Updated on 2024/10/22

Information

 

写真a

 
NAKAMURA YUGO
 
Organization
Faculty of Information Science and Electrical Engineering Department of Advanced Information Technology Assistant Professor
School of Engineering Department of Electrical Engineering and Computer Science(Concurrent)
Graduate School of Information Science and Electrical Engineering Department of Information Science and Technology(Concurrent)
Title
Assistant Professor
Contact information
メールアドレス
Profile
人を理解し、人を動かすIoT技術(IoTナッジ)の研究に従事

Degree

  • Doctor of Engineering, Ph.D

Research History

  • 2020年4月から2021年4月 奈良先端科学技術大学院大学 特任助教

Research Interests・Research Keywords

  • Research theme:Research on realtime detection and attention control of digital distraction

    Keyword:Digital Distraction, Personality, Multimodal Sensing, Tailored Intervention, Digital Wellbeing

    Research period: 2024.4 - 2027.3

  • Research theme:Empowerment ICT Platform for Health Behavior Security

    Keyword:Behavior recognition, behavior transformation, nudge, health behavior security, empowerment ICT

    Research period: 2021.10 - 2024.3

Awards

  • 優秀論文賞

    2024.4   情報処理学会 マルチメディア通信と分散処理ワークショップ (DPSWS2023)   イアラブルデバイスのマイクを用いた食事内容と咀嚼回数の推定手法の提案

  • 異能ジェネレーションアワード 分野賞 食に関する分野

    2024.3   異能ベーション   食べて、塗って、健やかに「eat2pic」

  • The 13th International Conference on the Internet of Things (IoT 2023)

    2023.11   The 13th International Conference on the Internet of Things (IoT 2023)  

  • Best Demonstration Runner-up Award

    2023.10   The 13th International Conference on the Internet of Things (IoT 2023)  

  • Best Demonstration Award

    2023.7   IEEE MDM 2023  

  • 船井研究奨励賞

    2023.3   船井情報科学振興財団   IoTナッジ:生活空間に溶け込むIoTデバイスを用いた行動認識に基づく次世代ナッジの創出

  • Best Paper Award

    2022.10   ACM WellComp 2022  

  • Best Paper Award

    2022.10   ACM WellComp 2022   Aromug: Mug-type Olfactory Interface to Assist in Reducing Sugar Intake

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Shinya Misaki, Keiichi Yasumoto

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  • 実用化期待賞

    2022.4   情報処理学会IoT行動変容学研究グループ   Aromug:糖分摂取量低減を補助するスマートマグカップの検討

  • ACM Ubicomp/ISWC2021 Best Poster Honorable Mention Award

    2021.9   ACM  

  • IEEE PerCom 2021 Best Demo Award

    2021.3  

  • JSPS インタラクション2021「論文賞」

    2020.9   eat2pic: 食事と描画の相互作用を用いた健康的な食生活を促すナッジシステム

  • JSPS DICOMO 2019「最優秀プレゼンテーション賞」

    2019.7   ウェアラブルセンサ装着位置/向きの違いにロバストな行動認識システムの実現に向けたデータ変換手法の検討

  • ACM Ubicomp/ISWC2016 Best Demo Award

    2016.10  

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Papers

  • Privacy-Preserving Federated Learning With Resource Adaptive Compression for Edge Devices Reviewed International journal

    Muhammad Ayat Hidayat, Yugo Nakamura, Yutaka Arakawa

    IEEE Internet of Things Journal   2024.3

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1109/JIOT.2023.3347552

  • Kaolid: A Lid-Type Olfactory Interface to Present Retronasal Smell towards Beverage Flavor Augmentation Reviewed International journal

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Shinya Misaki, Keiichi Yasumoto

    ACM International Conference Proceeding Series   1 - 8   2023.11   ISBN:9798400708541

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    In this paper, we introduce Kaolid, an olfactory interface that uses a lid mechanism to augment the flavor of beverages by delivering scents as retronasal smell. Kaolid aims to promote the consumption of healthier beverages by intensifying their perceived taste through the release of scents during drinking. The system features a compact olfactory display and an IMU sensor, triggering scents in response to drinking movements. It comes in two models: A straw-Type for cold beverages and a cup-Type for hot drinks. We tested the interface using sparkling and hot water and measured its efficacy in enhancing perceived sweetness when paired with scents. Results showed significant enhancements in all evaluation metrics (taste satisfaction, perceived sweetness, and preference) with the straw-Type device. Notably, the perceived sweetness increased by an amount equivalent to about 2.88 grams of sugar when a retronasal smell was introduced compared to when no scent was present. This innovative interface holds promise in elevating the flavor of sugar-free drinks and could support those aiming to limit sugar consumption. Furthermore, this research contributes to the future of IoT systems for health support by harnessing the power of scent, opening avenues for novel approaches in sensory-driven well-being advancements.

    DOI: 10.1145/3627050.3627056

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    Other Link: https://dblp.uni-trier.de/db/conf/iot/iot2023.html#MayumiN0MY23

  • eat2pic: An Eating-Painting Interactive System to Nudge Users into Making Healthier Diet Choices Reviewed International journal

    Yugo Nakamura, Rei Nakaoka, Yuki Matsuda, Keiichi Yasumoto

    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies   7 ( 1 )   1 - 23   2023.3   ISSN:2474-9567 eISSN:2474-9567

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Association for Computing Machinery ({ACM})  

    Given the complexity of human eating behaviors, developing interactions to change the way users eat or their choice of meals is challenging. In this study, we propose an interactive system called eat2pic designed to encourage healthy eating habits such as adopting a balanced diet and eating more slowly, by refraining the task of selecting meals into that of adding color to landscape pictures. The eat2pic system comprises a sensor-equipped chopstick (one of a pair) and two types of digital canvases. It provides fast feedback by recognizing a user's eating behavior in real time and displaying the result on a small canvas called "one-meal eat2pic."Moreover, it also provides slow feedback by displaying the number of colors of foods that the user consumed on a large canvas called "one-week eat2pic."The former was designed and implemented as a guide to help people eat more slowly, and the latter to encourage people to select more balanced menus. Through two user studies, we explored the experience of interaction with eat2pic, in which users' daily eating behavior was reflected in a series of "paintings,"that is, images produced by the automated system. The experimental results suggest that eat2pic may provide an opportunity for reflection in meal selection and while eating, as well as assist users in becoming more aware of how they are eating and how balanced their daily meals are. We expect this system to inspire users' curiosity about different diets and ways of eating. This research also contributes to expanding the design space for products and services related to dietary support.

    DOI: 10.1145/3580784

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  • Unsupervised Learning of Domain-Independent User Attributes Reviewed International journal

    Ishikawa, Y., Legaspi, R., Yonekawa, K., Nakamura, Y., Ishida, S., Mine, T., Arakawa, Y.

    IEEE Access   10   119649 - 119665   2022.11

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    DOI: 10.1109/ACCESS.2022.3220781

  • Large-Scale Evacuation Shelter Selection Method Through Iterations of Pedestrian Simulations With Dynamic Congestion Reproduction Reviewed International journal

    Kazuhito Umeki, Tomoki Tanaka, Yugo Nakamura, Manato Fujimoto, Teruhiro Mizumoto, Hirohiko Suwa, Yutaka Arakawa, Keiichi Yasumoto

    IEEE Access   10   89387 - 89401   2022.8   ISSN:2169-3536 eISSN:2169-3536

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    It is necessary to optimize evacuation guidance to shelters in short evacuation time. The state-of-the-art method based on an idea of combinatorial optimization problems related to evacuees' locations and the capacities of nearby shelters has been developed, while it cannot mitigate the effect of congestion on roads/streets after evacuation starts. In this study, to cover this problem, we develop a new method that utilizes simulations for estimating the effect of congestion on roads/streets during evacuation and reassigning shelters to evacuees based on the simulation results. By iterating this step, our method derives the congestion-aware solutions for shelter selection that can realize more smooth evacuation. To evaluate our method, we conducted multi-agent simulations assuming a disaster situation in a sightseeing spot. Specifically, we examined a hypothetical case scenario involving the evacuation of 30,000 visitors from the Gion Festival. We compared the proposed method with conventional methods, such as the nearest shelter selection method and our previous method. We found that our proposed method reduced average and total evacuation time and congestion on roads compared to the conventional methods including the nearest shelter selection method and our previous method that only employs combinatorial optimization without estimating congestion. From this result, our idea of simulation-based congestion estimation has an impact of easing congestion during evacuation and preventing overcapacity of shelters at the same time. It shows the possibilities of help in developing congestion-aware evacuation strategies in emergency situations of crowded areas like huge cities or sightseeing spots.

    DOI: 10.1109/ACCESS.2022.3194874

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  • ZEL: Net-Zero-Energy Lifelogging System using Heterogeneous Energy Harvesters. Reviewed International journal

    Mitsuru Arita, Yugo Nakamura, Shigemi Ishida, Yutaka Arakawa

    PerCom   172 - 179   2022.3

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    DOI: 10.1109/PerCom53586.2022.9762376

  • Estimating Congestion in a Fixed-Route Bus by Using BLE Signals. Reviewed International journal

    Yuji Kanamitsu, Eigo Taya, Koki Tachibana, Yugo Nakamura, Yuki Matsuda 0001, Hirohiko Suwa, Keiichi Yasumoto

    Sensors   22 ( 3 )   881 - 881   2022.2   ISSN:1424-8220 eISSN:1424-8220

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    Information on congestion of buses, which are one of the major public transportation modes, can be very useful in light of the current COVID-19 pandemic. Because it is unrealistic to manually monitor the number of riders on all buses in operation, a system that can automatically monitor congestion is necessary. The main goal of this paper’s work is to automatically estimate the congestion level on a bus route with acceptable performance. For practical operation, it is necessary to design a system that does not infringe on the privacy of passengers and ensures the safety of passengers and the installation sites. In this paper, we propose a congestion estimation system that protects passengers’ privacy and reduces the installation cost by using Bluetooth low-energy (BLE) signals as sensing data. The proposed system consists of (1) a sensing mechanism that acquires BLE signals emitted from passengers’ mobile terminals in the bus and (2) a mechanism that estimates the degree of congestion in the bus from the data obtained by the sensing mechanism. To evaluate the effectiveness of the proposed system, we conducted a data collection experiment on an actual bus route in cooperation with Nara Kotsu Co., Ltd. The results showed that the proposed system could estimate the number of passengers with a mean absolute error of 2.49 passengers (error rate of 38.8%).

    DOI: 10.3390/s22030881

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  • IoT Nudge: IoT Data-driven Nudging for Health Behavior Change. Reviewed International journal

    Yugo Nakamura

    UbiComp/ISWC '21: 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2021 ACM International Symposium on Wearable Computers   51 - 53   2021.9

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    DOI: 10.1145/3460418.3479280

  • INSHA: Intelligent Nudging System for Hand Hygiene Awareness. Reviewed International journal

    Sopicha Stirapongsasuti, Kundjanasith Thonglek, Shinya Misaki, Yugo Nakamura, Keiichi Yasumoto

    IVA '21: ACM International Conference on Intelligent Virtual Agents(IVA)   183 - 190   2021.9

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    DOI: 10.1145/3472306.3478355

  • DisCaaS: Micro Behavior Analysis on Discussion by Camera as a Sensor Reviewed International journal

    Ko Watanabe, Yusuke Soneda, Yuki Matsuda, Yugo Nakamura, Yutaka Arakawa, Andreas Dengel, Shoya Ishimaru

    Sensors   21 ( 17 )   5719 - 5719   2021.8

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    DOI: 10.3390/s21175719

  • LightSub: Unobtrusive Subtitles with Reduced Information and Decreased Eye Movement

    Nishi, Y; Nakamura, Y; Fukushima, S; Arakawa, Y

    MULTIMODAL TECHNOLOGIES AND INTERACTION   8 ( 6 )   2024.6   eISSN:2414-4088

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    Publisher:Multimodal Technologies and Interaction  

    Subtitles play a crucial role in facilitating the understanding of visual content when watching films and television programs. In this study, we propose a method for presenting subtitles in a way that considers cognitive load when viewing video content in a non-native language. Subtitles are generally displayed at the bottom of the screen, which causes frequent eye focus switching between subtitles and video, increasing the cognitive load. In our proposed method, we focused on the position, display time, and amount of information contained in the subtitles to reduce the cognitive load and to avoid disturbing the viewer’s concentration. We conducted two experiments to investigate the effects of our proposed subtitle method on gaze distribution, comprehension, and cognitive load during English-language video viewing. Twelve non-native English-speaking subjects participated in the first experiment. The results show that participants’ gazes were more focused around the center of the screen when using our proposed subtitles compared to regular subtitles. Comprehension levels recorded using LightSub were similar, but slightly inferior to those recorded using regular subtitles. However, it was confirmed that most of the participants were viewing the video with a higher cognitive load using the proposed subtitle method. In the second experiment, we investigated subtitles considering connected speech form in English with 18 non-native English speakers. The results revealed that the proposed method, considering connected speech form, demonstrated an improvement in cognitive load during video viewing but it remained higher than that of regular subtitles.

    DOI: 10.3390/mti8060051

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  • Privacy-Preserving Federated Learning with Resource-Adaptive Compression for Edge Devices Reviewed International journal

    Muhammad Ayat Hidayat, Yugo Nakamura, Yutaka Arakawa

    IEEE Internet of Things Journal   11 ( 8 )   13180 - 13198   2024.4

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    DOI: 10.1109/JIOT.2023.3347552

  • Privacy-aware Quantitative Measurement of Psychological State in Meetings based on Non-verbal Cues

    Hayashida, T; Nakamura, Y; Choi, H; Arakawa, Y

    2024 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS AND OTHER AFFILIATED EVENTS, PERCOM WORKSHOPS   433 - 436   2024   ISSN:2836-5348 ISBN:979-8-3503-0437-4

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    Publisher:2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2024  

    In recent years, with the trend towards shorter working hours, the quality of meetings has increasingly impacted these hours. Consequently, meeting quality and value become more important. To achieve better results in limited time, everyone needs to conduct meetings effectively. This requires skills such as facilitating the meeting, listening to others' opinions, accurately expressing one's own views, and using body language. However, these skills are currently only correlated with meeting effectiveness and lack comprehensive qualitative and quantitative assessments, leaving specific methods for improvement unclear. Additionally, the type of meeting can lead to participant stress or disinterest, making it essential to understand their psychological safety and engagement for more effective meetings. Measuring these psychological states poses significant challenges due to privacy and compliance concerns, particularly when using cameras or wearable sensors. This paper broadly addresses these issues and reports on our approach to detecting non-verbal cues, specifically nodding, from chair movements as a potential solution.

    DOI: 10.1109/PerComWorkshops59983.2024.10502817

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  • Preserving Data Utility in Differentially Private Smart Home Data

    Sopicha Stirapongsasuti, Francis Jerome Tiausas, Yugo Nakamura, Keiichi Yasumoto

    IEEE Access   12   56571 - 56581   2024   ISSN:2169-3536 eISSN:2169-3536

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    The development of smart sensors and appliances can provide a lot of services. Nevertheless, the act of aggregating data containing sensitive information related to privacy in a single location poses significant issues. Such information can be misused by a malicious attacker. Also, some previous studies attempted to apply privacy mechanisms, but they decreased data utility. In this paper, we propose privacy protection mechanisms to preserve privacy-sensitive sensor data generated in a smart home. We leverage Rényi differential privacy (RDP) to preserve privacy. However, the preliminary result showed that using only RDP still significantly decreases the utility of data. Thus, a novel scheme called feature merging anonymization (FMA) is proposed to preserve privacy while maintaining data utility by merging feature dataframes of the same activities from other homes before applying RDP. Also, the expected trade-off is defined so that data utility should be greater than the privacy preserved. To evaluate the proposed techniques, we define privacy preservation and data utility as inverse accuracy of person identification (PI) and accuracy of activity recognition (AR), respectively.We trained the AR and PI models for two cases with and without FMA, using 2 smart-home open datasets i.e. the HIS and Toyota dataset. As a result, we could lower the accuracy of PI in the HIS and Toyota dataset to 73.85% and and 41.18% with FMA respectively compared to 100% without FMA, while maintaining the accuracy of AR at 94.62% and 87.3% with FMA compared to 98.58% and 89.28% without FMA in the HIS and Toyota dataset, respectively. Another experiment was conducted to explore the feasibility of implementing FMA in a local server by partially merging frames of the original activity with frames of other activities at different merging ratios. The results show that the local server can still satisfy the expected trade-off at some ratios.

    DOI: 10.1109/ACCESS.2024.3390039

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  • Poster: Desk Activity Recognition Using On-desk Low-cost WiFi Transceiver

    Choi, H; Nakamura, Y; Fukushima, S; Arakawa, Y

    PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024   702 - 703   2024   ISBN:979-8-4007-0581-6

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    Publisher:MOBISYS 2024 - Proceedings of the 2024 22nd Annual International Conference on Mobile Systems, Applications and Services  

    Since office work has become large-scale and diversified in companies or organizations, work engagement and efficiency have been always an important index of a team's or group's evaluation because it is directly connected to their outcomes. In order to identify the group work context, we first need to recognize for what and how long the individual members are spending their time at their desks, but without privacy concerns and underestimation of their actual work. In this paper, we propose and evaluate the base system of personal desk activity recognition by using a low-cost compact WiFi node and its WiFi channel state information (CSI), which can lead to a lightweight group work context identification system. As a result, we achieved 94.2% desk activity recognition accuracy using the on-desk receiver, in recognizing five different classes.

    DOI: 10.1145/3643832.3661452

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  • Enhancing Efficiency in Privacy-Preserving Federated Learning for Healthcare: Adaptive Gaussian Clipping With DFT Aggregator

    Hidayat, MA; Nakamura, Y; Arakawa, Y

    IEEE ACCESS   12   88445 - 88457   2024   ISSN:2169-3536

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    Machine learning's exponential growth has transformed healthcare, with Federated Learning (FL) playing a pivotal role. Despite its significance, FL is vulnerable to privacy attacks. In response, researchers have integrated differential privacy (DP) into FL. Nevertheless, incorporating DP introduces challenges such as increased total communication costs and computational overheads due to the introduction of noise. This drawback renders FL with DP less viable for healthcare systems, characterized by numerous low-resource devices and network bandwidth constraints. To overcome this limitation, we propose integrating a Discrete Fourier Transform (DFT) aggregator post-noise addition to transform the gradient generated by local training before sending it to the central server. This process reduces the gradient size and provides rudimentary encryption. The evaluation results reveal the superior performance of our proposed method, demonstrating an enhanced accuracy ranging from 0.2% to 2% compared to existing differential privacy techniques, including RDP, DP-SGD, ZcDP, LDP-Fed, and DP-AdapClip. Our approach substantially reduces the total communication costs (ranging from 6% to 43% across different privacy budgets) with faster training times in healthcare datasets such as the PIMA Indian database and Breast Cancer Histopathology Images.

    DOI: 10.1109/ACCESS.2024.3418016

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  • Design and Implementation of Persuasive Public Wi-Fi to Derive Prosocial Network Usage

    Eguchi N., Choi H., Nakamura Y., Fukushima S., Arakawa Y.

    International Conference on Information Networking   351 - 356   2024   ISSN:19767684 ISBN:9798350330946

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    Publisher:International Conference on Information Networking  

    As the high-speed wireless network spreads, the usage of shared Wi-Fi in places such as offices, coworking spaces, and homes has been increased. Along with the development and diversification of digital content, the amount of data consumed by individual devices has also grown. In situations where multiple users share limited network resources, some content that consumes a large amount of bandwidth like video streaming can potentially degrade the Quality of Experience (QoE) for other users nearby. Consequently, a need for persuasive intervention systems that encourage prosocial behavior is rising taking into consideration the QoE of other network users. To address this issue, this study proposes a "Persuasive Public Wi-Fi"that employs Wi-Fi to incrementally convince users towards more considerate usage of network resources. To be specific, we suppose that the persuasive public Wi-Fi must include three different modes: 1) a mode of normal networking, 2) a mode that can intervene with individual users through a captive portal, and 3) a mode that intentionally limits bandwidth, i.e., Quality of Service (QoS) control. This work demonstrates the design and implementation of the proposed system and presents the results of operational verification using a prototype system.

    DOI: 10.1109/ICOIN59985.2024.10572181

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  • Demo: Privacy-Preserving Decentralized Machine Learning Framework for Clustered Resource-Constrained Devices

    Hidayat, MA; Nakamura, Y; Arakawa, Y

    PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024   612 - 613   2024   ISBN:979-8-4007-0581-6

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    Publisher:MOBISYS 2024 - Proceedings of the 2024 22nd Annual International Conference on Mobile Systems, Applications and Services  

    We present a secure decentralized learning framework suitable for resource-constrained devices within a cluster environment. Our approach focuses on enhancing privacy preservation during model aggregation by utilizing Differential Privacy. This technique adds random noise to gradients obtained from local training on edge devices before sending them for aggregation. This noise addition ensures that sensitive information within the gradients remains distorted, thus safeguarding user privacy. We showcase the implementation of our system on a cluster system employing Raspberry Pi 4 Model B devices, illustrating its feasibility and effectiveness in real-world scenarios. Through this demonstration, we highlight the practical applicability of our system in enabling secure decentralized learning within resource-constrained environments.

    DOI: 10.1145/3643832.3661843

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  • Color Psychology-Based Persuasive Interaction Design for Health Behavior Change

    Nakamura Y., Arakawa Y.

    CEUR Workshop Proceedings   3728   107 - 109   2024   ISSN:16130073

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    In an era where digital technology profoundly influences our daily habits, we explore the potential of color psychology as a key element in the design of persuasive technology to promote health behavior change. This paper presents a strategy that uses color psychology to both encourage positive behaviors and discourage negative ones. We present two different applications: "eat2pic," a system designed to promote healthier eating habits by transforming meal selection into an engaging activity of adding color to images, and "color-wall," an application designed to reduce digital distractions by applying a grayscale filter to non-essential digital content. Through these demonstrations, we explore the efficacy and potential of color psychology in persuasive technology to influence user behavior in a health context and offer promising solutions to improve dietary choices and concentration while using computers.

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  • Aromug: a Mug-type Olfactory Interface to Enhance the Sweetness Perception of Beverages

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Shinya Misaki, Keiichi Yasumoto

    IEEE Access   12   78366 - 78378   2024   ISSN:2169-3536 eISSN:2169-3536

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    Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/ACCESS.2024.3401392

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  • A Space Information-Enhanced Dense Video Caption for Indoor Human Action Recognition

    Chen B., Nakamura Y., Fukushima S., Arakawa Y.

    2024 8th International Conference on Robotics, Control and Automation, ICRCA 2024   423 - 427   2024   ISBN:9798350344721

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    Publisher:2024 8th International Conference on Robotics, Control and Automation, ICRCA 2024  

    Dense video captioning tasks are used to detect interesting events and provide descriptive text for these events from untrimmed videos. This technology has the potential to be used in security surveillance and human care applications. However, current methods often overlook the relationships between objects in the video, which limits their applicability and makes it challenging to adapt them to specific domains, such as video summarization for indoor human activities. In these scenarios, human activities are closely intertwined with the objects in the scene. In this paper, we propose a plug-and-play module designed to enhance existing dense video captioning methods with spatial information. Specifically, we extract spatial information about the interesting objects using Red-Green-Blue-Depth (RGB-D) images and the results of image segmentation. We then integrate this information into the captions generated by the Dense Video Captioning (DVC) method using a fine-tuned Large Language Model (LLM). We evaluate the performance of our model on a custom dataset and demonstrate that our system provides a convenient and effective approach for obtaining space-enhanced captions.

    DOI: 10.1109/ICRCA60878.2024.10649311

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  • Design of a Spoken Dialogue System to Provide Food Knowledge to Users while Eating Reviewed International journal

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Annalena Aicher, Keiichi Yasumoto, Wolfgang Minker

    ACM International Conference Proceeding Series   154 - 157   2023.11   ISBN:9798400708541

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    In this paper, we introduce the concept of a spoken dialogue system, which aims to recognize user eating behaviors during meals and promotes healthier eating habits by engaging users in an interactive co-dining experience. To provide an intuitive and more natural access, this information is integrated into a natural conversation with the user. Therefore, we conducted a preliminary study to explore how a human-like virtual avatar's eating speed affects the eating pace of a co-dining user. The results indicate that dining together with an avatar reduces the user's feeling of loneliness and enhances the overall satisfaction and enjoyment of the meal. Therefore, this work represents an important step toward realizing engaging co-dining experiences with human-like avatars and provides new insights into the future design of IoT systems to support solitary dining and health recommendations.

    DOI: 10.1145/3627050.3630728

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    Other Link: https://dblp.uni-trier.de/db/conf/iot/iot2023.html#MayumiN0AYM23

  • Automated Image Generation Reflecting Current Status of PoIs for Supporting On-Site Tourist Destination Selection Reviewed International journal

    Masaki Kawanaka, Yugo Nakamura, Hirohiko Suwa, Keiichi Yasumoto

    ACM International Conference Proceeding Series   121 - 128   2023.11   ISBN:9798400708541

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    To support the decision-making process for selecting upcoming tourist spots (PoI: Points of Interest), it is necessary to share the tourist destinations' current status. Methods for sharing the current status of PoIs could include installing live cameras or having tourists share real-Time photos. Still, there are challenges in terms of installation and maintenance costs and privacy concerns. In this paper, a tourism support system is proposed to aid in the decision-making of which PoI to visit next by automatically generating PoI current status images from template images and contextual information of tourist destinations while preserving privacy and presenting them to users. In the proposed system, semantic segmentation is used to divide template images into categories such as sky class, trees/grasses class, crowd class, and overall class. Based on the separately collected contextual information (weather, condition of trees/grass, crowd density, time, etc.), appropriate image transformations (using style transfer, etc) are applied to each category. The proposed system consists of an automated method for generating PoI status images and an application that presents these images to users. As part of a tourism experiment using the proposed system, 11 individuals aged 20 to 30 participated in a roughly 2-hour tour of Nara City in Japan. The results showed that compared to presenting template images, the proposed method yielded a decision-making score improvement of 0.27 and a similarity (to the current status) score improvement of 0.45 (out of five), both of which were statistically significant.

    DOI: 10.1145/3627050.3627068

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    Other Link: https://dblp.uni-trier.de/db/conf/iot/iot2023.html#KawanakaNSY23

  • Counting Nods from Chair Rocking Reviewed International journal

    Toshiki Hayashida, Yugo Nakamura, Hyuckjin Choi, Yutaka Arakawa

    ACM International Conference Proceeding Series   208 - 210   2023.11   ISBN:9798400708541

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    In this demo, we will show our proposed system that can count nodding without either a camera or any sensor attached to the person. Our proposed system capitalizes on the fact that the upper body moves in conjunction with nodding and that this body motion slightly shakes the chair. We explore the challenge of recognizing nodding from the extremely subtle sway of a chair. To recognize nods in real-Time, we employed a supervised learning approach using acceleration data from sensors attached to the chair's backrest. Ultimately, the Support Vector Machine (SVM) achieved a nodding recognition accuracy of 0.990. Further testing of the accuracy of nodding frequency measurements yielded an accuracy of 0.947, suggesting that the optimal position for the accelerometer is the backrest. These results indicate that simply placing the accelerometer on the backrest can effectively quantify the frequency of nods from seated participants.

    DOI: 10.1145/3627050.3630740

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  • ACOGARE: Acoustic-Based Litter Garbage Recognition Utilizing Smartwatch Reviewed International journal

    Koki Tachibana, Yugo Nakamura, Yuki Matsuda, Hirohiko Suwa, Keiichi Yasumoto

    Sustainability   15 ( 13 )   10079 - 10079   2023.6   eISSN:2071-1050

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    Litter has become a social problem. To prevent litter, we consider urban planning, the efficient placement of garbage bins, and interventions with litterers. In order to carry out these actions, we need to comprehensively grasp the types and locations of litter in advance. However, with the existing methods, collecting the types and locations of litter is very costly and has low privacy. In this research, we have proposed the conceptual design to estimate the types and locations of litter using only the sensor data from a smartwatch worn by the user. This system can record the types and locations of litter only when a user raps on the litter and picks it up. Also, we have constructed a sound recognition model to estimate the types of litter by using sound sensor data, and we have carried out experiments. We have confirmed that the model built with other people’s data enabled to estimate the F-measure of 80.2% in a noisy environment through the experiment with 12 participants.

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  • An End-To-End Hybrid Overhead Facial Orientation Estimation System for Offline Group Discussions

    Chen, CH; Nakamura, Y; Arakawa, Y

    2023 FOURTEENTH INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND UBIQUITOUS NETWORK, ICMU   2023   ISBN:978-4-907626-52-5

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  • WiLearn: Design and Implementation of a Microlearning System that Utilizes a Captive Portal of Wi-Fi

    Koushi Hiraoka, Shuta Matsuo, Yutaka Arakawa, Yugo Nakamura

    2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023   1 - 4   2023   ISBN:9784907626525

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    Internet use is expanding along with the spread of smartphones and the promotion of digital use, but information security literacy is required to use the Internet safely. This paper addresses these challenges by focusing on the potential of microlearning and nudge theory to support continuous learning to solve these problems and presents a novel learning system that utilizes a Wi-Fi landing portal that appears as a dialog or a browser. To assess the effectiveness of the proposed system, we conducted a comparative analysis of information security test scores before and after the operation of the learning system and questionnaire-based evaluation. The results showed that the analysis of answer scores before and after the operation of the learning system was significant (\mathrm{p} < 0.05), indicating an improvement in scores. It was also found that using interface information with nudges effectively motivated participants to engage in repeated learning behaviors. However, it should be noted that frequent interventions might reduce acceptability, and the psychological burden arising from task interruptions needs to be taken into account.

    DOI: 10.23919/ICMU58504.2023.10412210

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  • WiLearn: Design and Implementation of a Microlearning System that Utilizes a Captive Portal of Wi-Fi

    Hiraoka, K; Matsuo, S; Arakawa, Y; Nakamura, Y

    2023 FOURTEENTH INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND UBIQUITOUS NETWORK, ICMU   2023   ISBN:978-4-907626-52-5

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  • WatchLogger: Keyboard Typing Words Recognition Based on Smartwatch

    Gangkai Li, Yutaka Arakawa, Yugo Nakamura, Hyuckjin Choi, Shogo Fukushima, Wei Wang

    2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023   1 - 6   2023   ISBN:9784907626525

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    Nowadays more and more people are wearing smart-watches in their daily lives. The various sensors embedded in smartwatches bring the ability to evaluate users' status as well as the risk of privacy issues. For example, if users are typing on key-boards while wearing smartwatches, the attacker could know the typing contents from the sensor data collected by the malicious applications that are installed on the targets' smartwatches. In this paper, we propose WatchLogger, the framework using audio and accelerometer signals to recognize the English words being typed, for demonstrating how to implement the smartwatch-based side-channel attack. Different from the previous studies that focused on the recognition of each key or pair of keys being pressed, WatchLogger aims to perform recognition on the scale of words. To achieve this goal, WatchLogger exploits the audio signals for segmentation and the accelerometer signals for classification. In addition, we propose an ensemble classification model to deal with the problem caused by too many words. At last, we build the dataset WTW-100 with 100 classes of words and 100 samples for each class, and we conduct experiments on the dataset. The experimental results show an accuracy of 98.5 % for keystroke recognition and 91.5 % for word classification, showing a considerable performance of WatchLogger.

    DOI: 10.23919/ICMU58504.2023.10412218

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  • WatchLogger: Keyboard Typing Words Recognition based on Smartwatch

    Li, GK; Arakawa, Y; Nakamura, Y; Choi, H; Fukushima, S; Wang, W

    2023 FOURTEENTH INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND UBIQUITOUS NETWORK, ICMU   2023   ISBN:978-4-907626-52-5

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  • ToonMeet: A Real-time Portrait Toonification Framework with Frame Interpolation Fine-tuned for Online Meeting

    Chenhao Chen, Shogo Fukushima, Yugo Nakamura, Yutaka Arakawa

    Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI   30 - 37   2023   ISSN:1082-3409 ISBN:979-8-3503-4273-4

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    In this paper, we propose ToonMeet, a hybrid frame-work for high-resolution and style-controllable online meeting toonification that ensures real-time operation speed. ToonMeet applies video frame interpolation to traditional portrait toonification pipelines, allowing for the synthesis of intermediate frames between adjacent toonified keyframes, significantly accelerating the overall process and saving computational resources. However, this approach brings a new problem, where prevailing flow-based video frame interpolation methods tend to cause more ghost and blur artifacts in toonified scenes compared to non-toonified scenes, especially when fast-moving objects exist. We study this previously undiscussed problem and explore its causes. To address this, we introduce a new dataset called TM3B (Toonified Multi-modal Meeting Behaviors), offering high-resolution and cross-platform multi-modal stylized meeting data of Japanese youth in various scenarios. Then, we fine-tune ToonMeet on these tailored data and the resulting model presents improved optical flow estimation ability on toonified videos. Extensive experiments demonstrate that ToonMeet can achieve great spatiotemporal performance and perform high-quality toonification of online meetings with real-time operation speed.

    DOI: 10.1109/ICTAI59109.2023.00013

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  • System to Induce Accepting Unconsidered Information by Connecting Current Interests: Proof of Concept in Snack Purchasing Scenarios

    Taku Tokunaga, Hiromu Motomatsu, Kenji Sugihara, Honoka Ozaki, Mari Yasuda, Yugo Nakamura, Yutaka Arakawa

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   13832   105 - 119   2023   ISSN:0302-9743 ISBN:978-3-031-30932-8 eISSN:1611-3349

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    In this paper, we propose a purchasing support system for offline stores that can present information to users without being evasive by interactively presenting a small amount of product information according to their interest in the product as predicted by the system. We design and implement a proof-of-concept system for an actual use case scenario: a snack purchasing area in an office. We evaluated the effectiveness of the proposed system through a snack purchasing experiment with 11 participants. Experimental results suggest that the proposed method can induce user interest and encourage viewing and that some users may receive and consider the information presented while making a purchase.

    DOI: 10.1007/978-3-031-30933-5_8

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  • QoS-Aware Point Cloud Streaming of Wild Animals/Humans for Interactions in Virtual Space

    Hiroki Ishimaru, Yugo Nakamura, Manato Fujimoto, Hirohiko Suwa, Keiichi Yasumoto

    2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023   325 - 327   2023   ISBN:9781665453813

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    3D applications such as VR and AR are attracting increasing commercial attention, and point cloud video is expected to be one of the most suitable representations for real-time applications due to its simplicity and versatility. However, point cloud data is large in size and difficult to stream in a mobile network environment with limited bandwidth. Therefore, a method for streaming point clouds with low bandwidth consumption while maintaining the quality of the user experience is needed. In this paper, we present a point cloud streaming method of real-space objects such as humans and animals for real-time 3D reconstruction in VR space. The system uses a depth camera to scan a human or animal, divides the point cloud into parts of the body, and then controls the quality of the point cloud (i.e., resolution and frame rate) for each part in real-time according to the object's motion and context. This enables point cloud streaming with limited resources (computational and network resources) and maximizes the user's quality of experience. We exhibit a series of systems that enhance the user experience in remote communication in realistic environments and scenarios while maintaining interactivity between real-space objects and remote users.

    DOI: 10.1109/PerComWorkshops56833.2023.10150405

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  • Kaolid: Lid-type Olfactory Interface to Improve Taste of Beverages with Ortho-Retronasal Smell

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Kentaro Ueda, Shinya Misaki, Keiichi Yasumoto

    2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023   303 - 305   2023   ISBN:9781665453813

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    There are two nasal pathways through which we perceive odors: 'orthonasal smell,' which comes from the tip of the nose, and 'retronasal smell,' which comes from the mouth and exits through the nose. In particular, the retronasal smell is known to be more critical in influencing perceived taste than the orthonasal smell. In this study, we propose a smart lid called Kaolid that changes the taste of beverages by presenting scent information as retronasal smell. Kaolid achieves retronasal smell by equipping a small, lightweight straw- or cup-type olfactory device with a sensor that senses drinking behavior and the amount of water in the cup. The straw-type device injects the scent into the tube through the middle of the straw, delivering the scent to the user's mouth simultaneously as the beverage is being consumed. The cup-type device injects the scent into the cup through the lid and delivers the scent to the user's mouth at the beginning of drinking to achieve in-mouth scenting. The concept of Kaolid is to promote water consumption, considered insipid, by altering the sense of taste through a scent presented when drinking the beverage.

    DOI: 10.1109/PerComWorkshops56833.2023.10150412

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  • Efficient and Secure: Privacy-Preserving Federated Learning for Resource-Constrained Devices.

    Muhammad Ayat Hidayat, Yugo Nakamura, Yutaka Arakawa

    MDM   2023-July   184 - 187   2023   ISSN:1551-6245 ISBN:9798350341010

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    Federated learning has gained popularity as a distributed machine learning approach that provides security and privacy for data trained on local devices. However, vulnerabilities still exist in this approach, and common solutions such as encryption and blockchain techniques often suffer from high computation and communication costs, making them impractical for resource-constrained devices. To solve this problem, we propose a privacy-preserving federated learning system that leverages compressive sensing and differential privacy, specifically designed for devices with limited computational resources. In this paper, we demonstrate the capabilities of our proposed system in resource-limited environments. We outline the features, infrastructure, and algorithm of our proposed system, and simulate its performance using image datasets on a Raspberry Pi 4 and an Android smartphone in a cloud environment. Our approach offers a practical solution for secure and privacy-preserving federated learning in resource-constrained scenarios, with potential applications in various domains such as healthcare, IoT, and edge computing.

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  • Differential Privacy with Weighted for Privacy-Preservation in Human Activity Recognition

    Ryusei Fujimoto, Yugo Nakamura, Yutaka Arakawa

    2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023   634 - 639   2023   ISBN:9781665453813

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    Many services based on human activity recognition (HAR) have been developed; however, user activity data include a large amount of private information. Although privacy protection is important in activity recognition, it has not been sufficiently explored. Therefore, we propose a privacy-preserving mechanism for HAR services that uses differential privacy. The proposed method reduces the user recognition accuracy to a level that satisfies the privacy requirements by adding weighted noise to the features in the learning model construction and then improves the activity recognition accuracy (service usefulness). The results indicate that when the privacy requirement is defined as less than the probability of a user being identified by chance, the proposed method improves the activity recognition accuracy by approximately 10 % compared to the conventional method.

    DOI: 10.1109/PerComWorkshops56833.2023.10150239

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  • Design and Implementation of Nodding Recognition System Based on Chair Sway

    Toshiki Hayashida, Yugo Nakamura, Hyuckjin Choi, Yutaka Arakawa

    2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023   1 - 4   2023   ISBN:9784907626525

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    In this paper, we propose a method to measure human head motion, especially nodding, without attaching any sensors to the person. Our proposed system focuses on the fact that the upper body moves along with nodding and that the body motion slightly shakes the chair. We challenge the problem of whether it is possible to recognize a nodding from the extremely slight sway of a chair. To reveal the optimal position of sensors, we collected data by attaching multiple accelerometers to various positions on a chair, including the backrest, the seat's underside, and the legs. Using a supervised learning approach, we determined the best positions and combinations of sensors for recognizing nodding more collectively. The Support Vector Machine (SVM) achieved a nodding recognition accuracy of 0.990. Further testing of the accuracy of nodding frequency measurements resulted in an accuracy of 0.947, suggesting that the best position for the accelerometer is the backrest. These results suggest that simply placing the accelerometer on the backrest can effectively quantify the nod frequency of seated participants.

    DOI: 10.23919/ICMU58504.2023.10412249

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  • Design and Implementation of Nodding Recognition System Based on Chair Sway

    Hayashida, T; Nakamura, Y; Choi, H; Arakawa, Y

    2023 FOURTEENTH INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND UBIQUITOUS NETWORK, ICMU   2023   ISBN:978-4-907626-52-5

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  • Can a Nudge Induce Garbage Disposal Behavior? Inducement in Prosocial Behavior

    Ozono S., Kai K., Ori M., Yamazaki Y., Lian C., Kashimoto Y., Kamisaka D., Nakamura Y., Arakawa Y.

    CEUR Workshop Proceedings   3436   39 - 48   2023   ISSN:16130073

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    In this study, the target behavior of prosocial behavior was defined as garbage disposal (behavior of taking out the trash), and an intervention method using an inducement was proposed and evaluated. Specifically, we conducted an intervention in which the saturation of a trash can was visualized using a colored light that could be changed to red, yellow, and green. In addition, questionnaire surveys were administered before and after the intervention to 28 undergraduate and graduate students and faculty members, asking about their attitudes and feelings toward garbage disposal behavior, and personality traits. The results of a survey on the frequency of trash disposal be-fore and after the experiment showed that the time that the saturated trash can was left unattended was reduced by 81%. The questionnaire survey confirmed that the intervention increased the positive attitude toward trash disposal behavior, indicating that the intervention had an impact on trash disposal behavior. In addition, we were able to confirm the characteristics of individual personality traits and susceptibility to intervention.

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  • AGC-DP: Differential Privacy with Adaptive Gaussian Clipping for Federated Learning

    Hidayat M.A., Nakamura Y., Dawton B., Arakawa Y.

    Proceedings - IEEE International Conference on Mobile Data Management   2023-July   199 - 208   2023   ISSN:15516245 ISBN:9798350341010

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    Federated learning provides techniques for training algorithms using mobile or decentralized devices, in contrast to traditional machine learning in which algorithm training is performed on centralized devices. In addition, federated learning provides privacy and security features, as the client and server do not share raw data, which may contain confidential information. A number of studies have shown, however, that using federated learning alone is not enough to protect data privacy in certain situations. To overcome this problem, differential privacy is proposed, which is a technique in which artificial noise is added to the raw data. By implementing this method, a high level of privacy protection can be obtained, however this added noise also reduces model accuracy. To address this issue, this paper proposes a new approach to implement differential privacy in federated learning using adaptive Gaussian clipping. We implemented the method by tightening the privacy budget, and introducing dynamic sampling probability, adaptive clipping based on hyperparameters, and a new privacy loss calculation. Our method's main objective is to adaptively change the amount of noise given to the model, thereby maximizing the model's accuracy performance, while maintaining privacy protection levels. Evaluation results show that our proposed method presents slightly better accuracy when compared to other existing differential privacy variants such as RDP, DP-SGD, and ZcDP, for both balanced (i.i.d.) and unbalanced datasets (non-i.i.d.), for a lower total communication cost than some variants.

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  • A QoS-Aware 3D Point Cloud Streaming from Real Space for Interaction in Metaverse

    Hiroki Ishimaru, Yugo Nakamura, Manato Fujimoto, Hirohiko Suwa, Keiichi Yasumoto

    2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023   68 - 73   2023   ISBN:9781665453813

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    In this paper, we present a point cloud streaming method of real-space objects such as humans and animals for real-time 3D reconstruction in VR space. The system uses a depth camera to scan a human or animal, divides the point cloud into parts of the body, and then controls the quality of the point cloud (i.e., resolution and frame rate) for each part in real-time according to the object's motion and context. This enables point cloud streaming with limited resources (computational and network resources) and maximizes the user's quality of experience (QoE). We have implemented and evaluated a series of systems incorporating the proposed method to enhance the user experience in realistic environments and scenarios while maintaining interactivity in VR-based online communication. The results show that the proposed system is feasible under resource-constrained environments without significantly affecting the user's QoE.

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  • A Method for Expressing Intention for Suppressing Careless Responses in Participatory Sensing Reviewed International journal

    Kohei Oyama, Yuki Matsuda, Rio Yoshikawa, Yugo Nakamura, Hirohiko Suwa, Keiichi Yasumoto

    Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering   419 LNICST   769 - 782   2022.11

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    DOI: 10.1007/978-3-030-94822-1_50

  • Aromug: Mug-type Olfactory Interface to Assist in Reducing Sugar Intake Reviewed International journal

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Shinya Misaki, Keiichi Yasumoto

    UbiComp/ISWC 2022 Adjunct - Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers   183 - 187   2022.9   ISBN:9781450394239

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    Reducing the amount of sugar consumed from daily beverages is essential for well-being. However, since a sudden reduction in intake is mentally painful for those who prefer sweetened beverages, solutions are needed to help them gradually become accustomed to non-sweetened drinks. In this paper, we propose Aromug, a mug-type olfactory interface that amplifies the user's perceived sweetness by providing a sweet scent along with the action of drinking. Through user studies, we investigated the effect of the information presented by Aromug on the taste of iced coffee. The experiment results showed that the sugar-free coffee and chocolate aroma might enhance the perceived sweetness compared to the no-scent case. In addition, it was suggested that there were differences in preference for sweetness depending on age and frequency of coffee drinking.

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  • Color-wall: Adaptive Color Filter to Reduce Digital Distractions during PC Work Reviewed International journal

    Yugo Nakamura, Hirokazu Tanaka, Yutaka Arakawa

    UbiComp/ISWC 2022 Adjunct - Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers   193 - 197   2022.9   ISBN:9781450394239

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    As the Attention Economy has grown, numerous digital contents are made with the intention of capturing users' attention and spending more of their time by the use of attractive graphics and color psychology. In this paper, we propose a novel defense strategy, called a color-wall, to block digital distraction brought on by the consumption of visually seductive and addictive digital content. When it detects that a user is viewing media or using applications unrelated to the main task, it removes colors from the screen (gray-scaling) to make them less aesthetically pleasing and directs the user away from looking at them. We implemented a mac OS software as a proof-of-concept for the color-wall and conducted user testing (N=14) to assess the effectiveness of the proposed strategy. The evaluation results suggest that the color-wall is an effective strategy for reducing unwanted digital distractions such as browsing restricted content (YouTube, Twitter, etc.) while working on a PC.

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  • Inertial Measurement Unit-sensor-based Short Stick Exercise Tracking to Improve Health of Elderly People Reviewed International journal

    Kazuki Oi, Yugo Nakamura, Yuki Matsuda, Manato Fujimoto, Keiichi Yasumoto

    Sensors and Materials   34 ( 8 )   2911 - 2911   2022.8   ISSN:0914-4935 eISSN:2435-0869

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    Short stick exercises have been attracting attention from the viewpoint of preventing falls and improving the health of elderly people and are generally performed under the guidance of instructors and nursing staff at nursing homes. However, in situations such as the COVID-19 pandemic, where people should refrain from unnecessary outings, it is advisable that individuals perform short stick exercises at home and record their exercise implementation status. In this paper, we propose an inertial measurement unit (IMU)-sensor-based short stick exercise tracking method that can automatically record the types and amounts of exercises performed using a short stick equipped with an IMU sensor. The proposed method extracts time-domain and frequency-domain features from linear acceleration and quaternion time-series data obtained from the IMU sensor and classifies the type of exercise using an inference model based on machine learning algorithms. To evaluate the proposed method, we collected sensor data from 21 young subjects (in their 20s) and 14 elderly subjects (79-95 years old), where the participants performed three sets (10 times per set) of eight basic types of short stick exercises (five types for elderly people). As a result of evaluating the proposed method using this data set, we confirmed that when LightGBM was used as the learning algorithm, it achieved F values of 90.0 and 86.6% for recognizing the type of exercise for young and elderly people, respectively.

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  • Estimating Congestion in Train Cars by Using BLE Signals Reviewed International journal

    Eigo Taya, Yuji Kanamitsu, Koki Tachibana, Yugo Nakamura, Yuki Matsuda, Hirohiko Suwa, Keiichi Yasumoto

    2022 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop (DI-CPS)   1 - 7   2022.5   ISBN:978-1-6654-7042-1

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    In many of the world's major cities, commuter trains provide vital transportation support and thus play an essential role in our daily lives. Therefore, it has become necessary to estimate the degree of congestion in each train car, both to improve passenger comfort levels and, more recently, to prevent worsening the COVID-19 pandemic infection rate. However, it is difficult to estimate the degree of congestion within a train without violating passenger privacy. The same issues are true for busses, which is noteworthy because we have previously developed and evaluated a system that can estimate the degree of congestion within a bus while protecting passenger privacy by using Bluetooth Low Energy (BLE) signals. In this paper, we report on our efforts to extend that system to railway use, which were conducted on actual trains in cooperation with Kintetsu Railway Co., Ltd. During this trial, we collected BLE signals and used the data to estimate congestion levels in each car using an ML regression model. The results show that the mean absolute error (MAE) and the mean absolute percentage error (MAPE) could be estimated at accuracy levels of 5.56 and 0.27, respectively.

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  • Short Stick Exercise Tracking System for Elderly Rehabilitation using IMU Sensor Reviewed International journal

    Kazuki Oi, Yugo Nakamura, Yuki Matsuda, Manato Fujimoto, Keiichi Yasumoto

    2022 2nd International Workshop on Cyber-Physical-Human System Design and Implementation (CPHS)   13 - 18   2022.5   ISBN:9781665482035

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    Stick exercises, which have been attracting attention for improving the health of the elderly, are usually performed in nursing homes under the guidance of nursing staff. However, in the current pandemic in which the elderly are advised to refrain from going out unnecessarily, it is desirable for each individual to be able to perform the stick exercises alone. In this study, we aim to develop a stick exercise support system that can automatically record the number of times an elderly person performs each type of stick exercise and provide feedback to improve the movement for each exercise. As a first step toward the realization of this stick exercise support system, we investigated a method for recognizing exercise movements using inertial measurement unit (IMU) sensors. In the evaluation experiment, 21 subjects performed 3 sets (10 times per set) of eight basic stick exercises. The exercise movements were classified based on the linear acceleration and quaternion data obtained from the IMU. As a result, 90% of F-measure was achieved when using Light GBM as the learning algorithm.

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  • ZEL: Net-Zero-Energy Lifelogging System using Heterogeneous Energy Harvesters Reviewed International journal

    Mitsuru Arita, Yugo Nakamura, Shigemi Ishida, Yutaka Arakawa

    2022 IEEE International Conference on Pervasive Computing and Communications (PerCom)   2022.3

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    DOI: 10.1109/percom53586.2022.9762376

  • FedTour: Participatory Federated Learning of Tourism Object Recognition Models with Minimal Parameter Exchanges between User Devices. Reviewed International journal

    Shusaku Tomita, Jose Paolo Talusan, Yugo Nakamura, Hirohiko Suwa, Keiichi Yasumoto

    PerCom Workshops   667 - 673   2022.3   ISBN:978-1-6654-1647-4

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    In this paper, we propose FedTour, a federated learning-based method for training tourism object recognition models, which utilizes short-distance direct communication between user devices and maximizes the model performance within a limited number of updates. In FedTour, whenever two user devices are within range, they first exchange metadata including the learning degree (e.g., recognition accuracy) of their models, and determine whether it is effective to integrate the peer model by using a regressor trained with various pairs of models with different accuracy to predict the accuracy of the merged model. Once it is deemed effective, the model parameters are exchanged and the model is updated using FedAvg (averaging weights of two models of user devices). By carefully setting the threshold of whether FedAvg is applied or not, model performance is improved within a limited number of model parameter exchanges resulting in lower power consumption of user devices. We conducted a simulation using mobile phone trace data of actual users in a real sightseeing area and evaluated the improvement in accuracy of a CNN model that recognizes 10 objects while limiting the number of model parameter exchanges to only 40. Results show FedTour increased the initial model accuracy by 112%, while the baseline gossip-based method achieved 69%.

    DOI: 10.1109/PerComWorkshops53856.2022.9767391

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  • Aroma Nudges: Exploring the Effects on Shopping Behavior in a Supermarket Reviewed International journal

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Tomokazu Matsui, Shinya Misaki, Keiichi Yasumoto, Junko Nohara

    CEUR Workshop Proceedings   3153   2022.3

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  • Augmented Web Survey with enhanced response UI for Touch-based Psychological State Estimation. Reviewed International journal

    Takaaki Nakagawa, Yutaka Arakawa, Yugo Nakamura

    LifeTech   91 - 95   2022.3   ISBN:9781665419048

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    In this paper, we propose a method for estimating psychological states such as hesitation and interest during survey responses based on touch operation behavior (touch log). In addition, we propose two enhanced web survey RUIs (Response User Interfaces), (a) a slidebar type RUI and (b) a magnifier type RUI, to expand the operational differences due to hesitation and interest for more accurate estimation. To evaluate the proposed RUIs, we implemented Augmented Web Survey (AWS) as an extension of LimeSurvey and conducted two experiments. Responses were collected from 8 subjects in the experiment to evaluate (a) a slidebar type RUI and from 21 subjects to evaluate (b) a magnifier type RUI. We measured the degree of hesitation by evaluating the subjective hesitation to the questions on a 5-point scale. For the measurement of the degree of interest, the participants were asked to select their top two favorite images among the six images, and the true value was taken as the top two. As a result of comparing the operation logs of the conventional RUI and the slidebar type RUI, it was confirmed that there was a significant difference depending on the degree of hesitation. In addition, more magnification operations were obtained for the magnifier type RUI than the standard pinch-out operation suggesting that it may help estimate psychological states such as hesitation.

    DOI: 10.1109/LifeTech53646.2022.9754964

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  • Context-Aware Chatbot Based on Cyber-Physical Sensing for Promoting Serendipitous Face-to-Face Communication. Reviewed International journal

    Hirokazu Tanaka, Hiromu Motomatsu, Yugo Nakamura, Yutaka Arakawa

    PERSUASIVE   13213 LNCS   230 - 239   2022.3   ISSN:0302-9743 ISBN:978-3-030-98437-3 eISSN:1611-3349

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    To promote the face-to-face communication reduced by COVID-19, we proposed and implemented a context-aware Slack chatbot based on Cyber-Physical sensing that helps colleagues meet more often in the same place. Our system periodically collects the user’s internal context through Slack (cyber sensing) and uses small BLE beacons distributed to colleagues and beacon scanners installed in a laboratory to sense physical attendance (physical sensing). In addition, the system notifies the user of recommended actions, such as lunch or coffee break, depending on the context determined by the Cyber-Physical sensors. We deployed the proposed system in a laboratory environment and conducted an initial experiment for six weeks. Experimental results confirmed that our system can encourage serendipitous face-to-face communication during periods when the frequency of attending school and going to work dropped due to COVID-19. It was also found that in an environment such as a laboratory, where a certain level of trust has already been established, the openness of the collected information can further motivate users to participate in the system.

    DOI: 10.1007/978-3-030-98438-0_18

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  • Design and Development of Appendable Elevator Monitoring System to Nudge People Behavior Change. Reviewed International journal

    Yuta Ohira, Yugo Nakamura, Yutaka Arakawa

    PERSUASIVE (Adjunct)   3153   2022.3

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  • Design and Development of Appendable Elevator Monitoring System to Nudge People Behavior Change.

    Yuta Ohira, Yugo Nakamura, Yutaka Arakawa

    PERSUASIVE (Adjunct)   3153   2022.3   ISSN:1613-0073

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    In this study, we propose a behavior change support system that encourages people to use stairs instead of elevators. Using the stairs is not only good for one's health, but nowadays it also plays a role in dense avoidance from the perspective of COVID-19. Although many people are waiting for the elevator, we thought that if we knew how many people were on the elevator, more people could change their behavior. However, there are few buildings where the number of people in the elevator is displayed on each floor. So, we have developed a headcount measurement system in the cargo and a visualization system, those can be easily appended to the current elevator. As a method to measure the number of people in an elevator, we propose a method to detect BLE (Bluetooth Low Energy) signals transmitted from the terminals of elevator users who have installed COCOA, an application for confirming contact with the COVID-19 in Japan, and to measure in real time the number of detected BLE signals with a received signal strength (RSSI) exceeding a certain value. We propose a method to measure the number of BLE signals detected in real time. In this paper, we have designed and developed the system, verified the accuracy of the detection of the continuous operation time and the number of passengers, and estimated the behavior pattern and waiting time of elevator users using the system. The evaluation of the transformation of the decision making of the elevator users brought about by this system is out of the scope of this paper and will be discussed in the future.

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    Other Link: https://dblp.uni-trier.de/rec/conf/persuasive/2022a

  • Short Stick Exercise Tracking System for Elderly Rehabilitation using IMU Sensor

    Oi, K; Nakamura, Y; Matsuda, Y; Fujimoto, M; Yasumoto, K

    2ND INTERNATIONAL WORKSHOP ON CYBER-PHYSICAL-HUMAN SYSTEM DESIGN AND IMPLEMENTATION (CPHS 2022)   13 - 18   2022   ISBN:978-1-6654-8203-5

  • Learning Cross-Modal Factors from Multimodal Physiological Signals for Emotion Recognition.

    Yuichi Ishikawa, Nao Kobayashi, Yasushi Naruse, Yugo Nakamura, Shigemi Ishida, Tsunenori Mine, Yutaka Arakawa

    PRICAI (1)   14325 LNAI   438 - 450   2022   ISSN:0302-9743 ISBN:9789819970186 eISSN:1611-3349

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    Understanding user emotion is essential for Human-AI Interaction (HAI). Thus far, many approaches have been studied to recognize emotion from signals of various physiological modalities such as cardiac activity and skin conductance. However, little attention has been paid to the fact that physiological signals are influenced by and reflect various factors that have little or no association with emotion. While emotion is a cross-modal factor that triggers responses across multiple physiological modalities, features used in existing approaches also reflect modality-specific factors that affect only a single modality and have little association with emotion. To address this, we propose an approach to extract features that exclusively reflect cross-modal factors from multimodal physiological signals. Our approach introduces a multilayer RNN with two types of layers: multiple Modality-Specific Layers (MSLs) for modeling physiological activity in individual modalities and a single Cross-Modal Layer (CML) for modeling the process by which emotion affects physiological activity. By having all MSLs update their hidden states using the CML hidden states, our RNN causes the CML to learn cross-modal factors. Using real physiological signals, we confirmed that the features extracted by our RNN reflected emotions to a significantly greater extent than the features of existing approaches.

    DOI: 10.1007/978-981-99-7019-3_40

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    Other Link: https://dblp.uni-trier.de/db/conf/pricai/pricai2023-1.html#IshikawaKNNIMA22

  • How do Programmers Use the Internet? Discovering Domain Knowledge from Browsing and Coding Behaviors.

    Ko Watanabe, Yuki Matsuda 0001, Yugo Nakamura, Yutaka Arakawa, Shoya Ishimaru

    iThings/GreenCom/CPSCom/SmartData/Cybermatics   605 - 610   2022   ISBN:9781665454179

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    The Internet is an effective tool for learners to gain new knowledge. Often, people use search engines (e.g., Google) rather than accessing websites directly. People have their search techniques to find specific information. In particular, people with domain knowledge tend to search more efficiently than novices. By understanding the gap between people with domain knowledge and novices, the novice can understand the path to becoming an expert. Therefore, in this study, we wanted to know what differences exist in search and programming behavior with and without domain knowledge. In this experiment, we asked a group with and without domain knowledge to solve ten programming problems and collected search logs (input knowledge) and compilation logs (output knowledge). Specifically, the first dataset consisted of 13 participants who had taken a university programming class. The second dataset consisted of 20 participants who had not taken a programming class and had no domain knowledge. We examined differences in search and compilation behavior based on participants' domain knowledge from this data. Since we observed a difference between each group when referring to the correlation coefficient, we performed a binary classification of novice and experienced participants using Random Forest, and achieved an average precision of 0.95, indicating that there were different trends in behavior with and without domain knowledge.

    DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics55523.2022.00034

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    Other Link: https://dblp.uni-trier.de/db/conf/ithings/ithings2022.html#WatanabeMNAI22

  • Design and development of appendable elevator monitoring system to nudge people behavior change

    Ohira Y., Nakamura Y., Arakawa Y.

    CEUR Workshop Proceedings   3153   2022   ISSN:16130073

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    In this study, we propose a behavior change support system that encourages people to use stairs instead of elevators. Using the stairs is not only good for one's health, but nowadays it also plays a role in dense avoidance from the perspective of COVID-19. Although many people are waiting for the elevator, we thought that if we knew how many people were on the elevator, more people could change their behavior. However, there are few buildings where the number of people in the elevator is displayed on each floor. So, we have developed a headcount measurement system in the cargo and a visualization system, those can be easily appended to the current elevator. As a method to measure the number of people in an elevator, we propose a method to detect BLE (Bluetooth Low Energy) signals transmitted from the terminals of elevator users who have installed COCOA, an application for confirming contact with the COVID-19 in Japan, and to measure in real time the number of detected BLE signals with a received signal strength (RSSI) exceeding a certain value. We propose a method to measure the number of BLE signals detected in real time. In this paper, we have designed and developed the system, verified the accuracy of the detection of the continuous operation time and the number of passengers, and estimated the behavior pattern and waiting time of elevator users using the system. The evaluation of the transformation of the decision making of the elevator users brought about by this system is out of the scope of this paper and will be discussed in the future.

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  • Aroma Nudges: Exploring the Effects on Shopping Behavior in a Supermarket

    Daiki Mayumi, Yugo Nakamura, Yuki Matsuda, Tomokazu Matsui, Shinya Misaki, Keiichi Yasumoto, Junko Nohara

    CEUR Workshop Proceedings   3153   2022   ISSN:16130073

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    Due to the pandemic of COVID-19, product sampling at supermarkets has been restricted, and the disposal of unsold vegetables and other perishable foods has become a problem. To explore alternatives to product sampling, this study focuses on the “aroma” generated during product sampling and explores the effect of aroma nudges on purchasing behavior. Specifically, we focused on the scenario of promoting the purchase of Yamato-maru eggplant, a traditional vegetable of Nara Prefecture in Japan. We conducted an experiment in a supermarket for two months, from June to July of 2021, the season of the Yamato-maru eggplant. We compared the number of visits to the sales booth, the time spent in the booth, and the sales volume under four conditions: (1) no presentation, (2) presentation of paper media, (3) presentation of the paper and video media, and (4) presentation of a paper, video, and olfactory media. The experiment results suggest that the inclusion of aroma nudges has a positive potential to attract consumer interest and positively influence their purchasing decisions.

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  • Estimating Work Engagement with Wrist-Worn Heart Rate Sensors. Reviewed International journal

    Haruki Harashima, Yutaka Arakawa, Shigemi Ishida, Yugo Nakamura

    ICMU   1 - 6   2021.10

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    DOI: 10.23919/ICMU50196.2021.9638884

  • Using Interaction as Nudge to Increase Installation Rate of COVID-19 Contact-Confirming Application Reviewed International journal

    Yuji Kanamitsu, koki tachibana, Yugo Nakamura, Yuki Matsuda, Hirohiko Suwa, Keiichi Yasumoto

    Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers   36 - 37   2021.9

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    DOI: 10.1145/3460418.3479284

  • Eat2pic: Food-tech Design as a Healthy Nudge with Smart Chopsticks and Canvas Reviewed International journal

    Rei Nakaoka, Yugo Nakamura, Yuki Matsuda, Shinya Misaki, Keiichi Yasumoto

    2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021   389 - 391   2021.3

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    DOI: 10.1109/PerComWorkshops51409.2021.9431002

  • ProceThings: Data Processing Platform with In-situ IoT Devices for Smart Community Services Reviewed International journal

    Yugo Nakamura, Jose Paolo Talusan, Teruhiro Mizumoto, Hirohiko Suwa, Yutaka Arakawa, Hirozumi Yamaguchi, Keiichi Yasumoto

    ACM International Conference Proceeding Series   116 - 121   2021.1

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    DOI: 10.1145/3427477.3429275

  • A nudge-based smart system for hand hygiene promotion in private organizations: Poster abstract Reviewed International journal

    Sopicha Stirapongsasuti, Kundjanasith Thonglek, Shinya Misaki, Bunyapon Usawalertkamol, Yugo Nakamura, Keiichi Yasumoto

    SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems   743 - 744   2020.11

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    DOI: 10.1145/3384419.3430595

  • Privacy-Aware Sensor Data Upload Management for Securely Receiving Smart Home Services Reviewed International journal

    Sopicha Stirapongsasuti, Yugo Nakamura, Keiichi Yasumoto

    Proceedings - 2020 IEEE International Conference on Smart Computing, SMARTCOMP 2020   214 - 219   2020.9

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    DOI: 10.1109/SMARTCOMP50058.2020.00048

  • On-site Trip Planning Support System Based on Dynamic Information on Tourism Spots Reviewed International journal

    Masato Hidaka, Yuki Kanaya, Shogo Kawanaka, Yuki Matsuda, Yugo Nakamura, Hirohiko Suwa, Manato Fujimoto, Yutaka Arakawa, Keiichi Yasumoto

    Smart Cities   3 ( 2 )   212 - 231   2020.4

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    DOI: 10.3390/smartcities3020013

  • Strike activity detection and recognition using inertial measurement unit towards kendo skill improvement support system Reviewed International journal

    Yohei Torigoe, Yugo Nakamura, Manato Fujimoto, Yutaka Arakawa, Keiichi Yasumoto

    Sensors and Materials   32 ( 2 )   651 - 673   2020.1

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    DOI: 10.18494/SAM.2020.2615

  • Waistonbelt x: A belt-type wearable device with sensing and intervention toward health behavior change Reviewed International journal

    Yugo Nakamura, Yuki Matsuda, Yutaka Arakawa, Keiichi Yasumoto

    Sensors (Switzerland)   19 ( 20 )   4600 - 4600   2019.10

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    DOI: 10.3390/s19204600

  • Data collection and index creation for the vacant rental property using IoT sensing Reviewed International journal

    Hirohiko Suwa, Atsushi Otsubo, Yugo Nakamura, Masahito Noguchi

    2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019   449 - 450   2019.10

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    DOI: 10.1109/GCCE46687.2019.9015533

  • EHAAS: Energy harvesters as a sensor for place recognition on wearables Reviewed International journal

    Yoshinori Umetsu, Yugo Nakamura, Yutaka Arakawa, Manato Fujimoto, Hirohiko Suwa

    2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019   abs/1903.08592   1 - 10   2019.3

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    DOI: 10.1109/PERCOM.2019.8767385

  • Strikes-Thrusts Activity Recognition Using Wrist Sensor Towards Pervasive Kendo Support System Reviewed International journal

    Masashi Takata, Yugo Nakamura, Yohei Torigoe, Manato Fujimoto, Yutaka Arakawa, Keiichi Yasumoto

    2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019   243 - 248   2019.3

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    DOI: 10.1109/PERCOMW.2019.8730861

  • Evaluating Performance of In-Situ Distributed Processing on IoT Devices by Developing a Workspace Context Recognition Service Reviewed International journal

    Jose Paolo Talusan, Francis Tiausas, Sopicha Stirapongsasuti, Yugo Nakamura, Teruhiro Mizumoto, Keiichi Yasumoto

    2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019   633 - 638   2019.3

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    DOI: 10.1109/PERCOMW.2019.8730693

  • 混雑度の偏りを考慮した避難所決定手法 Reviewed

    梅木寿人, 中村優吾, 藤本まなと, 水本旭洋, 諏訪博彦, 荒川豊, 安本慶一

    情報処理学会論文誌   60 ( 2 )   608 - 616   2019.2

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    地震などの突発的災害発生時において,避難所への速やかな避難は重要な防災・減災対策の1つである.現状,災害時の避難誘導は,現在地から最寄りの避難所へと誘導するものが一般的である.しかしながら,災害発生時に,大多数の人々が特定エリアに偏って集中するような状況下においては,単に最寄りの避難所に誘導するだけでは避難所の収容数の超過を招き,別の避難所への移動を余儀なくされる.結果として,被災者は空きのある避難所へたどり着くまでたらい回しにされ,避難が大幅に遅れてしまう問題が生じる.本論文では,この問題を解決するために,多くの人々が活動している地域を対象として,被災者全体の避難時間を削減することを目的とする避難所決定手法を提案する.具体的には,被災時における被災者の位置情報と各避難所の収容可能数に基づいて,被災者全体の避難時間が短くなるように避難所を決定する.提案手法の有効性を評価するために,京都の祇園祭を想定したシミュレーション環境を構築し,一般的な避難所決定手法である最短経路選択およびランダム選択を適用した場合と提案手法を適用した場合の避難時間を比較した.その結果,提案手法を用いた場合に,最短経路選択と比較して平均避難時間を35.9&#37;削減できることを明らかにした.また,提案手法に従う人が全体の20&#37;であっても,平均避難時間を8.1&#37;削減できることを確認した.この結果から,たとえ一部の人であっても,提案手法に従って避難することによって,全体の避難時間を短縮でき,防災・減災に寄与できることが分かった.
    The quick and appropriate evacuation of the disaster victims is one of great concern in the disaster situation. Under the disaster situations, it is general that the victims evacuate from the present location to the nearest evacuation center depending on evacuation guidance. However, in case of the situation that many victims are at biased distribution to specific areas, the guidance to the closest evacuation center concentrates many victims to particular evacuation. As a result, the victims who could not enter the closest evacuation center need to evacuate to other evacuation centers, until accepted. Therefore, the problem occurs that the evacuation of victims is delayed significantly. In this paper, to solve this problem, we propose an evacuation center determination method aimed at reducing the evacuation time of the whole victims. Specifically, the proposed method determines an evacuation center so that the evacuation time of all victims becomes short based on the location information of victims and the capacity of evacuation centers. To evaluate the effectiveness of the proposed method, we compared our proposed method with the shortest route selection method and random selection method, by using the simulation study assuming the situation of the Gion festival in Kyoto. As a result, when using the proposed method, we showed that the average evacuation time can be reduced to 35.9&#37; compared with the shortest route selection method. Also, we confirmed that the average evacuation time can be reduced to 8.1&#37; even if victims who follow the proposed method is 20&#37; of the total. From these results, even if victims who follow the proposed method is a part of the total, we showed that our method can reduce the overall evacuation time, and contribute to disaster prevention.

  • Design and Evaluation of In-Situ Resource Provisioning Method for Regional IoT Services Reviewed International journal

    Yugo Nakamura, Teruhiro Mizumoto, Hirohiko Suwa, Yutaka Arakawa, Hirozumi Yamaguchi, Keiichi Yasumoto

    2018 IEEE/ACM 26th International Symposium on Quality of Service, IWQoS 2018   1 - 2   2019.1

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    DOI: 10.1109/IWQoS.2018.8624127

  • In-situ resource provisioning with adaptive scale-out for regional IoT services Reviewed International journal

    Yugo Nakamura, Teruhiro Mizumoto, Hirohiko Suwa, Yutaka Arakawa, Hirozumi Yamaguchi, Keiichi Yasumoto

    Proceedings - 2018 3rd ACM/IEEE Symposium on Edge Computing, SEC 2018   203 - 213   2018.12

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    DOI: 10.1109/SEC.2018.00022

  • Real-Time Congestion Estimation in Sightseeing Spots with BLE Devices Reviewed International journal

    Kazuhito Umeki, Yugo Nakamura, Manato Fujimoto, Yutaka Arakawa, Keiichi Yasumoto

    2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018   430 - 432   2018.10

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    DOI: 10.1109/PERCOMW.2018.8480395

  • Investigating the capitalize effect of sensor position for training type recognition in a body weight training support system Reviewed International journal

    Masashi Takata, Manato Fujimoto, Keiichi Yasumoto, Yugo Nakamura, Yutaka Arakawa

    UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers   1404 - 1408   2018.10

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    DOI: 10.1145/3267305.3267504

  • Multi-stage activity inference for locomotion and transportation analytics of mobile users Reviewed International journal

    Yugo Nakamura, Yoshinori Umetsu, Jose Paolo Talusan, Keiichi Yasumoto, Wataru Sasaki, Masashi Takata, Yutaka Arakawa

    UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers   1579 - 1588   2018.10

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    DOI: 10.1145/3267305.3267526

  • Poster: Feasibility study toward a battery-free place recognition system based on solar cells Reviewed International journal

    Yutaka Arakawa, Yugo Nakamura, Hirohiko Suwa, Yoshinori Umetsu, Manato Fujimoto, Keiichi Yasumoto

    UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers   1 - 4   2018.10

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    DOI: 10.1145/3267305.3267624

  • Near Cloud: Low-cost Low-Power Cloud Implementation for Rural Area Connectivity and Data Processing Reviewed International journal

    Jose Paolo Talusan, Yugo Nakamura, Teruhiro Mizumoto, Keiichi Yasumoto

    Proceedings - International Computer Software and Applications Conference   2   622 - 627   2018.6

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    DOI: 10.1109/COMPSAC.2018.10307

  • SenStick: Comprehensive Sensing Platform with an Ultra Tiny All-In-One Sensor Board for IoT Research Reviewed International journal

    Yugo Nakamura, Yutaka Arakawa, Takuya Kanehira, Masashi Fujiwara, Keiichi Yasumoto

    Journal of Sensors   2017   6308302 - 16   2017.9

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    DOI: 10.1155/2017/6308302

  • A System for Collecting and Curating Sightseeing Information toward Satisfactory Tour Plan Creation Reviewed International journal

    Masato Hidaka, Yuki Matsuda, Shogo Kawanaka, Yugo Nakamura, Manato Fujimoto, Yutaka Arakawa, Keiichi Yasumoto

    2017.8

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  • Senstick: A rapid prototyping platform for sensorizing things Reviewed International journal

    Yugo Nakamura, Yutaka Arakawa, Keiichi Yasumoto

    2016 9th International Conference on Mobile Computing and Ubiquitous Networking, ICMU 2016   31 - 36   2016.11

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    DOI: 10.1109/ICMU.2016.7742087

  • Design and Implementation of Middleware for IoT Devices toward Real-Time Flow Processing Reviewed International journal

    Yugo Nakamura, Hirohiko Suwa, Yutaka Arakawa, Hirozumi Yamaguchi, Keiichi Yasumoto

    Proceedings - 2016 IEEE 36th International Conference on Distributed Computing Systems Workshops, ICDCSW 2016   162 - 167   2016.11

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    DOI: 10.1109/ICDCSW.2016.37

  • Smart experimental platform for collecting various sensing data from various things Reviewed International journal

    Yugo Nakamura, Yutaka Arakawa, Keiichi Yasumoto

    UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing   1751 - 1754   2016.9

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    DOI: 10.1145/2968219.2968268

  • SenStick 2: Ultra tiny all-in-one sensor with wireless charging Reviewed International journal

    Yugo Nakamura, Takuya Kanehira, Yutaka Arakawa, Keiichi Yasumoto

    UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing   337 - 340   2016.9

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    DOI: 10.1145/2968219.2971399

  • Smart Experiment Platform for Wearable Computing Reviewed International journal

    Yugo Nakamura, Yutaka Arakawa, Keiichi Yasumoto

    First Workshop on Eye Wear Computing collocated with ISWC/UbiComp (EYEWEAR 2016)   2016.9

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    Smart Experiment Platform for Wearable Computing

  • Middleware for Proximity Distributed Real-Time Processing of IoT Data Flows Reviewed International journal

    Yugo Nakamura, Hirohiko Suwa, Yutaka Arakawa, Hirozumi Yamaguchi, Keiichi Yasumoto

    Proceedings - International Conference on Distributed Computing Systems   2016-August   771 - 772   2016.8

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    DOI: 10.1109/ICDCS.2016.101

  • CMSAS: A concept of middleware architecture to integrate heterogeneous sensor networks and actuators Reviewed International journal

    Yugo Nakamura, Takahiro Fujiwara

    S3 2014 - Proceedings of the 6th ACM MobiCom Workshop on Wireless of the Students, by the Students, for the Students   25 - 27   2014.9

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    DOI: 10.1145/2645884.2645888

  • A model for earthquake acceleration monitoring with wireless sensor networks in a structure Reviewed International journal

    Takahiro Fujiwara, Yugo Nakamura, Kousei Jinno, Taku Matsubara, Hideyuki Uehara

    SPIE Proceedings   2014.3

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    DOI: 10.1117/12.2044929

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Presentations

  • IoTセンサを用いたロバストな行動認識技術 Invited

    中村優吾

    応用物理学会「トータルバイオミメティクス領域グループ」シンポジウム  2020.11 

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  • 健康行動セキュリティのためのエンパワメントICTの実現に向けて Invited

    中村 優吾

    情報処理学会・第85回全国大会 企画セッション「Society 5.0時代の安心・安全・信頼を支える基盤ソフトウェア技術の構築」  2023.3 

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  • 健康行動セキュリティに基づくエンパワメントICTの実現に向けて Invited

    中村 優吾

    第104回モバイルコンピューティングと新社会システム・第75回ユビキタスコンピューティングシステム・第35回コンシューマ・デバイス&システム・第24回高齢社会デザイン合同研究発表会 若手研究者招待講演  2022.9 

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MISC

  • ゴミ捨て行動における誘因を活用した介入による行動変容に関する調査

    大園, 咲奈, 甲斐, 貴一朗, 織, 睦樹, 中村, 優吾, 荒川, 豊, 山崎, 悠大, 曹, 蓮, 柏本, 幸俊, 上坂, 大輔

    行動変容と社会システム vol.09   2023.3

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    近年,社会課題解決のための行動変容を促す様々な介入手段が検討されており,その中でも他人や他のの団体,社会のために行う行動である,向社会的行動の促進技術の研究が注目を浴びている.向社会的行動促進に関する従来研究では,短期的ではあるが大きな効果が期待できる,『誘因』による向社会的行動の促進要因が何であるか考察が十分になされていない.そこで本研究では,向社会的行動の対象行動をゴミ捨てと定め,誘因による介入手法の提案,及び被験者の行動とアンケート調査による評価を行った.具体的には,大学生・大学院生・教員28名を対象として,ゴミ箱の飽和度を赤,黄色,緑の色に変えられるカラーライトで可視化する誘因介入を行い,介入前後に個人のパーソナリティ特性や心理,態度を評価するアンケート調査を実施した.実験結果より誘因が対象行動に与える効果,及び介入による影響の受けやすさと各パーソナリティ特性や心理,態度との関係性を分析する.ゴミ捨て頻度の調査の結果,飽和したゴミ箱が放置される時間が83%短縮される結果となった.アンケート調査からは,介入によるゴミ捨て行動への積極性の向上が確認され,介入がゴミ捨て行動に影響を与えることが明らかとなった.一方で,個人の性格特性と介入による影響の受け方に大きな相関関係は見られず,本研究での性格特性の分析手法では,課題が発生する可能性があると考えらた.
    In recent years, various intervention methods to promote behavioral change for solving social problems have been studied, and among them, research on techniques to promote prosocial behavior, which is behavior performed for the benefit of others, other groups, and society, has attracted much attention. Conventional studies on the promotion of prosocial behavior have not sufficiently examined the factors that promote prosocial behavior by "inducements," which are expected to have a short-term but significant effect. In this study, the target behavior of prosocial behavior was defined as garbage disposal, and an intervention method with incentives was proposed and evaluated by the subjects' behavior and questionnaire surveys. Specifically, we conducted an incentive intervention in which the saturation of trash cans was visualized using colored lights that could be changed to red, yellow, and green, and a questionnaire survey was conducted before and after the intervention to evaluate individual personality characteristics, psychology, and attitudes. The results of the experiment show the effect of the inducement on the target behavior, and the relationship between the susceptibility to the intervention and each personality trait, psychology, and attitude. The results of a survey on the frequency of garbage disposal showed that the time that saturated garbage cans were left unattended was reduced by 83&#37;. The questionnaire survey confirmed that the intervention increased the positive attitude toward trash disposal behavior, indicating that the intervention had an impact on trash disposal behavior. On the other hand, there was no significant correlation between the personality characteristics of the individuals and the way they were affected by the intervention, suggesting that the analysis method of personality characteristics in this study may have some problems.

  • リアルタイム感情フィードバックによるカメラオフ会議でのコミュニケーションの円滑化

    甲斐, 貴一朗, 織, 睦樹, 江口, 直輝, 大平, 祐大, 中村, 優吾, 福嶋, 政期, 荒川, 豊

    第30回マルチメディア通信と分散処理ワークショップ論文集   2022.10

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    カメラやマイクをミュートにしたオンライン会議で参加者の反応を知ることは困難である.対話相手からのフィードバックが少ない状況では,話者は話しづらさを感じ,聴者は会議への積極性が低下するといった課題がある.我々は,オンライン会議で不足している対話相手からのフィードバックを補填するために,参加者の表情認識から推定された感情を絵文字としてリアルタイムにフィードバックするシステム「REmotion」の開発を行っている.我々の目的は,本システムをオンライン会議で用いることで,話者の話しづらさを解消することと聴者の会議への積極性を向上させることである.そのために,参加者が対話相手を意識して表情を変化させることが重要だと考える.本論文では,開発したシステムを用いて実験を行い,参加者がカメラやマイクをミュートにして参加するオンライン会議で本システムを用いると,参加者が自分の表情を意識的に変化させることを明らかにした.

  • 購買時の候補商品推定システムの構築と初期評価

    徳永, 大空, 本松, 大夢, Chen, Bin, 中村, 優吾, 荒川, 豊

    マルチメディア,分散,協調とモバイルシンポジウム2022論文集   2022.7

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    オンライン購買システムは,ページ遷移やクリックの履歴から購買者が商品の購買に至るまでの過程を記録することができる.これにより,興味がある商品や比較検討した商品がわかり,購買者のニーズに近く購買意欲を高めるような商品推薦が可能である.一方,実店舗においては商品の購買以外の情報は,取得と活用の両面における難しさからあまり記録されていない.そのため,購買者がどのような商品に興味を持っており何で悩んでいるのかがわからないという問題がある.こうした問題を解決するために,我々はLiDAR(Light Detection And Ranging)からの点群データとDepth(深度)カメラからの視線情報を用いた購買時における候補商品推定システムを構築し,その初期評価を行った.推定の上では,興味のある商品を購買候補商品とした.評価の結果,購買時の視線は候補商品と強く結びつき,視線の情報は候補商品を推定する上で非常に重要な特徴となり得ることがわかった.一方で,視線の評価を踏まえ点群データを使用した候補商品の予測を行った結果,予測対象の人物を含んだ状態で学習したモデルは49&#37;と12クラス分類であることを考えると一定の精度を出すことができた.一方でLOPOでは精度が最大22&#37;と,モデルの一般化はまだまだ課題が残ることがわかった.今後は,データ数を増やし,モデルをより適したものに変更・改善していく必要がある.

  • 抽選における高揚感の要因分析

    高尾, 亮太, 中村, 優吾, 福嶋, 政期, 荒川, 豊

    マルチメディア,分散,協調とモバイルシンポジウム2022論文集   2022.7

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    本研究では,行動変容を誘発する要素技術として,ゲーム等で利用される ''抽選'' がもたらす高揚感に着目し,ゲーム内で使用される抽選器を構成するどの要素が人の高揚感に影響を与えるかについて調査した.我々は,スロットを止めるボタンを押すという行為や手回しで抽選器を操作する行為が自己決定感を生み出し,さらに制御幻想を生じさせているのではないかと仮説を立て,抽選器として,手回し式の抽選器,自動でリールが停止するスロット,手動でリールを停止するスロットの 3 つの種類の抽選器を作成した.そして,実際のゲーム上で不特定多数の挙動を見るオンライン実験(アンケート回答者 428 名)と,表情筋や心拍など生理現象を定量的に計測するオフライン実験(被験者 1 名)を行った.その結果,スロットを自分で止めるという操作が制御幻想を生み出し,自己決定感が高揚感の向上に関係している可能性が示唆された.また,リーチによるニアミスなど当たりに近いハズレの存在も,ユーザの高揚感や表情の変化に影響を与える重要な要因であることが明らかとなった.

  • 高臨場感リモートCo-Cookingを実現するIoTまな板の設計と空間提示方法の検討

    三崎, 慎也, 松井, 智一, 中村, 優吾, 安本, 慶一

    行動変容と社会システム vol.08   2022.3

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    近年の3D-LiDARやHMDの進歩により,複数のユーザが,自身および周辺物理空間のセンシングし空間データを仮想空間に持ち寄ることで臨場感が高い交流を行うことを可能にするサイバーフィジカル空間共有システムが提案されている.このシステムは,没入感のある空間共有を実現できる一方で,点群データの粗さや,HMD装着による動きの制約により,現実空間の物理オブジェクトとの精緻なインタラクションを前提とするアプリケーションに適用するには課題がある.本研究では,HMDを使用せずに物理オブジェクトへの精緻なインタラクションを遠隔ユーザの間で高い臨場感を伴って共有するための新たな提示デバイスと空間提示法の開発を目的とする.ユースケースとして料理教室を想定し,講師の動作を見ながら調理することを可能にするIoTまな板を開発した.IoTまな板はアーム付きカメラ,ディスプレイ,ロードセルセンサを搭載し,まな板上の調理動作の撮影と共有,講師および他の参加者の調理動作のまな板上への表示,食材の重さや力の入り具合の計測・表示と共有を可能にする.さらに,追加のまな板を近くに置くことにより,他の調理者の調理状況をまな板上の映像や情報を通して高臨場感に再現可能である.また,本デバイスを用いた新しい空間提示方法として,利用可能なデバイス数を増やした場合や他デバイスと併用する場合における様々な高臨場感空間共有手法を提案する.
    In recent years, the technologies of 3D-LiDAR and HMD have advanced. It is now possible for multiple users to bring sensing and spatial data of themselves and the surrounding physical space into a virtual space. Therefore, a cyber-physical space sharing system has been proposed to enable highly realistic interaction. This system can realize an immersive space sharing experience. However, there are some limitations such as the coarseness of the point cloud data and the motion limitation due to the wearing of HMD. And The system is not suitable for applications that require precise interaction with physical objects in real space. The purpose of this study is to develop a new presentation device and spatial presentation method to share precise interaction with physical objects with a high sense of presence between remote users without using HMDs. As a use case, we assumed a cooking class. The IoT cutting board is equipped with two cameras, a load cell sensor and a display to measure the weight of the food and the amount of force applied. We also propose a new method of highly realistic space presentation using multiple IoT cutting board devices as well as using the devices with other kind of devices like a side monitor, a projector, etc.

  • 香りナッジが実店舗の購買行動に及ぼす影響の調査

    真弓, 大輝, 中村, 優吾, 松田, 裕貴, 松井, 智一, 三崎, 慎也, 安本, 慶一, 野原, 潤子

    行動変容と社会システム vol.08   2022.3

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    新型コロナウイルス感染拡大により,実店舗での試食販売の実施が制限され,売れ残った野菜などの生鮮食品の廃棄が問題となっている.本研究では,試食販売の代替案を模索するべく,試食販売時に発生する「香り」に着目し,香りのナッジが購買行動に及ぼす影響を調査する.具体的には,奈良県の伝統野菜である大和丸なすの購買促進を題材として取り上げ,大和丸なすの旬である2021年の6月から7月の2ヶ月間,実店舗での実証実験を行なった.そして,(1)提示なし,(2)紙媒体の提示,(3)紙・動画媒体の提示,(4)紙・動画・香り媒体の提示という4つの条件下における,販売ブースへの訪問回数,滞在時間,売上高を比較した.実験の結果,香りナッジを用いた介入によって消費者の興味を引き,購買の意思決定に正の影響を与える可能性が示唆された.
    Due to the pandemic of COVID-19, tasting sales at supermarkets have been restricted, and the disposal of unsold vegetables and other perishable foods has become a problem.To explore alternatives to tasting sales, this study focuses on the "aroma" generated during tasting sales and explores the effect of aroma nudges on purchasing behavior.Specifically, we focused on the scenario of promoting the purchase of Yamato-maru eggplant, a traditional vegetable of Nara Prefecture in Japan. We conducted an experiment in a supermarket for two months, from June to July of 2021, the season of the Yamato-maru eggplant. We compared the number of visits to the sales booth, the time spent in the booth, and the sales amount under four conditions: (1) no presentation, (2) presentation of paper media, (3) presentation of the paper and video media, and (4) presentation of a paper, video, and olfactory display media. The results of the experiment confirmed that sales increased by an average of 1.83 times from the previous year due to the intervention using aroma nudges. Through the demonstration experiment, it was suggested that interventions using aroma nudges have a positive potential to attract consumer interest and positively influence their purchasing decisions.

  • Webアンケート回答時のタッチ操作に基づく深層心理推定に向けた回答UIの提案

    中川 嵩章, 荒川 豊, 中村 優吾

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • エレベータ利用に関する意思決定を支援する状況センシングシステムの設計と開発

    大平 祐大, 荒川 豊, 中村 優吾

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • ウェアラブル心拍センサによるワーク・エンゲイジメントの推定

    原嶋 春輝, 荒川 豊, 石田 繁巳, 中村 優吾

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • センサ装着型トングを用いたポイ捨てごみの種別・位置情報収集システムの提案

    立花 巧樹, 中岡 黎, 宮地 篤士, 冨田 周作, 松田 裕貴, 中村 優吾, 諏訪 博彦

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • 連れ立ち行動促進システムの提案

    田中 宏和, 本松 大夢, 中村 優吾, 荒川 豊

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • 端末間の近距離通信を使ったFederated Learningによる観光オブジェクト認識モデルの参加型学習法とその評価

    冨田 周作, 中村 優吾, 諏訪 博彦, 安本 慶一

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • 新生活様式におけるコミュニティ形成のためのサイバーフィジカル空間共有基盤の設計開発

    天野 辰哉, 水本 旭洋, 山口 弘純, 松田 裕貴, 藤本 まなと, 諏訪 博彦, 安本 慶一, 中村 優吾, 田上 敦士

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • 懸垂マシンを用いた筋トレにおけるデバイスフリー種目推定

    難波 洸也, 中村 優吾, 荒川 豊

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • 充電不要なライフログ記録システムの提案と実用環境での性能検証

    有田 充, 中村 優吾, 石田 繁巳, 荒川 豊

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • メシクエ:ご飯を食べて敵を倒す食育ゲームの提案

    中岡 黎, 中村 優吾, 松田 裕貴, 三崎 慎也, 安本 慶一

    第29回マルチメディア通信と分散処理ワークショップ論文集   2021.10

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  • リアル/バーチャル空間でのコミュニケーションの違いとその差を埋めるAR技術の検討

    石丸 大稀, 藤本 まなと, 中村 優吾, 諏訪 博彦, 安本 慶一

    2021年度 情報処理学会関西支部 支部大会 講演論文集   2021.9

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  • 観光地のリアルタイム状況説明システムの検討

    河中 昌樹, 冨田 周作, 中村 優吾, 諏訪 博彦, 安本 慶一

    2021年度 情報処理学会関西支部 支部大会 講演論文集   2021.9

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  • 嗅覚に作用するナッジを用いた購買行動変容システムの検討

    真弓 大輝, 松井 智一, 中村 優吾, 松田 裕貴, 安本 慶一

    2021年度 情報処理学会関西支部 支部大会 講演論文集   2021.9

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  • BLEを用いた路線バスの混雑度推定

    金光 勇慈, 田谷 瑛悟, 立花 巧樹, 中村 優吾, 松田 裕貴, 諏訪 博彦, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • 観光オブジェクト認識モデルのユーザ参加型構築手法の提案

    冨田 周作, 中村 優吾, 諏訪 博彦, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • 宅内行動認識モデル最適化のためのナッジを用いたアノテーション行動誘導方法の検討

    佐藤 佑磨, 松井 智一, 中村 優吾, 諏訪 博彦, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • 参加型センシングにおける不良回答を抑制する立場表明手法の提案と評価

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    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • 人の知覚の集合知による参加型IoTセンサ調整プラットフォームの設計

    松田 裕貴, 中村 優吾, 諏訪 博彦, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • スマートウォッチの音響センサを用いたポイ捨てごみの種別認識手法の提案と評価

    立花 巧樹, 中村 優吾, 松田 裕貴, 諏訪 博彦, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • IMUセンサを用いた棒体操トラッキングシステムの検討

    大井 一輝, 中村 優吾, 松田 裕貴, 藤本 まなと, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2021論文集   2021.6

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  • ナッジを用いたコロナウイルス接触確認アプリのインストール促進

    金光 勇慈, 立花 功樹, 松田 裕貴, 中村 優吾, 諏訪 博彦, 安本 慶一

    人工知能学会第二種研究会資料   2020.11

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    DOI: 10.11517/jsaisigtwo.2020.sai-039_10

  • Federated Learning over DTNによるオブジェクト認識モデルの地域間での共有手法の検討

    冨田 周作, 中村 優吾, 諏訪 博彦, 安本 慶一

    2020年度 情報処理学会関西支部 支部大会 講演論文集   2020.9

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  • スマート棒を用いた棒体操支援システムの検討

    大井 一輝, 中村 優吾, 松田 裕貴, 藤本 まなと, 安本 慶一

    2020年度 情報処理学会関西支部 支部大会 講演論文集   2020.9

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  • スマートウォッチを用いたポイ捨てごみの種別・位置認識システムの提案

    立花 巧樹, 中村 優吾, 松田 裕貴, 諏訪 博彦, 安本 慶一

    2020年度 情報処理学会関西支部 支部大会 講演論文集   2020.9

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  • 物件情報による賃貸物件快適度指標推定にむけた検討

    諏訪 博彦, 大坪 淳, 中村 優吾, 野口 真史

    マルチメディア,分散協調とモバイルシンポジウム2061論文集   2020.6

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  • IMUを用いた剣道の素振り稽古における打突動作区間の検出手法

    鳥越庸平, 中村優吾, 藤本まなと, 荒川豊, 安本慶一

    第27回マルチメディア通信と分散処理ワークショップ(DPSWS 2019)論文集   2019.11

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  • ウェアラブルセンサ装着位置/向きの違いにロバストな行動認識システムの実現に向けたデータ変換手法の検討

    中村 優吾, 荒川 豊, 安本 慶一

    マルチメディア,分散協調とモバイルシンポジウム2019論文集   2019.6

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  • 新たな賃貸物件探索指標構築のためのセンシングシステム

    諏訪 博彦, 大坪 淳, 中村 優吾, 野口 真史

    マルチメディア,分散協調とモバイルシンポジウム2019論文集   2019.6

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  • 京都インバウンド観光におけるIoT2H観光情報アプリケーションの構築

    鈴木優, 藤本まなと, 吉野幸一郎, 日高真人, Nguyen Quynh Mai, 永野一馬, 中村優吾, 大坪敦, 田中翔平, 安本慶一, 中村哲

    第11回データ工学と情報マネジメントに関するフォーラム(DEIM2019)   2019.3

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  • 剣道上達支援のためのIMUを用いた打突動作認識

    鳥越庸平, 髙田将志, 中村優吾, 藤本まなと, 荒川豊, 安本慶一

    研究報告ユビキタスコンピューティングシステム(UBI)   2019.3

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  • 新たな賃貸物件探索指標のためのIoTセンシングデバイスの検討

    諏訪 博彦, 大坪 敦, 中村 優吾, 野口 真史

    ワークショップ2018 (GN Workshop 2018) 論文集   2018.11

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  • EHAAS : 環境発電素子の発電量に基づくウェアラブル場所推定システム,

    梅津 吉雅, 中村 優吾, 荒川 豊, 藤本 まなと, 安本 慶一

    マルチメディア、分散、協調とモバイル (DICOMO2018) シンポジウム   2018.7

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  • 地域IoTサービスに対する計算需要に応じた適応型地産地処リソース配分手法の提案,

    中村 優吾, 水本 旭洋, 諏訪 博彦, 荒川 豊, 山口 弘純, 安本 慶一

    マルチメディア、分散、協調とモバイル (DICOMO2018) シンポジウム   2018.7

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  • メニュー推薦に向けたセンサ取り付け位置に依存しない自重トレーニング種目認識手法の提案,

    高田 将志, 中村 優吾, 藤本 まなと, 荒川 豊, 安本 慶一

    マルチメディア、分散、協調とモバイル (DICOMO2018) シンポジウム   2018.7

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  • IoTセンシングによる新たな賃貸物件探索指標の検討

    諏訪 博彦, 中村 優吾, 野口 真史

    マルチメディア,分散協調とモバイルシンポジウム2018論文集   2018.6

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  • 環境発電素子の発電量に基づく行動認識手法の提案,

    梅津 吉雅, 中村 優吾, 荒川 豊, 藤本 まなと, 諏訪 博彦, 安本 慶一

    第87回モバイルコンピューティングとパーベイシブシステム(MBL)   2018.5

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  • ウェアラブルデバイスを用いた体幹トレーニング種目認識手法,

    高田 将志, 中村 優吾, 藤本 まなと, 荒川 豊, 安本 慶一

    2018年電子情報通信学会(IEICE) 総合大会 ISS 特別企画「学生ポスターセッション   2018.3

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  • 環境発電素子の発電量に基づく屋内行動認識システムの検討,

    梅津 吉雅, 藤原 聖司, 中村 優吾, 藤本 まなと, 荒川 豊, 安本 慶一

    2018年電子情報通信学会(IEICE) 総合大会 ISS 特別企画「学生ポスターセッション   2018.3

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  • 体幹トレーニング支援に向けたウェアラブルデバイスによる種目認識手法の提案

    高田 将志, 中村優吾, 藤本まなと, 荒川豊, 安本慶一

    第177回ヒューマンコンピュータインタラクション研究   2018.3

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  • 災害時の混雑情報を考慮した避難場所決定手法の提案 (モバイルネットワークとアプリケーション)

    梅木 寿人, 中村 優吾, 藤本 まなと, 水本 旭洋, 諏訪 博彦, 荒川 豊, 安本 慶一

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2018.2

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  • 災害時の混雑情報を考慮した避難場所決定手法の提案 (知的環境とセンサネットワーク)

    梅木 寿人, 中村 優吾, 藤本 まなと, 水本 旭洋, 諏訪 博彦, 荒川 豊, 安本 慶一

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2018.2

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  • 災害時の混雑情報を考慮した避難所決定手法の提案,

    梅木寿人, 中村優吾, 藤本まなと, 水本旭洋, 諏訪博彦, 荒川豊, 安本慶一

    第86回モバイルコンピューティングとパーベイシブシステム研究会(MBL2018)   2018.2

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  • 混雑情報を考慮した災害発生時の避難場所決定手法に関する一検討

    梅木寿人, 中村優吾, 水本旭洋, 藤本まなと, 諏訪博彦, 荒川豊, 安本慶一

    第25回 マルチメディア通信と分散処理ワークショップ (DPSWS2017)   2017.10

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  • 混雑地域における災害発生時の避難場所決定手法に関する一検討

    梅木 寿人, 中村 優吾, 水本 旭洋, 藤本 まなと, 諏訪 博彦, 荒川 豊, 安本 慶一

    第25回マルチメディア通信と分散処理ワークショップ論文集   2017.10

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  • 観光動画キュレーションの実現に向けたハイライト抽出手法の検討

    金谷勇輝, 中村優吾, 諏訪博彦, 荒川豊

    2017年度 情報処理学会関西支部 支部大会   2017.9

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  • IoTデータ流の実時間処理を実現するIoTデバイス向け分散処理ミドルウェアの設計と評価

    中村優吾, 水本旭洋, 諏訪博彦, 荒川豊, 山口弘純, 安本慶一

    第82回モバイルコンピューティングとパーペイシブシステム研究会   2017.3

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  • 実時間観光コンテンツ提供に向けた観光情報収集・キュレーションシステムの提案

    日高真人, 松田裕貴, 河中祥吾, 中村優吾, 藤本まなと, 荒川豊, 安本慶一

    第68回高度交通システムとスマートコミュニティ研究発表会   2017.3

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  • 位置情報サービスにおける個人特化型ゲーミフィケーション ~スタンプラリーイベントを通じた「慣れ」「飽き」の調査~

    松田 裕貴, Akpa Akpro Elder Hippocrate, Konan N’djabli Cedric Ange, 中村 優吾, 前田 直樹, 千住 琴音, 荒川 豊

    社会システムと情報技術研究ウィーク in ルスツリゾート   2017.3

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  • IoTデータ流を実時間で分散処理するためのIoTデバイス向け共通ミドルウェアの設計と評価 (モバイルネットワークとアプリケーション)

    中村 優吾, 水本 旭洋, 諏訪 博彦, 荒川 豊, 山口 弘純, 安本 慶一

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2017.3

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  • Ancient sedimentary DNA reveals past tsunami deposits

    Witold Szczucinski, Joanna Pawlowska, Franck Lejzerowicz, Yuichi Nishimura, Mikolaj Kokocinski, Wojciech Majewski, Yugo Nakamura, Jan Pawlowski

    MARINE GEOLOGY   2016.11

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    DOI: 10.1016/j.margeo.2016.08.006

  • 実時間観光プランニングシステムのためのCGMのキュレーションの課題検討

    日高真人, 中村優吾, 荒川豊, 安本慶一

    2016年度 情報処理学会関西支部 支部大会   2016.9

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  • 実時間雨量情報に基づく動的ハザードマップの検討

    梅木寿人, 中村優吾, 水本旭洋, 藤本まなと, 荒川豊, 安本慶一

    2016年度 情報処理学会関西支部 支部大会   2016.9

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  • Seeking Neural correlates of the Rorschach Response: a fMRI study

    Masahiro Ishibashi, Chigusa Uchiumi, Naoki Aizawa, Kiyoshi Makita, Yugo Nakamura, Daisuke N. Saito

    INTERNATIONAL JOURNAL OF PSYCHOLOGY   2016.7

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  • The relationship between projective psychological test score and the structure of human brain.

    Daisuke N. Saito, Chigusa Uchiumi, Naoki Aizawa, Kiyoshi Makita, Yugo Nakamura, Masahiro Ishibashi

    INTERNATIONAL JOURNAL OF PSYCHOLOGY   2016.7

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  • 観光案内向けCGMキュレーションのためのローカルIoTプラットフォームの提案

    中村優吾, 諏訪博彦, 荒川豊, 山口弘純, 安本慶一

    マルチメディア 分散 協調とモバイル(DICOMO 2016)シンポジウム   2016.7

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  • ローカル環境での効果的な動画像解析を実現する分散処理システムの提案 (モバイルネットワークとアプリケーション)

    中村 優吾, Tony Shi, 諏訪 博彦, 荒川 豊, 山口 弘純, 安本 慶一

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2016.5

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  • 多様なIoTデータストリームをクラウドレスで分散処理するミドルウェアの設計

    中村優吾, 諏訪博彦, 荒川豊, 山口弘純, 安本慶一

    情報処理学会モバイルコンピューティングとパーベイシブシステム研究会   2015.12

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  • GAIFoT: 情報流を活用した地域分散型アンヒ?エントインターフェース

    中村優吾, 松田 裕貴, 荒川周造, 金平卓也, 安本 慶一

    第23回マルチメディア通信と分散処理ワークショップ(DPSWS2015)   2015.10

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  • ポスター講演 地域情報流の高次利用を促す地域分散アンビエントインタフェース(GAIFoT)の提案 (コンピュータシステム) -- (萌芽的コンピュータシステム研究展示会)

    中村 優吾, 松田 裕貴, 荒川 周造

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2015.10

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  • 耐災害メッシュネットワークNerveNetを用いたテストベッドの構築(ポスター講演,知的環境,医療・健康・スポーツのための技術,スマートシティとモバイル通信,技術展時及び一般)

    藤原 孝洋, 中村 優吾, 中村 勇太, 小泉 僚平, 大和田 泰伯, 井上 真杉, 浜口 清

    電子情報通信学会技術研究報告. MoNA, モバイルネットワークとアプリケーション   2015.1

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    大規模災害時に被災状況を迅速に把握し,災害救助活動を支援するための情報通信システムの構築が求められている.しかし,そのシステムを社会で実用化するためには,導入時だけでなく運用時に要する経費や,災害用のシステムを平常時から運用するための仕組みなど様々な課題があり,普及が進んでいない.特に,研究機関の研究成果と耐災害システムのユーザである自治体等の要求をマッチングさせること,非常時に適切に稼働することが求められる.本研究では,情報通信機構(NICT)で開発された耐災害メッシュネットワークNerveNetを教育活動に導入し,その教育活動を通して災害時情報通信システムの社会実装を図ることを目的とする.多くの高等専門学校では,地域密着型教育活動を推進するとともに,実践的教育活動の中で実用に供するシステム構築を行っている.特に,函館高専では,専攻科で実施されている創造実験Project-based Learning(PBL)で,地域社会からの要請事項を実験テーマとして取り上げ,課題解決型教育活動の中で課題の解決を図り社会に還元している.その取り組みの中で耐災害システムの構築を実験テーマとして設定し,函館市やその他周辺自治体の要求を調査し,NerveNetを活用したテストベッドを構築した.テストベッドでは,安否情報管理やファイル管理機能をWebサーバによって提供し,その通信ネットワークにNerveNetを使用した.また,サーバ型カメラをシステムに導入して,映像による遠隔モニタリング機能を実装した.このテストベッドによって,自治体が求める要求を具体化して,有効に機能するシステム構築に役立てる.また,その教育活動による技術修得によって,災害時にシステム運用を支援する.

  • 高専を活用した災害時通信システムの社会実装に関する提案 (知的環境とセンサネットワーク)

    藤原 孝洋, 中村 優吾, 中村 勇太, 小泉 僚平, 井上 真杉, 大和田 泰伯, 浜口 清

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2015.1

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    大規模災害時に迅速に被災状況を把握し,自治体等の災害救助活動を支援する災害時情報通信システムの研究が多くの機関で実施されてきた.しかし,そのシステムを社会で実用化する社会実装には様々な課題があり,自然災害が多発している日本においても普及しているとは言い難い.本稿では,まず災害時通信システムとして,情報通信機構(NICT)で開発された耐災害メッシュネットワークNerveNetについて記述する.そのNerveNetを被災状況把握システムに活用するにあたり,自治体の要求を調査し,その要求を実現する災害時情報管理システムについて検討する.これらのシステム構築と社会実装に関して,地域密着型教育活動を推進している高等専門学校の教育活動とNICT及び地方自治体との連携において実施し,その教育活動によって応用システムの試作と災害時通信システムの運用に関する取り組みについて報告する.

  • Solar forcing of centennial-scale East Asian winter monsoon variability in the mid- to late Holocene

    Takuya Sagawa, Michinobu Kuwae, Kentaro Tsuruoka, Yugo Nakamura, Minoru Ikehara, Masafumi Murayama

    EARTH AND PLANETARY SCIENCE LETTERS   2014.6

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    Language:English  

    DOI: 10.1016/j.epsl.2014.03.043

  • 異種センサネットワーク/アクチュエータの相互連携を実現するミドルウェアアーキテクチャの検討 (知的環境とセンサネットワーク)

    中村 優吾, 藤原 孝洋

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2014.5

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    センサネットワーク技術は,多様な分野への応用が可能な技術であり,これまで数多くのセンサネットワークシステムが開発されてきた.しかし,現在使用されているセンサネットワークの多くが特定のアプリケーションに特化した専用のシステムとなっている.そこで我々は,異なる用途のセンサネットワークやその他の機器が連携することができるミドルウェアアーキテクチャとしてCMSAS(Common Middleware in Sensors,Actuators and Storagors)の検討を行っている.CMSASでは,システムを構成する全ての機器に共通のミドルウェアを導入し,共通のミドルウェアのルールに基づき機器の管理を統一化する.これによって,機器間の仮想的な相互の連携を実現することを目指す.本稿では,検討の第一段階として,産業技術総合研究所(AIST)で開発されたRTミドルウェアを利用したCMSASの概念について紹介し,センサネットワークを用いた加速度データ収集システムへのCMSASの実装について述べる.

  • 地震加速度分析と無線センサネットワーク通信制御に関する検討 (知的環境とセンサネットワーク)

    藤原 孝洋, 神能 孝誠, 中村 優吾, 松原 拓, 上原 秀幸

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2013.11

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    地震等大規模災害時に橋梁やトンネル,建物などの構造物に生じる加速度や歪を計測し,その構造物の状況を把握する構造物ヘルスモニタリングの研究が様々な研究機関で進められている.本研究は,建物に設置された加速度センサによって地震加速度を検出し,そのデータを無線センサネットワークで収集して,構造物ヘルスモニタリングシステムに情報を提供するデータ収集システムについて検討する.本稿では,地震時に観測された加速度信号を分析して帯域について考察し,センサネットワークで加速度データを収集するための通信制御方式について検討する.その通信制御方式の有効性を確認するため,無線センサネットワークのテストベッドを構築し,その省電力特性とデータ伝送特性について評価を行った.ここでは,地震加速度信号の分析と無線センサネットワークテストベッドによる評価実験について記す.

  • Sources and transportation modes of the 2011 Tohoku-Oki tsunami deposits on the central east Japan coast

    Purna Sulastya Putra, Yuichi Nishimura, Yugo Nakamura, Eko Yulianto

    SEDIMENTARY GEOLOGY   2013.8

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    DOI: 10.1016/j.sedgeo.2013.06.004

  • 無線センサネットワークを適用した加速度データ収集システムに関する一検討 : システムモデルの性能評価に基づく実験的考察 (ソフトウェア無線)

    神能 孝誠, 中村 優吾, 松原 拓, 藤原 孝洋, 上原 秀幸

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   2013.7

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    無線センサネットワーク(WSNs)を利用した地震加速度モニタリングに関する検討が行われおり,地震加速度の収集システムにおいては,数10~100Hzのサンプリングレートが要求される.これまでに著者らは,地震加速度の特性を調査したうえ,WSNs, Wireless Distribution System,データベースサーバから構成される加速度モニタリングシステムのテストベッドを構築した.テストベッドによる基礎実験から,WSNsではセンサノードからシンクノードへのシングルホップ通信において,サンプリングレート100Hzで生成されるデータを連続的に伝送することが可能であることを示した.本稿は,テストベッドを用いて加速度データをマルチホップ伝送し,データベースへ格納する実験結果について報告する.結果として,データの収集過程に損失が発生し,その原因はWSNsのマルチホップによる影響だけではなく,データベースへの格納時にも生じることを確認した.

  • 無線センサネットワークによる地震加速度モニタリング用サーバの検討

    中村優吾, 松原拓, 神能考誠, 藤原孝洋

    全国大会講演論文集   2013.3

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    Language:Japanese  

    近年、ユビキタス社会実現の基盤となる技術として無線センサネットワークが注目され、災害時の情報収集システムに応用することが期待されている。本研究では、加速度センサで地震加速度を計測し、無線センサネットワークを用いて加速度データを収集する技術を検討するとともに、そのデータを管理するモニタリングシステムの開発を行っている。本発表では、無線センサネットワークで収集され、大量に送られてくる加速度データの管理と、リアルタイムな情報提供を実現するWebサーバによるデータの提供方法について提案する。

  • 無線センサネットワークを広域な地震加速度モニタリングシステムに適用するための伝送方式の検討

    神能孝誠, 中村優吾, 松原拓, 藤原孝洋

    全国大会講演論文集   2013.3

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    無線センサネットワークの応用例として,地震加速度をモニタリングする研究が注目されている.無線センサネットワークを用いた地震加速度モニタリングでは,高サンプリングレートによる連続的な地震加速度データの収集,駆動電力の省電力化,モニタリング領域の拡張性という3つの要件を考慮せねばならない.しかし,対象とする領域が広域である場合,無線センサネットワークによる多段のマルチホップではスループットの低下や消費電力の増大により要件を満たすことが難しい.そこで,本研究では無線センサネットワーク領域を小クラスタに分け,無線LAN技術によって無線領域を拡張し,インターネットを介して地震加速度データを収集するモニタリングシステムを提案した.本稿では3層のネットワーク技術から成る地震加速度モニタリングシステムの設計を示したうえ,無線センサネットワーク領域に適した伝送方式を調査するべく加速度データ収集の基礎実験を実施し,伝送レートおよび伝送効率の特性を評価した.

  • 無線センサネットワークを用いた地震加速度モニタリングの省電力化のための一考察 ~サンプリング周波数と消費電力の関係調査~

    松原拓, 中村優吾, 神能孝誠, 藤原孝洋

    全国大会講演論文集   2013.3

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    Language:Japanese  

    地震加速度のモニタリングをセンサネットワークで行う場合、限られた通信帯域で連続してデータ収集するとともに省電力動作を実現することが求められる。しかし、これまで研究されたセンサネットワークの通信制御方式では、この要求を満たすことが困難である。そこで本研究では、地震による構造物の振動特性に注目し、サンプリング周波数を最適化して通信制御することによって消費電力を軽減する方式を検討している。本発表では、サンプリング周波数に応じて通信制御した場合の省電力効果について示す。

  • Using Evidence for Teacher Education Program Improvement and Accountability: An Illustrative Case of the Role of Value-Added Measures

    Margaret L. Plecki, Ana M. Elfers, Yugo Nakamura

    JOURNAL OF TEACHER EDUCATION   2012.11

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    Language:English  

    DOI: 10.1177/0022487112447110

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Industrial property rights

Patent   Number of applications: 1   Number of registrations: 0
Utility model   Number of applications: 0   Number of registrations: 0
Design   Number of applications: 0   Number of registrations: 0
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Professional Memberships

  • ACM

    2020.4

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  • ACM

  • IEEE

  • 情報処理学会

  • 電子情報通信学会

Committee Memberships

  • Organizer   Domestic

    2023.4 - 2025.3   

  • 情報処理学会   IoT行動変容学研究グループ 運営委員  

    2022.4 - Present   

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    Committee type:Academic society

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  • Steering committee member   Domestic

    2022.4 - 2025.3   

  • Steering committee member   Domestic

    2022.4 - 2025.3   

  • Steering committee member   Domestic

    2022.4 - 2025.3   

Academic Activities

  • Technical Program Co-Chairs International contribution

    Eighth IEEE International Workshop on Smart Service Systems SmartSys 2024  ( Japan ) 2024.6 - 2024.7

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    Type:Competition, symposium, etc. 

  • Publication Chair International contribution

    The 22nd ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2024)  ( Japan ) 2024.6

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    Type:Competition, symposium, etc. 

  • プログラム副委員長

    第31回 マルチメディア通信と分散処理ワークショップ (DPSWS2023)  ( 富山県 ) 2023.10

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    Type:Competition, symposium, etc. 

  • Technical Program Committee International contribution

    IEEE PerCom Workshop WristSense 2023  ( Japan ) 2023.3

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    Type:Competition, symposium, etc. 

  • プログラム副委員長

    第30回 マルチメディア通信と分散処理ワークショップ (DPSWS2022)  ( 皆生温泉 ) 2022.10

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    Type:Competition, symposium, etc. 

  • Technical Program Committee International contribution

    IEEE PerCom Workshop WristSense 2022  ( Online Italy ) 2022.3

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Research Projects

  • デジタル・ディストラクションの即時検知とアテンション制御に関する研究

    Grant number:24K15227  2024 - 2026

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Grant type:Scientific research funding

  • デジタル・ディストラクションの即時検知とアテンション制御に関する研究

    Grant number:24K15227  2024 - 2026

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • デジタルウェルビーイングに向けた情報選択行動支援

    Grant number:JP23H00216  2023 - 2028

    日本学術振興会  科学研究費助成事業  基盤研究(A)

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    Authorship:Coinvestigator(s)  Grant type:Scientific research funding

  • デジタルウェルビーイングに向けた情報選択行動支援

    Grant number:23H00216  2023 - 2027

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Grant type:Scientific research funding

  • 健康行動セキュリティのためのエンパワメントICT基盤

    2021 - 2024

    戦略的創造研究推進事業 (文部科学省)

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    Authorship:Principal investigator  Grant type:Contract research

  • 健康行動セキュリティのためのエンパワメントICT基盤 研究課題

    Grant number:JPMJPR21P7  2021 - 2023

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 介護職員の業務負担軽減に向けた時空間行動認識に基づく次世代介護プランニング基盤

    Grant number:20H04177  2020 - 2023

    日本学術振興会  科学研究費助成事業  基盤研究(B)

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    Grant type:Scientific research funding

  • 多様なIoTデバイスを用いたコンテキスト認識に基づく次世代ナッジの創出

    2020 - 2021

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 多様なIoTデバイスを用いたコンテキスト認識に基づく次世代ナッジの創出

    2020 - 2021

    戦略的創造研究推進事業 (文部科学省)

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    Authorship:Principal investigator  Grant type:Contract research

  • インターネット壊滅時でも持続可能な災害情報流通支援システムの構築Phase2

    Grant number:19H01139  2019 - 2022

    日本学術振興会  科学研究費助成事業  基盤研究(A)

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    Grant type:Scientific research funding

  • 人と環境に自己適応する柔軟性を備えたコンテキスト認識メカニズムの創出

    2018 - 2019

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 人と環境に自己適応する柔軟性を備えたコンテキスト認識メカニズムの創出

    2018 - 2019

    戦略的創造研究推進事業 (文部科学省)

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    Authorship:Principal investigator  Grant type:Contract research

  • IoTデータ流を実時間で価値化する分散処理基盤の研究開発

    Grant number:17J10021  2017 - 2019

    日本学術振興会  科学研究費助成事業  特別研究員奨励費

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    Grant type:Scientific research funding

  • WAISTON Belt:自動腹囲測定および姿勢・行動推定に基づく健康維持支援IoTデバイス

    2016

    日本学術振興会  科学研究費助成事業  基盤研究(C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • WAISTON Belt:自動腹囲測定および姿勢・行動推定に基づく健康維持支援IoTデバイス

    2016

    大学発ベンチャー創出推進のための事業 (文部科学省)

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    Authorship:Principal investigator  Grant type:Contract research

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Class subject

  • 基幹教育セミナー

    2024.6 - 2024.8   Summer quarter

  • 電気情報工学実験Ⅰ(CM)

    2024.4 - 2024.9   First semester

  • 電気情報工学実験Ⅰ(C)

    2024.4 - 2024.9   First semester

  • (IUPE)Lab. of Electrical Eng and Computer ScienceⅠ(CM)

    2024.4 - 2024.6   Spring quarter

  • (IUPE)System Programming Lab(for C)

    2024.4 - 2024.6   Spring quarter

  • 電気情報工学実験Ⅱ(CM)

    2023.10 - 2024.3   Second semester

  • (IUPE)Lab. of Electrical Eng and Computer Science-II(C)

    2023.10 - 2023.12   Fall quarter

  • 基礎PBLⅡ

    2023.4 - 2023.9   First semester

  • 基礎PBLⅡ

    2023.4 - 2023.9   First semester

  • 情報理工学演習

    2022.4 - 2023.3   Full year

  • 電気情報工学実験Ⅰ

    2022.4 - 2022.9   First semester

  • 情報理工学演習

    2021.4 - 2022.3   Full year

  • 電気情報工学実験Ⅰ

    2021.4 - 2021.9   First semester

  • 先進ソフトウェア 特別講究

    2021.4 - 2021.9   First semester

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Social Activities

  • エシカル消費研究会

    CCCマーケティング株式会社  オンライン  2022.6

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    Audience: General, Scientific, Company, Civic organization, Governmental agency

    Type:Lecture

  • DX Tech Play Edge Computingハンズオンセミナー

    デル・テクノロジーズ株式会社  オンライン  2021.9

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    Audience: General, Scientific, Company, Civic organization, Governmental agency

    Type:Seminar, workshop

Media Coverage

  • 大学院進学に関するインタビュー記事 Newspaper, magazine

    月刊高専  2021.12

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    大学院進学に関するインタビュー記事