Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Better Understanding of Player's Game Experience

Improving player's game experience has always been the common goal of video game practitioner. In order to get a better understanding of player's perception of game experience, we carry out experimental study for data collection and present game experience prediction model based on machine learning method. The model is trained on the proposed multi-modal database which contains: physiological modality, behavioral modality and meta-information to predict the player game experience in terms of difficulty, immersion and amusement. By investigating the model trained on separate and fusion feature sets, we show that physiological modality is effective. Moreover, better understanding is achieved with further analysis on the most relevant features in the behavioral and meta-information features set. We argue that combining the physiological modalities with behavioral and meta information can provide a better performance on the game experience prediction.
Collaborative Subspace Graph Hashing for Cross-modal Retrieval

Current hashing methods for cross-modal retrieval generally attempt to learn the separate modality-specific transformation matrices to embed multi-modality data into a latent common subspace, and usually ignore the fact that respecting the diversity of multi-modality features in the latent subspace could be beneficial for retrieval improvements. To this, we propose a collaborative subspace graph hashing method (CSGH) to perform a two-stage collaborative learning framework for cross-modal retrieval. Particularly, CSGH first embeds multi-modality data into separate latent subspaces through individual modality-specific transformation matrices, and then connects these latent subspaces to a common Hamming space through a shared transformation matrix. In this framework, CSGH considers the modality-specific neighborhood structure and the cross-modal correlation within multi-modality data through the Laplacian regularization and the graph based correlation constraint, respectively. To solve CSGH, we develop an alternative procedure to optimize it, and fortunately, each sub-problem of CSGH has the elegant analytical solution. Experiments of cross-modal retrieval on Wiki, NUS-WIDE, Flickr25K and Flickr1M datasets show the effectiveness of CSGH compared with the state-of-the-art cross-modal hashing methods.
Twenty Years of Creativity Research in Human-Computer Interaction: Current State and Future Directions

Creativity has been a growing topic in the ACM community since the 1990s; however, no clear overview of this trend has been offered. We present a thorough survey of 998 creativity-related publications in the ACM Digital Library collected using keyword search to determine prevailing approaches, topics, and characteristics of creativity- oriented Human-Computer Interaction (HCI) research. A selected sample based on yearly citations yielded 221 publications, which were analyzed using constant comparison analysis. We found that HCI is almost exclusively responsible for creativity-oriented publications; they focus on collaborative creativity rather than individual creativity; there is a general lack of definition of the term 'creativity'; empirically based contributions are prevalent; and many publications focus on new tools, often developed by researchers. On this basis, we present three implications for future creativity-oriented HCI research: develop and employ clearer definitions of creativity; go beyond in-vitro studies of novel tools; and move toward interdisciplinary research collaborations.
Learning to Plan with Portable Symbols

We present a framework for autonomously learning a portable symbolic representation that describes a collection of low-level continuous environments. We show that abstract representations can be learned in a task-independent space speciﬁc to the agent that, when combined with problem-speciﬁc information, can be used for planning. We demonstrate knowledge transfer in a video game domain where an agent learns portable, task-independent symbolic rules, and then learns instantiations of these rules on a per-task basis, reducing the number of samples required to learn a representation of a new task.
Ranking News-Quality Multimedia

News editors need to find the photos that best illustrate a news piece and fulfill news-media quality standards, while being pressed to also find the most recent photos of live events. Recently, it became common to use social-media content in the context of news media for its unique value in terms of immediacy and quality. Consequently, the amount of images to be considered and filtered through is now too much to be handled by a person. To aid the news editor in this process, we propose a framework designed to deliver high-quality, news-press type photos to the user. The framework, composed of two parts, is based on a ranking algorithm tuned to rank professional media highly and a visual SPAM detection module designed to filter-out low-quality media. The core ranking algorithm is leveraged by aesthetic, social and deep-learning semantic features. Evaluation showed that the proposed framework is effective at finding high-quality photos (true-positive rate) achieving a retrieval MAP of 64.5% and a classification precision of 70%.
Cognitive Emotion Regulation Strategies in Anxiety and Depression Understood as Types of Personality

The identification of distinctive and overlapping features of anxiety and depression remains an important scientific problem. Currently, the literature does not allow to determine stable similarities and differences in the use of cognitive emotion regulation strategies (CERS) in anxiety and depression, especially concerning the adaptive strategies. Consequently, the aim of this study was to identify the overlapping and distinctive patterns of CERS use in the recently proposed types of anxiety and depression in a general population. In this dimensional approach, types of anxiety and depression are considered as personality types and distinguished based on their specific structural composition and functional role (reactive or regulative) in stimulation processing. 1,632 participants from a representative sample completed the Anxiety and Depression Questionnaire (measuring the Arousal and Apprehension Types of anxiety and the Valence and Anhedonic Types of depression) and the Cognitive Emotion Regulation Questionnaire. Regression analyses were conducted with the affective types as predictors. The co-occurrence of the types was accounted for in order to examine their independent relationships with the CERS. We found that reactive arousal anxiety was not related to any strategies, while regulative apprehension anxiety primarily predicted the use of rumination, which is presumably related to the type's cognitive structural components. The strategy specific to reactive valence depression was other-blame (as predicted by the high negative affect in its structure), and the regulative, most structurally complex anhedonic depression predicted the use of the largest number of strategies, including the adaptive ones. The relationships between the types of depression and self-blame and refocus on planning were moderated by sex but the effects were small. These findings fit into the current trend of exploring the shared and specific features of anxiety and depression, which might facilitate their differentiation by identifying CERS that are characteristic for the specific types. This information can be used for supporting diagnosis and targeting selected strategies in therapy both in clinical and non-clinical populations.
What are we missing? Advantages of more than one viewpoint to estimate fish assemblages using baited video

Counting errors can bias assessments of species abundance and richness, which can affect assessments of stock structure, population structure and monitoring programmes. Many methods for studying ecology use fixed viewpoints (e.g. camera traps, underwater video), but there is little known about how this biases the data obtained. In the marine realm, most studies using baited underwater video, a common method for monitoring fish and nekton, have previously only assessed fishes using a single bait-facing viewpoint. To investigate the biases stemming from using fixed viewpoints, we added cameras to cover 360° views around the units. We found similar species richness for all observed viewpoints but the bait-facing viewpoint recorded the highest fish abundance. Sightings of infrequently seen and shy species increased with the additional cameras and the extra viewpoints allowed the abundance estimates of highly abundant schooling species to be up to 60% higher. We specifically recommend the use of additional cameras for studies focusing on shyer species or those particularly interested in increasing the sensitivity of the method by avoiding saturation in highly abundant species. Studies may also benefit from using additional cameras to focus observation on the downstream viewpoint.
Securing Named Data Networks: Challenges and the Way Forward

Despite decades of research on the Internet security, we constantly hear about mega data breaches and malware infections affecting hundreds of millions of hosts. The key reason is that the current threat model of the Internet relies on two assumptions that no longer hold true: (1) Web servers, hosting the content, are secure, (2) each Internet connection starts from the original content provider and terminates at the content consumer. Internet security is today merely patched on top of the TCP/IP protocol stack. In order to achieve comprehensive security for the Internet, we believe that a clean-slate approach must be adopted where a content based security model is employed. Named Data Networking (NDN) is a step in this direction which is envisioned to be the next generation Internet architecture based on a content centric communication model. NDN is currently being designed with security as a key requirement, and thus to support content integrity, authenticity, confidentiality and privacy. However, in order to meet such a requirement, one needs to overcome several challenges, especially in either large operational environments or resource constrained networks. In this paper, we explore the security challenges in achieving comprehensive content security in NDN and propose a research agenda to address some of the challenges.
Connecting Couture: Engaging With the Crafted Textile Interface in an Internet of Things Ecology

Many smart clothing concepts are appearing in research and industry, encompassing disparate disciplines, inhabiting many forms. However, few situated in the Internet of Things (IoT) ecology. Moreover, adding wireless data processing capability can extend their functionality. Highly stylized, speculative, wearable technology (wearables) garments with technologically augmented function (c.f.[1]) have been difficult to place into a broader social context as fashion.
Neuroimaging from Structure to Function

Introduction MRI has become the method of choice for diagnostic of all neurological diseases. Its strong soft tissue contrast allows exquisite depiction of the smallest lesions of any origin, and its recent improvement in scanning speed and resolution, due to the deployment of magnets working at 3T and above in most hospitals, has strongly reduced the number of failed examinations due to motion in uncooperative patients. As such, conventional MRI has found itself at the heart of the diagnostic in most neurological conditions, e.g.: In patients with multiple sclerosis, white matter lesions seen on conventional (T1w, T2w, FLAIR) images have been a hallmark of the disease since the 1980’s (1). In chronic stroke, lesions can be detected very clearly on T2w imaging (2). In dementia, repeated examinations demonstrating topical atrophy in the temporal lobe have recently become part of the new definition diagnostic criteria of the disease itself (3). But MRI can do much more than conventional imaging, and the increase in SNR provided by higher field strength has been harvested to start studying the very basic function of the organ. In particular, just around the turn of the 1990’s have appeared two very powerful methods to study tissue function: perfusion (4,5) and diffusion imaging (6). The former can be achieved both by injection of a contrast agent while continuously acquiring data over 60-90s, and has been used to clearly indicate disruption in the delivery of nutrient to ischemic areas, in acute ischemic stroke for example (7). In addition, the second method, made sensitive to the inherent random water motion in the tissue using pairs of strong, so-called “diffusion” gradients, has allowed highlighting cytotoxic oedema in the same patient population (8). The difference between dying tissue and salvable tissue, i.e. tissue presenting both a perfusion and diffusion deficit vs. perfusion only (9), has even been used in numerous clinical trials for neuroprotective agents in acute ischemic stroke (10). In this lecture, I will present the theoretical bases for each of these two methods, and how they are originally used in the brain.
How Does the Urban Environment Affect Health and Well-Being? A Systematic Review

In times of rapid urbanization, health and well-being of citizens is increasingly recognized as a challenge. A remarkable amount of research on relations between urban environments and health or well-being has been conducted. To get an insight about the existing measurements on both health combined with well-being, a systematic literature search was conducted using the databases PubMed and ScienceDirect including references until July 2017. To classify the references a conceptual model describing interrelationships between factors that may be associated with health-related urban well-being was used. The keywords “urban”, “well-being”, and “health” were applied together with factors described in the model. Twenty-four articles met the inclusion criteria. Of these, most studies focused on associations between urban green, health and well-being showing the great importance of green space usage in urban settings to promote better health and well-being. Health was mostly assessed by the General Health Questionnaire (GHQ-12); to measure well-being, the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) was mostly used. There are still only a few studies investigating the great complexity of urban health and well-being. More specifically, there is a lack in interdisciplinary approaches that highlight the complexity of urban structures and dynamics and their possible influence on urban health and well-being.
Design guidelines for location-based mobile games for learning

The objective of this course, is to introduce participants to location-based games and the challenges relating of designing such games for children. Key characteristics of this game genre are introduced first, followed by a design framework and a set of design guidelines. Examples of location-based games will be presented and typical design patterns as extracted from previous workshops will be discussed. Typical course participants include interaction designers, game designers and developers, practitioners and researchers interested in location-based games and mobile learning.
Interactive and Situated Guidelines to Help Users Design a Personal Desk that Fits Their Bodies

In this paper, we explored the application of human factor guidelines in personal fabrication. This is useful for several Do-It-Yourself (DIY) scenarios, including users adjusting workstation configurations or designing a desk to fit a single person. We identified a dependency map between the user's anthropometrics, ergonomic pose recommendations, and design dimensions. Based on this, we developed situated and interactive guidelines to assist users in design applications. We applied these guidelines in a Virtual Reality (VR) system that lets users customize their desk and provides real-time feedback and feedforward on pose and design. We evaluated the system with six participants, had each one design a personal desk, fabricated their desks, and let them work on their desks for four hours. The design and evaluation contribute to fabrication tools as it helped users be aware of their pose and ergonomic knowledge, and design for their bodies and needs.
Respectful Disconnection: Understanding Long Distance Family Relationships in a South Korean Context

We report upon the conduct and findings of an investigation into technology design for long-distance relationships (LDRs), where South Korean culture raises specific challenges. Through two qualitative studies we explore inter-generational LDRs from the perspective of South Korean students based in the United Kingdom. We identify and document the particular nuances within, and challenges that arise from, these relationships, before turning to the pragmatics of technology design for LDRs. Through both an extended diary study and interviews with students, we illustrate the impact of Korean familial obligations on intergenerational LDRs, and the mistrust and anxiety on both sides (parents and students) arising from limitations in communication channels. From our findings, we develop the notion of 'respectful disconnection' which we propose as a framework for designing interactions that appropriately support LDRs within this specific South Korean context.
Washing with the Wind: A Study of Scripting towards Sustainability

Within sustainable HCI research, we have witnessed a growing interest in studying interaction designs that support households to 'shift' energy usage to times when it is sustainably favourable. In this paper, we investigate shifting through a purposely provocative and scripted design, which challenges the idea that renewable electricity is an always-available resource for households to consume. To do so, we made electricity for washing laundry either free or not available. We conducted a detailed qualitative study with four families that experienced our intervention for a month. We present five themes that illustrate how families adapted, reflected, and formed new routines and expectations related to washing practices. We discuss the broader implications of combining scripting and provocation as a means to intervene, disrupt and understand energy consuming practices within the home.
MemoryPin: Turning Digitally Co-Present Moments into Tangible Memory Keepsakes

MemoryPin is a digital keepsake device that-like a photo album-provides tangible access to memories formed during online social interactions. By tangible, we mean that we designed these keepsake physical forms to afford distinctive storage and interactivity for selected digital memories created during an individual's everyday social media experience with others. Through a series of iterative design inquiries, we explored new forms and possibilities for digital-content-bearing artifacts and built our initial prototype in this work in progress.
A resource-rational analysis of human planning

People’s cognitive strategies are jointly shaped by function and computational constraints. Resource-rational analysis leverages these constraints to derive rational models of people’s cognitive strategies from the assumption that people make rational use of limited cognitive resources. We present a resource-rational analysis of planning and evaluate its predictions in a newly developed process tracing paradigm. In Experiment 1, we find that a resource-rational planning strategy predicts the process by which people plan more accurately than previous models of planning. Furthermore, in Experiment 2, we find that it also captures how people’s planning strategies adapt to the structure of the environment. In addition, our approach allows us to quantify for the first time how close people’s planning strategies are to being resource-rational and to characterize in which ways they conform to and deviate from optimal planning.
Traffico: A Tangible Timetable Delivering Transportation Information between Schedules

We introduce Traffico, a tangible timetable representing dematerialized schedule and transportation information. It delivers a user's schedules in chronological order along with transportation information between schedules. Placed on the user's desk, Traffico suggests required transportation times using four options-walking, bicycling, bussing, and driving a car-and through an e-ink display. To investigate the advantages that Traffico provides to users, we conducted an in-field study of 10 participants over five days. The results revealed that Traffico supports the planning of moving times in a day through displaying transportation options on each schedule. We also found that Traffico provides better schedule reminders with event notifications in a sequential order, along with rotating interaction for checking events. Through this type of tangible interaction, Traffico provides possibilities to reflect dematerialized digital information into a physical form and to adopt a new way of scheduling and handling time.
Naive, captive long-tailed macaques (Macaca fascicularis fascicularis) fail to individually and socially learn pound-hammering, a tool-use behaviour

A subspecies of long-tailed macaques (Macaca fascicularis aurea; Mfa) has been reported to use stone tools and a specific technique to process nuts in Southeast Asia, a behaviour known as ‘pound-hammering’. The aim of this study was to examine the development of pound-hammering in long-tailed macaques: whether this behavioural form can be individually learnt or whether it has to rely on some forms of social learning. Given the absence of Mfa from captivity, long-tailed macaques of a highly related subspecies (Macaca fascicularis fascicularis; Mff) were experimentally tested by providing them with the ecological materials necessary to show pound-hammering. A baseline was first carried out to observe whether pound-hammering would emerge spontaneously without social information. As this was not the case, different degrees of social information, culminating in a full demonstration of the behaviour, were provided. None of the subjects (n = 31) showed pound-hammering in any of the individual or social learning conditions. Although these data do not support the hypothesis that individual learning underlies this behaviour, no evidence was found that (at least) Mff learn pound-hammering socially either. We propose that other—potentially interacting—factors may determine whether this behaviour emerges in the various subspecies of long-tailed macaques, and provide a novel methodology to test the role of social and individual learning in the development of animal tool-use.
Independent Key Distribution Protocols for Broadcast Authentication

Broadcast authentication is an important problem in several network settings such as wireless sensor networks and ad-hoc networks. We focus on the problem of independent key distribution protocols, which use efficient symmetric key signatures in distributed systems to permit (local) broadcast authentication. We focus on five types of communication graphs: (1) star, (2) acyclic, (3) planar, (4) complete bipartite, and (5) fully connected graphs. A star graph is the simplest network topology where a central node is transmitting authenticated broadcast messages to several satellite nodes. For star graphs, we show that as n, the number of satellite nodes in the star network, tends to infinity, it suffices to maintain logn+1/2loglogn + 1 keys at the center node, but logn+1/2loglogn keys do not suffice. We establish that this is the optimal lower bound on the number of keys for a star graph. Building on this result, we describe storage efficient key distribution for acyclic, planar, and complete bipartite graphs, when compared to existing key distribution schemes. We extend our scheme for fully connected graphs and show that it is sufficient to store O(c log2 N) keys per node where c<1. We perform a detailed analysis of collusion resistance of our protocols and show the trade-offs against internal and external attacks depending on the size of storage. Finally, we demonstrate the practical applicability of our protocols for wireless sensor networks.