Miracle-dz/UniFAR-FTUs huggingface dataset:
Should I Interrupt or Not?: Understanding Interruptions in Head-Mounted Display Settings

Head-mounted displays (HMDs) are being used for VR and AR applications and increasingly permeate our everyday life. At the same time, a detailed understanding of interruptions in settings where people wearing an HMD (HMD user) and people not wearing an HMD (bystander) is missing. We investigate (a) whether bystanders are capable of identifying when HMD users switch tasks by observing their gestures, and hence exploit opportune moments for interruptions, and (b) which strategies bystanders employ. In a lab study (N=64) we found that bystanders are able to successfully identify both task switches (83%) and tasks (77%) within only a few seconds of the task switch. Furthermore, we identified interruption strategies of bystanders. From our results we derive implications meant to support designers and practitioners in building HMD applications that are used in a co-located collaborative setting.
The Apple Does Fall Far from the Tree: User Separation of a System from its Developers in Human-Automation Trust Repair

To promote safe and effective human-computer interactions, researchers have begun studying mechanisms for "trust repair" in response to automated system errors. The extent to which users distinguish between a system and the system's developers may be an important factor in the efficacy of trust repair messages. To investigate this, we conducted a 2 (reliability) x 3 (blame) between-group, factorial study. Participants interacted with a high or low reliability automated system that attributed blame for errors internally ("I was not able."), pseudo-externally ("The developers were not able."), or externally ("A third-party algorithm that I used was not able."). We found that pseudo-external blame and internal blame influenced subjective trust differently, suggesting that the system and its developers represent distinct trustees. We discuss the implications of our findings for the design and study of human-automation trust repair.
MorphIO: Entirely Soft Sensing and Actuation Modules for Programming Shape Changes through Tangible Interaction

We introduce MorphIO, entirely soft sensing and actuation modules for programming by demonstration of soft robots and shape-changing interfaces.MorphIO's hardware consists of a soft pneumatic actuator containing a conductive sponge sensor.This allows both input and output of three-dimensional deformation of a soft material.Leveraging this capability, MorphIO enables a user to record and later playback physical motion of programmable shape-changing materials.In addition, the modular design of MorphIO's unit allows the user to construct various shapes and topologies through magnetic connection.We demonstrate several application scenarios, including tangible character animation, locomotion experiment of a soft robot, and prototyping tools for animated soft objects.Our user study with six participants confirms the benefits of MorphIO, as compared to the existing programming paradigm.
FITing-Tree: A Data-aware Index Structure

Index structures are one of the most important tools that DBAs leverage to improve the performance of analytics and transactional workloads. However, building several indexes over large datasets can often become prohibitive and consume valuable system resources. In fact, a recent study showed that indexes created as part of the TPC-C benchmark can account for 55% of the total memory available in a modern DBMS. This overhead consumes valuable and expensive main memory, and limits the amount of space available to store new data or process existing data. In this paper, we present a novel data-aware index structure called FITing-Tree which approximates an index using piece-wise linear functions with a bounded error specified at construction time. This error knob provides a tunable parameter that allows a DBA to FIT an index to a dataset and workload by being able to balance lookup performance and space consumption. To navigate this tradeoff, we provide a cost model that helps determine an appropriate error parameter given either (1) a lookup latency requirement (e.g., 500ns) or (2) a storage budget (e.g., 100MB). Using a variety of real-world datasets, we show that our index is able to provide performance that is comparable to full index structures while reducing the storage footprint by orders of magnitude.
Talk to Me Intelligibly: Investigating An Answer Space to Match the User's Language in Visual Analysis

Conversational interfaces (CIs) have the potential to empower a broader spectrum of users to independently conduct visual analysis. Yet, recent approaches do not fully consider the user's characteristics. In particular, the objective of matching the user's language has been understudied in visual analysis. In order to close this gap, we introduce an answer space motivated by Grice's cooperative principle for framing personalized communication in complex data situations. We conducted both an online survey (N=76) to analyze communication preferences and a qualitative experiment (N=10) to investigate personalized conversations with an existing CI. In order to match the user's language properly, our results suggest to consider additional user characteristics along with their knowledge level. While mismatching communication preferences triggers negative reactions, a preference-aligned communication evokes positive reactions. As our analysis confirms the importance of matching the user's language in visual analysis, we provide design implications for future CIs.
Mobile Realities: Designing for the Medium of Smartphone-VR

We present two proof of concept experiences for a virtual reality (VR) game that draws on several medium-specific qualities of mobile, location-based, and tangible storytelling. In contemporary smartphone-VR, experiences are limited by short playtimes, limited interactions, and limited movement within a physical space. To address these limitations, we suggest a reconceptualization of smartphone-VR. Rather than design that deems the smartphone the least capable VR platform, we propose design that adds VR to an already rich mobile storytelling platform. We argue that by drawing on otherwise separate storytelling media, designers can circumvent limitations related to smartphone-VR while also extending the range of smartphone-based storytelling. We conclude by reflecting on possible implications of this extended design space.
Keeping and Discarding Personal Data: Exploring a Design Space

Today, most technology users have to deal with a growing amount of personal data across many devices and online platforms. There is a growing need for tools that can help people decide more intentionally what data to keep or discard. We created five design concepts in the form of video prototypes to probe on alternative design strategies for supporting users. Automation, aggressiveness, and temporality were key dimensions we explored. We conducted interviews with 16 participants using the concepts as a starting point for discussion. Participants had a range of reactions: some wanted to retain full control over keeping and discarding decisions, while others welcomed more automatic tools. We identify common ground in the need for a contextual and nuanced approach in design. We use these results to outline and reflect on possible future design directions for personalization, automation, new keeping or discarding actions, and privacy.
Our Symbiotic Life: An Exploration of Interspecies Relations

We will explore four plausible futures and experiment on a speculative approach to investigate "wicked problems" [14]. Grounded in the field of design fiction, this work combines insights from the climate impact research community, technology meta trends, and plant science, all of which work as a basis for the exploration of relationships between humans, plants, and technology. Based on scenarios from the climate impact research community, we prototyped four plausible worlds and visualized exemplary scenes in the daily life of the plausible citizens. Sketching and low-fidelity prototyping supported the process of gaining knowledge and iterating on storytelling.
Use of the Derin's algorithm in hidden semi-Markov models for automatic speech recognition

The application of hidden Markov models to speech pattern modeling suffers from two major deficiencies: the classical learning algorithm generates severe underflow problems and the implicit state occupancy function is inadequate for modeling speech-segment duration. To overcome the numerical problem, the classical joint probability formalism is replaced by a conditional probability formalism. To avoid the unrealistic implicit modeling of the state occupancy, the underlying Markov chain is replaced by a semi-Markov chain, a more general framework where the state occupancy is explicitly modeled by an appropriate probability density function, in the present case a gamma distribution. A particular scheme based on hidden semi-Markov models and an a posteriori probability formalism is presented. The learning algorithm is characterised on an isolated-word-recognition task. Preliminary results are given on demi-syllable modeling in the context of continuous speech decoding. <<ETX>>
Exploring the Addition of Audio Input to Wearable Punch Recognition

Martial arts can promote healthy lifestyles, improve self-confidence and provide self-defence skills. Previous work has demonstrated that inertial sensors can be used to recognise movements such as punches in boxing and support self-directed training. However, many martial arts do not use gloves which means that punches can be performed with different parts of the hand, and therefore produce a different sound on impact. We investigate if it is possible to recognise different punches executed with a bare hand, and if the recognition rate improves by combining audio input with the traditional inertial sensors. We conducted a pilot study collecting a total of 600 punches, using a wearable wristband to capture inertial data and a stand-alone microphone for audio input. The results showed that it was possible to distinguish five types of punches with 94.4% accuracy when using only inertial data, and that adding audio input did not improve the accuracy. These findings can guide the design of future wearables for punch recognition.
Activities as a Gateway to Sustained Subjective Well-Being Mediated by Products

Research in positive psychology indicates that sustained well-being is more determined by our actions than by our possessions. Products' contribution to well-being may thus be grounded in their potential to support well-being-enhancing activities rather than in their material value. In a laddering study, we investigated how products shape a range of well-being determinants, including activities, and well-being outcomes. Following a hierarchical structure, seven product experience qualities, six motivations, and seven activities were empirically found to be linked to long-term well-being. We describe these ingredients for sustained well-being in further detail and provide actionable guidance on how to address them by means of design. As the majority of product-supported long-term well-being outcomes were mediated by activities, we propose activities as most promising starting point in design for sustained well-being.
Mediating Relatedness for Adolescents with ME: Reducing Isolation through Minimal Interactions with a Robot Avatar

This paper discusses how a networked object in the form of a small robot designed to mediate experiences of care, social connectedness, and intimacy, was used by adolescents with Myalgic Encephalomyelitis, a condition that reduces their normal functioning, including the ability to socialize. A study with nine adolescents, each using the robot for about a year in average, revealed that it was largely effective at mediating their everyday experiences of relatedness, triggering productive new habits and social practices. We interpret these findings to propose a set of strategies for designing technologies that support relatedness while requiring minimal interactivity and engagement. Balance, extension-of-self, coolness, and acts-of-care, in addition to commonly used physicalness, expressivity and awareness, enable the robot to extend the adolescents' ability to relate to others, people and animals.
1+ε approximation of tree edit distance in quadratic time

Edit distance is one of the most fundamental problems in computer science. Tree edit distance is a natural generalization of edit distance to ordered rooted trees. Such a generalization extends the applications of edit distance to areas such as computational biology, structured data analysis (e.g., XML), image analysis, and compiler optimization. Perhaps the most notable application of tree edit distance is in the analysis of RNA molecules in computational biology where the secondary structure of RNA is typically represented as a rooted tree. The best-known solution for tree edit distance runs in cubic time. Recently, Bringmann et al. show that an O(n2.99) algorithm for weighted tree edit distance is unlikely by proving a conditional lower bound on the computational complexity of tree edit distance. This shows a substantial gap between the computational complexity of tree edit distance and that of edit distance for which a simple dynamic program solves the problem in quadratic time. In this work, we give the first non-trivial approximation algorithms for tree edit distance. Our main result is a quadratic time approximation scheme for tree edit distance that approximates the solution within a factor of 1+є for any constant є > 0.
Goals and Performance in Computer Programming

In all studies of human performance, the experimenter must be certain that the subject is performing the task that the experimenter believes he has set; otherwise results become uninterpretable. Early studies of computer programming have shown such wide variations in individual performance that one might suspect that subjects differed in their interpretation of the task. Experiments are reported which show how programming performance can be strongly influenced by slight differences in performing objectives. Conclusions are drawn from these results regarding both future experimentation and management practices in computer programming.
Flows in almost linear time via adaptive preconditioning

We present algorithms for solving a large class of flow and regression problems on unit weighted graphs to (1 + 1 / poly(n)) accuracy in almost-linear time. These problems include ℓp-norm minimizing flow for p large (p ∈ [ω(1), o(log2/3 n) ]), and their duals, ℓp-norm semi-supervised learning for p close to 1. As p tends to infinity, p-norm flow and its dual tend to max-flow and min-cut respectively. Using this connection and our algorithms, we give an alternate approach for approximating undirected max-flow, and the first almost-linear time approximations of discretizations of total variation minimization objectives. Our framework is inspired by the routing-based solver for Laplacian linear systems by Spielman and Teng (STOC ’04, SIMAX ’14), and is based on several new tools we develop, including adaptive non-linear preconditioning, tree-routings, and (ultra-)sparsification for mixed ℓ2 and ℓp norm objectives.
SpeakQL: Towards Speech-driven Multimodal Querying

Speech-based inputs have become popular in many applications on constrained device environments such as smartphones and tablets, and even personal conversational assistants such as Siri, Alexa, and Cortana. Inspired by this recent success of speech-driven interfaces, in this work, we consider an important fundamental question: How should one design a speech-driven system to query structured data? Recent works have studied new querying modalities like visual [4, 8], touch-based [3, 7], and natural language interfaces (NLIs) [5, 6], especially for constrained querying environments such as tablets, smartphones, and conversational assistants. The commands given by the user are then translated to the Structured Query Language (SQL). But conspicuous by its absence is a speech-driven interface for regular SQL or other structured querying. One might wonder: Why dictate structured queries and not just use NLIs or visual interfaces? From a practical standpoint, many users, including in the C-suite, enterprise, Web, and other domains are already familiar with SQL (even if only a subset of it) and use it routinely. A spoken SQL interface could help them speed up query specification, especially in constrained settings such as smartphones and tablets, where typing SQL would be painful. More fundamentally, there is a trade-off inherent in any query interface, as illustrated in Figure 1(A).
Lifting Kirigami Actuators Up Where They Belong: Possibilities for SCI

Kirigami Actuators are two-dimensional patterns that allow the translation of a simple actuation in one dimension into a complex transformation in another. Kirigami Actuators represent one metamaterial strategy that designers of Shape-changing Interfaces could utilize to minimize the size and complexity costs of actuation. Metamaterials yield great promise for HCI and Shape-changing Interfaces in particular. In an effort to reveal the promise of Kirigami Actuators for the design of Shape-changing Interfaces, this pictorial presents several design tactics for a specific Kirigami Actuator: The Lift pattern. These tactices outline how different components of the pattern can be changed to strategically alter the transformational qualities of the pattern. Initial concept sketches are presented as inspiration for future work.
How Peripheral Data Visualisation Systems Support Secondary School Teachers during VLE-Supported Lessons

Through the integration of technology-enhanced learning (TEL) in the classrooms, there is an increase in Virtual Learning Environment-supported classes in secondary schools, which brings unintentional complexities in terms of monitoring for teachers [25]. To support secondary school teachers during VLE-supported lessons, a peripheral data visualisation system was designed and implemented in a three-week field study. Both qualitative and quantitative data were gathered and analysed through methodological triangulation in order to get an in-depth understanding about the use of the system by teachers. The key findings from our study were that the peripheral data visualisation tool, by being a distributed, highly visible system, was well integrated in the teachers' practice. The peripheral visualisation served as a trigger for teacher interventions where the teacher could confront the student's level of concentration and provide support when a student needs it. Furthermore, by offloading the secondary tasks of checking the students' level of concentration and progress to the visualisation, most teachers experienced more peace of mind and space to manage their primary teaching practice. Lastly, approximately 95% of 89 students experienced the data visualisation as neutral or motivating, while 5.7% of the students experienced violation of privacy by this medium.
"The Printer is Telling Me about Itself": Supporting the Appropriation of Hardware by Using Projection Mapping

The increasing complexity of cyber-physical systems poses special challenges for users to be able to appropriate and apply such technologies within their practice. Classic tools to support appropriation have usually taken the form of written manuals or video tutorials. However, recent research regarding appropriation infrastructures and sociable technologies has suggested that appropriation support functionality can be integrated directly into software and cyber-physical systems. The problem confronting this kind of support is the adequate visualization of the information and the provision of user interfaces that could offer the necessary basis for appropriation. Based on the example of 3D printing, we examine how projection mapping-as an innovative form of visualization-can be used as a user interface for hardware-related appropriation support. Through reflections upon the design and evaluation of a projection-based 3D-printer system, we provide insights that extend the notion of appropriation support to encompass projection mapping and that can contribute to the future development of projection-based human-machine interfaces.
Exploring the Design of Social VR Experiences with Older Adults

There is growing interest in technologies that allow older adults to socialise across geographic boundaries. An emerging technology in this space is social virtual reality (VR). In this paper we report on a series of participatory design workshops that involved extended in-depth collaboration with 22 older adults (aged 70-81), that aimed to understand their views on the types of social VR experiences that they saw as being of value to older adults. This process culminated in a reminiscence-based social VR concept. Our study identifies: participants' ideas about the types of social VR experiences they found appealing; the potential for social VR as a powerful reminiscence tool; how social VR might be used as a tool to challenge ageing stereotypes and promote healthy ageing. Reflecting on the design process, we discuss how the diverse participant groups and the complexities involved in mediating between designers, the technical team, and participants could inform future design work.
Ratel: Interactive Analytics for Large Scale Trajectories

Trajectory data analytics plays an important role in many applications, such as transportation optimization, urban planning, taxi scheduling, and so on. However, trajectory data analytics has a great challenge that the time cost for processing queries is too high on big datasets. In this paper, we demonstrate a distributed in-memory framework Ratel base on Spark for analyzing large scale trajectories. Ratel groups trajectories into partitions by considering the data locality and load balance. We build R-Tree based global indexes to prune partitions when applying trajectory search and join. For each partition, Ratel uses a filter-refinement method to efficiently find similar trajectories. We show three kinds of scenarios - bus station planning, route recommendation, and transportation analytics. Demo attendees can interact with a web UI, pose different queries on the dataset, and navigate the query result.
Data Extraction and Alignment in Web Databases

Web databases comprises of large amount of data. There is a high demand for collecting data of interest from multiple web databases by the users. Query based interfaces are used to access the data from such databases. Data extraction from large portion of web databases is very tedious portion of many search engine processes. Without any consideration search engine returns result pages from the structural and unstructured databases based on a unique URL.A typical result page returned from such a web database has multiple query result records (QRR) and auxiliary information such as comments, advertisements and multiple sites pertaining to the advertisements. This paper defines the semantical representation of a concept as an entity, which means a data unit will be extracted from a structured or unstructured web page and are then organized into tables so that they can they be easily compared and aggregated to utilize the data. This paper aims to automatically extract wrappers, tags and values from a raw HTML file by employing Structural Semantic Combination of Tag and Value Similarity (SCTVS) method, which aims at automatically assigning meaningful labels to the data units in QRRs. It has a main objective of finding relative labels for QRR result set alignment. Optimal temporary storage is used to store the auxiliary information for enabling data extraction easier. In addition, a new method of data alignment called Priority alignment along with Data Summarization is used . Experimental results show that the current method yields high precision and accuracy compared with the existing methods.