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arXiv 2025年

作者： Hou, Abe Bohan Du, Hongru Wang, Yichen Zhang, Jingyu Wang, Zixiao Liang, Paul Pu Khashabi, Daniel Gardner, Lauren He, Tianxing Department of Computer Science Johns Hopkins University United States Civil & Systems Engineering Johns Hopkins University United States Department of Computer Science University of Chicago United States Department of Epidemiology Harvard University United States MIT Media Lab Department of EECS Massachusetts Institute of Technology United States Institute of Interdisciplinary Information Sciences Tsinghua University China Shanghai Qi Zhi Institute China

Can we simulate a sandbox society with generative agents to model human behavior, thereby reducing the over-reliance on real human trials for assessing public policies? In this work, we investigate the feasibility of simulating health-related decision-making, using vaccine hesitancy, defined as the delay in acceptance or refusal of vaccines despite the availability of vaccination services (MacDonald, 2015), as a case study. To this end, we introduce the VACSIM1 framework with 100 generative agents powered by Large Language Models (LLMs). VACSIM simulates vaccine policy outcomes with the following steps: 1) instantiate a population of agents with demographics based on census data;2) connect the agents via a social network and model vaccine attitudes as a function of social dynamics and disease-related information;3) design and evaluate various public health interventions aimed at mitigating vaccine hesitancy. To align with real-world results, we also introduce simulation warmup and attitude modulation to adjust agents’ attitudes. We propose a series of evaluations to assess the reliability of various LLM simulations. Experiments indicate that models like Llama and Qwen can simulate aspects of human behavior but also highlight real-world alignment challenges, such as inconsistent responses with demographic profiles. This early exploration of LLM-driven simulations is not meant to serve as definitive policy guidance;instead, it serves as a call for action to examine LLM-based social simulation for policy development. Copyright © 2025, The Authors. All rights reserved.

关键词： Population dynamics

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Phase-Based Quantification of Sports Performance Metrics Using a Smart IoT Sensor

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IEEE Internet of Things Journal 2023年第18期10卷 15900-15911页

作者： Chen, Meng Szu, Hui Fang Lin, Hsin Yen Liu, Yifan Chan, Ho-Yin Wang, Yufan Zhao, Yuliang Zhang, Guanglie Yao, Jeffrey Da-Jeng Li, Wen Jung National Tsing Hua University Physical Education Office Hsinchu City300 Taiwan Kla Corporation Tainan City744 Taiwan Michigan State University Department of Electronic and Computer Engineering East LansingMI48824 United States Shanghai Jiao Tong University School of Mechanical Engineering Department of Industrial Engineering and Management Shanghai200240 China Northeastern University at Qinhuangdao Hebei Key Lab. of Micro-Nano Prec. Optical Sensing and Msrmt. Technol. Sch. of Control Engineering Qinhuangdao066004 China City University of Hong Kong Department of Mechanical Engineering Kowloon Tong Hong Kong City University of Hong Kong Shenzhen Research Institute CASŰCityU Joint Laboratory for Robotics Shenzhen518057 China National Tsing Hua University Department of Power Mechanical Engineering Hsinchu City300 Taiwan

Sports performance is often judged based on the results of a series of motions rather than observing and analyzing the detailed sequential motions that lead to the results. Hence, subjective feedback from the coaches is often ineffective in improving player performance. In this work, we custom-built a smart Internet of Things wristband motion sensor to implement data-based sports performance evaluation. A phase-based feature selection method is also proposed to assess the athletes' sequential detailed motion for selected sport activities. To demonstrate the merits of this technology, we quantified the quality of the sequential motions of a specific type of volleyball serve by analyzing 183 samples of motion data obtained from a total of 18 players. The general skill levels (i.e., elite, subelite, and amateur) of the players were identified by machine learning algorithms, with accuracies of up to 95%. Moreover, we adopted biomechanical principles to extract 11 motion-related performance metrics from various phases of the players' serve motion. We identified the distributions of these metrics across different skill levels and found eight key metrics that were highly correlated to the skill level of a players. We suggest that these metric distributions can be used as a reference for providing feedback to the coaches and players, to improve a player's skill in the future. This phased-based analysis method can potentially be applied across many sports to increase the effectiveness of athletes' training. © 2014 IEEE.

关键词： Internet of things

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An EEG-based Intelligent Neuromarketing System for Predicting Consumers’ Choice 4th

An EEG-based Intelligent Neuromarketing System for Predicti...

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International Conference on 4th Industrial Revolution and Beyond, IC4IR 2021

作者： Mashrur, Fazla Rabbi Rahman, Khandoker Mahmudur Miya, Mohammad Tohidul Islam Vaidyanathan, Ravi Anwar, Syed Ferhat Sarker, Farhana Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab Institute of Advanced Research United International University Dhaka Bangladesh School of Business and Economics United International University Dhaka Bangladesh Department of Mechanical Engineering Imperial College London London United Kingdom Institute of Business Administration University of Dhaka Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh

ISBN: (纸本)9789811980312

Marketers use different marketing strategies to elicit the desired response from the target customers. To measure customer engagement, they usually conduct one-on-one interviews, surveys, broad polls, and focus group discussions. However, these are costly and sometimes unreliable. On the other hand, neuromarketing measures customer response to marketing stimuli by measuring the electrical activity of the brain and has the potential to address these drawbacks. which can be overcome by neuromarketing. In this work, we proposed a prediction algorithm that can identify consumer affective attitude (AA) and purchase intention (PI) from EEG signals from the brain. At first, the raw EEG signals are initially preprocessed to remove noise. After that, three features are extracted: time, frequency, and time frequency domain features. Wavelet packet transform is used to separate the EEG bands in time-domain feature extraction. Then, for feature selection, wrapper-based SVM-RFE is utilized. Finally, we use SVM to distinguish the classes in AA and PI. Results show that for SVM with radial basis function kernel performs better to classify positive and negative AA with an accuracy of 90 ± 4.33 and PI with an accuracy of 75 ± 2.5. So, EEG-based neuromarketing solutions can assist companies and organizations in accurately predicting future consumer preferences. As a result, neuromarketing based-solutions have the potential to increase sales by overcoming the constraints of traditional marketing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

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Best Practices for Quantum Error Mitigation with Digital Zero-Noise Extrapolation 4

Best Practices for Quantum Error Mitigation with Digital Zer...

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Majumdar, Ritajit Rivero, Pedro Metz, Friedrike Hasan, Areeq Wang, Derek S. Ibm Quantum Ibm India Research Lab India Ibm Quantum Ibm T. J. Watson Research Center United States Institute of Physics Ecole Polytechnique Fédérale de Lausanne Switzerland Center for Quantum Science and Engineering Ecole Polytechnique Fédérale de Lausanne Switzerland Princeton University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350343236

Digital zero-noise extrapolation (dZNE) has emerged as a common approach for quantum error mitigation (QEM) due to its conceptual simplicity, accessibility, and resource efficiency. In practice, however, properly applying dZNE to extend the computational reach of noisy quantum processors is rife with subtleties. Here, based on literature review and original experiments on noisy simulators and real quantum hardware, we define best practices for QEM with dZNE for each step of the workflow, including noise amplification, execution on the quantum device, extrapolation to the zero-noise limit, and composition with other QEM methods. We anticipate that this effort to establish best practices for dZNE will be extended to other QEM methods, leading to more reproducible and rigorous calculations on noisy quantum hardware. The full version of this paper can be found in Ref. [1]. © 2023 IEEE.

关键词： Extrapolation

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PSMiner: A Pattern-Aware Accelerator for High-Performance Streaming Graph Pattern Mining 23

PSMiner: A Pattern-Aware Accelerator for High-Performance St...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Hao Qi Yu Zhang Ligang He Kang Luo Jun Huang Haoyu Lu Jin Zhao Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China and Zhejiang-HUST Joint Research Center for Graph Processing Zhejiang Lab China Department of Computer Science University of Warwick United Kingdom

ISBN: (纸本)9798350323481

Streaming Graph Pattern Mining (GPM) has been widely used in many application fields. However, the existing streaming GPM solution suffers from many unnecessary explorations and isomorphism tests, while the existing static GPM ones require many repetitive operations to compute the full graph. In this paper, we propose a pattern-aware incremental execution approach and design the first streaming GPM accelerator called PSMiner, which integrates multiple optimizations to reduce redundant computation and improve computing efficiency. We have conducted extensive experiments. The results show that compared with the state-of-the-art software and hardware solutions, PSMiner achieves the average speedups of 770.9× and 60.4×, respectively.

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HexTileConnect: Achieving Connected k-Coverage in Planar Wireless Sensor Networks Using Irregular Hexagonal Tessellation

HexTileConnect: Achieving Connected k-Coverage in Planar Wir...

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Artificial Intelligence & Green Energy (ICAIGE), IEEE International Conference on

作者： Dakshanya Maddala Habib M. Ammari Department of Electrical Engineering and Computer Science WiSeMAN Research Lab Frank H. Dotterweich College of Engineering Texas A&M University-Kingsville Kingsville Texas USA WiSeMAN Research Lab School of Engineering College of Arts and Sciences Texas A&M International University Laredo Texas USA

ISBN: (数字)9798350389838

ISBN: (纸本)9798350389845

In wireless sensor networks (WSNs), achieving network connectivity and sensing coverage (or simply coverage) simultaneously is crucial for ensuring the desired quality of service of the underlying sensing application. The two main functions of sensors in WSNs are sensing and communication, which are assessed using the coverage and connectivity metrics. This study focuses on the problem of connected $\boldsymbol{k}$ -coverage in planar WSNs (PWSNs), denoted by $(\boldsymbol{CC}_{\boldsymbol{k}}\boldsymbol{P})$ , where every point in a planar field of interest (PFoI) is covered by at least $\boldsymbol{k}$ sensors at the same time, with $\boldsymbol{k} \geq\boldsymbol{1}$ , and all the participating sensors are mutually connected. To address this problem, our study follows a series of steps: First, we investigate the sensor placement problem, and compute the required sensor density for $\boldsymbol{k}$ -coverage of a PFoI. Second, we consider tiling a field using planar convex polygonal tiles with no gaps or overlaps, ensuring effective coverage. Third, we identify the necessary relationship between the sensors' communication and sensing ranges to ensure network connectivity. Fourth, we propose an energy-efficient $\boldsymbol{k}$ - coverage protocol using the “best” planar convex polygonal tile. Our goal is to extend the network lifespan while achieving $\boldsymbol{k}$ - coverage of a PFoI with a minimum number of sensors. We support our analysis with simulation results.

关键词： Wireless communication Measurement Wireless sensor networks Sensor placement Protocols Three-dimensional displays Simulation Stochastic processes Quality of service Sensors

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TADAD: Trust AI-based Decentralized Anomaly Detection for Urban Air Mobility Networks at Tactical Edges

TADAD: Trust AI-based Decentralized Anomaly Detection for Ur...

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Integrated Communications, Navigation and Surveillance Conference, ICNS

作者： Sixiao Wei Zhengyang Fan Genshe Chen Erik Blasch Yu Chen Khanh Pham Intelligent Fusion Technology Inc. Germantown MD Air Force Research Laboratory Arlington VA Department of Electrical and Computer Engineering Binghamton University Binghamton Air Force Research Lab NM

ISBN: (数字)9798350393095

ISBN: (纸本)9798350393101

Urban Air Mobility (UAM) networks pose challenges to confidentiality, availability, and integrity within security and safety concerns. Successfully planning and executing today’s complex operations in defense of national interests requires timely, accurate, trusted, and unambiguous communications up, down, and across an extended chain of command spanning multi-national air, ground, sea, and cyber forces. Understanding the underlying reasons for predictions in machine learning (ML)-based spoofing detection is crucial for gaining insights into attack tactics while improving the detection accuracy, and informing mitigation strategies. ML prediction enhances the interpretability, trust, and accountability in unmanned systems security and enables proactive defense measures and informed decision-making. In this paper, we introduce a Trust AI-based Decentralized Anomaly Detection (TADAD) framework to enhance the UAM capability to allow secured data accessing and sharing with low-latency and high explainable reliability among aircraft and Air Traffic Service (ATS) providers or ground stations within dynamic network environments. TADAD extends the existing airborne networks to heterogeneous open networks with advanced and autonomous detection at tactical edges. TADAD utilizes a software-in-the-loop (SITL) simulator to emulate the data communication messages (e.g., MAVLink) among UAVs and generates both benign and attack samples. An ML-based approach is then developed to incorporate explainable artificial intelligence (AI) techniques, specifically Shapley Additive Explanations (SHAP), to analyze why a signal is classified as an anomaly. Our experimental study validates the performance of TADAD in detecting accuracy and explainability against typical cyber-attacks (e.g., GPS spoofing).

关键词： Radio frequency Additives Image edge detection Surveillance Traffic control Boosting Software

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A Decentralized Cooperative Coverage Control for Networked Multiple UAVs Based on Deep Reinforcement Learning

A Decentralized Cooperative Coverage Control for Networked M...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Cheng, Longbo Qu, Guixian Zhou, Jianshan Zhao, Dezong Qu, Kaige Sheng, Zhengguo Zhai, Junda Ren, Chenghao Beihang University State Key Lab of Its Beijing China Research Institute of Aero-Engine Beihang University Beijing China School of James Watt Engineering University of Glasgow Glasgow United Kingdom University of Waterloo Electrical and Computer Engineering Department Waterloo Canada University of Sussex Department of Engineering and Design Brighton United Kingdom China Research and Development Academy of Machinery Equipment Beijing China Zibo Vaucrefly Intel. Tech. Co. Ltd. Zibo China

ISBN: (纸本)9798350316308

Deployment of the unarmed aerial vehicle (UAV) swarm promises increased efficiency and safety of area search coverage. Multiple UAVs must be capable of autonomous collaboration and area search coverage for this. Therefore, we integrate multi-agent reinforcement learning into the cooperative control method of UAV swarm and propose a decentralized cooperative control for networked multiple UAVs technique based on the extended-proximal policy optimization algorithm (EPPO). The proposed approach not only adopts distributed training for multiple agents, but also allows them to obtain some mutual state information, such as position information and searched sub-areas. So, it can significantly speed up training and increase the effectiveness and safety of task completion in real-world applications. After a simulation, the multi-intelligent UAV can rapidly cover 100% of the mission area and ensure more excellent safety. © 2023 IEEE.

关键词： Reinforcement learning

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Impact of Network Factors on QoE-sensitive Virtual Reality Environments: An Experimental Analysis Perspective using VR-based Mindfulness

Impact of Network Factors on QoE-sensitive Virtual Reality E...

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IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Jaime Burbano V Jorge Pillco Sebastian Genovez Patricia Ortega Neuroscience Lab Universidad del Azuay Ecuador Electronics Engineering Research Center Universidad del Azuay Ecuador Department of Computer Science Universidad del Azuay Ecuador

Virtual reality (VR) environments have gained significant attention in therapeutic use cases as a tool for generating controlled and immersive experiences. However, to ensure the effectiveness of the VR application, maintaining a high quality of experience (QoE) is critical. In QoE-sensitive VR environments, even a minor degradation or impairment can significantly impact user presence, engagement, and attention. This study presents an experimental analysis of the influence of network factors on QoE. We conduct the research using a VR-based mindfulness scenario over an 802.11ax network as an example of a QoE-sensitive VR environment, that has been applied to a sample population of 60 individuals. Our results demonstrate that QoE degradation in 2.4 GHz networks is primarily attributed to traffic, while in 5 GHz networks, it is primarily influenced by the signal strength captured by the VR device. These findings, among others, provide valuable insights for guiding the design of VR systems and optimizing network configurations to deliver an enhanced QoE.

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The Extension Principle for Angular Domains and its Application to Spatial Relations

The Extension Principle for Angular Domains and its Applicat...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Brendan Young Derek T. Anderson James M. Keller Fred Petry Chris Michael Electrical Engineering and Computer Science Department University of Missouri Columbia MO USA U.S. Naval Research Lab Stennis Space Center MS USA

ISBN: (数字)9798350319545

ISBN: (纸本)9798350319552

This paper delves into Zadeh's extension principle (EP) for angular domains, particularly in the context of spatial relations. We introduce modifications to the EP, specifically tailored for addressing ambiguities inherent in angular scenarios. The first enhancement employs a vector space to mitigate truth degree variations in operations with input variability. The second modification introduces a user-defined tolerance parameter, enabling the judicious consideration of inputs based on their alignment with existing data. This augmentation facilitates a more adaptive handling of contradictory or uncertain data, enhancing the EP's versatility in real-world scenarios. Through a set of synthetic case studies, we illustrate the efficacy of our extension in the interpretation of spatial relations. Furthermore, a practical example is presented to demonstrate the generation of a prototypical spatial relation. Overall, our proposed modifications provide the groundwork for applying complex operations using fuzzy arithmetic in cyclical, angular domains.

关键词： Vectors Fuzzy systems Arithmetic

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