Miracle-dz/UniFAR-FTUs huggingface dataset:
”I don’t want to feel like I’m working in a 1960s factory”: The Practitioner Perspective on Creativity Support Tool Adoption

With the rapid development of creativity support tools, creative practitioners (e.g., designers, artists, architects) have to constantly explore and adopt new tools into their practice. While HCI research has focused on developing novel creativity support tools, little is known about creative practitioner’s values when exploring and adopting these tools. We collect and analyze 23 videos, 13 interviews, and 105 survey responses of creative practitioners reflecting on their values to derive a value framework. We find that practitioners value the tools’ functionality, integration into their current workflow, performance, user interface and experience, learning support, costs and emotional connection, in that order. They largely discover tools through personal recommendations. To help unify and encourage reflection from the wider community of CST stakeholders (e.g., systems creators, researchers, marketers, educators), we situate the framework within existing research on systems, creativity support tools and technology adoption.
Complex Data Visualisation Made Easy with R and ggplot2

Being able to visualise data in consistent, high-quality ways is a useful skill for HCI researchers and practitioners. In this course, attendees will learn how to produce high quality plots and visualisations using the ggplot2 library for the R statistical computing language. There are no prerequisites and attendees will leave with scripts to get them started as well as foundational knowledge of free open-source tools that they can build on to produce complex, even interactive, visualisations. Course information materials can be found at https://www.sjjg. uk/chi22-course.
RMS: Removing Barriers to Analyze the Availability and Surge Pricing of Ridesharing Services

Ridesharing services do not make data of their availability (supply, utilization, idle time, and idle distance) and surge pricing publicly available. It limits the opportunities to study the spatiotemporal trends of the availability and surge pricing of these services. Only a few research studies conducted in North America analyzed these features for only Uber and Lyft. Despite the interesting observations, the results of prior works are not generalizable or reproducible because: i) the datasets collected in previous publications are spatiotemporally sensitive, i.e., previous works do not represent the current availability and surge pricing of ridesharing services in different parts of the world; and ii) the analyses presented in previous works are limited in scope (in terms of countries and ridesharing services they studied). Hence, prior works are not generally applicable to ridesharing services operating in different countries. This paper addresses the issue of ridesharing-data unavailability by presenting Ridesharing Measurement Suite (RMS). RMS removes the barrier of entry for analyzing the availability and surge pricing of ridesharing services for ridesharing users, researchers from various scientific domains, and regulators. RMS continuously collects the data of the availability and surge pricing of ridesharing services. It exposes real-time data of these services through i) graphical user interfaces and ii) public APIs to assist various stakeholders of these services and simplify the data collection and analysis process for future ridesharing research studies. To signify the utility of RMS, we deployed RMS to collect and analyze the availability and surge pricing data of 10 ridesharing services operating in nine countries for eight weeks in pre and during pandemic periods. Using the data collected and analyzed by RMS, we identify that previous articles miscalculated the utilization of ridesharing services as they did not count in the vehicles driving in multiple categories of the same service. We observe that during COVID-19, the supply of ridesharing services decreased by 54%, utilization of available vehicles increased by 6%, and a 5 × increase in the surge frequency of services. We also find that surge occurs in a small geographical region, and its intensity reduces by 50% in about 0.5 miles away from the location of a surge. We present several other interesting observations on ridesharing services’ availability and surge pricing.
EmoGlass: an End-to-End AI-Enabled Wearable Platform for Enhancing Self-Awareness of Emotional Health

Often, emotional disorders are overlooked due to their lack of awareness, resulting in potential mental issues. Recent advances in sensing and inference technology provide a viable path to wearable facial-expression-based emotion recognition. However, most prior work has explored only laboratory settings and few platforms are geared towards end-users in everyday lives or provide personalized emotional suggestions to promote self-regulation. We present EmoGlass, an end-to-end wearable platform that consists of emotion detection glasses and an accompanying mobile application. Our single-camera-mounted glasses can detect seven facial expressions based on partial face images. We conducted a three-day out-of-lab study (N=15) to evaluate the performance of EmoGlass. We iterated on the design of the EmoGlass application for effective self-monitoring and awareness of users’ daily emotional states. We report quantitative and qualitative findings, based on which we discuss design recommendations for future work on sensing and enhancing awareness of emotional health.
Simulating Human Imprecision in Temporal Statements of Intelligent Virtual Agents

Research on intelligent virtual agents (IVAs) often concerns the implementation of human-like behavior by integrating artificial intelligence algorithms. Thus far, few studies focused on mimicry of cognitive imperfections inherent to humans in IVAs. Neglecting to implement such imperfect behavior in IVAs might result in less believable or engaging human-agent interactions. In this paper, we simulate human imprecision in conversational IVAs’ temporal statements. We conducted a survey to identify temporal statement patterns, transferred them to a conversational IVA, and conducted a user study evaluating the effects of time precision on perceived anthropomorphism and usefulness. Statistical analyses reveal significant interaction between time precision and agents’ use of memory aids, indicating that (i) imprecise agents are perceived as more human-like than precise agents when responding immediately, and (ii) unnaturally high levels of temporal precision can be compensated for by memory aid use. Further findings underscore the value of continued inquiry into cultural variations.
Designing for Knowledge Construction to Facilitate the Uptake of Open Science: Laying out the Design Space

The uptake of open science resources needs knowledge construction on the side of the readers/receivers of scientific content. The design of technologies surrounding open science resources can facilitate such knowledge construction, but this has not been investigated yet. To do so, we first conducted a scoping review of literature, from which we draw design heuristics for knowledge construction in digital environments. Subsequently, we grouped the underlying technological functionalities into three design categories: i) structuring and supporting collaboration, ii) supporting the learning process, and iii) structuring, visualising and navigating (learning) content. Finally, we mapped the design categories and associated design heuristics to core components of popular open science platforms. This mapping constitutes a design space (design implications), which informs researchers and designers in the HCI community about suitable functionalities for supporting knowledge construction in existing or new digital open science platforms.
Impact of Out-of-Vocabulary Words on the Twitter Experience of Blind Users

Most people who are blind interact with social media content with the assistance of a screen reader, a software that converts text to speech. However, the language used in social media is well-known to contain several informal out-of-vocabulary words (e.g., abbreviations, wordplays, slang), many of which do not have corresponding standard pronunciations. The narration behavior of screen readers for such out-of-vocabulary words and the corresponding impact on the social media experience of blind screen reader users are still uncharted research territories. Therefore we seek to plug this knowledge gap by examining how current popular screen readers narrate different types of out-of-vocabulary words found on Twitter, and also, how the presence of such words in tweets influences the interaction behavior and comprehension of blind screen reader users. Our investigation showed that screen readers rarely autocorrect out-of-vocabulary words, and moreover they do not always exhibit ideal behavior for certain prolific types of out-of-vocabulary words such as acronyms and initialisms. We also observed that blind users often rely on tedious and taxing workarounds to comprehend actual meanings of out-of-vocabulary words. Informed by the observations, we finally discuss methods that can potentially reduce this interaction burden for blind users on social media.
“I Didn’t Know I Looked Angry”: Characterizing Observed Emotion and Reported Affect at Work

With the growing prevalence of affective computing applications, Automatic Emotion Recognition (AER) technologies have garnered attention in both research and industry settings. Initially limited to speech-based applications, AER technologies now include analysis of facial landmarks to provide predicted probabilities of a common subset of emotions (e.g., anger, happiness) for faces observed in an image or video frame. In this paper, we study the relationship between AER outputs and self-reports of affect employed by prior work, in the context of information work at a technology company. We compare the continuous observed emotion output from an AER tool to discrete reported affect obtained via a one-day combined tool-use and diary study (N = 15). We provide empirical evidence showing that these signals do not completely align, and find that using additional workplace context only improves alignment up to 58.6%. These results suggest affect must be studied in the context it is being expressed, and observed emotion signal should not replace internal reported affect for affective computing applications.
Exploring Esports Spectator Motivations

Gameplay spectatorship has developed significantly over the last decade, necessitating the need to design more engaging spectator experiences. In order to do this effectively, however, we must first better understand spectator behavior and motivations. In this paper, we build on the results of a previous work examining interaction preferences of remote livestream spectators depending on their user type, and report a new qualitative study exploring the underlying motivations that shape the experience of those engaged in interactive spectating. Our results highlight five main themes (entertainment, team support, learning, caster, social) that motivate spectators to engage with interactive esports experiences. This work will motivate ongoing research in this domain by promoting conversations about livestream spectator engagement and motivations, and facilitating engaging spectator experiences.
Understory evapotranspiration rates in a coast redwood forest

In forests where the overstorey canopy has been disturbed by timber harvest or other means, evapotranspiration (ET) by the understorey may be the main flux of water back to the atmosphere. However, little research has been apportioned to directly measuring understorey water use, and the technology to do so is thus limited. Here, we used a portable chamber to quickly and directly measure understorey ET by measuring the water flux from the soil and vegetation enclosed by the chamber. This method was used in a third‐growth coast redwood forest to measure ET rates from individuals of five species commonly found in the understorey: Sequoia sempervirens (coast redwood) sprouts, Notholithocarpus densiflorus (tanoak) sprouts, Vaccinium ovatum (evergreen huckleberry) sprouts, Polystichum munitum (sword fern) and Struthiopteris spicant (deer fern). Measurements were conducted in four small watersheds which were harvested to varying intensities ranging from 0% to 75% targeted reduction in preharvest overstory basal area. Mean understorey ET rate was highest in the watershed with the lowest residual basal area (x̅ = 0.036 ± 0.024 mm/h) and lowest in the unharvested control watershed (x̅ = 0.013 ± 0.0078 mm/h). Multiple regression modelling on resprouting species indicated that the difference in ET rate between watersheds was related to soil and light resources. These results imply that understorey water use can be significant, particularly in harvested watersheds, and should be quantified at the landscape scale.
Dupal Anomaly and Identification using Nd‐Hf Isotopes

The Dupal anomaly has attracted widespread attention since being discovered and is regarded as the most direct manifestation of mantle inhomogeneity at present. From the initially defined anomalies limited to the southern hemisphere to the global scale, the criteria for identifying anomalies defined by Pb isotopes have also been adjusted, providing an important method and reference for the study of the mantle evolution. Pearce and Peate (1995) proposed the method of Nd‐Hf isotope and element ratio to identify the Dupal anomaly. The Nd‐Hf method also offers a possible way to discriminate the mantle region of arc magmatism through the correction of Nd in the subduction process. This paper introduces the concepts and determination methods of the Dupal anomaly, and reports new Hf isotopic data of MORB‐type rocks with Dupal signature in the several Tethys ophiolites. Our results of Nd‐Hf method are in good agreement with those of previous Pb isotope identification. Moreover, origins and their controversy of Dupal anomaly are reviewed, and possible internal connections between Dupal anomalies and the two Large Low Shear Velocity Provinces (LLSVPs) in the lower mantle are discussed in depth. Further studies on origin and evolution of the Dupal anomaly are suggested, especially using integrated approach of Hf‐Nd and Pb isotopes.
Computationally efficient multi-step direct predictive torque control for surface-mounted permanent magnet synchronous motor

The multi-step direct model predictive control (M-DMPC) could reduce the switching frequency and improve the efficiency of the motor drive system while ensuring good steady and dynamic performance. However, the conventional M-DMPC, which uses the exhaustive optimisation method is with exponential time complexity, so it is difficult to realise in a short sample period. This study proposes a multi-step direct predictive torque control (M-DPTC) algorithm for two-level voltage source inverter fed surface-mounted permanent magnet synchronous motor (SPMSM) drive system. In the proposed algorithm, first, in order to reduce computation time in multi-step predictive process, a simplified multi-step predictive model is established. Compared with the complex operations, like square root and trigonometric function used in the conventional predictive model, only look-up table and addition operation are utilised in the proposed model for multistep prediction. Second, compared with the exhaustive searching method, the proposed optimisation method avoids the exploration of all possible switching sequences and has logarithmic time complexity. Combining the above two measures, the proposed M-DPTC can be achieved in a relatively shorter sample period. Simulation and experimental results for a 6-kW SPMSM are presented to validate the proposed algorithm.
Auto-Ignition Characteristics Study of Gas-to-Liquid Fuel at High Pressures and Low Temperatures

Onset of auto-ignition of premixed gas-to-liquid (GTL)/air mixture has been determined at high pressures and low temperatures over a wide range of equivalence ratios. The GTL fuel used in this study was provided by Air Force Research Laboratory (AFRL), designated by Syntroleum S-8, which is derived from natural gas via the Fischer–Tropsch (F–T) process. A blend of 32% iso-octane, 25% n-decane, and 43% n-dodecane is employed as the surrogates of GTL fuel for chemical kinetics study. A spherical chamber, which can withstand high pressures up to 400 atm and can be heated up to 500 K, was used to collect pressure rise data, due to combustion, to determine the onset of autoignition. A gas chromatograph (GC) system working in conjunction with specialized heated lines was used to verify the filling process. A liquid supply manifold was used to allow the fuel to enter and evaporate in a temperature-controlled portion of the manifold using two cartridge heaters. An accurate high-temperature pressure transducer was used to measure the partial pressure of the vaporized fuel. Pressure rise due to combustion process was collected using a high-speed pressure sensor and was stored in a local desktop via a data acquisition system. Measurements for the onset of auto-ignition were done in the spherical chamber for different equivalence ratios of 0.8–1.2 and different initial pressures of 8.6, 10, and 12 atm at initial temperature of 450 K. Critical pressures and temperatures of GTL/air mixture at which auto-ignition takes place have been identified by detecting aggressive oscillation of pressure data during the spontaneous combustion process throughout the unburned gas mixture. To interpret the auto-ignition conditions effectively, several available chemical kinetics mechanisms were used in modeling autoignition of GTL/air mixtures. For low-temperature mixtures, it was shown that autoignition of GTL fuel is a strong function of unburned gas temperature, and propensity of auto-ignition was increased as initial temperature and pressure increased. [DOI: 10.1115/1.4033983]
High performance silicon photonic filters for dense wavelength-division multiplexing applications

This dissertation presents theoretical and experimental results for silicon optical ring resonator filters that meet many of the typical commercial specifications for dense wavelength-division multiplexing (DWDM) filters. First, we theoretically demonstrate a silicon quadruple Vernier racetrack resonator that meets 4-port filter commercial specifications for a clear window of 0.08 nm and a channel spacing of 0.8 nm while being tolerant to typical fabrication variations. Next, we experimentally demonstrate a silicon quadruple Vernier racetrack resonator that meets many 3-port filter commercial specifications for a clear window of 0.048 nm and a channel spacing of 0.8 nm. Then, enhanced resonant tuning range using the Vernier effect is theoretically and experimentally demonstrated using a thermally tunable silicon quadruple Vernier racetrack resonator. Also, we sent 12.5 Gbps data through a thermally tunable silicon quadruple Vernier racetrack resonator and show open eye diagrams in both the drop port and through port of the filter, even within one of the minor through port notches. We then present theoretical and experimental results on a high performance silicon double microring resonator filter using Mach-Zhender interferometer-based coupling that meets numerous 3-port filter commercial specifications for a clear window of 8 GHz and a channel spacing of 200 GHz as well as having an FSR larger than the span of the C-band and low through port passband dispersion. Next, we present a FSR-eliminated silicon Vernier racetrack resonator filter. We demonstrate the performance of this filter both theoretically and experimentally. The FSR of this filter is eliminated by using contra-directional grating couplers (contra-DCs) to suppress all but one of the notches and peaks of the filter’s spectra. Lastly, a process calibration procedure is demonstrated that accurately determines the coupling coefficients of fabricated
Mediating Human-Robot Collaboration through Mixed Reality Cues

This work presents a communication paradigm, using a context-aware mixed reality approach, for instructing human workers when collaborating with robots. The main objective of this approach is to utilize the physical work environment as a canvas to communicate task-related instructions and robot intentions in the form of visual cues. A vision-based object tracking algorithm is used to precisely determine the pose and state of physical objects in and around the workspace. A projection mapping technique is used to overlay visual cues on tracked objects and the workspace. Simultaneous tracking and projection onto objects enables the system to provide just-in-time instructions for carrying out a procedural task. Additionally, the system can also inform and warn humans about the intentions of the robot and safety of the workspace. It was hypothesized that using this system for executing a human-robot collaborative task will improve the overall performance of the team and provide a positive experience to the human partner. To test this hypothesis, an experiment involving human subjects was conducted and the performance (both objective and subjective) of the presented system was compared with a conventional method based on printed instructions. It was found that projecting visual cues enabled human subjects to collaborate more effectively with the robot and resulted in higher efficiency in completing the task.
Flexible E-learning: Online Courses Tailored to Student´s Needs

The paper introduces a way of implementing the learning style theory in the field of e-learning. Since 2010 the three-year project “A flexible model of the ICT supported educational process reflecting individual learning styles“ has been running at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic. The main objective is to verify whether accommodating the individual learning style within the process of instruction supported by ICT results in increasing the level of student´s knowledge. The core part of the project is the analysis of various types of study materials which students of different learning styles consider to be suitable for their process of learning.The results are implemented in the learning strategy of the online course within which the flexible model is verified. For this purpose a software application was designedwhich generates the appropriate type of study materials and related learning activities. Thus the process of instruction will be tailored to the discovered student´s needs.
Basal Principles in Reading Readiness Testing

In a popular sense reading readiness implies that a child will be successful and interested in learning to read if reading is introduced when he is "ripe" for it and that he is likely to fail and to be annoyed when instruction is begun before this time. Such a general conception is justified by the findings of experimental studies on learning certain other activities and by the experiences of classroom teachers with immature pupils in reading. The major difficulties have been to determine the characteristics which underlie readiness and to appraise them.