Reviewerly/exHarmony huggingface dataset:
Translation as (Re)mediation: How Ethnic Community-Based Organizations Negotiate Legitimacy

Ethnic community-based organizations (CBOs) play an essential role in supporting the wellbeing of immigrants and refugees. CBO workers often act as linguistic and cultural translators between communities, government, and health and social service systems. However, resource constraints, technological barriers, and pressures to be data-driven require workers to perform additional forms of translation to ensure their organizations' survival. Drawing on 16 interviews with members of 7 Asian American and Pacific Islander CBOs, we examine opportunities and barriers concerning their technology-mediated work practices. We identify two circumstances where CBO workers perform translation: (1) as legitimacy work to build trust with funders and communities, and (2) as (re)mediation in attending to technological barriers and resisting hegemonic systems that treat their communities as "other." By unpacking the politics of translation work across these sites, we position CBO workers as a critical source for HCI research and practice as it seeks to support community wellbeing.
Soliloquy: Fostering Poetry Comprehension Using an Interactive Think-aloud Visualization

Complex texts like poetry are distinct from informative texts, requiring additional subprocesses to decode and interpret. Approaching a poem without knowledge of these cognitive strategies can result in confusion and frustration—rather than comprehension. In this work, we explore how interfaces can surface and demonstrate these cognitive processes to novice readers. We introduce Soliloquy, an interface that visualizes the thoughts of an expert as they read and interpret a poem by using animations of text and pop-up tooltips. We evaluate the interface in a five-condition Mechanical Turk study (n=254) by varying the detail of thoughts, including audio, and substituting a static text control. Our study detected a significant difference in comprehension between the detail of thoughts, but not between the Soliloquy interface and static text control. We further investigate this finding in a think-aloud study (n=13), revealing the impact individual differences, experience, and cognitive load could have on Soliloquy's effectiveness.
transPAF: Rendering Omnidirectional Impact Feedback with Dynamic Point of Application of Force All Round a Controller

Impact force is common haptic feedback on virtual reality (VR) controllers, such as hitting objects with weapons or rackets. It applies to different points of application of force (PAFs) and directions in varied scenarios. For example, using weapons with different shapes, e.g., a sword and a pickaxe, using a weapon in different ways, e.g., stabbing and slashing with a sword, or a ball flying and hitting a racket in different directions cause different PAFs and/or force directions. Therefore, to achieve realistic VR experiences, rendering dynamic PAF and force direction is essential. Although previous works have proposed the concept of dynamic PAF, the PAF is only in a limited space and without dynamic force direction. Therefore, we propose a controller, transPAF, to render omnidirectional impact feedback with dynamic PAF all round the controller for versatile VR scenarios. transPAF consists of a controller, a semicircular track, a linear track, and an impactor, which are all rotatable. The impactor can move to any position in a sphere, which means the whole 3D space all round the controller, and rotate in any direction. Therefore, dynamic PAF and force direction are achieved and independent to each other. We conducted a just-noticeable difference (JND) study to understand users' distinguishability in position and direction, separately. A VR experience study was further performed to verify that feedback from transPAF with dynamic PAF and force direction enhances the VR experiences and demonstrate some applications for transPAF.
Evaluating the Extension of Wall Displays with AR for Collaborative Work

Wall displays are well suited for collaborative work and are often placed in rooms with ample space in front of them that remains largely unused. Augmented Reality (AR) headsets can seamlessly extend the collaboration space around the Wall. Nevertheless, it is unclear if extending Walls with AR is effective and how it may affect collaboration. We first present a prototype combining a Wall and AR headsets to extend the Wall workspace. We then use this prototype to study how users utilize the virtual space created in AR. In an experiment with 24 participants, we compare how pairs solve collaborative tasks with the Wall alone and with Wall+AR. Our qualitative and quantitative results highlight that with Wall+AR, participants use the physical space in front and around the Wall extensively, and while this creates interaction overhead, it does not impact performance and improves the user experience.
SurfAirs: Surface + Mid-air Input for Large Vertical Displays

Large vertical surfaces such as wall displays allow users to work with a very large and high-resolution workspace. Such displays promote physical navigation: users can step close to the display to see details, but also move away to get a wider view of the workspace. In terms of input, current solutions usually combine direct touch on the wall with input on a handheld device, disconnecting close and distant input rather than treating it as a continuum. We present SurfAirs, which are physical controllers that users can manipulate on screen (surface input), in the air (mid-air input), and transition from the surface to the air during a single manipulation (hybrid input). We report on two user studies that compare SurfAirs' performance with bare-hand input for both mid-air and hybrid input. Participants prefer and perform better with SurfAirs.
Beyond Skin Deep: Generative Co-Design for Aesthetic Prosthetics

There is a trend for handcrafting bespoke prostheses that embody their wearers' aesthetic tastes and identities. We explore how this might be extended by enabling users to co-design with algorithms. We report a design-led exploration (Figure 1) in which professional disabled dancers danced with a generative design algorithm to create personalised designs called aesthetic seeds. Further algorithms applied these to prosthetic greaves, rendering them in various materials before optimising for additive manufacture. Interviews with our dancers revealed that the aesthetics of prosthetics reach beyond visual decoration to encompass form, function, bodily experience, body image, and identity; that interactions with generative design algorithms can harness people's expressive and aesthetic skills; and that we must redesign supporting technologies for diverse bodies. We generalise our findings into a process for how people may co-design 3D printable products with algorithms.
An Augmented Knitting Machine for Operational Assistance and Guided Improvisation

Computational mediation can unlock access to existing creative fabrication tools. By outfitting an otherwise purely mechanical hand-operated knitting machine with lightweight sensing capabilities, we produced a system which provides immediate feedback about the state and affordances of the underlying knitting machine. We describe our technical implementation, show modular interface applications which center the particular patterning capabilities of this kind of machine knitting, and discuss user experiences with interactive hybrid computational/mechanical systems.
Affective Profile Pictures: Exploring the Effects of Changing Facial Expressions in Profile Pictures on Text-Based Communication

When receiving text messages from unacquainted colleagues in fully remote workplaces, insufficient mutual understanding and limited social cues can lead people to misinterpret the tone of the message and further influence their impression of remote colleagues. Emojis have been commonly used for supporting expressive communication; however, people seldom use emojis before they become acquainted with each other. Hence, we explored how changing facial expressions in profile pictures could be an alternative channel to communicate socio-emotional cues. By conducting an online controlled experiment with 186 participants, we established that changing facial expressions of profile pictures can influence the impression of the message receivers toward the sender and the message valence when receiving neutral messages. Furthermore, presenting incongruent profile pictures to positive messages negatively affected the interpretation of the message valence, but did not have much effect on negative messages. We discuss the implications of affective profile pictures in supporting text-based communication.
Maintainers of Stability: The Labor of China’s Data-Driven Governance and Dynamic Zero-COVID

This paper examines the social, technological, and emotional labor of maintaining China's data-driven governance broadly, and dynamic zero-COVID management in particular. Drawing on ethnographic research in China, we examine the sociotechnical work of maintenance during the 2022 Shanghai lockdown. This labor included coordinating mass testing, quarantine, and lockdown procedures as well as implementing ad-hoc technological workarounds and managing public sentiments. We demonstrate that, far from being effected from the top down, China's data-driven governance relies on the circumscribed participation of citizens. During Shanghai's lockdown, citizens with relevant expertise helped to maintain technological stability by fixing or programming data systems, but also to ensure the ongoing production of"positive feelings" about social stability through data-driven governance. In so doing, such citizens simultaneously enacted an ambivalent and circumscribed form of agency, and maintained social and by extension political stability. This article sheds light on data-driven governance and political processes of maintenance.
Putting the Self in Self-Tracking: The Value of a Co-Designed ‘How Might You’ Self-Tracking Guide for Teenagers

Although teenagers engage with Personal Informatics tools to track their health and fitness, many do so without adequate guidance, and they express concerns regarding the potential for these practices to bring harm. Further research is needed to understand how we might leverage resources beyond these tools to support young self-trackers. We worked with 44 teenagers (aged 13-18 years) in the United Kingdom in two series of online workshops to co-design a reimagined 'how might you' guide to promote lifelong, healthy behaviors with self-tracking tools. Our findings emphasize the importance of flexible resources that can support teens' self-tracking practices. For example, guidance on asking critical questions can be particularly valuable in the preparation and reflection stages of self-tracking. To better design teens' interactions with health technologies, particularly Personal Informatics tools, we must think critically about how we design the broader information ecosystems within which these tools reside.
Tutor In-sight: Guiding and Visualizing Students’ Attention with Mixed Reality Avatar Presentation Tools

Remote conferencing systems are increasingly used to supplement or even replace in-person teaching. However, prevailing conferencing systems restrict the teacher's representation to a webcam live-stream, hamper the teacher's use of body-language, and result in students' decreased sense of co-presence and participation. While Virtual Reality (VR) systems may increase student engagement, the teacher may not have the time or expertise to conduct the lecture in VR. To address this issue and bridge the requirements between students and teachers, we have developed Tutor In-sight, a Mixed Reality (MR) avatar augmented into the student's workspace based on four design requirements derived from the existing literature, namely: integrated virtual with physical space, improved teacher's co-presence through avatar, direct attention with auto-generated body language, and usable workflow for teachers. Two user studies were conducted from the perspectives of students and teachers to determine the advantages of Tutor In-sight in comparison to two existing conferencing systems, Zoom (video-based) and Mozilla Hubs (VR-based). The participants of both studies favoured Tutor In-sight. Among others, this main finding indicates that Tutor In-sight satisfied the needs of both teachers and students. In addition, the participants' feedback was used to empirically determine the four main teacher requirements and the four main student requirements in order to improve the future design of MR educational tools.
Doufu, Rice Wine, and面饼: Supporting the Connections between Precision and Cultural Knowledge in Cooking

The digital codification and measurement of food preparation has made strong contributions to HCI food research, whether through ingredient manipulation, workflow management, or recipe interaction. But prior work has shown that technical developments that emphasize precise gourmet practices tend to overlook the importance of cultural knowledge. Drawing on an integrative autobiographical design approach, we describe an open-source hardware toolkit that we developed to examine the process of integrating precision techniques with ritual cooking practices across three recipes: flour skin, rice wine, and doufu. Our work points to the importance of understanding precision as a cultural process with roots in personal and familial experience. We end with a reflection on the particular knowledge-forms that come from cultivating cultural relationships to fabrication processes and their implications for reading digital fabrication processes as meaningfully relational.
Suspended Circles: Soma Designing a Musical Instrument

We present a soma design process of a digital musical instrument grounded in the designer's first-person perspective of practicing Dalcroze eurhythmics, a pedagogical approach to learning music through movement. Our goal is to design an instrument that invites musicians to experience music as movement. The designer engaged in the soma design process, by first sensitising her body through Dalcroze training. Subsequently, she articulated her bodily experiences into experiential design qualities that guided the making of the instrument. The process resulted in the design of a large suspended mobile played by touching it with bare skin. We shared our instrument with 7 professional musicians and observed how it inspires a variety of approaches to musical meaning-making, ranging from exploring sound, to choreographing the body. Finally, we discuss how engaging with Dalcroze eurhythmics can be generative to the design of music–movement interaction.
How Can Deep Neural Networks Aid Visualization Perception Research? Three Studies on Correlation Judgments in Scatterplots

How deep neural networks can aid visualization perception research is a wide-open question. This paper provides insights from three perspectives—prediction, generalization, and interpretation—via training and analyzing deep convolutional neural networks on human correlation judgments in scatterplots across three studies. The first study assesses the accuracy of twenty-nine neural network architectures in predicting human judgments, finding that a subset of the architectures (e.g., VGG-19) has comparable accuracy to the best-performing regression analyses in prior research. The second study shows that the resulting models from the first study display better generalizability than prior models on two other judgment datasets for different scatterplot designs. The third study interprets visual features learned by a convolutional neural network model, providing insights about how the model makes predictions, and identifies potential features that could be investigated in human correlation perception studies. Together, this paper suggests that deep neural networks can serve as a tool for visualization perception researchers in devising potential empirical study designs and hypothesizing about perpetual judgments. The preprint, data, code, and training logs are available at https://doi.org/10.17605/osf.io/exa8m.
Designing Anekdota: Investigating Personal Metadata for Legacy

This project uses research through design to explore how metadata could be used as a design material to create inheritable artefacts that make personal legacy experiential. Metadata is produced as traces of life, and by designing artifacts that capture and represent these traces, interaction design offers the possibility to experience the everyday practices of someone else as they are passed on and inherited. We use interviews with people interested in data practices, memorializing, and who have experienced grief to find themes and insights for designing with metadata as well as for legacy. Based on these, we developed the prototype Anekdota, a handheld metadata detector that lets an inheritor experience bequeathed location metadata. From a series of think-aloud walks, Anekdota was tested with participants to reveal sensitizing concepts for designing for metadata, and imaginative leaps for how this metadata may become a part of future legacy practices.
Preservation and Reflection of Bisimilarity via Invertible Steps

Abstract In the theory of coalgebras, distributive laws give a general perspective on determinisation and other automata constructions. This perspective has recently been extended to include so-called weak distributive laws, covering several constructions on state-based systems that are not captured by regular distributive laws, such as the construction of a belief-state transformer from a probabilistic automaton, and ultrafilter extensions of Kripke frames. In this paper we first observe that weak distributive laws give rise to the more general notion of what we call an invertible step: a pair of natural transformations that allows to move coalgebras along an adjunction. Our main result is that part of the construction induced by an invertible step preserves and reflects bisimilarity. This covers results that have previously been shown by hand for the instances of ultrafilter extensions and belief-state transformers.
A Preliminary Study of World Customizability for Virtual Reality Co-Play

Cooperative play, or "co-play", is the act of playing with others in a co-located setting, including co-location of avatars in virtual reality (VR). Customizability is the degree to which play artifacts like props can be changed to suit different needs, a factor of co-play which is easier to support in VR than in the real world. We present the results of a preliminary user study that explores how different levels of customization affect creativity in a two-person VR co-play setting. Using the Creativity Support Index, system logs, and observations, we found that increasing customizability of props used to improvise a story trended toward higher levels of perceived creativity. Our work introduces a new topic of investigation for social VR together with a study methodology and initial results to motivate further investigation.
Beyond Instructions: A Taxonomy of Information Types in How-to Videos

How-to videos are rich in information—they not only give instructions but also provide justifications or descriptions. People seek different information to meet their needs, and identifying different types of information present in the video can improve access to the desired knowledge. Thus, we present a taxonomy of information types in how-to videos. Through an iterative open coding of 4k sentences in 48 videos, 21 information types under 8 categories emerged. The taxonomy represents diverse information types that instructors provide beyond instructions. We first show how our taxonomy can serve as an analytical framework for video navigation systems. Then, we demonstrate through a user study (n=9) how type-based navigation helps participants locate the information they needed. Finally, we discuss how the taxonomy enables a wide range of video-related tasks, such as video authoring, viewing, and analysis. To allow researchers to build upon our taxonomy, we release a dataset of 120 videos containing 9.9k sentences labeled using the taxonomy.
Research on Data Acquisition Technology of Intelligent Laboratory Based on Retinex-Net Image Recognition

Abstract The reliability of electric power metering verification data is related to the accuracy and fairness of electric power trade settlement. Most of the existing verification equipment uses traditional pointer-type electrical verification instruments. The verification process requires the manual recording of data and the issuance of verification reports. There are problems such as low data collection efficiency, high error rate, and human tampering, which lead to great uncertainty in the detection results. This paper presents a data acquisition technology of pointer-type electrical verification instruments based on Retinex-Net image recognition for power metering verification data acquisition of intelligent laboratory, which realizes automatic data acquisition of power metering verification, ensures the accuracy and reliability of verification results, and effectively supports the digital transformation and development of power metering verification field.
PRESCAN Adaptive Vehicle Image Real-Time Stitching Algorithm Based on Improved SIFT

Aiming at the problems of high latency, low accuracy, and obvious stitching gaps of traditional image stitching techniques in PRESCAN, this paper proposes an adaptive real-time vehicle image stitching algorithm based on improved scale-invariant feature transform (SIFT). Firstly, a multi-threaded structure is utilized to combine the improved adaptive features from accelerated segment test algorithm with SIFT descriptors for feature extraction. Secondly, a mismatching filtering strategy based on the BF algorithm has been introduced. Finally, image stitching is performed by combining random sample consensus algorithm and adaptive region stitching strategy. The results show that the recall rate is about 30.64%, the accuracy of matching is about 98.86%, and the total stitching time is about 22.82ms. It effectively improves the quality of feature point extraction and matching accuracy and significantly reduces the stitching time of images. It provides a real-time and accurate vehicle image stitching method for the field of perception in the autonomous driving laboratory environment.
Dual-Branch Network Fused With Two-Level Attention Mechanism for Clothes-Changing Person Re-Identification

Clothes-changing person re-identification is a hot topic in the current academic circles. Most of the current methods assume that the clothes of a person will not change in a short period of time, but they are not applicable when people change clothes. Based on this situation, this paper proposes a dual-branch network for clothes-changing person re-identification that integrates a two-level attention mechanism and captures and aggregates fine-grained person semantic information in channels and spaces through a two-level attention mechanism and suppresses the sensitivity of the network to clothing features by training the clothing classification branch. The method does not use auxiliary means such as human skeletons, and the complexity of the model is greatly reduced compared with most methods. This paper conducts experiments on the popular clothes-changing person re-identification dataset PRCC and a very large-scale cross-spatial-temporal dataset (LaST). The experimental results show that the method in this paper is more advanced than the existing methods.