Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing最新文献_第10页

Test time feature ordering with FOCUS: interactive predictions with minimal user burden FOCUS的测试时间特征排序:以最小的用户负担进行交互式预测

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971748

Kirstin Early, S. Fienberg, Jennifer Mankoff

{"title":"Test time feature ordering with FOCUS: interactive predictions with minimal user burden","authors":"Kirstin Early, S. Fienberg, Jennifer Mankoff","doi":"10.1145/2971648.2971748","DOIUrl":"https://doi.org/10.1145/2971648.2971748","url":null,"abstract":"Predictive algorithms are a critical part of the ubiquitous computing vision, enabling appropriate action on behalf of users. A common class of algorithms, which has seen uptake in ubiquitous computing, is supervised machine learning algorithms. Such algorithms are trained to make predictions based on a set of features (selected at training time). However, features needed at prediction time (such as mobile information that impacts battery life, or information collected from users via experience sampling) may be costly to collect. In addition, both cost and value of a feature may change dynamically based on real-world context (such as battery life or user location) and prediction context (what features are already known, and what their values are). We contribute a framework for dynamically trading off feature cost against prediction quality at prediction time. We demonstrate this work in the context of three prediction tasks: providing prospective tenants estimates for energy costs in potential homes, estimating momentary stress levels from both sensed and user-provided mobile data, and classifying images to facilitate opportunistic device interactions. Our results show that while our approach to cost-sensitive feature selection is up to 45% less costly than competing approaches, error rates are equivalent or better.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114842912","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: 24

WiFinger: talk to your smart devices with finger-grained gesture WiFinger:用手指手势与智能设备对话

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971738

Hong Li, Wei Yang, Jianxin Wang, Yang Xu, Liusheng Huang

{"title":"WiFinger: talk to your smart devices with finger-grained gesture","authors":"Hong Li, Wei Yang, Jianxin Wang, Yang Xu, Liusheng Huang","doi":"10.1145/2971648.2971738","DOIUrl":"https://doi.org/10.1145/2971648.2971738","url":null,"abstract":"In recent literatures, WiFi signals have been widely used to \"sense\" people's locations and activities. Researchers have exploited the characteristics of wireless signals to \"hear\" people's talk and \"see\" keystrokes by human users. Inspired by the excellent work of relevant scholars, we turn to explore the field of human-computer interaction using finger-grained gestures under WiFi environment. In this paper, we present Wi-Finger - the first solution using ubiquitous wireless signals to achieve number text input in WiFi devices. We implement a prototype of WiFinger on a commercial Wi-Fi infrastructure. Our scheme is based on the key intuition that while performing a certain gesture, the fingers of a user move in a unique formation and direction and thus generate a unique pattern in the time series of Channel State Information (CSI) values. WiFinger is deigned to recognize a set of finger-grained gestures, which are further used to realize continuous text input in off-the-shelf WiFi devices. As the results show, WiFinger achieves up to 90.4% average classification accuracy for recognizing 9 digits finger-grained gestures from American Sign Language (ASL), and its average accuracy for single individual number text input in desktop reaches 82.67% within 90 digits.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115517144","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: 235

CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia 交叉检查:对精神分裂症患者心理健康变化的被动感知和检测

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971740

Rui Wang, M. Aung, Saeed Abdullah, R. Brian, A. Campbell, Tanzeem Choudhury, M. Hauser, J. Kane, Michael Merrill, E. Scherer, V. W. Tseng, Dror Ben-Zeev

{"title":"CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia","authors":"Rui Wang, M. Aung, Saeed Abdullah, R. Brian, A. Campbell, Tanzeem Choudhury, M. Hauser, J. Kane, Michael Merrill, E. Scherer, V. W. Tseng, Dror Ben-Zeev","doi":"10.1145/2971648.2971740","DOIUrl":"https://doi.org/10.1145/2971648.2971740","url":null,"abstract":"Early detection of mental health changes in individuals with serious mental illness is critical for effective intervention. CrossCheck is the first step towards the passive monitoring of mental health indicators in patients with schizophrenia and paves the way towards relapse prediction and early intervention. In this paper, we present initial results from an ongoing randomized control trial, where passive smartphone sensor data is collected from 21 outpatients with schizophrenia recently discharged from hospital over a period ranging from 2-8.5 months. Our results indicate that there are statistically significant associations between automatically tracked behavioral features related to sleep, mobility, conversations, smart-phone usage and self-reported indicators of mental health in schizophrenia. Using these features we build inference models capable of accurately predicting aggregated scores of mental health indicators in schizophrenia with a mean error of 7.6% of the score range. Finally, we discuss results on the level of personalization that is needed to account for the known variations within people. We show that by leveraging knowledge from a population with schizophrenia, it is possible to train accurate personalized models that require fewer individual-specific data to quickly adapt to new users.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115628936","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: 221

Is only one gps position sufficient to locate you to the road network accurately? 仅仅一个gps位置就足以准确地将你定位到道路网络上吗?

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971702

Hao-qing Wu, Weiwei Sun, Baihua Zheng

{"title":"Is only one gps position sufficient to locate you to the road network accurately?","authors":"Hao-qing Wu, Weiwei Sun, Baihua Zheng","doi":"10.1145/2971648.2971702","DOIUrl":"https://doi.org/10.1145/2971648.2971702","url":null,"abstract":"Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxi-hailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position to a road segment. We study the problem in a data-driven view to make this process ubiquitous by proposing a tractable, efficient and robust generative model. In addition, we extend our solution to the real application scenario, i.e., taxi-hailing service, and propose an approach to further improve the result accuracy by considering destination information. We use the real taxi GPS data to evaluate our approach. The results show that our approach outperforms all the existing approaches significantly while maintaining robustness, and it can achieve an accuracy as high as 90% in some situations.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126579220","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: 13

CueSee: exploring visual cues for people with low vision to facilitate a visual search task 提示:为视力低下的人探索视觉线索，以促进视觉搜索任务

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971730

Yuhang Zhao, S. Szpiro, J. Knighten, Shiri Azenkot

引用次数: 80

Accuracy of interpreting pointing gestures in egocentric view 以自我为中心观点解读指向手势的准确性

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971687

Deepak Akkil, Poika Isokoski

引用次数: 21

Finding a store, searching for a product: a study of daily challenges of low vision people 寻找商店，寻找产品:对低视力人群日常挑战的研究

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971723

S. Szpiro, Yuhang Zhao, Shiri Azenkot

{"title":"Finding a store, searching for a product: a study of daily challenges of low vision people","authors":"S. Szpiro, Yuhang Zhao, Shiri Azenkot","doi":"10.1145/2971648.2971723","DOIUrl":"https://doi.org/10.1145/2971648.2971723","url":null,"abstract":"Visual impairments encompass a range of visual abilities. People with low vision have functional vision and thus their experiences are likely to be different from people with no vision. We sought to answer two research questions: (1) what challenges do low vision people face when performing daily activities and (2) what aids (high- and low-tech) do low vision people use to alleviate these challenges? Our goal was to reveal gaps in current technologies that can be addressed by the UbiComp community. Using contextual inquiry, we observed 11 low vision people perform a wayfinding and shopping task in an unfamiliar environment. The task involved wayfinding and searching and purchasing a product. We found that, although there are low vision aids on the market, participants mostly used their smartphones, despite interface accessibility challenges. While smartphones helped them outdoors, participants were overwhelmed and frustrated when shopping in a store. We discuss the inadequacies of existing aids and highlight the need for systems that enhance visual information, rather than convert it to audio or tactile.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129061687","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: 58

Situational impairments to mobile interaction in cold environments 寒冷环境下移动交互的情境障碍

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971734

Zhanna Sarsenbayeva, Jorge Gonçalves, F. García-Peñalvo, Simon Klakegg, S. Rissanen, H. Rintamäki, J. Hannu, V. Kostakos

引用次数: 31

A contextual collaborative approach for app usage forecasting 应用程序使用预测的上下文协作方法

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971729

Yingzi Wang, Nicholas Jing Yuan, Yu Sun, Fuzheng Zhang, Xing Xie, Qi Liu, Enhong Chen

{"title":"A contextual collaborative approach for app usage forecasting","authors":"Yingzi Wang, Nicholas Jing Yuan, Yu Sun, Fuzheng Zhang, Xing Xie, Qi Liu, Enhong Chen","doi":"10.1145/2971648.2971729","DOIUrl":"https://doi.org/10.1145/2971648.2971729","url":null,"abstract":"Fine-grained long-term forecasting enables many emerging recommendation applications such as forecasting the usage amounts of various apps to guide future investments, and forecasting users' seasonal demands for a certain commodity to find potential repeat buyers. For these applications, there often exists certain homogeneity in terms of similar users and items (e.g., apps), which also correlates with various contexts like users' spatial movements and physical environments. Most existing works only focus on predicting the upcoming situation such as the next used app or next online purchase, without considering the long-term temporal co-evolution of items and contexts and the homogeneity among all dimensions. In this paper, we propose a contextual collaborative forecasting (CCF) model to address the above issues. The model integrates contextual collaborative filtering with time series analysis, and simultaneously captures various components of temporal patterns, including trend, seasonality, and stationarity. The approach models the temporal homogeneity of similar users, items, and contexts. We evaluate the model on a large real-world app usage dataset, which validates that CCF outperforms state-of-the-art methods in terms of both accuracy and efficiency for long-term app usage forecasting.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114782083","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: 14

ARTcode: preserve art and code in any image ARTcode:保留任何图像中的艺术和代码

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971733

Zhe Yang, Yuting Bao, Chuhao Luo, Xingya Zhao, Siyu Zhu, Chunyi Peng, Yunxin Liu, Xinbing Wang

{"title":"ARTcode: preserve art and code in any image","authors":"Zhe Yang, Yuting Bao, Chuhao Luo, Xingya Zhao, Siyu Zhu, Chunyi Peng, Yunxin Liu, Xinbing Wang","doi":"10.1145/2971648.2971733","DOIUrl":"https://doi.org/10.1145/2971648.2971733","url":null,"abstract":"The ubiquitous QR codes and some similar barcodes are becoming a convenient and popular approach to impromptu communication between mobile devices and their surrounding cyber-physical world. However, such codes suffer from two common drawbacks: poor viewing experience and inability to be identified through itself. In this work, we propose ART-code-- Adaptive Robust doT matrix barcode, which aims to preserve ART and CODE features in one visual pattern. It works on any surface (paper or electronic displays) and is able to convert any image or any form of human-readable contents (e.g., a picture, a logo, a slogan) into an ARTcode. It looks like an image which retains human-readable and aesthetically pleasant contents, and in the meanwhile, it acts as a QR code which conveys data bits over the visual channel. The core enablers in ARTcode are (1) the design of the colored dot matrix for data embedding with little distortion from the original image and (2) a comprehensive error correction scheme which enhances decoding robustness against noises and interferences from the original image in ARTcode. We implement ARTcode with the receiver on Android phones and the sender from a PC or a phone (it can be printed in paper). We conduct extensive user survey and experiments for evaluation. It validates the effectiveness and wide applicability of ARTcode: It works well with all of 197 images randomly downloaded, covering representative categories of the gray-scale images, logos, colored ones with low/medium/strong contrasts. The image quality is quite acceptable in a subjective user-perception survey with 50 participants and data communication accuracy achieves as high as 99% in almost all the cases (> 96% raw accuracy in ARTcode without error detection and other schemes).","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132751962","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: 27