Seyed Hossein Hosseinian Maryam Fani Gevork B. Gharehpetian Department of Physics and Energy Engineering Amirkabir University of Technology Tehran Iran Smart Control Systems Department Niroo Research Institute (NRI) Tehran Iran School of Electrical Engineering & Computer Science Washington State University Pullman Washington Department of Electrical Engineering Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350361322

ISBN: (纸本)9798350361339

As a crucial component of multi-energy systems (MES), the energy hub significantly enhances their performance and reliability. In the energy system, the utilization of renewable energy sources (RES) can presents a significant optimization problem, capable of substantially reducing environmental pollution and lowering energy costs for users. This paper presents an optimal load dispatch model incorporating a collection of wind turbines, aimed at reducing the overall cost of operating an energy hub. It is also proposes a hub structure based on wind, natural gas, and electricity as a combined heat and power system, utilizing converters and energy storage mechanisms to obtain electricity, thermal, and cooling energy. To accomplish this, two situations are executed in the network, aiming to minimize costs by applying a problem-solving approach to the installation of wind turbines at an energy hub. After implementing energy hub management in the optimal mode, the system’s operating costs are reduced by $16 \%$, demonstrating its advantage.

关键词： Renewable energy sources Costs Electricity Wind turbines Problem-solving Trigeneration Optimization

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Collaborative Perception for Connected and autonomous Driving: Challenges, Possible Solutions and Opportunities

arXiv

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arXiv 2024年

作者： Hu, Senkang Fang, Zhengru Deng, Yiqin Chen, Xianhao Fang, Yuguang The Department of Computer Science City University of Hong Kong Hong Kong The School of Control Science and Engineering Shandong University Jinan China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current autonomous driving systems are mostly based on a single vehicle, which has significant limitations which still poses threats to driving safety. Collaborative perception with connected and autonomous vehicles (CAVs) shows a promising solution to overcoming these limitations. In this article, we first identify the challenges of collaborative perception, such as data sharing asynchrony, data volume, and pose errors. Then, we discuss the possible solutions to address these challenges with various technologies, where the research opportunities are also elaborated. Furthermore, we propose a scheme to deal with communication efficiency and latency problems, which is a channel-aware collaborative perception framework to dynamically adjust the communication graph and minimize latency, thereby improving perception performance while increasing communication efficiency. Finally, we conduct experiments to demonstrate the effectiveness of our proposed scheme. Copyright © 2024, The Authors. All rights reserved.

关键词： autonomous vehicles

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Fusion of Time and Frequency Domain Attributes for the Automated Recognition of Emotion using EEG Recordings 21

Fusion of Time and Frequency Domain Attributes for the Autom...

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21st OITS International Conference on Information Technology, OCIT 2023

作者： Maithri, M. Raghavendra, U. Gudigar, Anjan Sambrama Praharaj, Samir Kumar Manipal Institute of Technology Manipal Academy of Higher Education Department of Mechatronics Manipal576104 India Manipal Institute of Technology Manipal Academy of Higher Education Department of Instrumentation and Control Engineering Manipal576104 India North Carolina State University Department of Electrical and Computer Engineering United States Manipal Academy of Higher Education Kasturba Medical College Manipal Department of Psychiatry Manipal India

ISBN: (纸本)9798350358230

Emotions have a significant impact on a person's behavior. Expression reflects how people perceive events, interactions, and judgment. It is possible to identify emotions and categorize them using several techniques, including electroencephalography (EEG) signals, gestures, facial expressions, speech patterns, etc. However, emotion recognition using physiological signals has gained popularity owing to its authenticity. In this study, 54 attributes were extracted from each EEG channel to gather emotional information. These attributes were then fed to multiple classifiers and the results were compared. The study attained a maximum accuracy of 89.52% for channel T7 - 24 using ensemble bagged tree classifiers. © 2023 IEEE.

关键词： Emotion Recognition

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Federated-Boosting: A Distributed and Dynamic Boosting-Powered Cyber-Attack Detection Scheme for Security and Privacy of Consumer IoT

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IEEE Transactions on Consumer Electronics 2024年

作者： Khan, Izhar Ahmed Pi, Dechang Kamal, Shaharyar Alsuhaibani, Mohammed Alshammari, Bandar Mzel Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China University of Chile Department of Electrical Engineering Chile Qassim University College of Computer Department of Computer Science Buraydah Saudi Arabia Technology Control Company Riyadh Saudi Arabia

Consumer Internet of Things (CIoT) is an emerging technology that took the traditional consumer electronics to next level with smarter devices and higher connectivity. However, the rapid boom of this technology has captured a great deal of hacker's attention in the past decade. Due to resource restricted nature of CIoT devices and limited computational abilities, security professionals are unable to strengthen the security and privacy measures. Since the existing security methods suffers from data imbalance and overfitting issues, this paper proposes a distributed and dynamic weighted boosting method named Federated-Boosting for the accurate and timely detection of cyber-Attacks in CIoT. Specifically, a weighting strategy is designed to overcome the data imbalance issue by dynamically adjusting the weights of weaker class samples. Additionally, a regularized loss function is designed that helps in controlling the overfitting of the model and provide enhance performance and generalization. Finally, a time-based and performance-based dynamic aggregation scheme is designed using distributed training model that keeps the privacy of the CIoT devices intact to the local server. Extensive experiments on two real-world datasets validates the superior performance of Federated-Boosting model against state-of-The-Art detection models. © 1975-2011 IEEE.

关键词： Network intrusion

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Survey of Distributed Algorithms for Resource Allocation over Multi-Agent Systems

arXiv

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arXiv 2024年

作者： Doostmohammadian, Mohammadreza Aghasi, Alireza Pirani, Mohammad Nekouei, Ehsan Zarrabi, Houman Keypour, Reza Rikos, Apostolos I. Johansson, Karl H. Faculty of Mechanical Engineering Semnan University Semnan Iran Department of Electrical Engineering and Computer Science Oregon State University United States Department of Mechanical Engineering University of Ottawa OttawaON Canada City University of Hong Kong China Tehran Iran Faculty of Electrical Engineering Semnan University Semnan Iran Department of Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA United States Division of Decision and Control Systems KTH Royal Institute of Technology Sweden

Resource allocation and scheduling in multi-agent systems present challenges due to complex interactions and decentralization. This survey paper provides a comprehensive analysis of distributed algorithms for addressing the distributed resource allocation (DRA) problem over multi-agent systems. It covers a significant area of research at the intersection of optimization, multiagent systems, and distributed consensus-based computing. The paper begins by presenting a mathematical formulation of the DRA problem, establishing a solid foundation for further exploration. Real-world applications of DRA in various domains are examined to underscore the importance of efficient resource allocation, and relevant distributed optimization formulations are presented. The survey then delves into existing solutions for DRA, encompassing linear, nonlinear, primal-based, and dual-formulation-based approaches. Furthermore, this paper evaluates the features and properties of DRA algorithms, addressing key aspects such as feasibility, convergence rate, and network reliability. The analysis of mathematical foundations, diverse applications, existing solutions, and algorithmic properties contributes to a broader comprehension of the challenges and potential solutions for this domain. © 2024, CC BY.

关键词： Multi agent systems

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Multi-Agent Distributed DQN and Transfer Learning for Energy-Efficient Power Management in Solar Energy-Harvested Small-Cell Networks

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IEEE Internet of Things Journal 2025年第12期12卷 19590-19604页

作者： Cho, Hyebin Kim, Hyungsub Na, JeeHyeon Lim, Seung-Chan Lee, Howon Hankyong National University School of Electrical Electronic and Control Engineering Anseong17579 Korea Republic of Electronics and Telecommunications Research Institute Daejeon34141 Korea Republic of Hankyong National University School of ICT Robotics and Mechanical Engineering and IITC Anseong17579 Korea Republic of Ajou University Department of Electrical and Computer Engineering Suwon16499 Korea Republic of

The integration of solar energy harvesting into small-cell networks is a promising solution for achieving energy-efficient and sustainable wireless communications. However, the inherent variability and intermittency of solar energy, coupled with precise inter-cell interference management, significantly hinder efficient network operation. To resolve these challenges, we propose a multi-agent distributed deep Q-network (MA-DDQN) framework, where the distributed base stations learn the optimal transmit power control policies. To further enhance adaptability under varying solar conditions, we present a daily model transfer with a fine-tuning approach, enabling efficient deployment without extensive training overhead. Simulation results demonstrate that the proposed methods remarkably improve energy efficiency while maintaining robust adaptability under dynamic solar conditions, revealing their potential for sustainable small-cell network deployments. © 2014 IEEE.

关键词： Solar cell efficiency

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A predictive model of death from cerebrovascular diseases in intensive care units

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Intelligent Medicine 2023年第4期3卷 267-279页

作者： Mohammad Karimi Moridani Seyed Kamaledin Setarehdan Ali Motie Nasrabadi Esmaeil Hajinasrollah Department of Biomedical Engineering Faculty of HealthTehran Medical SciencesIslamic Azad UniversityTehranIran Control and Intelligent Processing Centre of Excellence School of Electrical and Computer EngineeringCollege of EngineeringUniversity of TehranTehranIran Departments of Biomedical Engineering Shahed UniversityTehranIran Loghman Medical Center Shahid Beheshti University of Medical SciencesTehranIran

Objective This study aimed to explore the mortality prediction of patients with cerebrovascular diseases inthe intensive care unit(ICU)by examining the important signals during different periods of admission in theICU,which is considered one of the new topics in the medical *** approaches have been proposed forprediction in this *** of these methods has been able to predict mortality somewhat,but many of thesetechniques require recording a large amount of data from the patients,where recording all data is not possiblein most cases;at the same time,this study focused only on heart rate variability(HRV)and systolic and diastolicblood *** The ICU data used for the challenge were extracted from the Multiparameter Intelligent Monitoring inIntensive Care II(MIMIC-II)Clinical *** proposed algorithm was evaluated using data from 88 cerebrovascular ICU patients,48 men and 40 women,during their first 48 hours of ICU *** electrocardiogram(ECG)signals are related to lead II,and the sampling frequency is 125 *** time of admission and time ofdeath are labeled in all *** this study,the mortality prediction in patients with cerebral ischemia is evaluated using the features extracted from the return map generated by the signal of HRV and blood *** the patient’s future condition,the combination of features extracted from the return mapping generatedby the HRV signal,such as angle(𝛼),area(A),and various parameters generated by systolic and diastolic bloodpressure,including DBPMax−Min SBPSD have been ***,to select the best feature combination,the geneticalgorithm(GA)and mutual information(MI)methods were *** sample t-test statistical analysis was usedto compare the results of two episodes(death and non-death episodes).The P-value for detecting the significancelevel was considered less than *** The results indicate that the new approach presented in this paper can be compared with other methodsor l

关键词： Death prediction Cerebrovascular diseases Intensive care unit Heart rate variability Systolic and diastolic blood pressure Return map

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Development of a Modified Dummy Gas Lift Valve for Subsurface Depth-Resolved Microbiological Sampling and 3D Mapping

Development of a Modified Dummy Gas Lift Valve for Subsurfac...

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2024 SPE Water Lifecycle Management Conference and Exhibition, WLMC 2024

作者： McElhinney, J.M.W.R. Gomes, J.S. Hasan, A. Dias, J. BME Department Khalifa University Abu Dhabi United Arab Emirates Centre for Membranes and Advanced Water Technology Arzanah Building Khalifa University SAN Campus Abu Dhabi United Arab Emirates Computer and Electrical Engineering Dept. Khalifa University Abu Dhabi United Arab Emirates KU Center for Autonomous Robotic Systems

ISBN: (纸本)9781959025320

Objectives/Scope: This study outlines the development and use of a modified dummy gas lift valve designed to obtain subsurface microbiological samples from a defined depth series across a production well. An overview of the initial field pilot is presented wherein microbiological data from the modified valve will be contrasted with topside samples to evaluate the information yielded from sampling downhole biofilm communities in place of planktonic populations from the well head. Methods, Procedures, Process: In this approach, the modified dummy gas lift valve, preloaded topside with carbonate plugs and coupons, is deployed at various depths in the well's completion for downhole incubation. This modification allows production fluids to wet the payloads, enabling in situ biofilm colonization by reservoir communities across depth and temperature gradients. Post retrieval using a slickline tool, sample DNA is extracted for metagenomic sequencing, assessing microbial composition and metabolic capabilities (including souring and MIC-related activities). Concurrent production fluid samples from the wellhead will be analyzed for comparison to evaluate any information gained from biofilm over planktonic population sampling. Results, Observations, Conclusions: Samples from the modified valve are expected to provide sufficient yields of DNA, uncontaminated by non-resident microbes from outside of the producer. Microbial data from downhole biofilms is anticipated to provide a more diverse community makeup than production fluid communities sampled at the wellhead, with a corresponding increase in problematic species associated with MIC and souring. Corrosion coupon analyses will enable conclusions regarding proactive decision-making enablement and extrapolations of 3D projections of microbiological communities between modified valves across the completion column will provide the relationship between in situ conditions, microbial colonization in the context of pore space and risk

关键词： Decision making

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