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检索条件"主题词=Human-centered computing"

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VR Piano Learning Platform with Leap Motion and Pressure Sensors

VR Piano Learning Platform with Leap Motion and Pressure Sen...

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27th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Wijaya, Febrina Tseng, Ying-Chun Tsai, Wan-Lun Pan, Tse-Yu Hu, Min-Chun Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan Taiwan Natl Tsing Hua Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781728165325

Aiming at helping novices to learn and practice playing piano without a real piano teacher, we propose a virtual reality (VR) piano system which can record the user's piano fingering data. Our system uses two Leap Motion sensors for wide-range hand tracking, and we developed a method to calibrate and compose the tracking results of two Leap Motion sensors. However, Leap Motion sensors fail to accurately detect whether a finger presses a key because the precision of the estimated depth is not high enough. Hence, we employ multiple pressure sensors attached on the user's fingertips to more accurately check whether the user is pressing the piano key or not. An HTC Vive headset is used to display the immersive VR environment while the user practices. Moreover, a transparent acrylic board is mounted above the Leap Motion sensors so that the player can directly play on the board, which enhances the immersion and presence by touching a physical object. The experimental results show that our VR piano system provides users a great piano-playing experience and is helpful for piano learning.

关键词： human-centered computing human Computer Interaction Interaction Paradigms Virtual Reality

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A Tale on Abuse and Its Detection over Online Platforms, Especially over Emails": From the Context of Bangladesh 21

A Tale on Abuse and Its Detection over Online Platforms, Esp...

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8th International Conference on Networking, Systems and Security, NSysS 2021

作者： Haque, Ishita Adnin, Rudaiba Afroz, Sadia Huq, Faria Mahbub, Sazan Alim Al Islam, A.B.M. Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Bangladesh Computer Science University of Maryland at College Park United States

ISBN: (纸本)9781450387378

With the advent of pervasive usage of online platforms, online abusive behavior has become an indispensable part of our life demanding great attention from the research community. Accordingly, the research community is spending its effort on the demanding task, however, perhaps having much less effort on emails, even though emails are identified as a prominent source of exchanging online abusive behaviors. To fill in this gap in the literature, we conduct an in-depth study to investigate online abusive behavior having a special focus on emails. To do so, we perform a mixed-method user study consisting of formative interviews (n=15) and a survey (n=65) over user's experience, coping strategies, etc., pertinent to online abuse in Bangladesh, especially focusing on abuse over emails. We also dig into users' perspectives to analyze strengths and challenges associated with different types of abuse detection systems for online platforms, especially for emails. One of the noteworthy findings of our study is that there exists a significant demand for abuse detection systems over emailing platforms even after having a lesser frequency of abuse occurring over emails. Our findings also highlight a certain level of user preference for an automated abuse detection system potentially considering its more control and fewer privacy concerns to users, however, being challenged due to having the limitation of lesser ability to detect implicit abuse. We also identify several limiting factors associated with a human-moderator-based abuse detection system, including less comfort, less trust in different types of moderators, inhumane demands to the moderators, and time delay in detecting abuses. These findings point to opportunities for design interventions for hybrid abuse detection systems, which is the most preferred system to the users, to overcome all the limitations of automated and human-moderator-based systems. © 2021 ACM.

关键词： Abuse detection systems Privacy Emails User studies human-centered computing Online abuse

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Keynote Address: human-amplifying and Transformational computing 13

Keynote Address: Human-amplifying and Transformational Compu...

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Proceedings of Alice Symposium on Alice Symposium

作者： Tiffany Barnes North Carolina State University Raleigh NC USA

ISBN: (纸本)9781450322508

human-centered computing has at its core the idea that humans are central to many of the things we create and use computers to do. On a recent trip to Haiti, I began to rethink my own perspective on computing - what, exactly, are computers and computing for? computing is and should be about amplifying people - to be more of what we think of as "human". Not only can computing amplify intelligence - it can amplify compassion, communication, understanding, and creativity - and even transform people and our society. Programming languages like Alice, Scratch, and Snap and the creation of serious games highlight the importance of leveraging creativity to inspire the next wave of transformative innovation in computing. In this talk I'll lead in with this idea and give an overview of my work including: my new course on the Beauty and Joy of computing, the STARS Alliance for broadening participation, creating games for education, exercise, and energy, and using data to personalize learning experiences.

关键词： Serious Games Broadening Participation STARS Alliance Alice human-centered computing

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Reaching Across the Communication Gap: Evaluating How Augmented Reality Shared Gestural Spaces Impact Gesture and Language Usage 53

Reaching Across the Communication Gap: Evaluating How Augmen...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Hordemann, Glen Quek, Francis Powell, Larry Texas Am University Dept. of Electrical Eng. and Computer Science College StationTX United States

ISBN: (纸本)9798350336429

Instructional discourse around physically-based material typically involves the use of gestures to focus attention in the joint visual space of the instructor and the student. Such gestures are performed in conjunction with speech, thus situating the discourse in the space of what the student is learning or doing. This kind of situated discourse is missing in distance learning. The lack of situatedness between conversants contributes to communication inefficiencies, as was recently highlighted when classes began using Zoom during COVID. For instruction that involves hands-on learning, the inability for instructors to index the student's space and vice versa is a more significant problem. The use of telepresence technologies allows this spatial gap to be bridged but can often leave a communication gap. Little evaluation has been made into how these mechanisms alter gesture and speech. This paper explores how giving the instructor situated gestural access to the student's workspace in distant learning settings alters gesture and speech, with the goal of guiding design of future systems that are mindful of how these systems work, not simply whether they work. Our research is based on a system that supports situated instructional discourse through augmented reality gesturing. The instructor is able to see the student's workspace and perform gestures that are superposed into the student's workspace. This shared gestural space is used in tandem with a traditional video chat. Two spatially-focused tasks were examined: a two-dimension problem that required varying levels of assistance, and a three-dimension problem with complete guidance by the instructor needed. We evaluated how gestures were used to augment verbal communication and the types of gestures and verbal utterances used. We found that static pointing G-hand deictic gestures were more common in the augmented reality mode than in the co-situated mode and complex spatial structuring gestures (e.g. orientation gestu

关键词： augmented reality human computer interaction (HCI) human-centered computing Interaction paradigms

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Contextualizing User Perceptions about Biases for human-centered Explainable Artificial Intelligence 23

Contextualizing User Perceptions about Biases for Human-Cent...

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CHI conference on human Factors in computing Systems (CHI)

作者： Yuan, Chien Wen (Tina) Bi, Nanyi Lin, Ya-Fang Tseng, Yuen-Hsien Natl Taiwan Univ Taipei Taiwan Penn State Univ State Coll PA USA Natl Taiwan Normal Univ Taipei Taiwan

ISBN: (纸本)9781450394215

Biases in Artifcial Intelligence (AI) systems or their results are one important issue that demands AI explainability. Despite the prevalence of AI applications, the general public are not necessarily equipped with the ability to understand how the black-box algorithms work and how to deal with biases. To inform designs for explainable AI (XAI), we conducted in-depth interviews with major stakeholders, both end-users (n = 24) and engineers (n = 15), to investigate how they made sense of AI applications and the associated biases according to situations of high and low stakes. We discussed users' perceptions and attributions about AI biases and their desired levels and types of explainability. We found that personal relevance and boundaries as well as the level of stake are two major dimensions for developing user trust especially during biased situations and informing XAI designs.

关键词： Artifcial Intelligence human-Computer Interaction (HCI) Explainable AI (XAI) human-centered computing Explainability Transparency AI bias

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Parametric Dimension Reduction by Preserving Local Structure

Parametric Dimension Reduction by Preserving Local Structure

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IEEE Visualization Conference (VIS)

作者： Lai, Chien-Hsun Kuo, Ming-Feng Lien, Yun-Hsuan Su, Kuan-An Wang, Yu-Shuen Natl Yang Ming Chiao Tung Univ Hsinchu Taiwan

ISBN: (数字)9781665488129

ISBN: (纸本)9781665488129

We extend a well-known dimension reduction method, t-distributed stochastic neighbor embedding (t-SNE), from non-parametric to parametric by training neural networks. The main advantage of a parametric technique is the generalization of handling new data, which is beneficial for streaming data visualization. While previous parametric methods either require a network pre-training by the restricted Boltzmann machine or intermediate results obtained from the traditional non-parametric t-SNE, we found that recent network training skills can enable a direct optimization for the t-SNE objective function. Accordingly, our method achieves high embedding quality while enjoying generalization. Due to mini-batch network training, our parametric dimension reduction method is highly efficient. For evaluation, we compared our method to several baselines on a variety of datasets. Experiment results demonstrate the feasibility of our method. The source code is available at https://***/a07458666/parametric_dr.

关键词： computing methodologies Dimensionality reduction and manifold learning human-centered computing Visualization toolkits

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AMBIENCE & COLLABORATION Embedded Agents in a human-centered World

AMBIENCE & COLLABORATION <i>Embedded Agents in a Human</i>-<...

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4th International Conference on Software and Data Technologies

作者： O'Grady, M. J. O'Hare, G. M. P. Tynan, R. Collier, R. W. Muldoon, C. Univ Coll Dublin CLARITY Ctr Sensor Web Technol Sch Comp Sci & Informat Dublin 4 Ireland Univ Coll Dublin Sch Comp Sci & Informat Dublin Ireland

ISBN: (纸本)9789896740108

Supporting people in the pursuit of their everyday activities is a laudable objective and one which researchers in various disciplines including computing, actively seek to accomplish. The dynamic nature of the end-user community, the environments in which they operate, and the multiplicity of tasks in which they engage in, all seem to conspire against the desired objective of providing services to the end-user community in a transparent, intuitive and context-aware fashion. Indeed, this inherent complexity raises fundamental problems for software engineers as they frequently lack the tools to effectively model the various scenarios that dynamic user behaviour give rise to. This difficulty is not limited to exotic applications or services;rather, it is characteristic of situations where a number of factors must be identified, interpreted, and reconciled such that an accurate model of the prevailing situation at a given moment in time can be constructed. Only in this way, can services be delivered that take into account the prevailing human, social, environmental and technological conditions. Constructing such services calls for a software solution that exhibits, amongst others, diffusion, autonomy, cooperation and intelligence. In this paper, the potential of embedded agents for realising such solutions is explored.

关键词： Ambient Intelligence Embedded agents human-centered computing

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Using action-level metrics to report the performance of multi-step keyboards

Using action-level metrics to report the performance of mult...

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Graphics Interface 2021

作者： Rakhmetulla, Gulnar Arif, Ahmed Sabbir Castellucci, Steven J. MacKenzie, I. Scott Seim, Caitlyn E. Human-Computer Interaction Group University of California Merced United States Toronto Canada York University Canada Stanford University United States

ISBN: (纸本)9780994786869

Computer users commonly use multi-step text entry methods on handheld devices and as alternative input methods for accessibility. These methods are also commonly used to enter text in languages with large alphabets or complex writing systems. These methods require performing multiple actions simultaneously (chorded) or in a specific sequence (constructive) to produce input. However, evaluating these methods is difficult since traditional performance metrics were designed explicitly for non-ambiguous, uni-step methods (e.g., QWERTY). They fail to capture the actual performance of a multi-step method and do not provide enough detail to aid in design improvements. We present three new action-level performance metrics: UnitER, UA, and UnitCX. They account for the error rate, accuracy, and complexity of multi-step chorded and constructive methods. They describe the multiple inputs that comprise typing a single character-action-level metrics observe actions performed to type one character, while conventional metrics look into the whole character. In a longitudinal study, we used these metrics to identify probable causes of slower text entry and input errors with two existing multi-step methods. Consequently, we suggest design changes to improve learnability and input execution. © 2021 Canadian Information Processing Society. All rights reserved.

关键词： Empirical studies in HCI human-centered computing human-centered computing Usability testing humancentered computing User studies

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Revealing Factors Influencing Students' Perceived Fairness: A Case with a Predictive System for Math Learning 22

Revealing Factors Influencing Students' Perceived Fairness: ...

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9th Annual ACM Conference on Learning at Scale, L@S 2022

作者： Li, Chenglu Xing, Wanli University of Florida GainesvilleFL United States

ISBN: (纸本)9781450391580

Educational researchers have examined artificial intelligence (AI) to automatically support students' learning at a large scale. However, it has been broadly identified that AI models can suffer from algorithmic bias. A recent educational research initiative has shifted to evaluate and address algorithmic bias. Nonetheless, few studies have examined students' perceived fairness towards AI-enhanced systems in education. This study aimed to explore and understand factors that shape students' perceived fairness towards an AI system for math learning at the college level. Specifically, we have conducted a between-subjects randomized experiment with 395 participants to reveal factors that influenced participants' perceptions of fairness. The results showed that students' math anxiety levels and majors could influence participants' reported perceived fairness. In contrast, the outcome favorability of the predictive system did not affect students' perceptions of fairness. Future investigations have been planned to further understand the relationships between the designed manipulations and perceived fairness. © 2022 ACM.

关键词： fair AI math learning human-centered computing perceived fairness

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Exploratory Review: Trust Dynamics in AI-Enabled Retail Financial Investment Service

Exploratory Review: Trust Dynamics in AI-Enabled Retail Fina...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Ding, Ling Zhao, Zhao McEwen, Rhonda N. Victoria University in the University of Toronto Emerging Technologies and the Arts Lab Toronto Canada McMaster University Dept. of Computing and Software Hamilton Canada

ISBN: (纸本)9798350324136

Trust anchors financial markets, which directly contribute to the foundation of global economies, and simultaneously fuel FinTech innovations. AI-driven tools such as Robo-Advisors, Equity crowdfunding, and Peer-To-peer lending reshape investment paradigms, but understanding trust within this digital realm remains elusive. This scoping review examines AI trust dynamics within retail financial investments. We locate and dissect thematic constructs, and assess the complex interplay of pivotal variables. While initial insights emphasize trust's critical role in FinTech's evolution, they also illuminate the constraints of a universal framework to analyze trust in this context. Despite the popularity of models like TAM and UTAUT, their inherent weaknesses leave important facets unexplored. While qualitative and quantitative methods predominantly inform the current discourse, many studies base their conclusions on niche or self-crafted hypotheses. Through this systematic review, we chart a path for future discussions on AI-driven financial trust, highlighting gaps, and offering new avenues for exploration. © 2024 IEEE.

关键词： Computer Mediated Communication Concepts and models Finance/Money human computer interaction(HCI) human-centered computing Meta-Analysis/Literature Survey

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