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Reconfiguration of vertex-disjoint shortest paths on graphs

Journal of Graph Algorithms and Applications 2024年第3期28卷 87-101页

作者： Saito, Rin Eto, Hiroshi Ito, Takehiro Uehara, Ryuhei Graduate School of Information Sciences Tohoku University Sendai Japan School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan School of Information Science Japan Advanced Institute of Science and Technology Nomi Japan

We introduce and study reconfiguration problems for (internally) vertex-disjoint shortest paths: Given two tuples of internally vertex-disjoint shortest paths for fixed terminal pairs in an unweighted graph, we are asked to determine whether one tuple can be transformed into the other by exchanging a single vertex of one shortest path in the tuple at a time, so that all intermediate results remain tuples of internally vertex-disjoint shortest paths. We also study the shortest variant of the problem, that is, we wish to minimize the number of vertex-exchange steps required for such a transformation, if exists. These problems generalize the well-studied Shortest Path Reconfiguration problem. In this paper, we analyze the complexity of these problems from the viewpoint of graph classes, and give some interesting contrast. © 2024, Brown University. All rights reserved.

关键词： Graph theory

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Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification 17th

Spatiotemporal Pooling on Appropriate Topological Maps Repr...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Fukushima, Takuto Miyamoto, Ryusuke Department of Computer Science Graduate School of Science and Technology Meiji University Kawasaki Japan Department of Computer Science School of Science and Technology Meiji University Kawasaki Japan

ISBN: (纸本)9789819609000

Motor imagery classification based on electroencephalography (EEG) signals is one of the most important brain-computer interface applications, although it need further improvement. Several methods have attempted to obtain useful information from EEG signals by using recent deep learning techniques such as transformers. To improve the classification accuracy, this study proposes a novel EEG-based motor imagery classification method with three key features: generation of a topological map represented as a two-dimensional image from EEG signals with coordinate transformation based on t-SNE, use of the InternImage to extract spatial features, and use of spatiotemporal pooling inspired by PoolFormer to exploit spatiotemporal information concealed in a sequence of EEG images. Experimental results using the PhysioNet EEG Motor Movement/Imagery dataset showed that the proposed method achieved the best classification accuracy of 88.57%, 80.69%, and 70.20% on two-, three-, and four-class motor imagery tasks in cross-individual validation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electroencephalography

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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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A deep learning framework for automatic assessment of presence in virtual reality using multimodal behavioral cues

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Neural Computing and Applications 2025年第8期37卷 6283-6303页

作者： Pannattee, Peerawat Shimada, Shogo Yem, Vibol Nishiuchi, Nobuyuki Graduate School of Systems Design Tokyo Metropolitan University Tokyo191-0065 Japan Graduate School of Science and Technology Degree Program in Systems and Information Engineering University of Tsukuba Ibaraki3058573 Japan

Effective development of virtual reality (VR) applications is heavily reliant on the evaluation of user experience (UX). However, traditional methods such as questionnaires have inherent limitations which hinder their ability to capture nuanced behavioral responses and impede the agility of VR content creation: They are time-consuming, burdensome for users, and require significant human effort for interpretation. This study introduces an automated framework aimed at addressing the limitations of questionnaire-based evaluations to assess UX in VR. Our primary focus is to validate the concept of this framework through assessment of the sense of presence (SOP), a crucial psychological perception with significant impact on VR UX. Our proposed framework utilizes a deep neural network (DNN) to analyze patterns in multimodal behavioral cues, including facial expressions, head movements, and hand movements, to predict scores from the Igroup Presence Questionnaire (IPQ). Additionally, we introduce two statistical profiles: the Visual Entropy Profile (VEP), which offers insights into visual complexity by depicting scene entropy, and the Experiential Presence Profile (EPP), which is designed to capture users’ historical SOP levels to enable personalized baseline and sensitivity estimation. The proposed framework achieves a significant correlation between actual and predicted IPQ scores, with a Spearman’s rank correlation coefficient of 0.7303, showcasing the potential of DNNs in analyzing complex behavioral signals and automating SOP assessment. This study represents a pioneering effort in leveraging DNNs for the automatic assessment of SOP and paves the way for future advances in automatically assessing VR UX and unlocking new opportunities in the field. © The Author(s) 2025.

关键词： Virtual environments

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A Blockchain-assisted Authentication Protocol for RFID-enabled Supply Chain Management System

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IEEE Transactions on Network science and Engineering 2025年第4期12卷 3108-3117页

作者： Tariq, Tayyaba Obaidat, Mohammad S. Kuo, Wen-Chung Mahmood, Khalid Ayub, Muhammad Faizan Alenazi, Mohammed J.F National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan The University of Jordan King Abdullah II School of Information Technology Amman11942 Jordan University of Science and Technology Beijing School of Communication and Computing Engineering Beijing100083 China Amity University Amity School of Engineering and Technology Noida201301 India National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Riyadh11451 Saudi Arabia

In the dynamic domain of supply chain management, integrating Radio-Frequency Identification (RFID) technology with blockchain technology represents a significant leap forward. This integration has created a blockchain-assisted RFID-enabled Supply Chain Management System (SCMS). With its ability to utilize electromagnetic fields to identify and track tags attached to objects, RFID technology has revolutionized product management and tracking within supply chains. (SCMS) transmits tracking and product management information through public communication channels. However, (SCMS)'s communication on these channels is vulnerable to various security attacks and privacy challenges. Numerous authentication protocols have recently been proposed to tackle these security and privacy challenges. Unfortunately, most protocols are susceptible to different security attacks, such as tag or reader impersonation, denial of service, physical cloning, desynchronization attacks, etc. Therefore, we have proposed an authentication protocol for an RFID-enabled (SCMS) that also leverages blockchain technology. The integration of blockchain technology ensures data integrity, immutability and transparency across each department involved in (SCMS). In the proposed protocol, we also employ a Physically Unclonable Function (PUF) to secure (SCMS) against physical cloning attacks. We validate the security of the proposed protocol through both informal and formal analysis. The informal analysis confirms that our protocol significantly enhances security and efficiency. Moreover, a performance analysis of the proposed protocol against various competing existing protocols shows its superior performance. Notably, the proposed protocol substantially reduces computational and communication costs by 24.38% and 8.03%, respectively, which underscores its enhanced performance and resource efficiency. © 2013 IEEE.

关键词： Efficiency

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Study of Electrical Characteristics for Dual-Gate TFTs With Asymmetric Defect Distributions and Gate Work Functions

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IEEE Transactions on Electron Devices 2023年第6期70卷 3390-3393页

作者： Hsu, Chih-Chieh Li, Jin-Xian Huang, Po-Cheng Jhang, Wun-Ciang Joodaki, Mojtaba National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Graduate School of Electronic Engineering Yunlin640301 Taiwan Constructor University School of Computer Science and Engineering Bremen28759 Germany

Combined effects of asymmetric defect distributions and asymmetric gate work functions (WFs) on the performances of self-aligned dual-gate poly-Si TFTs are investigated. Normally, small grains with plentiful grain boundaries (GBs) or other structural defects appear at different positions of the poly-Si film, which is dependent on the growth process of the film. Subgap states of acceptor-like tail, acceptor-like deep-level, donor-like tail, and donor-like deep-level states are used to emulate the defects. Two sets of density of states (DOS) are employed. We find that defects at different positions of the source-side and drain-side channels exhibit different influences on TFT performance and the influences are dependent on the WFs of the gates. TFTs with a higher gate WF can have a higher tolerance to the depth of the defect region. Besides the electrical characteristics, the combined effects of defects and gate WFs on current density distributions and electric field distributions in the channel regions are explored. The performance variations caused by the asymmetric defects along with asymmetric gate WFs can be explained. © 1963-2012 IEEE.

关键词： Thin film transistors

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YOLOv5-LSMA: A Detection Algorithm for Deep-sea Plastic Garbage

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第1期9卷 300-312页

作者： Han, Jin Li, Shengxia Liu, Chunhui College of Computer Science and Technology Shandong University of science and technology Qingdao266590 China Graduate School of Fisheries and Environmental Sciences Nagasaki University Nagasaki852-8521 Japan

With the development of industry and the passage of time, the problem of deep-sea garbage has become more and more obvious. To more effectively detect deep-sea garbage, this paper proposes a detection algorithm YOLOv5-LSMA based on YOLOv5 for deep-sea plastic garbage. Firstly, the loss-reduction down-sampling (LRDS) module is proposed to reduce the feature loss in the process of down-sampling in the neck network. Secondly, to improve the detection ability of the deep network, a multi-scale channel attention mechanism (MCAM) module is proposed, and the dilated convolution is introduced to make the deep network have a wider receptive field. Finally, to make full use of the detailed information on shallow features, a simplified bi-directional feature pyramid network (S-BiFPN) structure is constructed based on the simplification and improvement of the BiFPN structure. According to the experimental results, the detection precision of the YOLOv5-LSMA algorithm proposed in this paper is 4.7% higher than that of YOLOv5 algorithm, and the model detection capability is effectively improved. It provides an effective algorithm for the identification of deep-sea plastic garbage. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Bismuth compounds

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Advanced Aerial Medical Logistics: Cold Chain Supply and Organ Delivery Drone 4

Advanced Aerial Medical Logistics: Cold Chain Supply and Org...

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4th International Conference on Advancement in Electronics and Communication Engineering, AECE 2024

作者： Bhayje, Sarvesh Kharche, Shubhangi Shetty, Sanmitha Gawade, Ved Sakhare, Sakshi Sies Graduate School of Technology Department of Electronics & Computer Science India

ISBN: (纸本)9798350364729

Organ transplantation is a life-saving medical procedure, but the increasing global demand for transplantable organs has exposed significant challenges, particularly in the timely and secure transportation of organs between donors and recipients. The success of these procedures often hinges on rapid and reliable organ delivery, where delays or mishandling can mean the difference between life and death. To address these challenges, the use of cold chain supply drones has emerged as a promising solution. By leveraging autonomous aerial technology, drones can transport organs efficiently while maintaining strict temperature control, crucial for organ viability. This survey paper explores the latest advancements in drone technology for organ transport, the legal frameworks governing their use, and the primary obstacles faced by the industry. Our research demonstrates a payload capacity of 1.2 kg for organ delivery drones and identifies quadcopters as the optimal platform. We further address temperature regulation within the organ storage box, ensuring precise preservation during transit. By combining stability analysis, payload capacity, and temperature control, our project aims to revolutionize organ delivery, making it more efficient, reliable, and accessible. © 2024 IEEE.

关键词： Drones

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Investigation of player emotion and instinct on racing video game using 6-11 framework (case study: split second (2010) single player modes) 9th

Investigation of player emotion and instinct on racing video...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Pratama, Galih Dea Novika, Andien Dwi Ardiyanto, Elshad Ryan Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Binus Graduate Program Bina Nusantara University Jakarta11480 Indonesia

Racing is one of the most prominent genres in the modern video game industry, where the games within the genre enable players to use any vehicle of their choice and win through doing series of action within gameplay. Thus, it made the genre popular over the years, spawning many famous titles such as Split Second back in 2010. Like every other video game title, Split Second also invokes the player emotion and instinct during its gameplay session. To understand the emotion and instinct aspect present in players of the game, we will use 6-11 framework which focuses on the two aspects. As part of the conclusion, Split Second game involves instincts such as Competition, Collecting, and Survival, with emotions including Fear, Pride, Joy, and Excitement, which can be found from its vast single player game modes. © 2024 The Authors.

关键词： 6-11 framework game analysis racing video games video games

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3D Structure Estimation of Room Environment Using Semantic Segmentation and Model Fitting

3D Structure Estimation of Room Environment Using Semantic S...

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2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024

作者： Morioka, Junya Miyamoto, Ryusuke Graduate School of Science and Technology Meiji University Department of Computer Science Kawasaki Japan School of Science and Technology Meiji University Department of Computer Science Kawasaki Japan

ISBN: (纸本)9798350385014

Recent advances in VR devices and technology have increased the demand for technologies that reflect real space in virtual space. In particular, technologies that reflect the indoor environment in a virtual space are used in various fields such as architecture, interior design, and robotics. To reflect a real space in a virtual space, estimating the 3D structure of the real space is significant. Yet, this requires expensive equipment and poses challenges in computational complexity and ease of measurement. In this study, we propose a method of estimating 3D structure of indoor environments using a single image. Existing methods generally use depth estimation, but in this study, we introduce a new approach using semantic segmentation and rectangular fitting. Experimental results with 3D CG show that the proposed method outperforms existing methods in accuracy and competitive results. © 2024 IEEE.

关键词： Semantics

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