Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication最新文献_第3页

PriCal: context-adaptive privacy in ambient calendar displays PriCal:环境日历显示中的上下文自适应隐私

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2632048.2632087

F. Schaub, Bastian Könings, Peter Lang, Björn Wiedersheim, Christian Winkler, M. Weber

引用次数: 26

Adapting Wi-Fi samples to environmental changes automatically 自动调整Wi-Fi样本以适应环境变化

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2638728.2641302

T. Sakaguchi, N. Nishio, M. Mochizuki, Kazuya Murao

{"title":"Adapting Wi-Fi samples to environmental changes automatically","authors":"T. Sakaguchi, N. Nishio, M. Mochizuki, Kazuya Murao","doi":"10.1145/2638728.2641302","DOIUrl":"https://doi.org/10.1145/2638728.2641302","url":null,"abstract":"In recent years, a positioning method which utilizes wireless LAN without using GPS has attracted attention. Especially, in the case of a method which combines absolute position with a Wi-Fi radio environment in advance, the cost of operation and management becomes enormous. Therefore, by sampling Wi-Fi radio information observed at points where users stay frequently or in the long-term, a method which automates to collect and update the Wi-Fi radio information has been proposed. In the case of a long-term operating, the positioning accuracy, however, decreases because this method does not perform well in maintaining and managing samples. It cannot adapt samples to environmental changes although Wi-Fi radio signals change in case of long-term operating. Accordingly, this paper proposes a new calculation formula for improving a positioning accuracy. The formula is calculated with the weight of each base station for avoidance of ill-behaving stations. In addition, this paper also proposes the automated management system with two steps. It adapts samples to changes of Wi-Fi radio signals and a user's behavior. As a result, a positioning accuracy of the new system is higher than existing one.","PeriodicalId":20496,"journal":{"name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88585868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Contexto: lessons learned from mobile context inference 语境:从移动语境推理中获得的经验教训

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2638728.2638781

Moshe Unger, L. Rokach, Ariel Bar, E. Gudes, Bracha Shapira

{"title":"Contexto: lessons learned from mobile context inference","authors":"Moshe Unger, L. Rokach, Ariel Bar, E. Gudes, Bracha Shapira","doi":"10.1145/2638728.2638781","DOIUrl":"https://doi.org/10.1145/2638728.2638781","url":null,"abstract":"Context-aware computing aims at tailoring services to the user's circumstances and surroundings. Our study examines how data collected from mobile devices can be utilized to infer users' behavior and environment. We present the results and the lessons learned from a two-week user study of 40 students. The data collection was performed using Contexto, a framework for collecting data from a rich set of sensors installed on mobile devices, which was developed for this purpose. We studied various new and fine-grained user contexts which are relevant to students' daily activities, such as \"in class and interested in the learned materials\" and \"on my way to campus\". These contexts might later be utilized for various purposes such as recommending relevant items to the students' context. We compare various machine learning methods and report their effectiveness for the purposes of inferring the users' context from the collected data. In addition, we present our findings on how to evaluate context inference systems, on the importance of explicit and latent labeling for context inference and on the effect of new users on the results' accuracy.","PeriodicalId":20496,"journal":{"name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87374773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Non-invasive rapid and efficient firmware update for wireless sensor networks 无线传感器网络的非侵入式快速高效固件更新

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2638728.2638782

Huiung Park, Jongsoo Jeong, P. Mah

引用次数: 8

A method for detecting gaze-required action while cooking for assisting video communication 一种用于在烹饪时检测视线所需动作以辅助视频通信的方法

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2638728.2641337

Yoko Yamakata, Takuya Funatomi, Asuka Miyazawa, M. Minoh, Atsushi Hashimoto

引用次数: 1

Session details: Mobile applications 会话详细信息:移动应用

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/1240624.3258864

Christine Lv

引用次数: 0

Pedestrian dead reckoning based on human activity sensing knowledge 基于人类活动感知知识的行人航位推算

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2638728.2641305

Yuya Murata, Kei Hiroi, K. Kaji, Nobuo Kawaguchi

{"title":"Pedestrian dead reckoning based on human activity sensing knowledge","authors":"Yuya Murata, Kei Hiroi, K. Kaji, Nobuo Kawaguchi","doi":"10.1145/2638728.2641305","DOIUrl":"https://doi.org/10.1145/2638728.2641305","url":null,"abstract":"This research addresses improvement of the accuracy of pedestrian dead reckoning (PDR), which is one effective technique to estimate indoor positions using smartphone sensors. Even though various techniques using step lengths and their number have been previously proposed for PDR, insufficient accuracy is gotten from smartphone sensors. In this research, we define human activity sensing knowledge and propose improvements to PDR accuracy based on it. Human activity sensing knowledge consists of four kinds of information: pedestrian, environmental, activity, and terminal. Previous studies separately used these kinds of information; however, no study has systematically arranged them for use in PDR. We improved PDR accuracy by adjusting the step length in passages and on stairs and revised activity recognition error with human activity sensing knowledge. To investigate the effectiveness of that strategy, we used HASC-IPSC, which is an indoor pedestrian sensing corpus. After our investigation, activity recognition accuracy improved from 71.2% to 91.4%, and the distance estimation error was reduced from approximately 27 m to approximately 7 m using human activity sensing knowledge.","PeriodicalId":20496,"journal":{"name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89666453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Probabilistic identification of visited point-of-interest for personalized automatic check-in 为个性化自动登记提供访问兴趣点的概率识别

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2632048.2632092

Kyosuke Nishida, H. Toda, Takeshi Kurashima, Yoshihiko Suhara

引用次数: 25

Session details: Human behavior 会话细节:人类行为

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/3255111

Sunny Consolvo

引用次数: 0

Limitations with activity recognition methodology & data sets 活动识别方法和数据集的局限性

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication Pub Date : 2014-09-13 DOI: 10.1145/2638728.2641306

J. W. Lockhart, Gary M. Weiss

{"title":"Limitations with activity recognition methodology & data sets","authors":"J. W. Lockhart, Gary M. Weiss","doi":"10.1145/2638728.2641306","DOIUrl":"https://doi.org/10.1145/2638728.2641306","url":null,"abstract":"Human activity recognition (AR) has begun to mature as a field, but for AR research to thrive, large, diverse, high quality, AR data sets must be publically available and AR methodology must be clearly documented and standardized. In the process of comparing our AR research to other efforts, however, we found that most AR data sets are sufficiently limited as to impact the reliability of existing research results, and that many AR research papers do not clearly document their experimental methodology and often make unrealistic assumptions. In this paper we outline problems and limitations with AR data sets and describe the methodology problems we noticed, in the hope that this will lead to the creation of improved and better documented data sets and improved AR experimental methodology. Although we cover a broad array of methodological issues, our primary focus is on an often overlooked factor, model type, which determines how AR training and test data are partitioned---and how AR models are evaluated. Our prior research indicates that personal, hybrid, and impersonal/universal models yield dramatically different performance [30], yet many research studies do not highlight or even identify this factor. We make concrete recommendations to address these issues and also describe our own publically available AR data sets.","PeriodicalId":20496,"journal":{"name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78554921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 63