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

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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Verification of Impedance Matching Using Input/Output Current Equalization Control in Wireless Power Transfer Systems with Active Rectifier

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IEEJ Transactions on Industry Applications 2025年第4期145卷 261-271页

作者： Kobayashi, Seiya Maekawa, Sari Electrical Engineering Program Graduate School of Science and Technology Meiji University 1-1-1 Higashimita Tama-ku Kanagawa Kawasaki214-8571 Japan

The efficiency of a wireless power transfer system changes with the load. To solve this problem, an impedance matching method has been developed. Conventional methods control the equivalent load to the optimal value using circuit parameters and the detected load voltage and current. However, they require estimating the mutual inductance M in case of misalignment or an airgap change. M-estimation has some issues such as a limited operating range. In this study, we developed a high-efficiency operation method that can respond to a change in M without its estimation by controlling the currents in the coils to equalize them. We confirmed that the developed method enables highly efficient operation without M-estimation despite misalignment. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Inductive power transmission

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Path Planning Method for Mobile Robots in Pedestrian-Friendly Environments Using Drone Bird's-Eye View

Path Planning Method for Mobile Robots in Pedestrian-Friendl...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Ye, Linghao Chugo, Daisuke Muramatsu, Satoshi Yokota, Sho Hashimoto, Hiroshi Kwansei Gakuin University Graduate School of Science and Technology Hyogo Sanda6691330 Japan Tokai University School of Information Science and Technology Kanagawa Hiratsuka2591292 Japan Toyo University Faculty of Science and Engineering Saitama Kawagoe3508585 Japan Advanced Institute of Industrial Technology Master Program of Innovation for Design and Engineering Shinagawa Tokyo1400011 Japan

ISBN: (纸本)9798331531614

The objective of this paper is to develop a robot system that can transmit the video taken by the drone to the computer in real time, use YOLO to recognize the image of pedestrians, and enable the ground robot to plan the path to avoid pedestrians. External sensors, such as laser range finders (LRF) and CCD cameras, are often used on mobile robots. As we all know, these sensors are susceptible to occlusion. Therefore, even if the mobile robot avoids the pedestrian in front of it, it is likely to collide with other pedestrians that cannot be detected due to occlusion. In this study, we used a drone to shoot videos at high altitudes, transferred the videos to a computer, used YOLO on the computer to perform image recognition of pedestrians around the robot, and passed the recognition results to ROS, which enabled it to plan a path to avoid pedestrians around it. As a result, showed that the videos shot at high altitudes could effectively identify pedestrians around the robot after being recognized by YOLO. © 2025 IEEE.

关键词： Drones

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Production and characterization of polymeric nanocomposite foams based on starch and cellulose nanofibers from oil palm mesocarp fiber

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Applied Nanoscience (Switzerland) 2025年第2期15卷 1-11页

作者： Souza, Mariana Costa Gonçalves, Ana Paula Bispo da Silva Oliveira, Emanoel Igor dos Santos, Juscivaldo Passos Lazzari, Lídia Kunz Zattera, Ademir José José, Nadia Mamede Chemical Engineering Graduate Program Polytechnic School Federal University of Bahia Bahia Salvador Brazil Department of Education Federal Institute of Education Science and Technology Feira de Santana Bahia Brazil Postgraduate Program in Process Engineering and Technologies University of Caxias Do Sul Rio Grande Do Sul Caxias Do Sul Brazil

The demand for sustainable and eco-friendly materials has promoted studies over the years to explore different polymeric materials that meet requirements such as biodegradability and sustainability. In this context, biopolymer materials based on cellulose nanoparticles and starch from different botanical sources have been investigated, aiming to achieve satisfactory performance. The present study aims to develop and characterize cassava starch foams based on density, scanning electron microscopy (SEM), and three-point flexure tests, and to evaluate the effect of cellulose nanofibers obtained from palm mesocarp fibers using the ultrafine friction grinding method after different processing times, characterized by X-ray diffractometry (XRD), microscopy, and chemical composition, as a reinforcing filler. The chemical composition and scanning electron microscopy revealed the effectiveness of the cellulose isolation process, with the analysis of the chemical composition revealing a cellulose content of 55.70% in the fibers after pulping and bleaching, in addition to changes in the visual characteristics of the material after the process aimed at isolating the cellulose. After grinding, XRD showed an increase in crystallinity (76.1% at the maximum grinding time), along with typical microscopy images of cellulose nanofibers. The analysis of the obtained nanocomposites provided insights into the role of these nanostructures in the thermo-expanded starch matrix, indicating that the nanofibers promoted changes such as an increase in mechanical properties and crystallinity, which contributed to improving overall mechanical performance. A 67.48% increase in flexural strength was achieved for the formulation with cellulose nanofibers that underwent 150 min of grinding, without causing major variations in density. © King Abdulaziz City for science and technology 2025.

关键词： Starch

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A Design Study on Integrated Complex Coefficient Filters with Peripheral Circuits for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 16-24页

作者： Shouno, Kazuhiro Sato, Lina Fukagawa, Kanta Tanimoto, Hiroshi Muto, Cosy Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan

This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square waves to an FUT (Filter Under Test) instead of sinusoidal waves or by superposing transfer characteristics obtained by applying a single sinusoidal wave to an FUT. In both of the above methods, the output signal connected to the external measurement equipment via a 50 Ω coaxial cable and so on. In this case, the output signal of the FUT should be amplified by internal or external amplifiers, which degrades the response. However, it is cancelled out by the proposed calibration circuitry with some analog switches. In addition to the above, for the RC polyphase filter, the source resistance and the load capacitance degrade the measurement results and their effect is discussed. The validity of the proposal is confirmed through computer simulation for a third-order RCPF whose passband is 8–40 MHz fabricated by Phenitec 0.6 µm CMOS process. It is shown that the measurement error is −1.10 dB for the square-wave method and −1.00 dB and −0.43 degrees for the superposition method at 40 MHz. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Analysis of the Musculoskeletal Load Generated when a Small Dog Walks on a Slippery Floor

Analysis of the Musculoskeletal Load Generated when a Small ...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Li, Shijian Chugo, Daisuke Muramatsu, Satoshi Yokota, Sho She, Jin-Hua Hashimoto, Hiroshi Takashi, Uemura Kamishina, Hiroaki Hata, Yoshiharu Yamada, Takayuki Uchida, Takahiro Kwansei Gakuin University Graduate School of Science and Technology Hyogo Sanda6691330 Japan Tokai University School of Information Science and Technology Kanagawa Hiratsuka2591292 Japan Toyo University Faculty of Science and Engineering Saitama Kawagoe3508585 Japan Tokyo University of Technology School of Engineering Hachioji Tokyo1920982 Japan Advanced Institute of Industrial Technology Master Program of Innovation for Design and Engineering Shinagawa Tokyo1400011 Japan KyotoAR Animal Advanced Medical Center Kuse Kyoto6130034 Japan Rinrei Co. Ltd. Chuo Tokyo1040061 Japan

ISBN: (纸本)9798331531614

The objective of this paper is to identify the stresses placed on the musculoskeletal system when small dogs walk on floors with low friction coefficients. In many households, and small dogs in particular are often kept indoors. According to veterinary experience, it is known that small dogs kept indoors that walk with their lower limbs slipping cause a great deal of stress on the musculoskeletal system, and that the incidence of joint disease in the lower limbs of such small dogs is high. In this study, we measured the body movements of small dogs walking on slippery floors using a three-dimensional motion capture system and force plate system. Furthermore, by inputting these measurements into the musculoskeletal simulation model we have developed to simulate the musculoskeletal system of dogs, we derived the load on the musculoskeletal system of small dogs on slippery and non-slippery floors. As a result, it was identified that walking on a slippery floor causes a strong load on the lower limb muscles of small dogs. © 2025 IEEE.

关键词： Friction

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Optimizing waste pre-collection model in Indonesian communities: comparing drop-off and door-to-door models through social cost–benefit analysis

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Journal of Material Cycles and Waste Management 2025年 1-17页

作者： Miftahadi, Machmuddin Fitra Hibino, Kohei Rachman, Indriyani Matsumoto, Toru Graduate Program in Environmental System Graduate School of Environmental Engineering The University of Kitakyushu Kitakyushu808-0135 Japan Kitakyushu Urban Centre Institute for Global Environmental Strategies Kitakyushu805-0062 Japan Department of Natural Science Education School of Postgraduate Studies Universitas Pakuan Kota Bogor16143 Indonesia Research Center for Urban Energy Management Institute of Environmental Science and Technology The University of Kitakyushu Kitakyushu808-0135 Japan

Indonesia lacks an established waste pre-collection system resulting 90% waste ending up in open-dumping site. This study identifies a 35-m radius per drop-off points as the most optimal model. The City of South Tangerang, on 21 residential areas with a population of 63,157, being examine. Utilizing ArcGIS Pro and Python scripting, 12 scenarios were developed, model drop-off radii of 15–45 m and household limits of 4–32 per drop-off point, including combined models. Spatial clustering KD-Tree algorithm and Proximity-based Routing were employed to determine collection placements and walking distances. Heatmap and ANOVA tests evaluated conformity with residential characteristics. Model then organized into eight frequency schemes, utilizing motorcart and handcart systems with 4-day and 2-day pickup schedules for waste bank and in-house compost programs. This optimized model reduces collection time by up to 81% and costs by 50% compared to traditional door-to-door systems, achieving cost reductions of $30–$38 USD per ton and lowering CO₂ emissions. The discussion covers opportunity costs and occupational risk. This approach supports Indonesia’s waste reduction targets and offers policy alignment for urban waste management. © The Author(s), under exclusive licence to Springer Nature Japan KK, part of Springer Nature 2025.

关键词： Python

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Multi-modal Multitask Learning Model for Simultaneous Classification of Two Epilepsy Biomarkers 27th

Multi-modal Multitask Learning Model for Simultaneous Classi...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Broti, Nawara Mahmood Sawada, Masaki Takayama, Yutaro Iijima, Keiya Iwasaki, Masaki Ono, Yumie Electrical Engineering Program Graduate School of Science and Technology Meiji University Kanagawa Kawasaki Japan Department of Neurosurgery Yokohama City University Hospital Kanagawa Yokohama Japan Department of Neurosurgery National Center Hospital National Center of Neurology and Psychiatry Tokyo Kodaira Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University Kanagawa Kawasaki Japan

ISBN: (纸本)9783031781971

Accurate estimation of the epileptogenic zone is critical for surgical treatment of drug-resistant epilepsy. While epilepsy biomarkers detection for epileptogenic zone localization has traditionally relied on expert clinician knowledge, the use of deep learning in this context has recently gained appeal for objective diagnosis and reducing clinician burden. However, previously proposed classifiers for electrocorticogram data focused on only single biomarkers among many types, requiring separate models and large datasets for each. To minimize clinicians’ workload and patients’ sufferings, innovative methods to classify multiple biomarkers using small training datasets and minimal computation time is required. This research marks the first implementation of multi-modal multitask learning in epilepsy biomarker classification, proposing a model to automatically classify two biomarkers—high-frequency oscillations (HFO) and interictal epileptiform discharges (IED)—from separate datasets simultaneously. We validated the proposed model on 1500 annotated HFO and IED candidate signals each, obtained from 5 patients. Our proposed model can perform both HFO and IED classification simultaneously, with cross-validation accuracies of 90.99% and 93.99%;F1 scores were reported as 0.80 and 0.82, respectively. Our leave-one-patient-out experiments achieved 78.03% and 81.19% accuracy for HFO and IED classification, respectively. Compared to existing state-of-the-art classification architectures, our model is shown to be efficient and robust, yet simple and lightweight. The usefulness of sharing parameters between the two classifiers was confirmed in this practical clinical setting of epileptic biomarker detection, potentially contributing to minimizing the number of annotated datasets and realizing robust, accurate, and simultaneous identification of two biomarkers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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Development of a Smartphone-Linked Immunosensing System for Oxytocin Determination

Biosensors

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Biosensors 2025年第4期15卷 261-261页

作者： Sarubo, Miku Suzuki, Yoka Numazaki, Yuka Kudo, Hiroyuki Electrical Engineering Program Graduate School of Science and Technology Meiji University Kanagawa Kawasaki City214-8571 Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University Kanagawa Kawasaki City214-8571 Japan

We report an optical immunosensing system for oxytocin (OXT) based on image analysis of color reactions in an enzyme-linked immunosorbent assay (ELISA). We employed a miniaturized optical immunosensing unit that was functionally connected to an LED and a smartphone camera. Our system measures OXT levels using a metric called the RGBscore, which is derived from the red, green, and blue (RGB) information in the captured images. By calculating the RGBscore regressively using the brute-force method, this approach can be applied to smartphones with various CMOS image sensors and firmware. The lower detection limit was determined to be 5.26 pg/mL, and the measurement results showed a higher correlation (r = 0.972) with those obtained from conventional ELISA. These results suggest the potential for its application in a simplified health management system for individuals. © 2025 by the authors.

关键词： Firmware

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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis

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Procedia Computer science 2025年 253卷 84-93页

作者： Anak Agung Ayu Putri Ardyanti Zhiqiang Xie Andrea Stevens Karnyoto Bens Pardamean Ni Made Estiyanti School of Computer Science and Technology Harbin University of Science and Technology Harbin 150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Doctoral School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of engineering, Computer science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions.

关键词： integrated scheduling assembly job shop scheduling heuristic algorithm genetic algorithm bibliometric analysis

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