Reviewerly/exHarmony huggingface dataset:
Exploring AltNarrative in HCI Imagery and Comics

It is often assumed that imagery provides an easy or universal mode of communication, but when we imagine our worlds through sketches, visualizations, and comics are we leaving anyone behind? The visual world is rich, it transcends boundaries and connects us... but not all of us. To be able to create an image or visualize something is a skill, but to be able to view and interpret that image is a privilege: how can we bridge the gap between visual and textual interpretation? We propose that alt-narrative could bridge the gap between visual communication and imagery to connect everyone in storytelling, visualization, and thought. This AltCHI paper puts forward exploration of the AltNarrative method in HCI imagery and comics. To engage with this research, the reader should either activate their computer or smart device screen reader or open in Adobe Acrobat in Mac or Windows then activate Read Out loud.
Critical-Playful Speculations with Cameras in the Home

Smart home cameras present new challenges for understanding behaviors and relationships surrounding always-on, domestic recording systems. We designed a series of discursive activities involving 16 individuals from ten households for six weeks in their everyday settings. These activities functioned as speculative probes—prompting participants to reflect on themes of privacy and power through filming with cameras in their households. Our research design foregrounded critical-playful enactments that allowed participants to speculate potentials for relationships with cameras in the home beyond everyday use. We present four key dynamics with participants and home cameras by examining their relationships to: the camera's eye, filming, their data, and camera's societal contexts. We contribute discussions about the mundane, information privacy, and post-hoc reflection with one's camera footage. Overall, our findings reveal the camera as a strange, yet banal entity in the home—interrogating how participants compose and handle their own and others’ video data.
Embodied Notes: A Cognitive Support Tool For Remote Scientific Collaboration in VR

Scientists collaborate remotely across institutions, countries and continents. However, collaborating remotely is challenging. Video-conferencing tools used for meetings limit the cognitive practices that collaborators can partake in. In virtual reality (VR) users can gain back some of the spatial and social affordances present in collocated collaboration, as well as benefit from interactions that would not be possible in the real world. We introduce Embodied Notes: a cognitive support tool designed to be used in a collaborative virtual environment.
To What Extent Can Code Quality be Improved by Eliminating Test Smells?

Software testing is a key activity to guarantee software reliability and maintainability. However, developers tend to ignore the maintenance of test code when performing a tradeoff between code quality and release deadlines. Moreover, the lack of research to quantify the relationship between test code and production code quality. As a result, test quality degrades due to the lack of appropriate refactoring plans. This paper fills the gap by evaluating to what extent can code quality be improved by eliminating test smells. First, we detect the presence of test smells in 119 historical releases of 10 open-source projects. Afterward, we evaluate code quality in 2 aspects, i.e., defect- and change-proneness. Finally, we exploit the odds ratio and Mann-Whitney test to quantify the extent of variation for the code quality. Results show that the OR values of the test code and production code are both much greater than 1, which proves that the test smell is indeed a risk factor to increase the defect-proneness of code. Moreover, the change-proneness of the test code and associated production code reduces significantly after their elimination. Experiment also reveals Assertion Roulette is the riskiest smell to degrade production code quality.
Supercharging Trial-and-Error for Learning Complex Software Applications

Despite an abundance of carefully-crafted tutorials, trial-and-error remains many people's preferred way to learn complex software. Yet, approaches to facilitate trial-and-error (such as tooltips) have evolved very little since the 1980s. While existing mechanisms work well for simple software, they scale poorly to large feature-rich applications. In this paper, we explore new techniques to support trial-and-error in complex applications. We identify key benefits and challenges of trial-and-error, and introduce a framework with a conceptual model and design space. Using this framework, we developed three techniques: ToolTrack to keep track of trial-and-error progress; ToolTrip to go beyond trial-and-error of single commands by highlighting related commands that are frequently used together; and ToolTaste to quickly and safely try commands. We demonstrate how these techniques facilitate trial-and-error, as illustrated through a proof-of-concept implementation in the CAD software Fusion 360. We conclude by discussing possible scenarios and outline directions for future research on trial-and-error.
Research on reading recognition method of pointer meter based on magnifying the virtual circle

In order to reduce manual patrol and improve the efficiency of meter reading in substations, many researchers began to recognize the reading of pointer meter by image recognition technology in recent years. At present, the recognition methods of most pointer meters find the contour of pointer through image processing, then determine the reading of pointer according to its outline. However, in the process of pointer recognition, there is a certain error for the position of pointer recognized by image processing, which has a certain influence on the accuracy of the reading. Therefore, this paper proposes a pointer meter reading recognition method based on magnifying the virtual circle, which can quickly and accurately identify the pointer meter reading and improve the accuracy and efficiency of meter recognition. Moreover, the proposed method has important significance for the automatic identification of pointer meter reading in smart substations.
TeleOperationStation: XR-Exploration of User Interfaces for Remote Automated Vehicle Operation

With increased automation levels of vehicle technology, human involvement is expected to be transformed from a driver towards an operator role. This transition will entail remote monitoring and possibilities for intervention of driverless vehicle fleets. Thus far, there are insufficient tools available for user interface development and experimentation, which renders it difficult to quickly devise, prototype, and test solutions to support operators in their specific work contexts. We present the TeleOperationStation, an extended-reality experience prototyping environment, which coherently simulates automated fleet operation workflows, covering non-driving tasks, monitoring, takeover requests, and full remote vehicle operation. During this interactive demonstration, on-site and online conference participants will be enabled to experience and co-create user interfaces for remote automated vehicle operation, using AR from a first-person viewpoint, and controlling a physical miniature vehicle.
Fontana: Triggering Physical Activity and Social Connectedness through an Interactive Water Installation

Promoting healthy and active lifestyles is an important objective for many governing agencies. The design of active urban environments can be an effective tool to encourage more active behaviors and water features can attract people, improving their experience of the urban space. To explore the potential of these concepts, we designed Fontana; an interactive public installation that aims to stimulate physical activity and social connectedness in the urban outdoor space, using the multidimensional attractiveness of water. We focus on the use of embedded interactive technology to promote physical activity, using water as a linking element between users. Adopting a research-through-design approach, we explored how such installations can nudge people into an active behavior while additionally strengthening social connectedness, using inclusive design principles. We report on insights gathered through this case study and findings of a preliminary user test, discussing the implications of this work for design researchers and practitioners.
An Immersive Environment for Embodied Code

The increasing sophistication and availability of Augmented and Virtual Reality (AR/VR) technologies wield the potential to transform how we teach and learn computational concepts and coding. This project develops a platform for creative coding in virtual and augmented reality. The Embodied Coding Environment (ECE) is a flow-based visual coding system designed to increase physical engagement with programming and lower the barrier to entry for novice programmers. It is conceptualized as a merged digital/physical workspace where spatial representation of code, the visual outputs of the code, and user interactions and edit histories are co-located in a virtual 3D space.
ONYX - User Interfaces for Assisting in Interactive Task Learning for Natural Language Interfaces of Data Visualization Tools

While natural language interfaces (NLIs) are increasingly utilized to simplify the interaction with data visualization tools, improving and adapting the NLIs to the individual needs of users still requires the support of developers. ONYX introduces an interactive task learning (ITL) based approach which enables NLIs to learn from users through natural interactions. Users can personalize the NLI with new commands using direct manipulation, known commands, or by combining both. To further support users during the training process, we derived two design goals for the user interface, namely providing suggestions based on sub-parts of the command and addressing ambiguities through follow-up questions and instantiated them in ONYX. In order to trigger reflections and gain feedback on possible design trade-offs of ONYX and the instantiated design goals, we performed a formative user study to understand how to successfully integrate the suggestions and follow-up question into the interaction.
Tangible Version Control: Exploring a Physical Object’s Alternative Versions

In iterative physical object creation, only the latest design state is manifested in the physical artifact, while information about previous versions are lost. This makes it challenging to keep track of changes and developments in iterative physical design. In this paper, we propose the concept of Tangible Version Control (TVC), inspired by the visualizations of traditional version control systems. In TVC, the real-world artifact itself is used for exploring its alternative versions in physical space, while comparisons to an alternative version are displayed seamlessly on the artifact with the use of augmented reality. Our implementation of TVC includes three different comparison modes, namely SideBySide, Overlay, and Differences. Furthermore, we discuss the anticipated use, opportunities, and challenges of using TVC in the future for individual users as well as for asynchronous collaborative work.
Can User Reviews Indicate Usability Heuristic Issues?

User reviews of mobile applications in online stores have been used as a source for numerous studies. Many focus on indicating new functional requirements and extracting problems regarding quality characteristics, such as Usability. One of the most known strategies to evaluate Usability is Nielsen’s heuristics. We believe that user reviews in online stores can indicate heuristics issues, thus supporting evaluations more focused on the user feedback. Therefore, this study aims to investigate the presence of usability heuristic issues through user reviews. To achieve this goal, we collected and analyzed 200 reviews, split into 528 statements, from 10 free and paid Android and iOS apps. Our results showed that user reviews have certain potential to indicate heuristic issues, suggesting new and challenging future research for the CHI community.
Many Islands, Many Problems: An Empirical Examination of Online Safety Behaviors in the Caribbean

Little is known about non-Western social media users’ motivations for adopting behaviors that protect them against pervasive threats to their privacy, security, and personal well-being. Drawing on Rogers’ Protection Motivation Theory (PMT), this survey study explores Caribbean people’s (N=551) perceptions of safety threats and the factors contributing to their intention to adopt protective behaviors. Our analysis revealed that prior victimization was associated with increased perceptions of vulnerability and severity of harms, which, in turn, influenced elevated safety protection behaviors. For harassment-related harms in particular, participants’ trust in social media sites increased their intention to adopt protective behaviors. We observe significant country-to-country differences, which we contextualize through interviews with experts throughout the region. Our findings provide a new understanding of users’ mental models, behaviors, and attitudes with respect to online safety. We conclude by discussing theoretical and practical implications and outline opportunities for the design of inclusive and culturally-aware safety tools.
Am I a Resource-Poor Language? Data Sets, Embeddings, Models and Analysis for four different NLP Tasks in Telugu Language

Due to the lack of a large annotated corpus, many resource-poor Indian languages struggle to reap the benefits of recent deep feature representations in Natural Language Processing (NLP) . Moreover, adopting existing language models trained on large English corpora for Indian languages is often limited by data availability, rich morphological variation, syntax, and semantic differences. In this paper, we explore the traditional to recent efficient representations to overcome the challenges of a low resource language, Telugu. In particular, our main objective is to mitigate the low-resource problem for Telugu. Overall, we present several contributions to a resource-poor language viz. Telugu. (i) a large annotated data (35,142 sentences in each task) for multiple NLP tasks such as sentiment analysis, emotion identification, hate-speech detection, and sarcasm detection, (ii) we create different lexicons for sentiment, emotion, and hate-speech for improving the efficiency of the models, (iii) pretrained word and sentence embeddings, and (iv) different pretrained language models for Telugu such as ELMo-Te , BERT-Te , RoBERTa-Te , ALBERT-Te , and DistilBERT-Te on a large Telugu corpus consisting of 8,015,588 sentences (1,637,408 sentences from Telugu Wikipedia and 6,378,180 sentences crawled from different Telugu websites). Further, we show that these representations significantly improve the performance of four NLP tasks and present the benchmark results for Telugu. We argue that our pretrained embeddings are competitive or better than the existing multilingual pretrained models: mBERT , XLM-R , and IndicBERT . Lastly, the fine-tuning of pretrained models show higher performance than linear probing results on four NLP tasks with the following F1-scores: Sentiment (68.72), Emotion (58.04), Hate-Speech (64.27), and Sarcasm (77.93). We also experiment on publicly available Telugu datasets (Named Entity Recognition, Article Genre Classification, and Sentiment Analysis) and find that our Telugu pretrained language models ( BERT-Te and RoBERTa-Te ) outperform the state-of-the-art system except for the sentiment task. We open-source our corpus, four different datasets, lexicons, embeddings, and code https://github.com/Cha14ran/DREAM-T. The pretrained Transformer models for Telugu are available at https://huggingface.co/ltrctelugu.
AKER: An open-source security platform integrating IDS and SIEM functions with encrypted traffic analytic capability

This research proposes Aker, an open-source security platform that integrates IDS and SIEM functions while supporting the automated investigation of threats hidden in encrypted traffic. Aker is based on open-source technologies, whose aim is to simplify and integrate network monitoring and security alerts management through coherent and interconnected dashboards. Aker enables the detection of malware concealed in encrypted traffic and uses a heuristic-based decision-tree model to classify these threats into different severity levels, based on seven specific criteria and indicators originating mainly from TLS handshake unencrypted metadata, and HTTP/ DNS contextual flows linked to the encrypted traffic. Our approach does not require deep packet inspection nor intensive traffic analysis, but rather relies on the analysis of a reduced set of network telemetry indicators and session descriptors. Aker permits to automate data collection and investigation while providing user-friendly dedicated dashboards to provide SOC analysts and threat intelligence experts with valuable decision support tools. We present the design and implementation aspects of the proposed platform along with some validation results.
Machine-Mediated Teaming: Mixture of Human and Machine in Physical Gaming Experience

Technological advancement has opened up opportunities for new sports and physical activities. We introduce a concept called machine-mediated teaming, in which a human and a surrogate machine form a team to participate in physical sports games. To understand the experience of machine-mediated teaming and the guidelines for designing the system to achieve the concept, we built a case study system based on tug-of-war. Our system is a sports game played by two against two. One team consists of a player who actually pulls the rope and another player who participates in the physical game by controlling the machine's actuators. We conducted user studies using this system to investigate the sport experience in this form and to reveal insights to inform future research on machine-mediated teaming. Based on the data obtained from the user studies, we clarified three perspectives, machine stamina, action space, and explicit feedback, that should be considered when designing future machine-mediated teaming systems. The research presented in this paper offers a first step towards exploring how humans and machines can coexist in highly dynamic physical interactions.
Terrain Modelling with a Pen &amp; Touch Tablet and Mid-Air Gestures in Virtual Reality

World building or terrain modelling is an essential task when designing games, natural simulations or artistic creations involving virtual 3D landscapes. To support this task, we propose a virtual reality (VR) system based on a pen and touch tablet used in a sitting position (desktop VR) such that both hands are free to interact in an asymmetric way (pen hand + other bare hand). We present and compare several techniques to perform navigation, sculpting and menu operations using the two hands, which interact on and above the tablet surface, i.e. using the pen, touch and mid-air input spaces. A qualitative evaluation with 16 participants confirms the entertaining nature and practical benefits of our system. The study further underlines the complementarity of the different modalities and identifies the promising—and as of yet underexplored—combination of bimanual touch + pen + mid-air interaction in desktop VR.
Blockchain-Based Reference Architecture for Automated, Transparent, and Notarized Attestation of Compliance Adaptations

With cloud computing, organizations must comply with applicable laws, policies, and best practices. Companies typically rely on cloud service providers to implement and adopt regulations. This consulting phase is often time-consuming, costly, and not transparent. Organizations must trust the third party’s implementation and associated documentation processes. To resolve this dilemma, we present a blockchain-based reference architecture for the automated, transparent, and notarized attestation of such compliance adaptations. Before proposing a solution, our approach is to understand the underlying research context. We conduct a machine-learning-supported systematic literature review to create a knowledge base. A reference architecture, including a prototype for configuring intrusion-detection systems, is developed using design science research. A mixed-methods-based approach is used for the evaluation of the proposed architecture. A quantitative survey is then used to show that the user experience of the developed prototype can be rated as positive, with an average value of 0.7. Finally, two focus group discussions are used to analyze the presented prototype qualitatively. As a result, we demonstrate how to actively support secure and trustworthy communication between a cloud service provider and an organization applying blockchain configurations.
Style Blink: Exploring Digital Inking of Structured Information via Handcrafted Styling as a First-Class Object

Structured note-taking forms such as sketchnoting, self-tracking journals, and bullet journaling go beyond immediate capture of information scraps. Instead, hand-drawn pride-in-craftmanship increases perceived value for sharing and display. But hand-crafting lists, tables, and calendars is tedious and repetitive. To support these practices digitally, Style Blink (“Style-Blocks+Ink”) explores handcrafted styling as a first-class object. Style-blocks encapsulate digital ink, enabling people to craft, modify, and reuse embellishments and decorations for larger structures, and apply custom layouts. For example, we provide interaction instruments that style ink for personal expression, inking palettes that afford creative experimentation, fillable pens that can be “loaded” with commands and actions to replace menu selections, techniques to customize inked structures post-creation by modifying the underlying handcrafted style-blocks and to re-layout the overall structure to match users’ preferred template. In effect, any ink stroke, notation, or sketch can be encapsulated as a style-object and re-purposed as a tool. Feedback from 13 users show the potential of style adaptation and re-use in individual sketching practices.
FitVid: Responsive and Flexible Video Content Adaptation

Mobile video-based learning attracts many learners with its mobility and ease of access. However, most lectures are designed for desktops. Our formative study reveals mobile learners’ two major needs: more readable content and customizable video design. To support mobile-optimized learning, we present FitVid, a system that provides responsive and customizable video content. Our system consists of (1) an adaptation pipeline that reverse-engineers pixels to retrieve design elements (e.g., text, images) from videos, leveraging deep learning with a custom dataset, which powers (2) a UI that enables resizing, repositioning, and toggling in-video elements. The content adaptation improves the guideline compliance rate by 24% and 8% for word count and font size. The content evaluation study (n=198) shows that the adaptation significantly increases readability and user satisfaction. The user study (n=31) indicates that FitVid significantly improves learning experience, interactivity, and concentration. We discuss design implications for responsive and customizable video adaptation.