論文 - 大越　匡

Smarttention, please!: 2nd workshop on intelligent attention management on mobile devices

D Weber, AS Shirazi, S Gehring, N Henze, B Poppinga, M Pielot, T Okoshi

Proceedings of the 18th International Conference on Human-Computer … （ACM Press）     914 2016年

共著, 査読有り

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Proceedings of on MobiSys 2016 PhD Forum

LiKamWa Robert, Okoshi Tadashi, Kang Seungwoo

Publication of MobiSys'16 The 14th Annual International Conference on Mobile Systems, Applications, and Services （ACM）  2016年

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Poster: NiSleep: Gamification-friendly quantitative evaluation methodology of sleep quality

K Egashira, Y Furukawa, Y Nishiyama, T Okoshi, J Nakazawa, H Tokuda

Proceedings of the 14th Annual International Conference on Mobile Systems … （ACM Press）     132 2016年

共著, 査読有り,  ISSN  9781450344166

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Investigating interruptibility at activity breakpoints using smartphone activity recognition API

M Obuchi, W Sasaki, T Okoshi, J Nakazawa, H Tokuda

Proceedings of the 2016 ACM International Joint Conference on Pervasive and … （ACM Press）     1602 - 1607 2016年

共著, 査読有り,  ISSN  9781450344623

　概要を見る

© 2016 ACM. We propose a system for improving the answer rate to ES inquiry to reduce the user's mental burden by detectin breakpoints in user's physical activity and pushing notification in such timings. We conducted an in-The-wild use study with 30 participants for 4-days. The results reveale the effectiveness of breakpoint-based notification delivery In the best case, 70.0% improvement in user's respons time to notifications was observed at a transition to th user's activity from "walking" to "stationary".

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Interruptibility research: opportunities for future flourishment

T Okoshi, J Nakazawa, H Tokuda

Proceedings of the 2016 ACM International Joint Conference on Pervasive and … （ACM Press）     1524 - 1529 2016年

共著, 査読有り,  ISSN  9781450344623

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© 2016 ACM. As users enjoy their computing with an increasing number of devices, applications and services, and connected other users, users' attention is getting the most precious resource in computing due to increasing information fragments provided proactively. Research on user's attention management and especially interruptibility have been accelerated in the recent years. After clarifying some recent background computing trends, this paper focuses on those researches areas, specifies several possible opportunities in the area, and proposes 3 key future opportunities that include being a layer and platform, communication with industries, and intersection with research areas. This paper aims to motivate active discussion on how we can make our research flourish in rather longer term.

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Towards attention-aware adaptive notification on smart phones

T Okoshi, H Nozaki, J Nakazawa, H Tokuda, J Ramos, AK Dey

Pervasive and Mobile Computing 26, 17-34 （Pervasive and Mobile Computing）  26   17 - 34 2016年

共著, 査読有り,  ISSN  15741192

　概要を見る

© 2015 Elsevier B.V. All rights reserved. As the amount of information to users increases with the trends of an increasing numbers of devices, applications, and web services, the new bottleneck in computing is human attention. To minimize users attentional overload, we propose a novel middleware "Attelia" that detects breakpoints of user's mobile interactions to deliver notifications adaptively. Attelia detects such timings in real-time, using only users phones, without any external sensors, and without any modifications to applications. Our extensive evaluation proved Attelias effectiveness. In-the-wild user study with 30 participants for 16 days showed that, specifically for the users with greater sensitivity for interruptive notification timings, notification scheduling in Attelia's breakpoint timing reduced users frustration by 28% in users' real smart phone environments.

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ACM Mobisys' 16 PhD forum welcome message

R LiKamWa, T Okoshi, S Kang

Unknown Journal, vi （PhD Forum 2016 - Proceedings of the MobiSys 2016 PhD Forum, co-located with MobiSys 2016）  2016年

ISSN  9781450343312

3 rd international workshop on ubiquitous mobile instrumentation

D Ferreira, T Okoshi, Y Nishiyama, C Koehler, JW Park, A Lucero

Proceedings of the 2016 ACM International Joint Conference on Pervasive and … （UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing）     608 - 611 2016年

ISSN  9781450344623

　概要を見る

© 2016 ACM. Mobile phones allow us to reach people anywhere, anytime. In addition to the benefits for end users, researchers and developers can also benefit from the powerful devices that people carry on a daily basis. Collectively, mobile phones form a ubiquitous computer. The Ubiquitous Mobile Instrumentation (UbiMI) workshop focuses on using mobile devices as instruments to collect data and conduct mobile user studies, to understand human-behavior and routines, and to gather users' context.

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UbiTtention: smart & ambient notification and attention management

A Voit, B Poppinga, D Weber, M Böhmer, N Henze, S Gehring, T Okoshi, ...

Proceedings of the 2016 ACM International Joint Conference on Pervasive and … （ACM Press）     1520 2016年

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UbiMI: 3rd international workshop on ubiquitous mobile instrumentation

Ferreira Denzil, Okoshi Tadashi, Nishiyama Yuuki, Koehler Christian, Park Jung Wook, Lucero Andr{\'{e}}s

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16 （ACM Press）     608 2016年

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QueueVadis: Queuing analytics using smartphones

Okoshi T., Lu Y., Vig C., Lee Y., Balan R., Misra A.

IPSN 2015 - Proceedings of the 14th International Symposium on Information Processing in Sensor Networks (Part of CPS Week) （IPSN 2015 - Proceedings of the 14th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)）     214 - 225 2015年04月

ISSN  9781450334754

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We present QueueVadis, a system that addresses the problem of estimating, in real-time, the properties of queues at commonplace urban locations, such as coffee shops, taxi stands and movie theaters. Abjuring the use of any queuing-specific infrastructure sensors, QueueVadis uses participatory mobile sensing to detect both (i) the individual-level queuing episodes for any arbitrarily-shaped queue (by a characteristic locomotive signature of short bursts of "shuffling forward" between periods of "standing") and (ii) the aggregate-level queue properties (such as expected wait or service times) via appropriate statistical aggregation of multi-person data. Moreover, for venues where multiple queues are too close to be separated via location estimates, QueueVadis also uses a novel disambiguation technique to separate users into multiple distinct queues. User studies, performed with 138 cumulative total users observed at 23 different real-world queues across Singapore and Japan, show that QueueVadis is able to (a) identify all individual queuing episodes, (b) predict service and wait times fairly accurately (with median estimation errors in the 10%-20% range), independent of the queue's shape, (c) separate users in multiple proximate queues with close to 80% accuracy and (d) provide reasonable estimates when the participation rate (the fraction of QueueVadis-equipped people in the queue) is modest.

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ライフログデータを用いたチームの行動変容促進

西山 勇毅, 大越 匡, 米澤 拓郎, 中澤 仁, 高汐 一紀, 徳田 英幸

情報処理学会論文誌 （一般社団法人情報処理学会）  56 （ 1 ） 349 - 361 2015年01月

ISSN  1882-7764

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近年，携帯端末の普及にともない誰もが日常生活中の活動情報を検知・蓄積可能なライフログ環境が整ってきた．これまでライフログデータは，個人を対象として行動変容の促進に活用されてきたが，今後は研究室やスポーツチーム，企業といった集団を対象とした行動変容の促進が可能になると考えられる．しかし，集団は個人とは異なり内部に様々な人間関係が存在するため，これまでの個人を対象とした行動変容促進手法が集団に対して効果的であるかは明らかではない．本研究では，集団の行動変容を促進するモデルとして，既存手法の「競争」と「協力」の要素を組み合わせた6種類の集団の行動変容促進モデルの提案し，効果の検証を行った．提案モデルに基づいた行動変容促進を行うAaron2を実装し，2つの集団（64名）を対象に3週間の実験を行った．1週間ごとの行動変容について考察した結果，チーム目標と直接的に関係ない活動では行動変容への効果が低く，日頃からチーム単位で競争を行っているチームでは「チーム間での競争要素」用いたモデルが最も行動変容への効果が高くなる可能性が示された．Recent technological trends on mobile/wearable devices and sensors have been enabling increasing number of people to collect and store their "lifelog" easily in their daily lives. Beyond exercise behavior change of individual user, our research focus is on the behavior change of teams, based on life-logging technologies and information sharing. In this paper, we propose and evaluate six different types of information sharing model among team members for their exercise promotion, leveraging concepts of "competition" and "collaboration". According to our experimental mobile web application for exercise promotion and extensive user study among 64 total users for three weeks, the model with "competition" technique resulted the most effective performance for competitive teams such as sport teams.

ライフログデータを用いたチームの行動変容促進

西山 勇毅, 大越 匡, 米澤 拓郎, 中澤 仁, 高汐 一紀, 徳田 英幸

情報処理学会論文誌 （Information Processing Society of Japan (IPSJ)）  56 （ 1 ） 349 2015年01月

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Detection of User's Interruptibility for Attention Awareness in Ubiquitous Computing (本文)

大越匡

慶應義塾大学 2015年

Senbay: smartphone-based activity capturing and sharing using sensor-federated video

Y Nishiyama, T Okoshi, Y Chen, T Yonezawa, J Nakazawa, H Tokuda

Adjunct Proceedings of the 2015 ACM International Joint Conference on … （ACM Press）     21 - 24 2015年

共著, 査読有り,  ISSN  9781450335751

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We present Senbay, a novel smartphone-based platform for capturing and sharing synchronously-recorded video/sensor data stream using animated two-dimensional barcode. In the ubicomp environment, mobile devices have enabled us to capture video and various types of sensor data easily. However, currently we do not have a framework to instantly integrate video and those sensor data on smartphones and share them easily with other users on the net. In this paper, we present Senbay, a platform to integrate video and sensor data stream into single video on smartphones. With Senbay, sensor data stream will be embedded into a video as animated QR code in real-time, thus users can share the \sensor-federated" video easily on the web, through lots of popular video sharing services. This paper introduces the architecture and evaluation of Senbay and discusses future vision of the sensor-federated video sharing platform along with several applications.

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Reducing users' perceived mental effort due to interruptive notifications in multi-device mobile environments

T Okoshi, J Ramos, H Nozaki, J Nakazawa, AK Dey, H Tokuda

Proceedings of the 2015 ACM International Joint Conference on Pervasive and … （ACM Press）     475 - 486 2015年

共著, 査読有り,  ISSN  9781450335744

　概要を見る

Copyright © 2015 ACM. In today's ubiquitous computing environment where users carry, manipulate, and interact with an increasing number of networked devices, applications and web services, human attention is the new bottleneck in computing. It is therefore important to minimize a user's mental effort due to notifications, especially in situations where users are mobile and using multiple wearable and mobile devices. To this end, we propose Attelia II, a novel middleware that identifies breakpoints in users' lives while using those devices, and delivers notifications at these moments. Attelia II works in real-Time and uses only the mobile and wearable devices that users naturally use and wear, without any modifications to applications, and without any dedicated psycho-physiological sensors. Our in-The-wild evaluation in users' multi-device environment (smart phones and smart watches) with 41 participants for 1 month validated the effectiveness of Attelia. Our new physical activity-based breakpoint detection, in addition to the UI Event-based breakpoint detection, resulted in a 71.8% greater reduction of users' perception of workload, compared with our previous system that used UI events only. Adding this functionality to a smart watch reduced workload perception by 19.4% compared to random timing of notification deliveries. Our multi-device breakpoint detection across smart phones and watches resulted in about 3 times greater reduction in workload perception than our previous system.

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QueueVadis: Queuing Analytics using Smartphones

Okoshi Tadashi, Lu Yu, Vig Chetna, Lee Youngki, Balan Rajesh Krishna, Misra Archan

Proceedings of The 14th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN '15) （ACM Press）     214 2015年

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Queuevadis: Queuing analytics using smartphones

T Okoshi, Y Lu, C Vig, Y Lee, RK Balan, A Misra

Proceedings of the 14th International Conference on Information Processing … 2015年

EverCuate: Asynchronous Tsunami Evacuation Training - Whoever, Wherever, Whenever -

Okoshi Tadashi

2015年

単著, 査読有り

Detection of User’s Interruptibility for Attention Awareness in Ubiquitous Computing

T Okoshi

Keio University 2015年