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Local differential privacy for human-centered computing

EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2020年第1期2020卷 1-12页

作者： Fang, Xianjin Zeng, Qingkui Yang, Gaoming Anhui Univ Sci & Technol Sch Comp Sci & Engn Huainan 232001 Peoples R China

human-centered computing in cloud, edge, and fog is one of the most concerning issues. Edge and fog nodes generate huge amounts of data continuously, and the analysis of these data provides valuable information. But they also increase privacy risks. The personal sensitive data may be disclosed by untrusted third-party service providers, and the current solutions to privacy protection are inefficient, costly. It is difficult to obtain available statistics. To solve these problems, we propose a local differential privacy sensitive data collection protocol in human-centered computing. Firstly, to maintain high data utility, the selection of the optimal number of hash functions and the mapping length is based on the size of the collected data. Secondly, we hash the sensitive data, add the appropriate Laplace noise to the client side, and send the reports to the server side. Thirdly, we construct the count sketch matrix to obtain privacy statistics on the server side. Finally, the utility of the proposed protocol is verified by synthetic datasets and a real dataset. The experimental results demonstrate that the protocol can achieve a balance between data utility and privacy protection.

关键词： human-centered computing Local differential privacy Laplace noise Count sketch

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Focus on People: Five Questions from human-centered computing 22

Focus on People: Five Questions from Human-Centered Computin...

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Proceedings of the 2022 International Conference on Multimodal Interaction

作者： Daniel Gatica-Perez Social Computing Group Idiap Research Institute Switzerland and School of Engineering and College of Humanities Ecole Polytechnique Federale de Lausanne (EPFL) Switzerland

ISBN: (纸本)9781450393904

A substantial body of research in multimodal interaction has studied how people naturally interact –face-to-face and through machines– and developed technology to analyze, support, and extend such forms of interaction. The talk will share personal experiences and views on how audio-visual and ubiquitous research on social interaction has evolved over the past two decades. Five recurrent questions, then and now, include how to study interaction in everyday life; how to learn from and collaborate with the humanities and social sciences; how to think about data; how to address the challenges brought by automation; and how to engage and empower individuals and communities to take part in research projects. Today, the limitations of technology-centric solutions are more evident than ever. Future research with a people-first focus will continue to call for reflection, commitment, and action for a long-term alignment with societal needs and nature’s limits.

关键词： social interaction human-centered computing interaction in everyday life

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Small sample-based disease diagnosis model acquisition in medical human-centered computing

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2019年第1期2019卷 1页

作者： Jia, Xueqing Luo, Tao Ren, Sheng Guo, Kehua Li, Fangfang Natl Univ Def Technol Coll Elect Sci & Technol Changsha Hunan Peoples R China Cent South Univ Sch Comp Sci & Engn Changsha Hunan Peoples R China Hunan Univ Arts & Sci Sch Comp & Elect Engn Changde Peoples R China Cent South Univ Xiangya Hosp Dept Dermatol Changsha Hunan Peoples R China

With the development of wireless communications and networks, HCC (human-centred computing) has attracted considerable attention in recent years throughout the medical field. HCC can provide an effective integration of various medical auxiliary diagnosis models using machine learning algorithms. In medical HCC, deep learning has demonstrated its powerful ability in the field of computer vision. However, image processing based on deep learning usually requires a large amount of labeled data, which requires significant resources since it needs to be completed by doctors, and it is difficult to collect a large amount of data for some rare diseases. Therefore, how to use the deep learning method to obtain an effective auxiliary diagnosis model based on a small sample or zero sample data set has become an important issue in the study of medical auxiliary diagnosis. We proposes an auxiliary diagnosis model acquisition method based on a variational auto-encoder and zero sample augmentation technology, and the incremental update training program based on wireless communications and networks is designed to obtain the auxiliary diagnosis model to solve the difficulty of collecting a large amount of valid data. The experimental results show that the model obtained by the above method based on a small sample or zero sample data set can effectively diagnose the types of skin diseases, which helps doctors make better judgments.

关键词： Auxiliary diagnosis Small sample Variational auto-encoder human-centered computing

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Bringing Shades of Feminism to human-centered computing

Bringing Shades of Feminism to Human-Centered Computing

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CHI Conference on human Factors in computing Systems (CHI)

作者： Narvilkar, Manasee Mangiameli, Josiah Garcia, Adriana Alvarado Ismail, Azra Schiff, Daniel Schechter, Danielle Chen, Jordan Bhat, Karthik Wong-Villacres, Marisol Vasudeva, Anusha Ramesh, Aparna Dye, Michaelanne Karusala, Naveena Singh, Pragati Murthy, Savanthi Gupta, Shubhangi Lakshmi, Udaya Kumar, Neha Georgia Inst Technol Atlanta GA 30332 USA Univ Washington Seattle WA 98195 USA

This consolidation of 18 stories from students and researchers of human-centered computing (HCC) represents only some of the diverse shades of feminism that are present and emerging in our discipline. These stories-ou... 详细信息

ISBN: (纸本)9781450359719

关键词： human-centered computing feminism stories

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Learning from Wireless: a Prospective Approach to human-centered computing

Learning from Wireless: a Prospective Approach to Human-Cent...

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International Joint Conference on Neural Networks

作者： Yong Lu Shaohe Lv Xue Yang Xiaodong Wang Minne Li Xingming Zhou Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

ISBN: (纸本)9781509006212

One of the most important topics in human-centered computing (HCC) is to recognise human's activities. In this paper, the technology of wireless-based activity recognition is introduced. By using wireless signals, one can achieve Non-Line-Of-Sight (NLOS) recognition without carrying any devices. Also, it is easy to deploy a wireless-based recognition system due to the ubiquity of wireless communication systems. The basic idea is to detect different characteristics of signal propagation that correspond to the distinct human behaviors. As a result, action recognition is performed by analyzing the distinguishable features of signal propagation. This paper introduces the basic principles and applications of wireless-based activity recognition, and discusses the challenges and related performance metrics. Finally, open problems are discussed to point out the future research trends.

关键词： human-centered computing wireless Wireless communication systems Activity recognition recognition system Performance metrics signals Learning Paper Technology human behavior

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Exploring annotation taxonomy in grouped bar charts: A qualitative classroom study

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INFORMATION VISUALIZATION 2025年第1期24卷 79-94页

作者： Rahman, Md Dilshadur Quadri, Ghulam Jilani Szafir, Danielle Albers Rosen, Paul Univ Utah Sci Comp & Imaging Inst 72 Cent Campus Dr Salt Lake City UT 84112 USA Univ Oklahoma Sch Comp Sci Norman OK USA Univ North Carolina Chapel Hill Dept Comp Sci Chapel Hill NC 27599 USA

Annotations are an essential part of data analysis and communication in visualizations, which focus a readers attention on critical visual elements (e.g. an arrow that emphasizes a downward trend in a bar chart). Annotations enhance comprehension, mental organization, memorability, user engagement, and interaction and are crucial for data externalization and exploration, collaborative data analysis, and narrative storytelling in visualizations. However, we have identified a general lack of understanding of how people annotate visualizations to support effective communication. In this study, we evaluate how visualization students annotate grouped bar charts when answering high-level questions about the data. The resulting annotations were qualitatively coded to generate a taxonomy of how they leverage different visual elements to communicate critical information. We found that the annotations used significantly varied by the task they were supporting and that whereas several annotation types supported many tasks, others were usable only in special cases. We also found that some tasks were so challenging that ensembles of annotations were necessary to support the tasks sufficiently. The resulting taxonomy of approaches provides a foundation for understanding the usage of annotations in broader contexts to help visualizations achieve their desired message.

关键词： human-centered computing visualization empirical study bar chart annotation taxonomy

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Beyond the Screen With DanceSculpt: A 3D Dancer Reconstruction and Tracking System for Learning Dance

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INTERNATIONAL JOURNAL OF human-COMPUTER INTERACTION 2025年第9期41卷 5406-5419页

作者： Lee, Sanghyub Kang, Woojin Hong, Jin-Hyuk Kong, Duk-Jo Gwangju Inst Sci & Technol Sch Integrated Technol Gwangju South Korea Gwangju Inst Sci & Technol AI Grad Sch Gwangju South Korea Gwangju Inst Sci & Technol Ctr Res Innovat Gwangju South Korea

Dance learning through online videos has gained popularity, but it presents challenges in providing comprehensive information and personalized feedback. This paper introduces DanceSculpt, a system that utilizes 3D human reconstruction and tracking technology to enhance the dance learning experience. DanceSculpt consists of a dancer viewer that reconstructs dancers in video into 3D avatars and a dance feedback tool that analyzes and compares the user's performance with that of the reference dancer. We conducted a comparative study to investigate the effectiveness of DanceSculpt against conventional video-based learning. Participants' dance performances were evaluated using a motion comparison algorithm that measured the temporal and spatial deviation between the users' and reference dancers' movements in terms of pose, trajectory, formation, and timing accuracy. Additionally, user experience was assessed through questionnaires and interviews, focusing on aspects such as effectiveness, usefulness, and satisfaction with the system. The results showed that participants using DanceSculpt achieved significant improvements in dance performance compared to those using conventional methods. Furthermore, the participants rated DanceSculpt highly in terms of effectiveness (avg. 4.27) and usefulness (avg. 4.17) for learning dance. The DanceSculpt system demonstrates the potential of leveraging 3D human reconstruction and tracking technology to provide a more informative and interactive dance learning experience. By offering detailed visual information, multiple viewpoints, and quantitative performance feedback, DanceSculpt addresses the limitations of traditional video-based learning and supports learners in effectively analyzing and improving their dance skills.

关键词： human computer interaction human-centered computing dance support tool dance learning 3D human reconstruction

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Mobile edge assisted multi-view light field video system: Prototype design and empirical evaluation

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2024年 153卷 154-168页

作者： Pan, Yuxuan Luo, Kaiyue Liu, Yunming Xu, Chen Liu, Yu Zhang, Lin Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing 100876 Peoples R China

Metaverse is recently envisioned as the main driver for immersive multimedia in future networks. Light field video (LFV), considered an intermediate transition scheme towards the metaverse, is conducive to sensing and reconstructing realistic scenes in the digital twins. However, the research on LFV systems still lacks comprehensive investigation, impeding their practical application. This paper addresses major technical challenges involved in LFV delivery through mobile networks, showing a trade-off between equipment cost, calibration effort, and workflow simplicity. It also considers the balance of communications and computations latency when maintaining reconstruction performance. Leveraging edge and cloud infrastructure, a novel Mobile Edge Assisted Multi-view Light-field-video System (MEAMLS) is proposed, integrating LFV collection, volumetric video construction, and an immersive viewing scheme. A custom-made LFV capture array is designed to capture real-world scenes, while employing a learning method-integrated edge server to facilitate adaptive LFV coding. Moreover, a fast sparse reconstruction algorithm is established, leveraging edge-cloud collaboration to minimize computation latency during volumetric video construction. Intelligent service for users is deployed on edge to enable viewport-driven virtual reality viewing. By providing an immersive visual experience, the proposed MEAMLS bridges the physical world and its digital twins. The system is prototyped on a realistic 5G network to empirically validate the performance under static and dynamic circumstances. Experimental results yield fundamental insights for designing mobile edge networks-assisted LFV system from the perspective of transmission resource, adaptability, and deployment.

关键词： Edge intelligence Light field video 5G resource management human-centered computing 3D reconstruction Prototype

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Devising a High-Level Command Language for the Teleoperation of Autonomous Vehicles

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INTERNATIONAL JOURNAL OF human-COMPUTER INTERACTION 2025年第9期41卷 5299-5315页

作者： Tener, Felix Lanir, Joel Univ Haifa Informat Syst Haifa Israel

Autonomous vehicles (AVs) are rapidly evolving as a novel way of transportation. Nevertheless, there is a consensus that AVs cannot address all traffic scenarios independently. Consequently, there arises a need for remote human intervention. To pave the way for large-scale deployment of AVs onto public roadways, innovative models of remote operation must evolve. Such a paradigm is Tele-assistance, which posits that the low-level control of AVs should be delegated through high-level commands. Our work explores how such a command language should be constructed as a first step in designing a Tele-assistance user interface. Through interviews with 17 experienced teleoperators, we elicit a set of discrete commands that a remote operator can use to resolve various road scenarios. Subsequently, we create a scenario-command mapping and a thematic classification of the defined commands. Finally, we present an initial Tele-assistance interface design based on these commands.

关键词： human-centered computing human-computer interaction interaction design automobile empirical study elicitation study qualitative methods user interface design tele-driving tele-assistance

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mmTAA: A Contact-Less Thoracoabdominal Asynchrony Measurement System Based on mmWave Sensing

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IEEE TRANSACTIONS ON MOBILE computing 2025年第2期24卷 627-641页

作者： Zhang, Fenglin Zhang, Zhebin Kang, Le Zhou, Anfu Ma, Huadong Beijing Univ Posts & Telecommun Beijing Key Lab Intelligent Telecommun Software & Beijing 100876 Peoples R China

Thoracoabdominal Asynchrony (TAA) is a key metric in respiration monitoring, which characterizes the non-parallel periodical motion of human's rib cage (RC) and abdomen (AB) during each breath. Long-term measurement of TAA plays a significant role in respiration health tracking. Existing TAA measurement methods including Respiratory Inductive Plethysmography (RIP) and Optoelectronic Plethysmography (OEP) all intrusive to subjects and have certain requirements on operation conditions, which limit their usage to hospital scenario. To address this gap, we propose mmTAA, the first mmWave-based, non-intrusive TAA measurement system ready for ubiquitous usage in daily-life. In mmTAA, we design a Two-stage RC-AB centroid finding module, aiming to identify the most probable location of RC-AB centroid, which can best represent RC and AB in mmWave sensing scenario. Subsequently, we design TAANet, a novel Convolutional Neural Network (CNN)-based architecture with residual modules, tailored for TAA measurement. Meanwhile, in order to address the imbalance of continuous data, we add imbalance information equalizer including feature and label equalizer during network training. We implement mmTAA on a commonly used multi-antenna mmWave radar. We prototype, deploy and evaluate mmTAA on 25 subjects and 25.7h data in total. mmTAA achieves 4.01 degrees MAE and 1.56 degrees average error, close to OEP method.

关键词： Radar Millimeter wave communication Sensors Oscillators Mobile computing Equalizers Training Receivers Monitoring Cameras mmWave sensing thoracoabdominal asynchrony(TAA) human-centered computing

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