Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Fitness Tracker Users’ and Non-Users’ Requirements for Interactive and Transparent Privacy Information

While fitness tracker users consent to the processing of their sensitive data based on privacy policies, previous research has demonstrated that legal texts often remain unread or incomprehensible. This questions whether the given consent is indeed informed. While past research concentrated on improving privacy comprehension, our research aims to better understand user requirements for interactive and transparent privacy information and control systems. We mainly focus on users’ assessment of contextual and functional aspects. Findings from an online survey with fitness tracker users and non-users (N = 204) reveal that such systems need to support users and potential users throughout the usage life cycle, illustrating a dynamic change in requirements and their prioritization of information transparency and privacy control. Design recommendations derived from our results support the development of interactive and comprehensible privacy systems that enable more knowledgeable decisions on sharing and processing fitness tracker data.
SurfAirs: Surface + Mid-air Input for Large Vertical Displays

Large vertical surfaces such as wall displays allow users to work with a very large and high-resolution workspace. Such displays promote physical navigation: users can step close to the display to see details, but also move away to get a wider view of the workspace. In terms of input, current solutions usually combine direct touch on the wall with input on a handheld device, disconnecting close and distant input rather than treating it as a continuum. We present SurfAirs, which are physical controllers that users can manipulate on screen (surface input), in the air (mid-air input), and transition from the surface to the air during a single manipulation (hybrid input). We report on two user studies that compare SurfAirs’ performance with bare-hand input for both mid-air and hybrid input. Participants prefer and perform better with SurfAirs.
De-Stijl: Facilitating Graphics Design with Interactive 2D Color Palette Recommendation

Selecting a proper color palette is critical in crafting a high-quality graphic design to gain visibility and communicate ideas effectively. To facilitate this process, we propose De-Stijl, an intelligent and interactive color authoring tool to assist novice designers in crafting harmonic color palettes, achieving quick design iterations, and fulfilling design constraints. Through De-Stijl, we contribute a novel 2D color palette concept that allows users to intuitively perceive color designs in context with their proportions and proximities. Further, De-Stijl implements a holistic color authoring system that supports 2D palette extraction, theme-aware and spatial-sensitive color recommendation, and automatic graphical elements (re)colorization. We evaluated De-Stijl through an in-lab user study by comparing the system with existing industry standard tools, followed by in-depth user interviews. Quantitative and qualitative results demonstrate that De-Stijl is effective in assisting novice design practitioners to quickly colorize graphic designs and easily deliver several alternatives.
Understanding Wheelchair Users’ Preferences for On-Body, In-Air, and On-Wheelchair Gestures

We present empirical results from a gesture elicitation study conducted with eleven wheelchair users that proposed on-body, in-air, and on-wheelchair gestures to effect twenty-one referents representing common actions, types of digital content, and navigation commands for interactive systems. We report a large preference for on-body (47.6%) and in-air (40.7%) compared to on-wheelchair (11.7%) gestures, mostly represented by touch input on different parts of the body and hand poses performed in mid-air with one hand. Following an agreement analysis that revealed low consensus (≤ 5.5%) between users, although high perceived gesture ease, goodness, and social acceptability within users, we examine our participants’ gesture characteristics in relation to their self-reported motor impairments, e.g., low strength, rapid fatigue, etc. We highlight the need for personalized gesture sets, tailored to and reflective of both users’ preferences and specific motor abilities, an implication that we examine through the lenses of ability-based design.
A Systematic Methodology for performance characterizing of Heterogeneous Systems with a dataflow runtime simulator

As innovations in AI/ML heterogeneous systems and DNN models continue to grow, there is a need for accurate performance analysis methodology to understand and navigate this complex SW-HW interplay to support efficient running of DNN models for future systems. The great success of dataflow paradigm for representing the neural network computation with dataflow graph has drawn attentions from both industry and academia. For the given deep learning workloads, to organize the corresponding directed acyclic graphs (DAGs) on the dedicated heterogeneous environment involves a complex interplay between DNN algorithms, hardware, algorithm-to-hardware mapping. In this work, we propose a fine-grained dataflow runtime simulator for achieving highly accurate performance modeling towards the deep learning workloads. It makes two major contributions. (i) The end-to-end ML method is used to realize the performance modeling of DNN operator, task-based modeling with cycle-accurate simulation. (ii) Research on task scheduling and task division of heterogeneous data flow runtime system. Based on our dataflow runtime simulator, we systematically analyze the computational graph scheduling and data flow granularity of typical AI workloads in complex heterogeneous hardware environments from the dataflow perspective. As an example of the dataflow method in Huawei Ascend 910 scenarios, it provides a reference build performance model for fast and accurate performance (e.g. iteration training time) prediction without actually executing DNN models on the dedicated hardware can better realize software and hardware co-design on heterogeneous systems.
Empathic Accuracy and Mental Effort During Remote Assessments of Emotions

Observing users in remote settings is unfavorable because it adds filters altering the information that underlie judgement. Still, the COVID pandemic led to an unprecedented popularity of remote user experience tests. In this work, we revisited the question, which information is most important for evaluators to assess users’ emotions successfully and efficiently. In an online study, we asked N=55 participants to assess users’ emotions from short videos of 30 interaction situations. As independent variable, we manipulated the combination of the information channels video of users, video of the interactive technology, and audio within subjects. Our findings indicate that empathic accuracy is highest and mental effort is lowest when all stimuli are present. Surprisingly, empathic accuracy was lowest and mental effort highest, when only video of users was available. We discuss these findings in the light of emotion literature focusing on persons’ facial expressions and derive practical implications for remote observations.
Multi-objective Optimization Layout of Intelligent Robot Integrated Workshop Based on Machine Vision

The application object of layer manufacturing unit is mainly intelligent factory or robot manufacturing unit with high degree of automation. Compared with the traditional single layer manufacturing unit, the number of equipment of multi-layer manufacturing unit is more, and the three-dimensional space factor needs to be considered, so the problem is more complicated. This paper mainly studies the multi-objective optimization layout of intelligent robot integrated workshop based on machine vision. In this paper, based on the proposed DCSGSA algorithm, according to the computational complexity and multi-scale characteristics of the integrated model, a multi-layer optimization strategy of robot work unit layout is designed to solve the model. The proposed algorithm was used to solve a practical case of intelligent die casting island parts taking robot unit of a die casting machine company, and compared with other multi-objective algorithms, the efficiency of the proposed algorithm was verified.
Chronic Care in a Life Transition: Challenges and Opportunities for Artificial Intelligence to Support Young Adults With Type 1 Diabetes Moving to University

Self-managing a chronic condition involves adapting management strategies to life’s continual change. Among these changes, moments of significant life transition can render routine self-management practices obsolete without significant modification to the new context. In this study, we examine one significant life transition for young adults living with Type 1 Diabetes, the move from home to university, to understand how near future AI-enhanced technologies might provide opportunities and challenges for supporting care. From interviews with 24 students in the UK who had moved away from their childhood homes, we used sensemaking literature to frame the process of initial disruption to the rebuilding of self-care practices around a new lifestyle and support networks. By studying a significant life transition, we uncover implications for the design of T1D technology, particularly closed-loop systems, through AI enhancements and human-centred design approaches, then extrapolate for other significant life transitions and chronic conditions.
Why “why”? The Importance of Communicating Rationales for Edits in Collaborative Writing

Collaborative writing is prevalent, yet is rife with issues of discomfort and miscommunication among others despite access to limitless text. Editing, one key activity in collaborative writing, is prone to such issues, and providing rationales could be a promising solution. To understand the efficacy of rationales in this context, we conducted an online experiment pairing 40 participants to co-write two essays on Google Docs—one without rationales (control) and another with rationales (treatment)—followed by post-experiment surveys (N=40) and interviews (N=11) with participants who received edits with and without rationales. Despite no significant differences between conditions in survey results, interviews revealed that most people preferred collaborating with those who provided rationales and perceived them more favorably. All interviewees deemed rationales important in collaborative writing and felt the pros outweighed the cons. We contribute design recommendations with illustrative examples for effective collaborative writing.
Monkeypox Diagnosis with Convolutional Neural Networks Combined with Colour Space Models

The rapidly rising incidence of monkeypox has gradually become an emerging infectious disease threat. An effective and quick strategy for early diagnosis potentially can reduce its infectiousness. This paper explores the classification of monkeypox and other skin diseases using CNN models. Specifically, we first increase the amount of data by applying the data augmentation method to the images, and colour feature selection is performed to use the most effective RGB as the image input feature. The presented CNN model is constructed to be applicable to the classification of monkey pox. We evaluate our model's efficacy by contrasting it with the widely accepted transfer learning approaches. Our model achieves an accuracy of 91%, presenting 8-17% higher accuracy than the transfer learning models. The experimental results demonstrate that our CNN model is superior for monkeypox classification. Our model can be a reliable and effective tool for the initial screening of monkeypox.
Effects of Delivery Time and Delivery Distance of Indoor Robot Delivery Service on User Satisfaction and Reuse Intention

The indoor robot service industry has been growing rapidly, industrial and academic research has been actively conducted. However, several previous studies have focused on the acceptance of robots, and there is a lack of research on delivery robot services. Moreover, research cases targeting users who have experienced actual robot delivery services are rare. Therefore, we conducted this study targeting employees who have used actual robot delivery services in a large office space with a total floor area of 165,000 m2 built as a robot-friendly building. Providing delivery services with approximately 100 robots in a large building is a rare case in the world. This study expanded the technology acceptance model and analyzed how delivery time and distance, which are the characteristics of robot delivery services, affect the robot acceptance intention.
Intelligent power grid load scheduling method based on multi-agent game

Considering that user demand will affect the effect of multi-time scale intelligent load scheduling in distribution network to some extent, an intelligent load scheduling method based on multi-agent game is proposed. Due to the fluctuation of power load in the operation process of the distribution network, this paper analyzes the multi-time scale source load change scenario of the distribution network, alleviates the operation pressure of the distribution network through the short time interaction, analyzes the source load characteristics of the distribution network, and establishes the intelligent optimization objective function of the source load of the distribution network aiming at the lowest operating cost based on the multi-agent game under the premise of considering the variation of the difference value. According to the day-ahead scheduling model, the intra-day 2h scheduling model and the intra-day 15min scheduling model of the distribution network, the multi-time-scale source load scheduling model of the distribution network is constructed, and the multi-time-scale source load scheduling of the distribution network is realized. The experimental results show that the proposed method has better scheduling effect under different strategies and scenarios, and is suitable for widespread use.
CHI2023 Course on How to Peer Review for CHI (and Beyond)

A key challenge for people that are new to reviewing is pitching the review at the right level, and getting the tone and structure of a review right. This course aims to help participants understand a) the different expectations of different venues and submission types, b) the processes they use to make decisions, and c) good techniques for producing a review for these different circumstances. Combined with developing a good understanding of these different expectations, participants have a chance to critique anonymised but real reviews, and try to guess the venue they are written for and the recommendation they make.
Optimal layout scheme of roadside intelligent sensing equipment

With the increasing number of vehicles and the continuous increase of highway mileage. Traffic safety issues are gradually coming into view. Placing lidar on the side of the road can increase the safety of driving at high highway speeds. In order to achieve uninterrupted detection of vehicles on the highway. It is necessary to rationally deploy lidar. In this paper, the installation inclination, installation height, installation distance from the highway and the layout distance of adjacent lidar are studied. And the optimal layout scheme is given according to the highway in different scenarios.
The Spatial Performance Assessment for Cognitive Evaluation (SPACE): A Novel Game for the Early Detection of Cognitive Impairment

Dementia is a leading cause of dependency and death among older adults and an economic burden to healthcare. In the fast-paced non-gaming environment of healthcare, the detection of dementia is limited to invasive and expensive procedures (e.g., PET) or less sensitive paper and pencil tests. Typically, dementia is preceded by Mild Cognitive Impairment (MCI) which is characterised by the loss of cognitive function including deficits in spatial ability. Spatial ability may be a sensitive marker for discriminating between healthy individuals and MCI patients. Virtual Reality now allows for spatial tests to be easily and safely deployed in clinics or at home. We introduce the Spatial Performance Assessment for Cognitive Evaluation (SPACE) as a transgressive, transformative gamified battery of spatial tests for tablets. SPACE is designed to identify differences in spatial ability to support clinicians in the early detection of dementia and offers a flexible ecosystem for immediate and longitudinal assessments.
ProxSituated Visualization: An Extended Model of Situated Visualization using Proxies for Physical Referents

Existing situated visualization models assume the user is able to directly interact with the objects and spaces to which the data refers (known as physical referents). We review a growing body of work exploring scenarios where the user interacts with a proxy representation of the physical referent rather than immediately with the object itself. This introduces a complex mixture of immediate situatedness and proxies of situatedness that goes beyond the expressiveness of current models. We propose an extended model of situated visualization that encompasses Immediate Situated Visualization and ProxSituated (Proxy of Situated) Visualization. Our model describes a set of key entities involved in proxSituated scenarios and important relationships between them. From this model, we derive design dimensions and apply them to existing situated visualization work. The resulting design space allows us to describe and evaluate existing scenarios, as well as to creatively generate new conceptual scenarios.
Self-Supervised Interest Recommendation Based Intelligent System Design on Mental Health Education

Mental health education plays an important role for psychological health of college students. It is worth exploring how to effectively carry out mental health education online courses, give full play to the advantages of online courses. With the rapid development of robotics and intelligent control technology, online education can be completed depending on different intelligent devices. However, it is still a challenge to implement better online education programs on multiple intelligent devices and even educational robots. To solve this challenge, combining the artificial intelligence and intelligent control technologies, we propose a self-supervised interest recommendation based intelligent system design, which can be applied to mental health education and easily adapted to different intelligent devices. In particular, we introduce a self-supervised method to capture the students’ interests when they learn about the mental health courses, and reinforce their knowledge by recommending top-K courses that are likely to interest them most. The experiment results show the model performance, and also demonstrate the effectiveness of the proposed intelligent system.
Remote Wavelength: Design and Evaluation of a System for Social Connectedness Through Distributed Tabletop Gameplay

Playing remote tabletop games is a fun way to connect with distant friends. Yet most systems for remote tabletop gaming lack support for tangible and social interaction, two important aspects of gameplay for most players. We are interested in how to better design systems for remote tangible gameplay that support social connection. We investigate this topic through the design and evaluation of a prototype system for playing the board game Wavelength across two locations. First, we describe the design goals that informed our prototype: “Remote Wavelength”. Then, we discuss the results of a qualitative user study in which ten friend groups played Remote Wavelength. Our findings indicate that a synchronized, tangible gameboard benefits player engagement, communication, and awareness. Our results also illustrate the value of integration across communication and gameplay systems. We conclude by offering considerations for the design of both digital and remote tangible gameplay systems.
How Pricing and Ratings Affect Perceived Value of Digital Detox Apps

As the number of mobile apps has exploded over the last decade, different pricing models have emerged (e.g., free, paid, freemium). However, it is not clear how these models affect users’ perceptions of the value of apps that promote behavior change, such as digital detox apps, and what role social ratings play in this relationship. This paper investigates this issue using an experimental approach. The results of a controlled between-subjects experiment (N = 894) suggest that pricing models significantly influence the perceived value of digital detox apps. Digital detox apps using the paid model are perceived to be significantly less valuable than free and freemium apps. No significant difference has been found between free and freemium pricing models. Theoretical and practical implications are discussed.
The Halting problem: Video analysis of self-driving cars in traffic

Using publicly uploaded videos of the Waymo and Tesla FSD self-driving cars, this paper documents how self-driving vehicles still struggle with some basics of road interaction. To drive safely self-driving cars need to interact in traffic with other road users. Yet traffic is a complex, long established social domain. We focus on one core element of road interaction: when road users yield for each other. Yielding – such as by slowing down for others in traffic – involves communication between different road users to decide who will ‘go’ and who will ‘yield’. Videos of the Waymo and Tesla FSD self-driving cars show how these systems fail to both yield for others, as well as failing to go when yielded to. In discussion, we explore how these ‘problems’ illustrate both the complexity of designing for road interaction, but also how the space of physical machine/human social interactions more broadly can be designed for.
HapticPalmrest: Haptic Feedback through the Palm for the Laptop Keyboard

Programmable haptic feedback on touchscreen keyboards enriches user experiences but is hard to realize for physical keyboards because this requires individually augmenting each key with an actuator. As an alternative approach, we propose HapticPalmrest, where haptic feedback for a physical keyboard is provided to the palms. This is particularly feasible for a laptop environment, where users usually rest their palms while interacting with the keyboard. To verify the feasibility of the approach, we conducted two user studies. The first study showed that at least one palm was on palmrest for more than 90% of key interaction time. The second study showed a vibration power of 1.17 g (peak-to-peak) and a duration of 4 ms was sufficient for reliable perception of palmrest vibrations during keyboard interaction. We finally demonstrated the potential of such an approach by designing Dwell+ Key, an application that extends the function of each key by enabling timed dwelling operations.