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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Yoshimi, Sho Ikegami, Yuka Negishi, Ryotaro Hisafuru, Kota Togawa, Nozomu Department of Computer Science and Communications Engineering Waseda University Japan

ISBN: (纸本)9798331521165

During the design and manufacturing stages of IoT devices, there is a risk of Hardware Trojans (HTs) being inserted into circuits due to the intervention of outside companies. One method for effectively detecting HTs from gate-level netlists is to use an ensemble learning model. In this paper, we use four ensemble learning models: Random Forest, XGBoost, LightGBM, and CatBoost, and evaluate the accuracy of HT detection by adding a new Trojan circuit generated using an automatic HT generation framework as a netlist for training and evaluation. We also use SMOTE, ADASYN, and Borderline-SMOTE as oversampling methods used in training, and evaluate the HT detection accuracy when the hyperparameters of each method are optimized. © 2025 IEEE.

关键词： ensemble learning gate-level netlist hardware Trojan machine learning

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Effectiveness of Consumer-Grade EEG Devices in Brainwaves Signal Processing: A Review

Effectiveness of Consumer-Grade EEG Devices in Brainwaves Si...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Pigtain, Rhou Ian A. Oppus, Carlos M. Agustin, Luisito L. Legarda, Jon M. Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines Deusto Institute of Technology Univesidad de Deusto Bilbao Spain

ISBN: (纸本)9798350350821

Electroencephalography (EEG) is a versatile tool for neuroscience research and medical applications. While high-end research-grade EEG devices offer superior accuracy and performance, they can be costly and complex. This study evaluates the suitability of consumer-grade EEG devices for brainwave signal processing tasks. Two popular consumer-grade EEG devices, the Emotiv Epoc X and the NeuroSky Mindwave Mobile, were compared. Their performance was assessed in three recognition tasks: concentration, relaxation, and eye blink. The Emotiv Epoc X consistently outperformed the NeuroSky Mindwave Mobile in all tasks. Notably, the Epoc X achieved a recognition accuracy of over 75 percent for eye blinks, while the Mindwave Mobile fell below 50 percent. These findings suggest that the Emotiv Epoc X is a more promising option for brainwave signal processing in research and medical applications. While consumer-grade devices may not always match the performance of research-grade equipment, they offer a more accessible and cost-effective alternative for certain applications. © 2024 IEEE.

关键词： Electroencephalography

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Shifting Reward Assignment for Learning Coordinated Behavior in Time-Limited Ordered Tasks 20th

Shifting Reward Assignment for Learning Coordinated Behavio...

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20th International Conference on Practical Applications of Agents and Multi-Agent Systems , PAAMS 2022

作者： Oguni, Yoshihiro Miyashita, Yuki Sugawara, Toshiharu Department of Computer Science and Communications Engineering Waseda University Tokyo1698555 Japan

ISBN: (纸本)9783031181917

We propose a variable reward scheme in decentralized multi-agent deep reinforcement learning for a sequential task consisting of a number of subtasks which can be completed when all subtasks are executed in a certain order before a deadline by agents with different capabilities. Developments in computer science and robotics are drawing attention to multi-agent systems for complex tasks. However, coordinated behavior among agents requires sophistication and is highly dependent on the structures of tasks and environments;thus, it is preferable to individually learn appropriate coordination depending on specific tasks. This study focuses on the learning of a sequential task by cooperative agents from a practical perspective. In such tasks, agents must learn both efficiency for their own subtasks and coordinated behavior for other agents because the former provides more chances for the subsequent agents to learn, while the latter facilitates the execution of subsequent subtasks. Our proposed reward scheme enables agents to learn these behaviors in a balanced manner. We then experimentally show that agents in the proposed reward scheme can achieve more efficient task execution compared to baseline methods based on static reward schemes. We also analyzed the learned coordinated behavior to see the reasons of efficiency. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Efficiency

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A Three-Stage-Concatenated Non-Linear MMSE Interference Rejection Combining Aided MIMO-OFDM Receiver and its EXIT-Chart Analysis

IEEE Open Journal of Vehicular Technology

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IEEE Open Journal of Vehicular Technology 2024年 5卷 507-522页

作者： Chen, Jue Lu, Siyao Wang, Tsang-Yi Wu, Jwo-Yuh Li, Chih-Peng Ng, Soon Xin Maunder, Robert G. Hanzo, Lajos University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan National Science and Technology Council Department of Engineering and Technologies Taipei106214 Taiwan

The demodulation reference signal of the 5G Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) waveform has been designed for supporting Minimum Mean-Square Error-Interference Rejection Combining (MMSE-IRC) equalization, which has become the state-of-the-art, owing to its enhanced performance in the case of dense frequency reuse, which is typical in 5G. By contrast, in the 4G LTE system, typically turbo equalization techniques were used. The family of Non-Linear receiver techniques tend to be eminently suitable for tough rank-deficient scenarios, when the received signal constellation becomes linearly non-separable. Hence, we propose a novel receiver for interference-constrained MIMO-OFDM systems, relying on a linear MMSE-IRC detector intrinsically amalgamated with an additional NL equalizer. In this way, we may achieve the best of both worlds, retaining the interference rejection capability of the MMSE-IRC detector and the superior performance of the NL equalizer. Our solution circumvents the potential failure of the MMSE-IRC, when the MIMO channels' degree freedom is completely exhausted by the desired users in case the transmitter has a high number of transmission layers for example. Based on this concept, we then design a novel NL equalizer relying on the Smart Ordering and Candidate Adding (SOCA) algorithm. This reduced complexity NL detection algorithm is particularly well suited for practical hardware implementation using parallel processing at a low latency. Briefly, the proposed scheme employs the MMSE-IRC detector for mitigating the interference. It makes the first estimate of the desired user signals and then uses the SOCA detector for further decontaminating the received signals. It also generates the soft information, enabling turbo equalization, wherein iterative detector and decoder iteratively exchange their soft information. We present BLock Error Rate (BLER) results, which show that the proposed scheme can always

关键词： Mean square error

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Deadlock-Free Method for Multi-Agent Pickup and Delivery Problem Using Priority Inheritance with Temporary Priority 26

Deadlock-Free Method for Multi-Agent Pickup and Delivery Pro...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2022

作者： Fujitani, Yukita Yamauchi, Tomoki Miyashita, Yuki Sugawara, Toshiharu Department of Computer Science and Communications Engineering Waseda University Tokyo1698555 Japan

This paper proposes a control method for the multi-agent pickup and delivery problem (MAPD problem) by extending the priority inheritance with backtracking (PIBT) method to make it applicable to more general environments. PIBT is an effective algorithm that introduces a priority to each agent, and at each timestep, the agents, in descending order of priority, decide their next neighboring locations in the next timestep through communications only with the local agents. Unfortunately, PIBT is only applicable to environments that are modeled as a bi-connected area, and if it contains dead-ends, such as tree-shaped paths, PIBT may cause deadlocks. However, in the real-world environment, there are many dead-end paths to locations such as the shelves where materials are stored as well as loading/unloading locations to transportation trucks. Our proposed method enables MAPD tasks to be performed in environments with some tree-shaped paths without deadlock while preserving the PIBT feature;it does this by allowing the agents to have temporary priorities and restricting agents' movements in the trees. First, we demonstrate that agents can always reach their delivery location without deadlock. Our experiments indicate that the proposed method is very efficient, even in environments where PIBT is not applicable, by comparing them with those obtained using the well-known token passing method as a baseline. © 2022 The Authors. Published by Elsevier B.V.

关键词： Multi agent systems

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Fault-Tolerant FPGA-Based System for Mitigating SEUs in Configuration and User Bits

Fault-Tolerant FPGA-Based System for Mitigating SEUs in Conf...

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2024 International Conference on Microelectronics, ICM 2024

作者： Amer, O.T. Alkady, G.I. Mohamed, F.Y. Mahmoud, A.W. Amer, H.H. Daoud, R.M. Cairo University Communication & Computer Eng. Dep. Faculty of Engineering Cairo Egypt American University in Cairo Electronics & Communications Engineering Department Sead Group Cairo Egypt

ISBN: (纸本)9798350379396

This paper addresses two issues. First, in the context of factory automation, a low-cost fault-tolerant sensor system is proposed along with its FPGA-based voter. Second, the voter itself is designed to recover from failures affecting its own circuitry. The sensor system consists of one high-quality sensor used for measurement along with two functionally identical, but lower cost sensors used for monitoring purposes. A biased voter circuit is designed and implemented on the same Field Programmable Gate Array (FPGA) used to house the controller. It is shown that the voter can detect and recover from Single Event Upsets (SEUs) which often occur in the harsh factory environments. Both FPGA configuration and user bits are protected. It was shown that the proposed design requires less resources and power than some other designs presented in the literature. Focusing next on recovering from SEUs in both user and configuration FPGA bits, another use case is investigated, namely an I2C master;it is shown that the proposed design again requires less resources than some other commonly used techniques. Both proposed designs were implemented on the Xilinx Zynq-7000 (xc7z020clg400-1). © 2024 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Evaluation of Ensemble Learning Models for Hardware-Trojan Identification at Gate-level Netlists

Evaluation of Ensemble Learning Models for Hardware-Trojan I...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Ryotaro Negishi Nozomu Togawa Department of Computer Science and Communications Engineering Waseda University

IoT (Internet-of-Things) devices are tremendously widespread in our daily lives and these devices are very often outsourced to third-party companies to save cost. However, it is pointed out that the risk to insert malicious circuitry, called hardware Trojans (HTs), much increases there. The methods using machine learning for detecting HTs at gate-level netlists have been proposed, and those based on ensemble learning models are considered the most effective among them. This paper evaluates the performance of HT detection at gate-level netlists using various machine learning models based on ensemble learning, including random forest, XGBoost, LightGBM, and CatBoost. In particular, we optimize HT features for each machine-learning model and perform HT detection for various gate-level netlists, including intellectual property core netlists. The detailed HT detection results are thoroughly summarized and compared.

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Publication performance and trends in virtual reality research in education fields: a bibliometric analysis

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Multimedia Tools and Applications 2025年第10期84卷 6999-7026页

作者： Elaish, Monther M. Yadegaridehkordi, Elaheh Ho, Yuh-Shan Computer Science Department Information Technology Faculty University of Benghazi Benghazi Libya College of Information and Communications Technology School of Engineering and Technology CQUniversity Sydney Australia Trend Research Centre Asia University No. 500 Lioufeng Road Taichung41354 Taiwan

Virtual Reality (VR) technology has the potential to enhance education by providing immersive and engaging learning experiences that can improve teaching and learning outcomes. While there is a growing interest in utilizing VR in education settings, further research is needed to understand its pedagogical effectiveness and address associated considerations and challenges. This bibliometric study comprehensively analyzes 1,157 relevant articles from the Social Science Citation Index (SSCI) and the Science Citation Index Expanded (SCI-EPANDED) to gain insights into the current state of VR integration in education. The analysis revealed variation in VR adoption and research output across countries and institutions, underscoring the importance of collaboration and knowledge-sharing in the field. Key research areas and trends, such as the use of VR for skill development and training, were identified. Additionally, the study highlighted the need for more research on the pedagogical effectiveness of VR. The findings carry practical implications for guiding future research shaping policy decisions and advocating for a concerted effort to harness VR’s capabilities in education. This study serves as a practical roadmap, promoting the implementation and improvement of VR technology and fostering equitable and inclusive educational practices. © The Author(s) 2024.

关键词： Virtual reality

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Task Placement and Resource Allocation for Edge Machine Learning: A GNN-Based Multi-Agent Reinforcement Learning Paradigm

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IEEE Transactions on Parallel and Distributed Systems 2023年第12期34卷 3073-3089页

作者： Li, Yihong Zhang, Xiaoxi Zeng, Tianyu Duan, Jingpu Wu, Chuan Wu, Di Chen, Xu Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Peng Cheng Laboratory Department of Communications Shenzhen518066 China Southern University of Science and Technology Institute of Future Networks Shenzhen518055 China University of Hong Kong Department of Computer Science Hong Kong Hong Kong

Machine learning (ML) tasks are one of the major workloads in today's edge computing networks. Existing edge-cloud schedulers allocate the requested amounts of resources to each task, falling short of best utilizing the limited edge resources for ML tasks. This paper proposes TapFinger, a distributed scheduler for edge clusters that minimizes the total completion time of ML tasks through co-optimizing task placement and fine-grained multi-resource allocation. To learn the tasks' uncertain resource sensitivity and enable distributed scheduling, we adopt multi-agent reinforcement learning (MARL) and propose several techniques to make it efficient, including a heterogeneous graph attention network as the MARL backbone, a tailored task selection phase in the actor network, and the integration of Bayes' theorem and masking schemes. We first implement a single-task scheduling version, which schedules at most one task each time. Then we generalize to the multi-task scheduling case, in which a sequence of tasks is scheduled simultaneously. Our design can mitigate the expanded decision space and yield fast convergence to optimal scheduling solutions. Extensive experiments using synthetic and test-bed ML task traces show that TapFinger can achieve up to 54.9% reduction in the average task completion time and improve resource efficiency as compared to state-of-the-art schedulers. © 1990-2012 IEEE.

关键词： Reinforcement learning

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Meander-Line Slots Based Miniaturized Inset-Fed Patch-Sensor Antenna for Water Characterization Technique 13

Meander-Line Slots Based Miniaturized Inset-Fed Patch-Sensor...

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13th IEEE International Conference on System engineering and Technology, ICSET 2023

作者： Hadi, Aya Khalid Mosleh, Mahmood Farhan Azeez, Adham R. Abd-Alhameed, Raed A. University of Middle Technique Department of Computer Techniques Engineering Baghdad Iraq University of Information Technology and Communications Department of Media Technology and Communications Engineering College of Engineering Baghdad Iraq University of Bradford Faculty of Engineering and Informatics Bradford United Kingdom

ISBN: (纸本)9798350340891

This article presents a miniaturized size Microstrip-patch sensor structure based on meander-line slot for water-quality and salinity measurement applications. The HFSS-software tool is employed to design and simulate the proposed sensor. The proposed sensor is printed on 60× 50× 1mm3 a dielectric material of FR-4 type. The meander-line slot resonator is inserted in the patch-sensor for miniaturize with the sensitivity enhancement. In order to contain the water sample that wants to be tested, a receptacle with dimensions of 47.75× 50× 4mm3 is mounted on the sensor structure. The receptacle is made from PTFE-Teflon dielectric material. The miniaturize sensor is noticed resonant at 2.74 GHz for unloaded-state. Furthermore, it's found resonant at;2.44 GHz, 2.49 GHz, and 2.5 GHz for DI-water, fresh-water and sea-water respectfully. The miniaturized-sensor is showed good sensing values that equals to 0.901 for DI-water, 0.751 for fresh-water, and 0.721 for Sea-water. Finally, a good agreement is showed between the measurement results and those from simulation. © 2023 IEEE.

关键词： Dielectric materials

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