Miracle-dz/UniFAR-FTUs huggingface dataset:
Can a Computer Tell Differences between Vibrations?: Physiology-Based Computational Model for Perceptual Dissimilarity Prediction

Perceptual dissimilarities, requiring high-cost user ratings, have contributed to designing well-distinguishable vibrations for associated meaning delivery. Appropriate metrics can reduce the cost, but known metrics in vibration similarity/dissimilarity could not predict them robustly. We propose a physiology-based model (PM) that predicts the perceptual dissimilarities of a given vibration set via two parallel processes: Neural Coding (NC), mimicking the neural signal transfer, and One-dimensional Convolution (OC), capturing rhythmic features. Eight parameters were trained using six datasets published in the literature to maximize Spearman’s Rank Correlation. We validated PM and six metrics of RMSE, DTW, Spectral/Temporal Matchings, ST-SIM, and SPQI in twelve datasets: six trained and six untrained datasets including measured accelerations. In all validations, PM’s predictions showed robust correlations with user data and similar structures in perceptual spaces. Other baseline metrics showed better fit in specific datasets, but none of them robustly showed correlations and similar perceptual spaces over twelve datasets.
Image Recognition Algorithm of Sousa Chinensis based on deep learning

At present, most of the work of using images to identify Sousa Chinensis still relies on manual labor, which is time-consuming and difficult to process a large number of pictures taken during the survey in time. This paper proposes an image recognition method of Sousa Chinensis based on deep learning to improve Sousa Chinensis' recognition efficiency and accuracy significantly. Using technologies such as the improved YOLO V5 neural network model and the Kmeans clustering algorithm, Sousa Chinensis ' images can be quickly and accurately recognized. The dorsal fin area can be automatically selected to add keyword labels. After the successful identification of the dorsal fin profile of the Sousa Chinensis, this study also accurately distinguished the Sousa Chinensis among individuals by constructing a convolutional neural network, ResNet101 network model, and Faster-RCNN target detection algorithm according to the occurrence time, gray level of body color, dorsal fin shape, and spots and other parameters of the Sousa Chinensis. Experimental results show that this study can effectively identify the dorsal fin of Sousa Chinensis and improve the work efficiency of Marine biologists.
Hearing the Way Forward: Exploring Ambient Navigational Awareness with Reduced Cognitive Load through Spatial Audio-AR

Notifications and alerts can both convey critical data needed to make decisions as we go about our day, and at the same time be completely ignored as a result of the overuse of these channels. Auditory notifications can be especially intrusive given their demand for synchronous attention. However, during some activities, such as navigation guidance via GPS, immediate information cues are necessary. In this case audio alerts and instructions are typically implemented as voice commands, but processing language requires significant cognitive resources and attention. In this study we report findings about the feasibility of a novel ambient pedestrian guidance system inspired by neuroscience. Results suggest that it is possible to communicate precise spatial actions without the intrusion of verbal turn-by-turn cues. We also share learnings from our use of low-fidelity prototyping to evaluate the novel audio-AR interaction.
Vortex Wakes Of Bird Flight: Old Theory, New Data AndFuture Prospects

Flying birds leave a vortex wake. Fluid dynamic theory in the form of Helmholtz’ theorems dictate the allowable topologies, and Kelvin’s circulation theorem requires that changes in wake circulation are directly proportional to force changes on the wing/aerofoil that generated the wake. Much bird flight research has therefore been focused on the properties of trailing wake vortices behind birds, since an accurate quantitative description of these will reveal also the aerodynamics of bird wings. The first vortex theory of bird flight assumed the periodic shedding of discrete vortex loops, each one generated during a downstroke, while the upstroke was considered aerodynamically functionless. This view received some support from early visualization experiments of take-off flight or very low speeds, while experiments at a higher speed (U = 7 m/s) in one species showed undulating wing-tip vortices of similar circulation on both down and upstroke. The necessary force asymmetry between downstroke and upstroke was obtained by wing flexing during the upstroke. Then followed an almost 20-year drought, with no further quantitative experiments, until recently when digital particle imaging velocimetry (DPIV) was successfully deployed in a low-turbulence wind tunnel, and where the same small (30 g) bird could be studied across a large range of flight speeds (4–11 m/s). These new experiments revealed a much more complicated wake pattern than previous data suggested, mainly due to the improved experimental resolution. The bird generated structures most closely resembling vortex loops at slow speeds, which gradually transformed into something similar to a constant circulation wake at the highest speeds. However, the wakes were never as clean as the idealized cartoon models of the vortex theory of bird flight, and previous paradoxical results were shown to be attributable to the resulting difficulty in accounting for all wake components. New DPIV data on other species indicate that these findings are quite general.
Digital Reading Rulers: Evaluating Inclusively Designed Rulers for Readers With Dyslexia and Without

Physical reading rulers are simple yet effective interventions that help readers with dyslexia. Digital reading rulers may offer similar benefits. Given their potential value, we provide the following contributions: (1) We host focus group sessions including people with dyslexia to build upon their lived experiences, (2) We provide evidence for designs that are effective and preferred, (3) We measure reading gains of rulers for readers with and without dyslexia. Using inclusive design principles, we arrive at four digital ruler designs - Grey Bar, Lightbox, Shade, and Underline. For the first time, we offer a comprehensive evaluation of digital ruler effectiveness on 91 crowdsourced readers with dyslexia and 86 without. Considering reading speed, comprehension, and preference, many readers benefit from these rulers, with the largest gains among readers with dyslexia. Rulers designed by readers with dyslexia increased the reading speeds of readers with dyslexia, supporting the need for inclusive design practices.
An Intelligent Fault Detection Method for Raw Material Grinding of Vertical Cement Mills Using Wavelet Kernel Based Light-weighted Neural Networks

The vertical cement mill is widely used in the cement industry due to low power consumption, high energy efficiency, and its compact size. The intelligent fault detection using reducer vibration data for vertical cement mills is of great importance for safe, stable, and efficient operation. In this paper, a deep learning based fault diagnosis method using 1D samples is proposed. For fast and low cost detection, the convolution neural network is improved for real-time implementation. The depthwise separable convolution and inverted residual block are applied for light-weighted network construction. The feature extraction is performed by the wavelet kernel based convolution layer. Three kinds of wavelet basis have been applied, namely Laplace, Mexhat, and Morlet basis. To improve the feature extraction performance of the first convolution layer, different wavelet basis functions are testd. The number of convolution layers is reduced to extract more features. Measured signals from a cement slurry factory in China are used to verify the effectiveness of proposed detection method. The light-weighted network structure provides 75% reduction of the memory space. Compared with conventional cement mill fault diagnosis methods, which acquire high-dimensional data and high frequency sampled signals, the proposed method adopts data measured in a simpler way with compatible detection accuracy.
How bold can we be? The impact of adjusting font grade on readability in light and dark polarities

Variable font file technology enables adjusting fonts on scaled axes that can include weight, and grade. While making text bold increases the character width, grade achieves boldness without increasing character width or causing text reflow. Through two studies with a total of 459 participants, we examined the effect of varying grade levels on both glancing and paragraph reading tasks in light and dark modes. We show that dark text on a light background (Light Mode) is read reliably faster than its polar opposite (Dark Mode). We found an effect of mode for both glance and paragraph reading and an effect of grade for LM with heavier, increased grade levels. Paragraph readers are not choosing, or preferring, LM over DM despite fluency benefits and reported visual clarity. Software designers can vary grade across the tested font formats to influence design aesthetics and user preferences without worrying about reducing reading fluency.
SwitchTube: A Proof-of-Concept System Introducing “Adaptable Commitment Interfaces” as a Tool for Digital Wellbeing

YouTube has many features, such as homepage recommendations, that encourage users to explore its vast library of videos. However, when users visit YouTube with a specific intention, e.g., learning how to program in Python, these features to encourage exploration are often distracting. Prior work has innovated ‘commitment interfaces’ that restrict social media but finds that they often indiscriminately block needed content. In this paper, we describe the design, development, and evaluation of an ‘adaptable commitment interface,’ the SwitchTube mobile app, in which users can toggle between two interfaces when watching YouTube videos: Focus Mode (search-first) and Explore Mode (recommendations-first). In a three-week field deployment with 46 US participants, we evaluate how the ability to switch between interfaces affects user experience, finding that it provides users with a greater sense of agency, satisfaction, and goal alignment. We conclude with design implications for how adaptable commitment interfaces can support digital wellbeing.
VRGit: A Version Control System for Collaborative Content Creation in Virtual Reality

Immersive authoring tools allow users to intuitively create and manipulate 3D scenes while immersed in Virtual Reality (VR). Collaboratively designing these scenes is a creative process that involves numerous edits, explorations of design alternatives, and frequent communication with collaborators. Version Control Systems (VCSs) help users achieve this by keeping track of the version history and creating a shared hub for communication. However, most VCSs are unsuitable for managing the version history of VR content because their underlying line differencing mechanism is designed for text and lacks the semantic information of 3D content; and the widely adopted commit model is designed for asynchronous collaboration rather than real-time awareness and communication in VR. We introduce VRGit, a new collaborative VCS that visualizes version history as a directed graph composed of 3D miniatures, and enables users to easily navigate versions, create branches, as well as preview and reuse versions directly in VR. Beyond individual uses, VRGit also facilitates synchronous collaboration in VR by providing awareness of users’ activities and version history through portals and shared history visualizations. In a lab study with 14 participants (seven groups), we demonstrate that VRGit enables users to easily manage version history both individually and collaboratively in VR.
External noise reduction using WhisperMask, a mask-type wearable microphone

Conversation through voice is one of the basic means of human communication. Online communication systems and voice user interfaces for operating smartphones or smart devices are increasingly important as an interface that anyone can use daily. However, voice input is difficult to use in noisy environments or in environments where multiple people speak at the same time because unintended voices are included. Conventional microphones such as pin microphones or contact-type microphones such as throat microphones, and NAM microphones have been proposed for reducing external noise, however, pin microphones are not tolerant of high volume, and contact-type microphones generate contact noise when the user nods or walks. We propose WhisperMask, a wearable electret condenser microphone that can acquire speech even in noisy environments. In addition, the proposed mask-shaped microphone allows hands-free input and is wearable, unobtrusive, and lightweight interface.
Rapid Flight Maneuver Modeling Technology for Large-Scale Simulation

In order to meet the requirements of intelligent confrontation game system for system simulation acceleration ability, this paper has analyzed large-scale air force simulation and then proposed a rapid flight maneuver simulation modeling, through reducing variables, simplifying parameters, equivalent calculation, etc., grounded on the requirements of system confrontation for the fidelity, real-time and accuracy of the modeling of aerial vehicles such as aircraft, missiles, etc. The modeling proposed in the paper can model the trajectory and attitude of the aircraft correctly with conforming to the general laws of flight physics to meet the requirements of system confrontation modeling simulation and intelligent game confrontation, and also greatly improve the efficiency of simulation model. This method has been proved correct by virtue of the computer simulation results.
LearnIoTVR: An End-to-End Virtual Reality Environment Providing Authentic Learning Experiences for Internet of Things

The rapid growth of Internet-of-Things (IoT) applications has generated interest from many industries and a need for graduates with relevant knowledge. An IoT system is comprised of spatially distributed interactions between humans and various interconnected IoT components. These interactions are contextualized within their ambient environment, thus impeding educators from recreating authentic tasks for hands-on IoT learning. We propose LearnIoTVR, an end-to-end virtual reality (VR) learning environment which helps students to acquire IoT knowledge through immersive design, programming, and exploration of real-world environments empowered by IoT (e.g., a smart house). The students start the learning process by installing virtual IoT components we created in different locations inside the VR environment so that the learning will be situated in the same context where the IoT is applied. With our custom-designed 3D block-based language, students can program IoT behaviors directly within VR and get immediate feedback on their programming outcome. In the user study, we evaluated the learning outcomes among students using LearnIoTVR with a pre- and post-test to understand to what extent does engagement in LearnIoTVR lead to gains in learning programming skills and IoT competencies. Additionally, we examined what aspects of LearnIoTVR support usability and learning of programming skills compared to a traditional desktop-based learning environment. The results from these studies were promising. We also acquired insightful user feedback which provides inspiration for further expansions of this system.
EchoSpeech: Continuous Silent Speech Recognition on Minimally-obtrusive Eyewear Powered by Acoustic Sensing

We present EchoSpeech, a minimally-obtrusive silent speech interface (SSI) powered by low-power active acoustic sensing. EchoSpeech uses speakers and microphones mounted on a glass-frame and emits inaudible sound waves towards the skin. By analyzing echos from multiple paths, EchoSpeech captures subtle skin deformations caused by silent utterances and uses them to infer silent speech. With a user study of 12 participants, we demonstrate that EchoSpeech can recognize 31 isolated commands and 3-6 figure connected digits with 4.5% (std 3.5%) and 6.1% (std 4.2%) Word Error Rate (WER), respectively. We further evaluated EchoSpeech under scenarios including walking and noise injection to test its robustness. We then demonstrated using EchoSpeech in demo applications in real-time operating at 73.3mW, where the real-time pipeline was implemented on a smartphone with only 1-6 minutes of training data. We believe that EchoSpeech takes a solid step towards minimally-obtrusive wearable SSI for real-life deployment.
ResType: Invisible and Adaptive Tablet Keyboard Leveraging Resting Fingers

Text entry on tablet touchscreens is a basic need nowadays. Tablet keyboards require visual attention for users to locate keys, thus not supporting efficient touch typing. They also take up a large proportion of screen space, which affects the access to information. To solve these problems, we propose ResType, an adaptive and invisible keyboard on three-state touch surfaces (e.g. tablets with unintentional touch prevention). ResType allows users to rest their hands on it and automatically adapts the keyboard to the resting fingers. Thus, users do not need visual attention to locate keys, which supports touch typing. We quantitatively explored users’ resting finger patterns on ResType, based on which we proposed an augmented Bayesian decoding algorithm for ResType, with 96.3% top-1 and 99.0% top-3 accuracies. After a 5-day evaluation, ResType achieved 41.26 WPM, outperforming normal tablet keyboards by 13.5% and reaching 86.7% of physical keyboards. It solves the occlusion problem while maintaining comparable typing speed with current methods on visible tablet keyboards.
Towards Designing Playful Bodily Extensions: Learning from Expert Interviews

Interactive technologies offer novel opportunities for physically extending our bodies, with the most prominent examples being prosthetics along with systems emerging from the wearables community. However, most such systems appear to focus on instrumental benefits, missing out on the opportunity to use bodily extensions for play and its associated benefits (including a lower adoption barrier and the potential to reveal a broader understanding of such technologies). To begin understanding the design of playful bodily extensions, we interviewed five designers of bodily extensions that have been showcased in prestigious academic venues or turned into commercial products. Here we present themes and actionable advice from these interviews for the design of playful bodily extensions through a thematic analysis. Our work aims to support the design of future playful bodily extensions while promoting the experiential qualities of bodily extension design, with the ultimate goal of bringing more playful experiences to people’s lives.
TactorBots: A Haptic Design Toolkit for Out-of-lab Exploration of Emotional Robotic Touch

Emerging research has demonstrated the viability of emotional communication through haptic technology inspired by interpersonal touch. However, the meaning-making of artificial touch remains ambiguous and contextual. We see this ambiguity caused by robotic touch’s "otherness" as an opportunity for exploring alternatives. To empower emotional haptic design in longitudinal out-of-lab exploration, we devise TactorBots, a design toolkit consisting of eight wearable hardware modules for rendering robotic touch gestures controlled by a web-based software application. We deployed TactorBots to thirteen designers and researchers to validate its functionality, characterize its design experience, and analyze what, how, and why alternative perceptions, practices, contexts, and metaphors would emerge in the experiment. We provide suggestions for designing future toolkits and field studies based on our experiences. Reflecting on the findings, we derive design implications for further enhancing the ambiguity and shifting the mindsets to expand the design space.
Libraries of Things: Understanding the Challenges of Sharing Tangible Collections and the Opportunities for HCI

“Libraries of Things” are tangible collections of borrowable objects. There are many benefits to Libraries of Things such as making objects and skill-building accessible, reducing waste through the sharing of items, and saving costs associated with purchasing rarely-used items. We introduce the first HCI study of Library of Things by interviewing 23 librarians who run a variety of collections such as handheld tools, gear, and musical instruments – within public institutions and more grass-roots efforts in the private sector. In our findings, we discuss the challenges these collections experience in changing behavioural patterns from buying to borrowing, helping individuals ‘try new things’, iterating to find sharable items, training staff, and manual intervention throughout the borrowing cycle. We present 5 opportunities for HCI research to support interactive skill-sharing, self-borrowing, maintenance recognition and cataloguing ‘things’, organizing non-uniform inventories, and creating public-awareness. Further in-the-wild studies should also consider the tensions between the values of these organizations and low-cost convenient usage.
A Psychometric Scale to Measure Individuals’ Value of Other People’s Privacy (VOPP)

Researchers invested enormous efforts to understand and mitigate the concerns of users as technologies collect their private data. However, users often undermine other people’s privacy when, e.g., posting other people’s photos online, granting mobile applications to access contacts, or using technologies that continuously sense the surrounding. Research to understand technology adoption and behaviors related to collecting and sharing data about non-users has been severely lacking. An essential step to progress in this direction is to identify and quantify factors that affect technology’s use. Toward this goal, we propose and validate a psychometric scale to measure how much an individual values other people’s privacy. We theoretically grounded the appropriateness and relevance of the construct and empirically demonstrated the scale’s internal consistency and validity. This scale will advance the field by enabling researchers to predict behaviors, design adaptive privacy-enhancing technologies, and develop interventions to raise awareness and mitigate privacy risks.
Breathing based immersive interactions for enhanced agency and body awareness: a claustrophobia motivated study

This work explores utilizing representations of one’s physiological breath (embreathment) in immersive experiences, for enhancing presence and body awareness. Particularly, embreathment is proposed for reducing claustrophobia and associated negative cognitions such as feelings of restriction, loss of agency, and sense of suffocation, by enhancing agency and interoception in circumstances where one’s ability to act is restricted. The informed design process of an experience designed for this purpose is presented, alongside an experiment employing the experience, evaluating embodiment, presence, and interoception. The results indicate that embreathment leads to significantly greater levels of embodiment and presence than either an entrainment or control condition. In addition, a modest trend was observed in a heartbeat detection task implying better interoception in the intervention conditions than the control. These findings support the initial assumptions regarding presence and body awareness, paving the way for further evaluation with individuals and situations related to the claustrophobia use case.