Miracle-dz/UniFAR-FTUs huggingface dataset:
The Development and Validation of the Difficulties in Emotion Regulation Scale-8: Providing Respondents with a Uniform Context That Elicits Thinking About Situations Requiring Emotion Regulation

Abstract Emotion regulation difficulties are associated with a range of psychological disorders. A widely used measure of emotion regulation is the Difficulties in Emotion Regulation Scale (DERS-36). There are also three shortened DERS versions. Consistent with current efforts to build very brief versions of measures, the aim of this research is to develop a briefer DERS and evaluate its construct validity. Study 1 uses IRT methods coupled with content considerations to develop a briefer unidimensional DERS. Previous attempts to shorten the DERS have not considered how frame of reference may influence responses to items. The new DERS-8 includes only items prefaced with the phrase “When I’m upset,” to provide respondents with a uniform context that elicits thinking about situations requiring regulation of negative emotion; answers to items are more likely to represent affect, thought, and actions in response to such situations. Study 2 showed that the DERS-8 performed well in an IRT analysis among adolescents with psychiatric disorders and showed similar group differences, sensitivity to change, and correlations with other variables compared to existing DERS versions, in both healthy adult and clinical adolescent samples. The DERS-8 offers a very brief unidimensional measure of difficulties in emotion regulation for adolescents and adults.
Modeling the Impact of Rain on Population Exposed to Air Pollution

Abstract Air pollution is caused by contamination of air due to various natural and anthropogenic activities. The growing air pollution has diverse adverse effects on human health and other living species. However, a significant reduction in the concentration of air pollutants has been observed during the rainy season. Recently, a number of studies have been performed to understand the mechanism of removal of air pollutants due to the rain. These studies have found that rain is helpful in removing many air pollutants from the environment. In this paper, we proposed a mathematical model to investigate the role of rain in the removal of air pollutants and its subsequent impacts on the human population.
TipTrap: A Co-located Direct Manipulation Technique for Acoustically Levitated Content.

Acoustic levitation has emerged as a promising approach for mid-air displays, by using multiple levitated particles as 3D voxels, cloth and thread props, or high-speed tracer particles, under the promise of creating 3D displays that users can see, hear and feel with their bare eyes, ears and hands. However, interaction with this mid-air content always occurred at a distance, since external objects in the display volume (e.g. user’s hands) can disturb the acoustic fields and make the particles fall. This paper proposes TipTrap, a co-located direct manipulation technique for acoustically levitated particles. TipTrap leverages the reflection of ultrasound on the users’ skin and employs a closed-loop system to create functional acoustic traps 2.1 mm below the fingertips, and addresses its 3 basic stages: selection, manipulation and deselection. We use Finite-Differences Time Domain (FDTD) simulations to explain the principles enabling TipTrap, and explore how finger reflections and user strategies influence the quality of the traps (e.g. approaching direction, orientation and tracking errors), and use these results to design our technique. We then implement the technique, characterizing its performance with a robotic hand setup and finish with an exploration of the ability of TipTrap to manipulate different types of levitated content.
SilentWhisper: faint whisper speech using wearable microphone

Voice interaction is a fundamental human capacity, and we can use voice user interfaces just speaking. However, in public spaces, we are hesitant to use them because of consideration for their surroundings and low privacy. Silent speech, a method that recognizes the movement of speech in silence, has been proposed as a solution to this problem, and it allows us to maintain our privacy when speaking. However, existing silent speech interfaces are burdensome because the sensor must be kept in contact with the face and mouth, and commands must be prepared for each user. In this study, we propose a method to input whispered speech at a quiet volume that cannot be heard by others using a pin microphone. Experimental results show that a recognition rate was 13.9% WER and 6.4% CER for 210 phrases. We showed that privacy-preserving vocal input is possible by whispering voices which are not comprehensible to others.
On the physical nature of globular cluster candidates in the Milky Way bulge

We present results from 2MASS JKs photometry on the physical reality of recently reported globular cluster (GC) candidates in the Milky Way (MW) bulge. We relied our analysis on photometric membership probabilities that allowed us to distinguish real stellar aggregates from the composite field star population. When building colour-magnitude diagrams and stellar density maps for stars at different membership probability levels, the genuine GC candidate populations are clearly highlighted. We then used the tip of the red giant branch (RGB) as distance estimator, resulting heliocentric distances that place many of the objects in regions near of the MW bulge where no GC had been previously recognised. Some few GC candidates resulted to be MW halo/disc objects.Metallicities estimated from the standard RGB method are in agreement with the values expected according to the position of the GC candidates in the Galaxy. We finally derived from the first time their structural parameters. We found that the studied objects have core, half-light and tidal radii in the ranges spanned by the population of known MW GCs. Their internal dynamical evolutionary stages will be described properly when their masses are estimated.
VRhook: A Data Collection Tool for VR Motion Sickness Research

Despite the increasing popularity of VR games, one factor hindering the industry’s rapid growth is motion sickness experienced by the users. Symptoms such as fatigue and nausea severely hamper the user experience. Machine Learning methods could be used to automatically detect motion sickness in VR experiences, but generating the extensive labeled dataset needed is a challenging task. It needs either very time consuming manual labeling by human experts or modification of proprietary VR application source codes for label capturing. To overcome these challenges, we developed a novel data collection tool, VRhook, which can collect data from any VR game without needing access to its source code. This is achieved by dynamic hooking, where we can inject custom code into a game’s run-time memory to record each video frame and its associated transformation matrices. Using this, we can automatically extract various useful labels such as rotation, speed, and acceleration. In addition, VRhook can blend a customized screen overlay on top of game contents to collect self-reported comfort scores. In this paper, we describe the technical development of VRhook, demonstrate its utility with an example, and describe directions for future research.
Muscle Synergies Learning with Electrical Muscle Stimulation for Playing the Piano

When playing scales on the piano, playing all notes evenly is a basic technique to improve the quality of music. However, it is difficult for beginners to do this because they need to achieve appropriate muscle synergies of the forearm and shoulder muscles, i.e., pressing keys as well as sliding their hands sideways. In this paper, we propose a system using electrical muscle stimulation (EMS) to teach beginners how to improve their muscle synergies while playing scales. We focus on “thumb-under” method and assist with it by applying EMS to the deltoid muscle. We conducted a user study to investigate whether our EMS-based system can help beginners learn new muscle synergies in playing ascending scales. We divided the participants into two groups: an experimental group that practiced with EMS and a control group that practiced without EMS. The results showed that practicing with EMS was more effective in improving the evenness of scales than without EMS and that the muscle synergies changed after practicing.
A Feature-enhanced Ship License Plate Recognition Algorithm Based on Matched Filter

Water transportation is an indispensable part of country's transportation, and water transportation is mainly based on shipping. The accurate identification of ship license plate is of great significance for ship entry and exit supervision and ship collision avoidance. Based on the end-to-end variable-length text recognition algorithm of CRNN, this paper proposes a new solution for ship license plate recognition. Aiming at the problems of ambiguity and low resolution of the ship's license plate, an enhancement branch is introduced, and an enhance block is designed to enhance the feature of the character area. In addition, in view of the problem that the character tubular area extends to different directions, the matched filter in the enhance block is rotated to form a filter bank of 12 directions, so as to fit the character area in different directions. Experiments are carried out on the real dataset and the generated simulation dataset, and the experimental results show that the scheme can effectively identify ship license plate.
Document Segmentation for WebAR application

In recent years, we have witnessed the appearance of consumer applications of Augmented Reality (AR) available natively on smartphones. More recently, these applications are also implemented in web browsers. Among various AR applications, a simple one consisting in detecting a target object filmed by the phone and trigger an event following the detection. The target object can be of any kind, including 3D objects or simpler documents and printed pictures. The underlying process consists in comparing the image captured by the camera with large scale image remote database. The goal is then to display new content over the target object, by keeping the 3D spatial registration. When the target object is a document (or printed picture), the image captured by the camera contains, in many cases, a lot of useless information (such as the background). It is therefore more optimal to segment the captured image and send only to the server the representation of the target object. In this paper, we propose a deep-learning (DL) based method for fast detection and segmentation of printed documents within natural images. The goal is to provide a light and fast DL model to be used directly in the web browser, on mobile devices. We designed a compact and fast DL architecture, allowing to keep the same accuracy as the reference architecture, but dividing the inference time by 3 and the number of parameters by 10.
ReCapture: AR-Guided Time-lapse Photography

We present ReCapture, a system that leverages AR-based guidance to help users capture time-lapse data with hand-held mobile devices. ReCapture works by repeatedly guiding users back to the precise location of previously captured images so they can record time-lapse videos one frame at a time without leaving their camera in the scene. Building on previous work in computational re-photography, we combine three different guidance modes to enable parallel hand-held time-lapse capture in general settings. We demonstrate the versatility of our system on a wide variety of subjects and scenes captured over a year of development and regular use, and explore different visualizations of unstructured hand-held time-lapse data.
LETTER TO THE EDITOR: What is the length of a knot in a polymer?

We give statistical definitions of the length, l, of a loose prime knot tied into a long, fluctuating ring macromolecule. Monte Carlo results for the equilibrium, good solvent regime show that l ~ Nt, where N is the ring length and t 0.75 is independent of the knot type. In the collapsed regime below the theta temperature, length determinations based on the entropic competition of different knots within the same ring show knot delocalization (t 1).
Sharing Heartbeat: Toward Conducting Heartrate and Speech Rhythm through Tactile Presentation of Pseudo-heartbeats

Currently, the ongoing COVID-19 pandemic makes physical contact, such as handshakes, difficult. However, physical contact is effective in strengthening the bonds between people. In this study, we aim to compensate for the physical contact lost during the COVID-19 pandemic by presenting a pseudo-heartbeat through a speaker to reproduce entrainment and the synchronized state of heartbeats induced by physiological synchronization. We evaluated the effects of the device in terms of speech rhythm and heart rate. The experimental results showed that a presentation of 80 BPM significantly reduced the difference in heart rate between the two participants, bringing them closer to a synchronized heart rate state. The heart rates of participants were significantly lower when 45 BPM and 80 BPM were presented than when no stimulus was given. Furthermore, when 45 BPM was presented, the silent periods between conversations were significantly more extended than when no stimulus was given. This result indicates that this device can intentionally create the entrainment phenomenon and a synchronized heart rate state, thereby producing the same effect of physical contact communication without contact.
A Fast SAR Raw Data Simulator for Extended Scenes Using Block Clipping Method

With the improvement of SAR observation swath and image resolution, the computational complexity of SAR raw data simulation increases greatly, which challenges the engineering application of SAR simulation technology. To improve the simulation efficiency of SAR raw data, a block clipping method is proposed in this paper, which can remove the targets not illuminated by the radar beam in the scene with little computation. The range frequency-domain pulse coherence (RFPC) algorithm is widely used for SAR raw data simulation in the engineering field. The Block clipping algorithm can be combined with the RFPC algorithm to improve the simulation efficiency of the extended scene. The experimental results show that when the number of targets in the simulation scene is 6000×6000, the simulation efficiency of the RFPC algorithm is improved by 2-3 times after using block clipping technology.
Shadowed Speech: an Audio Feedback System which Slows Down Speech Rate

In oral communication, it is important to speak at a speed appropriate for the situation. However, we need a lot of training in order to control our speech rate as intended. This paper proposes a speech rate control system which enables the user to speak at a pace closer to the target rate using Delayed Auditory Feedback (DAF). We implement a prototype and confirm that the proposed system can slow down the speech rate when the user speaks too fast without giving any instructions to the speaker on how to respond to the audio feedback.
iThem: Programming Internet of Things Beyond Trigger-Action Pattern

With emerging technologies bringing Internet of Things (IoT) devices into domestic environments, trigger-action programming such as IFTTT with its simple if-this-then-that pattern provides an effective way for end-users to connect fragmented intelligent services and program their own smart home/work space automation. While the simplicity of trigger-action programming can be effective for non-programmers with its straightforward concepts and graphical user interface, it does not allow the algorithmic expressivity that a programming language has. For instance, the simple if-this-then-that structure cannot cover complex algorithms that arise from real world scenarios involving multiple conditions or keeping track of a sequence of conditions (e.g., incrementing counters, triggering one action if two conditions are both true). In this exploratory work, we take an alternative approach by creating a programmable channel between application programming interfaces (APIs), which allows programmers to preserve states and to use them to write complex algorithms. We propose iThem, which stands for intelligence of them—internet of things, that allow programmers to author any complex algorithms that can connect different IoT services and fully unleash the freedom of a general programming language. In this poster, we share the design, development, and ongoing validation progress of iThem, which piggybacks on existing programmable IoT system IFTTT, and which allows for a programmable channel that connects triggers and actions in IFTTT with versatility.
On the nature of the Newton's gravitational constant and the possible quantum-field theory of gravitation

On the basis of the coincidence of the physical dimensions (in natural units $\hbar = c = 1$) of the Newton's gravitational constant $G_{N} $ and the phenomenological Fermi constant $G_{F} $ for weak interaction, it is suggested that there is a certain similarity between weak forces, which are caused by the exchange of massive intermediate vector bosons with spin $S=1$, and "superweak" gravitational forces that can be caused by the exchange of "supermassive" hypothetical tensor bosons with spin $S=2$. By analogy with how the masses of intermediate bosons in the theory of electroweak interaction arise as a result of spontaneous breaking of the gauge symmetry of the electromagnetic field due to its interaction with the nonlinear scalar Higgs field, the masses of hypothetical tensor bosons carrying gravitational interaction can also arise as a result of spontaneous breaking of gauge symmetry of the massless gravitons when they interact with a fundamental nonlinear scalar field in a flat 4-dimensional space-time.
Flexel: A Modular Floor Interface for Room-Scale Tactile Sensing

Human environments are physically supported by floors, which prevent people and furniture from gravitational pull. Since our body motions continuously generate vibrations and loads that propagate into the ground, measurement of these expressive signals leads to unobtrusive activity sensing. In this study, we present Flexel, a modular floor interface for room-scale tactile sensing. By paving a room with floor interfaces, our system can immediately begin to infer touch locations, track user locations, recognize foot gestures, and detect object locations. Through a series of exploratory studies, we determined the preferable hardware design that adheres to construction conventions, as well as the optimal sensor density that mediates the trade-off between cost and performance. We summarize our findings into design guidelines that are generalizable to other floor interfaces. Finally, we provide example applications for room-scale tactile sensing enabled by our Flexel system.
iWood: Makeable Vibration Sensor for Interactive Plywood

iWood is interactive plywood that can sense vibration based on triboelectric effect. As a material, iWood survives common woodworking operations, such as sawing, screwing, and nailing and can be used to create furniture and artifacts. Things created using iWood inherit its sensing capability and can detect a variety of user input and activities based on their unique vibration patterns. Through a series of experiments and machine simulations, we carefully chose the size of the sensor electrodes, the type of triboelectric materials, and the bonding method of the sensor layers to optimize the sensitivity and fabrication complexity. The sensing performance of iWood was evaluated with 4 gestures and 12 daily activities carried out on a table, nightstand, and cutting board, all created using iWood. Our result suggested over 90% accuracies for activity and gesture recognition.
Adaptations to Trust Incidents with Artificial Intelligence

Artificial Intelligence (AI) is becoming ubiquitous in national security work (intelligence, defense, etc.); however, introducing AI into work systems is fraught with challenges. Trust is gained and lost through experiences, and there are many factors that affect trust in AI. Similarly, users adapt their workflows based on trust in these systems. We used a naturalistic approach to understand how intelligence professionals adapted their work practices after gaining or losing trust in AI. We found a variety of adaptations, which were characterized as either being task-based or frequency-based; where users added or removed tasks from their workflow or where they changed the frequency in which they used the AI in their workflow, respectively. We provide specific examples and quotes from participants along with findings, and discuss potential methodological implications for studying and designing AI-driven work systems.
How Well Do Privacy-Protective Behaviours Age? The Prevalence of Privacy Heuristics Among Older Adults

Digital technology adoption and engagement is increasing amongst older adults, prompting concerns regarding their privacy-related behaviour while engaging with these technologies. The use of cognitive biases and heuristics may help explain why older adults, and some younger people as well, make decisions that compromise their privacy in digital contexts. A literature review was carried out to assess the use of cognitive biases and heuristics by older adults when deciding whether to adopt, and while using, digital technologies. Tools are needed that guide users away from mental shortcuts such as hyperbolic discounting, anchoring, and shortcut decisions based on trust and that promote privacy protection. In addition to reviewing current literature on the use of privacy-related biases and heuristics amongst older adults, we also present possible future research directions on this topic.
Me and My VE 2022: Human Factors Applications Using Virtual Reality, Mixed Reality, and Virtual Environments

This abstract is a companion piece to the ninth iteration of the “Me and My VE” interactive session. The purpose of this alternative format session is to allow human factors researchers to demonstrate how they use virtual reality, mixed reality, and virtual environments to support end-user research. The session begins with each presenter providing a brief introduction of their virtual reality, mixed reality, or virtual environment application. After this introduction, attendees engage with the presenters and their virtual environments in an interactive demonstration period. This year’s demonstrations include applications ranging from designing virtual environments for accessibility to using virtual and extended reality to support medical and aviation training, content validation, and human-computer interaction studies. The goal of the session is to allow attendees to experience how human factors professionals use virtual environments to support human factors-oriented research and to learn about the exciting work being conducted in this field.