GIS and urban data science

With the emergence of new forms of geospatial/urban big data and advanced spatial analytics and machine learning methods, new patterns and phenomena can be explored and discovered in our cities and societies. In this special issue, we presented an overview of nine studies to understand how to use urban data science and GIS in healthcare services, hospitality and safety, transportation and mobility, economy, urban planning, higher education, and natural disasters, spreading across developed countries in North America and Europe, as well as Global South areas in Asia and the Middle East. The embrace of diverse geo-computational methods in this special issue brings forward an outlook to future GIS and Urban Data Science towards more advanced computational capability, global vision and urban-focused research

Gaze Detection and Analysis for Initiating Joint Activity in Industrial Human-Robot Collaboration

Collaborative robots (cobots) are widely used in industrial applications, yet extensive research is still needed to enhance human-robot collaborations and operator experience. A potential approach to improve the collaboration experience involves adapting cobot behavior based on natural cues from the operator. Inspired by the literature on human-human interactions, we conducted a wizard-of-oz study to examine whether a gaze towards the cobot can serve as a trigger for initiating joint activities in collaborative sessions. In this study, 37 participants engaged in an assembly task while their gaze behavior was analyzed. We employ a gaze-based attention recognition model to identify when the participants look at the cobot. Our results indicate that in most cases (84.88\%), the joint activity is preceded by a gaze towards the cobot. Furthermore, during the entire assembly cycle, the participants tend to look at the cobot around the time of the joint activity. To the best of our knowledge, this is the first study to analyze the natural gaze behavior of participants working on a joint activity with a robot during a collaborative assembly task.Comment: First draft for a paper submitted to Frontiers in Robotics and A

Hijab Discourse in Indonesia: The Battle of Meaning Between Sharia and Culture in Public Space

The phenomenon of wearing hijab is not only a reality in Indonesia but also in the Muslim world and even the world in general such as Europe, America, and Australia. This paper aims to examine the discourse on hijab between Islamic law (sharia) and culture. This is a normative study using legal pluralism as an approach.  This paper concludes that Indonesia has the largest Muslim population in the world, and the wearing of hijab has a long history until contemporary times. Currently, the phenomenon of hijra among Muslims is also on the rise, the hijab is then formalized into educational institutions and offices which not a few cause problems that sometimes arise discriminatory actions to those who do not want to use it. Another phenomenon about the use of hijab occurs in the realm of law. A woman dealing with legal issues, when presented at a press conference, some public figures wear hijab. Even in the judicial room, women who usually do not wear headscarves also change their appearance by wearing headscarves. Likewise, in a political campaign, women who usually do not wear headscarves, appear in hijab suits in public. Of these various phenomena, the hijab as a marker symbol has meaning, namely as a form of religious obedience, the identity of a Muslim woman, discipline in public spaces, and camouflage piety. From the perspective of legal pluralism, hijab is an articulation of strictness to the commandments of sharia as well as an inseparable part of the culture that has become a living practice in Indonesian society

Feedback Control of Human Stress with Music Modulation

Mental stress has known detrimental effects on human health, however few algorithmic methods of reducing mental stress have been widely explored. While the act of listening to music has been shown to have beneficial effects for stress reduction, and furthermore, audio players have been designed to selectively choose music and other inputs with the intent of stress reduction, limited work has been conducted for real-time stress reduction with feedback control using physiological input signals such as heart rate or Heart Rate Variability (HRV). This thesis proposes a feedback controller that uses HRV signals from wearable sensors to perform real-time (< 1 second) modulations to music through tempo changes with the goal to regulate and reduce stress levels. A standardized, stress inducing test based on the popular Stroop test is also introduced, which has been shown to induce acute stress in subjects and can be used as a testing benchmark for controller design. Ultimately, a controller is presented that when used is not only able to maintain stress levels during stress-inducing inputs to a human but even provides de-stressing effects beyond baseline performance.No embargoAcademic Major: Electrical and Computer Engineerin

Investigating Correlations of Automatically Extracted Multimodal Features and Lecture Video Quality

Ranking and recommendation of multimedia content such as videos is usually realized with respect to the relevance to a user query. However, for lecture videos and MOOCs (Massive Open Online Courses) it is not only required to retrieve relevant videos, but particularly to find lecture videos of high quality that facilitate learning, for instance, independent of the video's or speaker's popularity. Thus, metadata about a lecture video's quality are crucial features for learning contexts, e.g., lecture video recommendation in search as learning scenarios. In this paper, we investigate whether automatically extracted features are correlated to quality aspects of a video. A set of scholarly videos from a Mass Open Online Course (MOOC) is analyzed regarding audio, linguistic, and visual features. Furthermore, a set of cross-modal features is proposed which are derived by combining transcripts, audio, video, and slide content. A user study is conducted to investigate the correlations between the automatically collected features and human ratings of quality aspects of a lecture video. Finally, the impact of our features on the knowledge gain of the participants is discussed

A case study on the investigation of reasoning skills in geometry

The aim of this study is to evaluate the reasoning skills in geometry-related subjects of six 8th Grade students. The study data were obtained at the end of the 2011-2012 spring period in a public elementary school. The study uses a case study with qualitative research techniques to investigate how students use reasoning skills. In this study, six geometry problems were used to collect the study data. The students were asked to think aloud when solving the  problems so as to be better able to explain their thoughts. From the data obtained, it was identified that the processes involved when demonstrating reasoning skills showed a number of differences.Keywords: geometry, reasoning, reasoning skills, teaching geometr

More than buttons on controllers: engaging social interactions in narrative VR games through social attitudes detection

People can understand how human interaction unfolds and can pinpoint social attitudes such as showing interest or social engagement with a conversational partner. However, summarising this with a set of rules is difficult, as our judgement is sometimes subtle and subconscious. Hence, it is challenging to program agents or non-player characters (NPCs) to react towards social signals appropriately, which is important for immersive narrative games in Virtual Reality (VR). We present a collaborative work between two game studios (Maze Theory and Dream Reality Interactive) and academia to develop an immersive machine learning (ML) pipeline for detecting social engagement. Here we introduce the motivation and the methodology of the immersive ML pipeline, then we cover the motivation for the industry-academia collaboration, how it progressed, the implications of joined work on the industry and reflective insights on the collaboration. Overall, we highlight the industry-academia collaborative work on an immersive ML pipeline for detecting social engagement. We demonstrate how creatives could use ML and VR to expand their ability to design more engaging commercial games