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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Xu, Jiahua Xie, Ningyi Lee, Xinwei Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng University of Tsukuba Graduate School of Science and Technology Japan Singapore Management University School of Computing and Information Systems Singapore University of Aizu Graduate School of Computer Science and Engineering Japan University of Aizu School of Computer Science and Engineering Japan University of Tsukuba Faculty of Engineering Information and Systems Japan

ISBN: (纸本)9798331530471

The research on Variational Quantum Algorithms (VQAs) has gained significant momentum because of their promising practicality in the noisy intermediate-scale quantum (NISQ) era. Recent studies highlight the potential of VQAs in reinforcement learning (RL) by replacing classical components with parameterized quantum circuits (PQCs). Building on this, we propose a quantum Q-learning model for the Capacitated Vehicle Routing Problem (CVRP), combining a PQC with an RL training process. We present a PQC for embedding both static and dynamic states in RL environments. The proposed PQC approximates the Q-value function by using the expectation values of different observables. Experimental results demonstrate that the proposed PQC outperforms the existing PQC for the CVRP with fewer quantum resources. Furthermore, our method shows competitive performance compared to the classical counterpart. © 2024 IEEE.

关键词： Vehicle routing

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QoE Comparison between Multi-User OFDMA and Reliable Groupcast for Wireless LAN Audiovisual Transmission

QoE Comparison between Multi-User OFDMA and Reliable Groupca...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Deguchi, Daiki Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350364866

This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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MPEG-DASH Multi-View Video and Audio Transmission QoE Over HTTP/2 Stream

MPEG-DASH Multi-View Video and Audio Transmission QoE Over H...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Wakayama, Yamato Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350353983

In this paper, we consider multi-view video and audio streaming using MPEG-DASH, which enables to transmit video tailored to the network conditions over HTTP communication. This paper uses HTTP/2 instead of HTTP/1.1, which the authors previously used. HTTP/2 manages a series of request-response exchanges called a stream, which is assigned a unique stream ID. We perform a subjective experiment under various network conditions to evaluate application-level QoS and QoE. From the evaluation results, we investigate the effect of the HTTP/2 stream on the video and audio quality of the users in the multi-view video transmission scenario. © 2024 IEEE.

关键词： Audio streaming

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Educational Data Analysis using Generative AI

Educational Data Analysis using Generative AI

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2024 Joint of International Conference on Learning Analytics and Knowledge Workshops, LAK-WS 2024

作者： Berr, Abdul Leelaluk, Sukrit Tang, Cheng Chen, Li Okubo, Fumiya Shimada, Atsushi Department of Electrical Engineering and Computer Science Kyushu University Japan Graduate School of Information Science and Electrical Engineering Kyushu University Japan

With the advent of generative artificial intelligence (AI), the scope of data analysis, prediction of performances, real-time feedback, etc. in learning analytics has widened. The purpose of this study is to explore the possibility of using generative AI to analyze educational data. Moreover, the performances of two large language models (LLMs): GPT-4 and text-davinci-003, are compared with respect to different types of analyses. Additionally, a framework, LangChain, is integrated with the LLM in order to achieve deeper insights into the analysis, which can be beneficial for beginner data scientists. LangChain has a component called an agent, which can help study the analysis being performed step-by-step. Furthermore, the impact of the OpenLA library, which pre-processes the data by calculating the number of reading seconds of students, counting the number of operations performed by students, and making page-wise behavior of each student, is also studied. Besides, factors with the most significant impact on students’ performances were also discovered in this analysis. The results show that GPT-4, when using the data pre-processed by OpenLA, provides the best analysis in terms of both, the accuracy of the final answer, and the step-by-step insights provided by LangChain’s agent. Also, we learn the significance of reading time and interactions used (Add marker, bookmark, memo) by students in predicting grades. © 2024 CEUR-WS. All rights reserved.

关键词： Students

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Physical Layer Security for CR-NOMA Network with Cooperative Jamming

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Tsinghua science and Technology 2025年第2期30卷 708-720页

作者： Meiling Li Peng Xue Hu Yuan Yuxing Han School of Electronics Information Engineering Taiyuan University of Science and TechnologyTaiyuan 030024China School of Computer Science and Mathematics Kingston UniversityLondonKT12EEUK Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China

Cooperative jamming can effectively combat eavesdropping in physical layer security communication without affecting the legal receiver and improve the security performance of the *** paper introduces cooperative jamming to cognitive radio(CR)networks with non-orthogonal multiple access(NOMA)*** secure performance of the considered CR and NOMA(CR-NOMA)network is evaluated using two modes:non-cooperative jamming and cooperative *** particular,the secrecy outage probabilities(SOPs)of the primary user(PU)in the two modes are derived under Rician fading channels,based on which,the influences of the transmission signal-to-noise ratio(SNR)of secondary users(SUs),the number of SUs,the secrecy rate,and the power allocation coefficient on the SOPs of PU are analyzed *** analysis and simulation results show that cooperative jamming effectively prevents eavesdropping behaviour,which reduces the SOP of PU compared to non-cooperative *** also show that the transmission SNR,the number of SUs,the secrecy rate,and the power distribution coefficients greatly influence performance improvement.

关键词： cognitive radio non-orthogonal multiple access physical layer security cooperative jamming

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CBAR-UNet: A novel methodology for segmentation of cardiac magnetic resonance images using block attention-based deep residual neural network

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Multimedia Tools and Applications 2024年第37期83卷 85047-85063页

作者： Kumar, Rakesh Gupta, Meenu Agarwal, Aman Nayyar, Anand Department of Computer Science and Engineering Chandigarh University Punjab140413 India Graduate School Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

computer-aided Medical Image Segmentation (MIS) plays a leading role in diagnosing diseases automatically. MIS is used extensively in diagnosing medical ailments to obtain clinically relevant information of the shapes and volumes of the target organs and tissues. In order to facilitate accurate segmentation, a Block Attention Based Deep Residual Neural Network, i.e., CBAR-UNet model, is proposed to perform cardiac image segmentation on short axis Magnetic Resonance Images (MRI) stacks from top to bottom slice. The Automated Cardiac Diagnosis Challenge (ACDC) dataset is used in the proposed work, which comprise of a 3D MRI of 100 patients (i.e., 200 MRI stacks). Further, 3D MRIs are converted into 2D by slicing each image to train the model, and Contrast Limited Adaptive Histogram Equalization (CLAHE) is performed on the 2D dataset. Residual connections are introduced that aid in training deeper models. Convolutional Block Attention Module (CBAM) is also added in the proposed network, which consists of Spatial and Channel attention that enhances the spatial and channel-wise features in the image by providing information like ‘what’ and ‘where’ to pay attention respectively. To test and validate the proposed methodology, extensive experimentations were conducted and it was observed that proposed image segmentation model delivers better results by 2.47% when compared to both 2D and 3D State-Of-The-Art (SOTA) methods with a Dice Score of 0.9428. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image segmentation

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Image Recognition and Geographic information Based Pest Management Planning Support System for Coreopsis Lanceolata 12

Image Recognition and Geographic Information Based Pest Mana...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Sato, Toshiyuki Toyoshima, Kyohei Yukawa, Chihiro Asada, Sora Yamashita, Yuma Oda, Tetsuya Department of Information and Computer Engineering Okayama Japan Graduate School of Engineering Okayama Japan Graduate School of Science and Engineering Okayama Japan

ISBN: (纸本)9798350340181

The Coreopsis Lanceolata, a designated invasive foreign species is inhabiting a wide range of areas in Japan. Therefore, it is necessary to map its distribution for pest management planning. On the other hand, a camera and Global Navigation Satellite System (GNSS) can be mounted on the vehicle to obtain video and geographic information around the vehicle. In this paper, we propose a pest management planning support system for the Coreopsis Lanceolata based on image recognition and geographic information. © 2023 IEEE.

关键词： Image recognition

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Design of an Animal Types and Movement Based Pest Animal Repellent System 12

Design of an Animal Types and Movement Based Pest Animal Rep...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Asada, Sora Tabuchi, Kei Toyoshima, Kyohei Nagai, Yuki Yukawa, Chihiro Oda, Tetsuya Graduate School of Science and Engineering Okayama Japan Graduate School of Engineering Okayama Japan Department of Information and Computer Engineering Okayama Japan

ISBN: (纸本)9798350340181

In Japan, it is a need for countermeasures against animal damage caused by pests animals, such as deer and boars. Therefore, there are pest animals repellent by stimulation of sound containing ultrasonic frequency ranges. However, the problem is that if pest animals are listening to repellent sounds continuously, the effect is lower than before. On the other hand, it is possible to prevent pest animals from becoming resistant to repellent sounds by listening to sound stimuli only to the pest movement. In this paper, we develop a pest animal avoidance system that adapts to the pest animal situation and generates vermin avoidance sounds by classifying vermin based on object recognition and estimating their eating behavior based on posture estimation. © 2023 IEEE.

关键词： Animals

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A Neural Computing-Based Access Control Protocol for AI-Driven Intelligent Flying Vehicles in Industry 5.0-Assisted Consumer Electronics

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 3573-3581页

作者： Mahmood, Khalid Tariq, Tayyaba Sangaiah, Arun Kumar Ghaffar, Zahid Saleem, Muhammad Asad Shamshad, Salman National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology International Graduate School of AI Douliu64002 Taiwan Lebanese American University Department of Electrical and Computer Engineering Byblos1102 2801 Lebanon University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China The University of Lahore Department of Software Engineering Lahore54590 Pakistan

The continuous revolution in Artificial Intelligence (AI) has played a significant role in the development of key consumer applications, including Industry 5.0, autonomous decision-making, fault diagnosis, etc. In practice, autonomous and intelligent robots and flying vehicles (i.e., drones) are also becoming the integral part of Industry 5.0. These vehicles are attaining significant importance nowadays because of their applications in consumer electronics. However, there may be numerous privacy issues in such an infrastructure. Nevertheless, neural computing-driven security solutions have played a significant role in overcoming the security and privacy issues of AI-driven intelligent flying vehicles. Motivated by these facts, this article presents a neural computing-based access control protocol for AI-driven flying vehicles to prevent all possible security threats. A detailed security evaluation of the devised protocol is done formally using the extensively recognized Real-Or-Random (ROR) oracle model. Similarly, the informal security analysis ensures the resistance of our scheme against various potential attacks under the assumptions of CK and DY adversarial models. Moreover, detailed performance scrutiny of the devised protocol with various existing schemes shows the robustness and supremacy of our scheme in terms of computation, communication overhead, and security attributes. © 1975-2011 IEEE.

关键词： Authentication

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A Route Conditions Based Adaptive Route Planning System Considering Yoshii River Floods 12

A Route Conditions Based Adaptive Route Planning System Cons...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Okage, Kenya Asada, Sora Tabuchi, Kei Nagai, Yuki Toyoshima, Kyohei Oda, Tetsuya Department of Information and Computer Engineering Okayama Japan Graduate School of Science and Engineering Okayama Japan Graduate School of Engineering Okayama Japan

ISBN: (纸本)9798350340181

In recent years, floods caused by overflowing rivers by heavy rainfall have caused significant damage as disasters have become more severe. Evacuation during disasters presents challenges, such as delays in evacuation activities with traffic congestion and the difficulty for evacuees to decide the appropriate evacuation route by themselves. Therefore, it is necessary to support the decisions of appropriate evacuation routes for each evacuee, taking into account the evacuation route situation. In this paper, we proposed an evacuation route planning system for river flooding by making evacuation route decisions based on Analytic Hierarchy Process (AHP) from the candidate evacuation routes decided based on Ant Colony Optimisation (ACO). © 2023 IEEE.

关键词： Ant colony optimization

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