LU MIN

写真a

Affiliation

Faculty of Informatics and Data Science  Department of Informatics and Data Science 

Date of Birth

1986
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Research Interests 【 display / non-display 】

  • ラーニングアナリティクス

  • 位置情報サービス

  • 利用者インタフェース

  • 地図

  • 地図学

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Graduating School 【 display / non-display 】

  • 2004.09
    -
    2008.07

    Peking University   School of Space and Earth Sciences   Geographic Information System   Graduated

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Graduate School 【 display / non-display 】

  • 2011.10
    -
    2014.09

    The University of Tokyo  Graduate School of Frontier Sciences  Socio-Cultural Environmental Studies  Doctor's Course  Completed

  • 2008.09
    -
    2011.07

    Peking University  School of Space and Earth Sciences  Cartology and Geographyic Information System  Master's Course  Completed

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Campus Career 【 display / non-display 】

  • 2025.04
    -
    Now

    Akita University   Faculty of Informatics and Data Science   Department of Informatics and Data Science   Assistant Professor  

  • 2022.09
    -
    2025.03

    Akita University   Graduate School of Engineering Science   Department of Mathematical Science and Electrical-Electronic-Computer Engineering   Human-Centered Computing Course   Assistant Professor  

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Research Areas 【 display / non-display 】

  • Natural Science / Human geosciences

  • Humanities & Social Sciences / Geography

  • Informatics / Learning support system

  • Informatics / Human interface and interaction

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Thesis for a degree 【 display / non-display 】

  • Human-Centered Mapping in Mobile Environments

    Min Lu 

      2014.09  [Refereed]

    Single author

    DOI

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Research Achievements 【 display / non-display 】

    ◆Original paper【 display / non-display 】

  • Hierarchical geofencing for location-aware generative audio tours

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    Urban Informatics ( Springer Science and Business Media LLC )  3 ( 1 )   2024.12  [Refereed]

    Research paper (journal)   Domestic Co-author

    Abstract

    This study aims to restructure a location-aware audio guide mobile application designed for urban walking tours. Traditional points of interest-based geofencing, which triggers automatic guide delivery as users approach specific locations, struggle to provide continuous and consistent storytelling in areas with limited notable spots, thereby diminishing tourist experiences. To address this challenge, we propose a hierarchical geofencing framework that forms the basis for seamless audio guide experiences through scale-based feature switching and the definition of story serialization rules. In addition, this study proposes geofence-to-conversation techniques utilizing text-to-speech engines and large language models to dynamically adapt guide document resources to dynamic tourists’ movements. A demonstration conducted in a historic urban park area highlighted that the guide generation time in both English and Japanese guide modes is significantly shorter than playback duration, confirming technical feasibility for seamless regional storytelling. Furthermore, we define metrics such as starting time errors, ending time errors, undelivered time to evaluate the real-time performance of location-aware audio guide applications. The experimental results demonstrate effective strategies for geofence configuration and operations, enhancing user experiences in our generative audio tours. This intelligent guide approach, designed for complex urban environments, is expected to enrich tourism and foster regional learning.

    DOI

  • Verification of Sensor Data-Driven Lifecycle for Improvement of Location-Based Services in Walking Tourism

    SASAKI Iori, ARIKAWA Masatoshi, Min LU, UTSUMI Tomihiro, SATO Ryo

    Map, Journal of the Japan Cartographers Association ( Japan Cartographers Association )  62 ( 3 ) 1 - 12   2024.09  [Refereed]

    Research paper (journal)   Domestic Co-author

    DOI CiNii Research

  • Data-Driven Geofencing Design for Point-Of-Interest Notifiers Utilizing Genetic Algorithm

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    ISPRS International Journal of Geo-Information ( MDPI AG )  13 ( 6 ) 174 - 174   2024.05  [Refereed]

    Research paper (journal)   Domestic Co-author

    This study proposes a method for generating geofences driven by GPS trajectory data to realize scalable point-of-interest (POI) notifiers, encouraging walking tourists to discover new local spots. The case study revealed that manual geofence settings degrade the location relevance and user coverage—key objectives of POI notifiers—and hinder the scalability and reliability of services. The formalization presented computationally equips geofence designers with practical solutions through two implementations based on prior GPS trajectory logs: (1) a multiobjective genetic algorithm that suggests cost-effective geofences by providing trade-off visualizations and (2) a user coverage-penalized genetic algorithm that determines an optimal geofence based on the designers’ expectations. The feasibility and stability of the proposed implementations were tested in areas with varying tourist flow patterns. A comparative survey among manual settings, settings incorporating a reliability simulation, and data-driven settings demonstrates significant performance improvements for geofence services.

    DOI

  • Indoor AR Navigation Framework Based on Geofencing and Image-Tracking with Accumulated Error Correction

    Min Lu, Masatoshi Arikawa, Kohei Oba, Keiichi Ishikawa, Yuhan Jin, Tomihiro Utsumi, Ryo Sato

    Applied Sciences ( Applied Sciences (Switzerland) )  14 ( 10 ) 4262   2024.05  [Refereed]

    Research paper (journal)   Domestic Co-author

    DOI

  • How Students Use Learning Analytics Dashboards in Higher Education: A Learning Performance Perspective

    Li Chen, Xuewang Geng, Min Lu, Atsushi Shimada, Masanori Yamada

    SAGE Open ( SAGE Open )  13 ( 3 )   2023.07  [Refereed]

    Research paper (journal)   Domestic Co-author

    Developed to maximize learning performance, learning analytics dashboards (LAD) are becoming increasingly commonplace in education. An LAD’s effectiveness depends on how it is used and varies according to users’ academic levels. In this study, two LADs and a learning support system were used in a higher education course to support students’ cognitive and self-regulated learning (SRL) strategies. A total of 54 students’ learning logs on three systems and their learning performance scores were collected; descriptive statistics of learning behaviors, Mann-Whitney U test, and lag sequential analysis were used to explore how students with different learning performances used LADs to support their learning. Compared to low-performers, high-performers used the LADs more frequently during preview and review phases and conducted more monitoring and reflection strategies to support their learning. Finally, some practical implications for improving the design and use of LADs were provided.

    DOI CiNii Research

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    ◆International conference proceedings【 display / non-display 】

  • Generative Live Commentaries Interacting with Geospatial Context for Promoting Local Festivals

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    Proceedings of the 2024 8th International Conference on Big Data and Internet of Things ( ACM )    125 - 131   2024.09  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Space-Division-Based Pseudo-Occlusion in 3D Trajectory Data Visualization for Indoor AR Navigation

    Yuhan Jin, Xiangling Peng, Kohei Oba, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    Proceedings of the 2024 8th International Conference on Big Data and Internet of Things ( ACM )    138 - 143   2024.09  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Geofence-to-Conversation: Hierarchical Geofencing for Augmenting City Walks with Large Language Models

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    26th International Conference on Mobile Human-Computer Interaction ( ACM )  ( 24 ) 1 - 5   2024.09  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Adaptive visualization of tourists' preferred spots and streets using trajectory articulation

    Iori Sasaki, Masatoshi Arikawa, Min Lu

    Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility ( ACM )    27 - 32   2022.11  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Understanding Student Slide Reading Patterns During the Pandemic

    Boxuan Ma, Min Lu, Shin’ichi Konomi

    Proceedings of 18th International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2021) ( IADIS Press )    87 - 94   2021.10  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

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    ◆Other【 display / non-display 】

  • Enhancing E-Book Learning Dashboards with GPT-Assisted Page Grouping and Adaptive Navigation Link Visualization

    Min Lu, Boxuan Ma, Xuewang Geng, Masatoshi Yamada

    The 15th International Learning Analytics and Knowledge Conference (LAK 2025)     2025.03  [Refereed]

    Summary of the papers read (international conference)   Domestic Co-author

  • Exploring the Role of Metacognition in Enhancing Learning Outcomes through Learning Analytics Dashboard

    Masanori Yamada, Xuewang Geng, Min Lu, Yuta Taniguchi

    Proceedings of eLearn 2024     2024.10  [Refereed]

    Summary of the papers read (international conference)   International Co-author

  • Adaptable Data-Driven Geofences for Notifying Points of Interest Using Tourists' GPS Trajectories

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato, Tomihiro Utsumi

    Proceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising ( ACM )    2023.11  [Refereed]

    Summary of the papers read (international conference)   Domestic Co-author

    DOI

  • Educational Potential of Map Storytelling Creation using Data Objects-Driven Mobile Mapping Toolkit – KoPpoMai

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato

    Abstracts of the ICA ( Copernicus GmbH )  6   1 - 2   2023.08  [Refereed]

    Summary of the papers read (international conference)   Domestic Co-author

    DOI

  • Learning Analytics Dashboard Supporting Metacognition

    Li Chen, Min Lu, Yoshiko Goda, Atsushi Shimada, Masanori Yamada

    Balancing the Tension between Digital Technologies and Learning Sciences ( Springer International Publishing )    129 - 149   2021.02  [Refereed]

    Domestic Co-author

    DOI

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Books 【 display / non-display 】

  • Ubiquitous Mapping: Perspectives from Japan - Chapter 2: Ubiquitous Digital Storytelling with Local and Dynamic Georeferencing of Analog Maps

    Masatoshi Arikawa, Min Lu

    Springer Singapore  2022.07 ISBN: 978-981-19-1535-2

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Grant-in-Aid for Scientific Research 【 display / non-display 】

  • Grant-in-Aid for Scientific Research(C)

    Project Year： 2023.04  -  2027.03 

  • Grant-in-Aid for Scientific Research(A)

    Project Year： 2022.04  -  2026.03 

  • Grant-in-Aid for Challenging Research (Pioneering)/(Exploratory)

    Project Year： 2021.07  -  2025.03 

  • Grant-in-Aid for Early-Career Scientists

    Project Year： 2020.04  -  2023.03 

  • Fund for the Promotion of Joint International Research

    Project Year： 2019.10  -  2023.03 

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Presentations 【 display / non-display 】

  • Bridging Traditional and Digital Cartography: Techniques in Dynamic Local Georeferencing

    Quang Sang Tran, Min Lu, Iori Sasaki, Masatoshi Arikawa

    The First Asian Cartographic Conference (AsiaCarto 2024)  2024.12  -  2024.12 

  • Dynamic Local Georeferencing for Investigating Common and Different Objects among Distorted Maps

    チャン クアン サン, Lu Min, 佐々木 一織, 田村 公季, 有川 正俊

    2024年度電気関係学会東北支部連合大会  2024.08  -  2024.08 

  • Functions of Orienting Users to Right Position for Viewing Photos in AR Spaces

    藤原稜大, 黒崎 蓮, 有川正俊, Lu Min, 佐藤 諒, 佐々木一織, 内海富博

    2023年度 電気関係学会 東北支部連合大会  2023.09  -  2023.09 

  • Design and Implementation of Programming Classes using MediaLib for Beginners in Universities

    Min Lu, Jingyun Wang, Masatoshi Arikawa, Ryo Sato

    The 85th National Convention of IPSJ  2023.03  -  2023.03 

  • Development of Learning Analytics Platform for Macro and Micro Learning Analytics

    Masanori YAMADA, Min LU, Yuta TANIGUCHI, Fumiya OKUBO, Chen LI,Rin-Ichiro TANIGUCHI

    Annual conference of Japanese Society of Educational Technology 2022 Spring  2022.03  -  2022.03 

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