Searching through vast libraries of sound samples can be a daunting and time-consuming task. Modern audio sample browsers use mappings between acoustic properties and visual attributes to visually differentiate displayed items. There are few studies focused on how well these mappings help users search for a specific sample. We propose new methods for generating textural labels and positioning samples

Peer review is the backbone of academia and humans constitute a cornerstone of this process, being responsible for reviewing papers and making the final acceptance/rejection decisions. Given that human decision making is known to be susceptible to various cognitive biases, it is important to understand which (if any) biases are present in the peer-review process and design the pipeline such that the

Conference peer review constitutes a human-computation process whose importance cannot be overstated: not only it identifies the best submissions for acceptance, but, ultimately, it impacts the future of the whole research area by promoting some ideas and restraining others. A surge in the number of submissions received by leading AI conferences has challenged the sustainability of the review process

Smartphone overuse has many negative effects on human beings. The function App Limits in our phones, which belongs to behavior reinforcement strategies for overcoming problematic smartphone overuse, constrains users by shutting them completely out of an app after a certain period of time. While it has the effectiveness to some extent, lacking procedural detection of problematic behavior always brings

As space exploration efforts shift to deep space missions, new challenges emerge regarding astronaut communication and task completion. While the round trip propagation delay for lunar communications is 2.6 seconds, the time delay increases to nearly 22 minutes for Mars missions. This creates a need for astronaut independence from earth-based assistance, and places greater significance upon the limited

Nowadays, with the rise of Internet access and mobile devices around the globe, more people are using social networks for collaboration and receiving real-time information. Twitter, the microblogging that is becoming a critical source of communication and news propagation, has grabbed the attention of spammers to distract users. So far, researchers have introduced various defense techniques to detect

Modern machine learning and computer science conferences are experiencing a surge in the number of submissions that challenges the quality of peer review as the number of competent reviewers is growing at a much slower rate. To curb this trend and reduce the burden on reviewers, several conferences have started encouraging or even requiring authors to declare the previous submission history of their

We suggest a low cost, non invasive healthcare system that measures haemoglobin levels in patients and can be used as a preliminary diagnostic test for anaemia. A combination of image processing, machine learning and deep learning techniques are employed to develop predictive models to measure haemoglobin levels. This is achieved through the color analysis of the fingernail beds, palpebral conjunctiva

Remote services and applications that users access via their local clients (laptops or desktops) usually assume that, following a successful user authentication at the beginning of the session, all subsequent communication reflects the user's intent. However, this is not true if the adversary gains control of the client and can therefore manipulate what the user sees and what is sent to the remote

Wearable devices are a trending topic in both commercial and academic areas. Increasing demand for innovation has led to increased research and new products, addressing new challenges and creating profitable opportunities. However, despite a number of reviews and surveys on wearable computing, a study outlining how this area has recently evolved, which provides a broad and objective view of the main

We present a methodological framework aiming at the support of HCI practitioners and researchers in selecting and applying the most appropriate combination of HCI methods for particular problems. We highlight the need for a clear and effective overview of methods and provide further discussion on possible extensions that can support recent trends and needs, such as the focus on specific application

KG (Knowledge Generation) and understanding have traditionally been a Human-centric activity. KE (Knowledge Engineering) and KM (Knowledge Management) have tried to augment human knowledge on two separate planes: the first deals with machine interpretation of knowledge while the later explore interactions in human networks for KG and understanding. However, both remain computer-centric. Crowdsourced

A BCI user awareness of an error is associated with a cortical signature named error-related potential (ErrP). The incorporation of ErrPs' detection in BCIs can improve BCIs' performance. This work is three-folded. First, we investigate if an ErrP classifier is transferable from able-bodied participants to participants with spinal cord injury (SCI). Second, we test this generic ErrP classifier with

Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional---consisting of curves varying over a continuum, which is time in this case. When analyzing continuous data, functional data analysis (FDA) provides substantial benefits, such as the ability to study the derivatives and to restrict the ordering of data. However, continuous data inherently has

This workshop paper reports on an ongoing mixed-methods study on the two arguably most popular social network sites, Facebook and Twitter, for the same users. The overarching goal of the study is to shed light into the nuances of social media selection and cross-platform use by combining survey data about participants' motivations with usage data collected via API extraction. We describe the set-up

This paper examines the community formed by the Twitter users that used a city-level hashtag. In particular, we provide a network perspective of the city of Athens, Greece, as demonstrated by the analysis and visualization of the relevant Twitter hashtag data, in order to present both an overview and deeper insights at the microblogging practices of this geographic local network. Further analysis suggests

Due to the boom in technical compute in the last few years, the world has seen massive advances in artificially intelligent systems solving diverse real-world problems. But a major roadblock in the ubiquitous acceptance of these models is their enormous computational complexity and memory footprint. Hence efficient architectures and training techniques are required for deployment on extremely low resource

This chapter presents an overview of Interactive Machine Learning (IML) techniques applied to the analysis and design of musical gestures. We go through the main challenges and needs related to capturing, analysing, and applying IML techniques to human bodily gestures with the purpose of performing with sound synthesis systems. We discuss how different algorithms may be used to accomplish different

The game industry has long been troubled by malicious activities utilizing game bots. The game bots disturb other game players and destroy the environmental system of the games. For these reasons, the game industry put their best efforts to detect the game bots among players' characters using the learning-based detections. However, one problem with the detection methodologies is that they do not provide

Pulmonary diseases impact millions of lives globally and annually. The recent outbreak of the pandemic of the COVID-19, a novel pulmonary infection, has more than ever brought the attention of the research community to the machine-aided diagnosis of respiratory problems. This paper is thus an effort to exploit machine learning for classification of respiratory problems and proposes a framework that

Since 2016, the amount of academic research with the keyword "misinformation" has more than doubled [2]. This research often focuses on article headlines shown in artificial testing environments, yet misinformation largely spreads through images and video posts shared in highly-personalized platform contexts. A foundation of qualitative research is necessary to begin filling this gap to ensure platforms'

Internet Users' Information Privacy Concerns (IUIPC-10) is one of the most endorsed privacy concern scales. It is widely used in the evaluation of human factors of PETs and the investigation of the privacy paradox. Even though its predecessor Concern For Information Privacy (CFIP) has been evaluated independently and the instrument itself seen some scrutiny, we are still missing a dedicated confirmation

This paper contributes a novel visualization method, Missingness Glyph, for analysis and exploration of missing values in data. Missing values are a common challenge in most data generating domains and may cause a range of analysis issues. Missingness in data may indicate potential problems in data collection and pre-processing, or highlight important data characteristics. While the development and

In this paper we address feedback strategies for an autonomous virtual trainer. First, a pilot study was conducted to identify and specify feedback strategies for assisting participants in performing a given task. The task involved sorting virtual cubes according to areas of countries displayed on them. Two feedback strategies were specified. The first provides correctness feedback by fully correcting

What does the age of participation look like from the perspective of a museum visitor? Arguably, the concept of participative experiences is already so deeply ingrained in our culture that we may not even think about it as participation. Museum visitors engage in a number of activities, of which observing the exhibits is only one part. Since most visitors come to the museum together with someone else

We reflect on two museum visiting experiences that adopted the strategy of interpersonalization in which one visitor creates an experience for another. In the Gift app, visitors create personal mini-tours for specific others. In Never let me go, one visitor controls the experience of another by sending them remote instructions as they follow them around the museum. By reflecting on the design of these

Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. Unfortunately, medical staff does not always follow the World Health Organization (WHO) hand washing guidelines in their everyday work. To this end, we present neural networks for automatically recognizing the different washing movements defined by the WHO. We train the neural network on a part of a

This paper presents a research through design exploration using tangible interactions in order to seamlessly integrate technology in a historical house museum. The study addresses a longstanding concern in museum exhibition design that interactive technologies may distract from the artifacts on display. Through an iterative design process including user studies, a co-creation workshop with museum staff

In this study, the German "Corona-Warn-App" of the German Federal Government and the Robert-Koch-Institute is examined by means of a non-representative online survey with 1482 participants for reasons of use and non-use. The study provides insights into user behavior with the app during the Corona pandemic, highlights the topic of data protection and how the app is used in general. Our results show

Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in recent years. However, similar to other deep neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), GNNs behave like a black box with their details hidden from model developers and users

The high penetration of transportation electrification and its associated charging requirements magnify the interdependency of the transportation and power distribution systems. The emergent interdependency requires that system operators fully understand the status of both systems. To this end, a visualization tool is presented to illustrate the interdependency of battery bus transit and power distribution

The use of automatic grading tools has become nearly ubiquitous in large undergraduate programming courses, and recent work has focused on improving the quality of automatically generated feedback. However, there is a relative lack of data directly comparing student outcomes when receiving computer-generated feedback and human-written feedback. This paper addresses this gap by splitting one 90-student

With humans increasingly serving as computational elements in distributed information processing systems and in consideration of the profit-driven motives and potential inequities that might accompany the emerging thinking economy[1], we recognize the need for establishing a set of related ethics to ensure the fair treatment and wellbeing of online cognitive laborers and the conscientious use of the

Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotated scans for good performance. We investigate whether crowdsourcing can be used to gather airway annotations. We generate image slices at known locations

A diverse team of engineers, artists, and algorithms, collaborated to create songs for SophiaPop, via various neural networks, robotics technologies, and artistic tools, and animated the results on Sophia the Robot, a robotic celebrity and animated character. Sophia is a platform for arts, research, and other uses. To advance the art and technology of Sophia, we combine various AI with a fictional

Recent years have witnessed the rapid progress of perception algorithms on top of LiDAR, a widely adopted sensor for autonomous driving systems. These LiDAR-based solutions are typically data hungry, requiring a large amount of data to be labeled for training and evaluation. However, annotating this kind of data is very challenging due to the sparsity and irregularity of point clouds and more complex

Aerial vehicles are revolutionizing the way film-makers can capture shots of actors by composing novel aerial and dynamic viewpoints. However, despite great advancements in autonomous flight technology, generating expressive camera behaviors is still a challenge and requires non-technical users to edit a large number of unintuitive control parameters. In this work we develop a data-driven framework

Mixed-initiative visual analytics systems incorporate well-established design principles that improve users' abilities to solve problems. As these systems consider whether to take initiative towards achieving user goals, many current systems address the potential for cognitive bias in human initiatives statically, relying on fixed initiatives they can take instead of identifying, communicating and

Temporal Blind Source Separation (TBSS) is used to obtain the true, underlying processes from noisy temporal multivariate data, such as electrocardiograms. While these algorithms are widely used, the involved tasks are not well supported in current visualization tools, which offer only text-based interactions and static images. Analysts are limited in analyzing and comparing obtained results, which

In this work we study the use of moderate deviation functions to measure similarity and dissimilarity among a set of given interval-valued data. To do so, we introduce the notion of interval-valued moderate deviation function and we study in particular those interval-valued moderate deviation functions which preserve the width of the input intervals. Then, we study how to apply these functions to construct

Interest in and development of touchless gestural interfaces has recently exploded, fueled by the diffusion of both commercial midair gesture platforms and public interactive displays. This paper focuses on an application based on Microsoft Kinect that allows students to browse a university website, hosted on a public display, through simple gestures. We present two empirical evaluations where we evaluated

Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read

The performance of a task-completion dialogue agent usually affects the user experience: when the conversation system yields an unreasonable response, users may feel dissatisfied. Besides, early termination often occurs in disappointing conversations. However, existing off-the-shelf user simulators generally assume an ideal and cooperative user, which is somewhat different from a real user, and inevitably

One of the main weaknesses of current chatbots or dialogue systems is that they do not learn online during conversations after they are deployed. This is a major loss of opportunity. Clearly, each human user has a great deal of knowledge about the world that may be useful to others. If a chatbot can learn from their users during chatting, it will greatly expand its knowledge base and serve its users

Driven by digitization in society and industry, automating behavior in an autonomous way substantially alters industrial value chains in the smart service world. As processes are enhanced with sensor and actuator technology, they become digitally interconnected and merge into an Internet of Things (IoT) to form cyber-physical systems (CPS). Using these automated systems, enterprises can improve the

Game feel design is the intentional design of the affective impact of moment-to-moment interaction with games. In this paper we survey academic research and publications by practitioners to give a complete overview of the state of research concerning this aspect of game design, including context from related areas. We analysed over 200 sources and categorised their content according to the design purpose

Modeling 3D objects in domains like Computer Aided Design (CAD) is time-consuming and comes with a steep learning curve needed to master the design process as well as tool complexities. In order to simplify the modeling process, we designed and implemented a prototypical system that leverages the strengths of Virtual Reality (VR) hand gesture recognition in combination with the expressiveness of a

Event sequence data is increasingly available in various application domains, such as business process management, software engineering, or medical pathways. Processes in these domains are typically represented as process diagrams or flow charts. So far, various techniques have been developed for automatically generating such diagrams from event sequence data. An open challenge is the visual analysis

We present three patterns for computer-mediated interaction which we discovered during the design and development of a platform for remote teaching and learning of kanji, the Chinese characters used in written Japanese. Our aim in developing this system was to provide a basis for embodiment in remote interaction, and in particular to support the experience of empathy by both teacher and student. From

Using open-source and creative coding frameworks, a teamof artist-engineers from Portland Community College work-ing with artists who experience Intellectual/Developmentaldisabilities prototyped an ensemble of adapted instrumentsand synthesizers that facilitate real-time in-key collabora-tion. The instruments employ a variety of sensors, send-ing the resulting musical controls to software sound gener-ators

Software development requires understanding of users, user needs, user tasks and context in which they are operating. These skills are familiar to entrepreneurs, product managers, and marketing experts. However, our teaching experience suggests that students generally find these topics less attractive as they perceive them to be far too theoretical and thus, not as useful. During the years of teaching

The deployment of reinforcement learning (RL) in the real world comes with challenges in calibrating user trust and expectations. As a step toward developing RL systems that are able to communicate their competencies, we present a method of generating human-interpretable abstract behavior models that identify the experiential conditions leading to different task execution strategies and outcomes. Our

The identification and removal/replacement of protected information from social media data is an understudied problem, despite being desirable from an ethical and legal perspective. This paper identifies types of potentially directly identifiable information (inspired by protected health information in clinical texts) contained in tweets that may be readily removed using off-the-shelf algorithms, introduces

JITAI is an emerging technique with great potential to support health behavior by providing the right type and amount of support at the right time. A crucial aspect of JITAIs is properly timing the delivery of interventions, to ensure that a user is receptive and ready to process and use the support provided. Some prior works have explored the association of context and some user-specific traits on

We present ABC-Net, a novel semi-supervised multimodal GAN framework to detect engagement levels in video conversations based on psychology literature. We use three constructs: behavioral, cognitive, and affective engagement, to extract various features that can effectively capture engagement levels. We feed these features to our semi-supervised GAN network that does regression using these latent representations

This paper studies conspiracy and debunking narratives about COVID-19 origination on a major Chinese social media platform, Weibo, from January to April 2020. Popular conspiracies about COVID-19 on Weibo, including that the virus is human-synthesized or a bioweapon, differ substantially from those in the US. They attribute more responsibility to the US than to China, especially following Sino-US confrontations

We propose a model-agnostic approach for mitigating the prediction bias of a black-box decision-maker, and in particular, a human decision-maker. Our method detects in the feature space where the black-box decision-maker is biased and replaces it with a few short decision rules, acting as a "fair surrogate". The rule-based surrogate model is trained under two objectives, predictive performance and

We present a new approach to dialogue specification for Virtual Personal Assistants (VPAs) based on so-called dialogue workflow graphs, with several demonstrated advantages over current ontology-based methods. Our new dialogue specification language (DSL) enables customers to more easily participate in the VPA modeling process due to a user-friendly modeling framework. Resulting models are also significantly

This paper describes a Google Educator funded project devoted to the training of teachers (primary and secondary school) through an e-learning platform that will introduce them to educational robotics using Wolly, a social, educational and affective robot.

We introduce a Virtual Reality (VR) one-on-one tutoring system to support anatomy education. A student uses a fully immersive VR headset to explore the anatomy of the base of the human skull. A teacher guides the student by using the semi-immersive zSpace. Both systems are connected via network and each action is synchronized between both systems. The teacher is provided with various features to direct