Personality in Computational Advertising: A Benchmark

In the last decade, new ways of shopping online have increased the possibility of buying products and services more easily and faster than ever. In this new context, personality is a key determinant in the decision making of the consumer when shopping. A person’s buying choices are influenced by psychological factors like impulsiveness; indeed some consumers may be more susceptible to making impulse purchases than others. Since affective metadata are more closely related to the user’s experience than generic parameters, accurate predictions reveal important aspects of user’s attitudes, social life, including attitude of others and social identity. This work proposes a highly innovative research that uses a personality perspective to determine the unique associations among the consumer’s buying tendency and advert recommendations. In fact, the lack of a publicly available benchmark for computational advertising do not allow both the exploration of this intriguing research direction and the evaluation of recent algorithms. We present the ADS Dataset, a publicly available benchmark consisting of 300 real advertisements (i.e., Rich Media Ads, Image Ads, Text Ads) rated by 120 unacquainted individuals, enriched with Big-Five users’ personality factors and 1,200 personal users’ pictures

Count three for wear able computers

This paper is a postprint of a paper submitted to and accepted for publication in the Proceedings of the IEE Eurowearable 2003 Conference, and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library. A revised version of this paper was also published in Electronics Systems and Software, also subject to Institution of Engineering and Technology Copyright. The copy of record is also available at the IET Digital Library.A description of 'ubiquitous computer' is presented. Ubiquitous computers imply portable computers embedded into everyday objects, which would replace personal computers. Ubiquitous computers can be mapped into a three-tier scheme, differentiated by processor performance and flexibility of function. The power consumption of mobile devices is one of the most important design considerations. The size of a wearable system is often a design limitation

Affective Videogames and Modes of Affective Gaming: Assist Me, Challenge Me, Emote Me

In this paper we describe the fundamentals of affective gaming from a physiological point of view, covering some of the origins of the genre, how affective videogames operate and current conceptual and technological capabilities. We ground this overview of the ongoing research by taking an in-depth look at one of our own early biofeedback-based affective games. Based on our analysis of existing videogames and our own experience with affective videogames, we propose a new approach to game design based on several high-level design heuristics: assist me, challenge me and emote me (ACE), a series of gameplay "tweaks" made possible through affective videogames

A solution to fashion textile un-sustainability

Today, polarisation of the fashion textile industry has already begun as smart, intelligent and conscientious fashion emerges as a backlash to the experience of choice fatigue, poor quality, dumb design and greenwash. But the process, development and manufacture of fashion textiles is complex. And the demand, both customer and industry driven, for new integrated product policies,2 designed to minimise environmental impacts by looking at all phases of a product's life cycle, is problematic due to complexity and a lack of networking tools. This article explores these issues through the construct of the department store of the future

Biofeedback systems for stress reduction: Towards a Bright Future for a Revitalized Field

Stress has recently been baptized as the black death of the 21st century, which illustrates its threat to current health standards. This article proposes biofeedback systems as a means to reduce stress. A concise state-ofthe-art introduction on biofeedback systems is given. The field of mental health informatics is introduced. A compact state-of-the-art introduction on stress (reduction) is provided. A pragmatic solution for the pressing societal problem of illness due to chronic stress is provided in terms of closed loop biofeedback systems. A concise set of such biofeedback systems for stress reduction is presented. We end with the identification of several development phases and ethical concerns

Communication-Wear: User Feedback as Part of a Co-Design Process

Communication-Wear is a clothing concept that augments the mobile phone by enabling expressive messages to be exchanged remotely, by conveying a sense of touch, and presence. It proposes to synthesise conventions and cultures of fashion with those of mobile communications, where there are shared attributes in terms of communication and expression. Using garment prototypes as research probes as part of an on-going iterative co-design process, we endeavoured to mobilise participants’ tacit knowledge in order to gauge user perceptions on touch communication in a lab-based trial. The aim of this study was to determine whether established sensory associations people have with the tactile qualities of textiles could be used as signs and metaphors for experiences, moods, social interactions and gestures, related to interpersonal touch. The findings are used to inspire new design ideas for textile actuators for use in touch communication in successive iterations

Stress detection in computer users from keyboard and mouse dynamics

Detecting stress in computer users, while technically challenging, is of the utmost importance in the workplace, especially now that remote working scenarios are becoming ubiquitous. In this context, cost-effective, subject-independent systems are needed that can be embedded in consumer devices and classify users' stress in a reliable and unobtrusive fashion. Leveraging keyboard and mouse dynamics is particularly appealing in this context as it exploits readily available sensors. However, available studies are mostly performed in laboratory conditions, and there is a lack of on-field investigations in closer-to-real-world settings. In this study, keyboard and mouse data from 62 volunteers were experimentally collected in-the-wild using a purpose-built Web application, designed to induce stress by asking each subject to perform 8 computer tasks under different stressful conditions. The application of Multiple Instance Learning (MIL) to Random Forest (RF) classification allowed the devised system to successfully distinguish 3 stress-level classes from keyboard (76% accuracy) and mouse (63% accuracy) data. Classifiers were further evaluated via confusion matrix, precision, recall, and F1-score