Toward a Robust Diversity-Based Model to Detect Changes of Context

Being able to automatically and quickly understand the user context during a session is a main issue for recommender systems. As a first step toward achieving that goal, we propose a model that observes in real time the diversity brought by each item relatively to a short sequence of consultations, corresponding to the recent user history. Our model has a complexity in constant time, and is generic since it can apply to any type of items within an online service (e.g. profiles, products, music tracks) and any application domain (e-commerce, social network, music streaming), as long as we have partial item descriptions. The observation of the diversity level over time allows us to detect implicit changes. In the long term, we plan to characterize the context, i.e. to find common features among a contiguous sub-sequence of items between two changes of context determined by our model. This will allow us to make context-aware and privacy-preserving recommendations, to explain them to users. As this is an ongoing research, the first step consists here in studying the robustness of our model while detecting changes of context. In order to do so, we use a music corpus of 100 users and more than 210,000 consultations (number of songs played in the global history). We validate the relevancy of our detections by finding connections between changes of context and events, such as ends of session. Of course, these events are a subset of the possible changes of context, since there might be several contexts within a session. We altered the quality of our corpus in several manners, so as to test the performances of our model when confronted with sparsity and different types of items. The results show that our model is robust and constitutes a promising approach.Comment: 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2015), Nov 2015, Vietri sul Mare, Ital

Using System Analysis and Personas for e-Health Interaction Design

Today, designers obtain more central roles in product and service development (Perks, Cooper, & Jones, 2005). They have to deal with increasingly complicated problems, like integrating the needs of various stakeholders while taking care about social, ethical and ecological consequences of their designs. To deal with this demanding design situation, they need to apply new methods to organize the available information and to negotiate the stakeholder’s perspectives. This paper describes how systems analysis supports the design process in a complex environment. In a case study, we demonstrate how this method enables designers to describe user requirements for complex design environments while considering the perspectives of various stakeholders. We present a design research project applying cybernetic systems analysis using the software ''System-Tools'' (Vester, 2002). Results from the analysis were taken to inform the design of an electronic patient record (EPR), considering the particularities of the German health care system. Based on the analysis, we developed a set of requirements for every stakeholder group, detailing the patients' perspective with persona descriptions. We then picked a main persona as reference for the EPR design. We describe the resulting design sketch and discuss the value of cybernetic systems analysis as a tool to deal with complex social environments. The result shows how the method helps designers to structure and organize information about the context and identify fruitful intervention opportunities for design. Keywords: E-Health; System Analysis, Cybernetics; Personas.</p

Toward a model of computational attention based on expressive behavior: applications to cultural heritage scenarios

Our project goals consisted in the development of attention-based analysis of human expressive behavior and the implementation of real-time algorithm in EyesWeb XMI in order to improve naturalness of human-computer interaction and context-based monitoring of human behavior. To this aim, perceptual-model that mimic human attentional processes was developed for expressivity analysis and modeled by entropy. Museum scenarios were selected as an ecological test-bed to elaborate three experiments that focus on visitor profiling and visitors flow regulation

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices

Characterizing Natural User Interface with Wearable Smart Watches

Background - The emergence of new interaction paradigms makes the use of technology inrealizing the users??? natural ways of exploring the real world the ultimate goal of designers today.Research on interactive and immersive technologies for user interface design is still a challenging chore for engineers and scientists when it comes to designing natural interaction for wearable smart devices. To address the challenge, our study aims to develop guidelines for design practitioners in designing wearable smart watches that could offer natural user experiences. Methods - To better understand natural user experiences with smart watches, an extensive literature review was conducted. A quantitative survey with 80 participants was conducted, of which the focus was on the expected functions of smart watches. Based on the survey results, we selected eight participants in terms of technology familiarity. To achieve the objectives of our research, three studies were conducted: a design workshop (Study 1), a cultural probe (Study 2), and a focus group interview (Study 3). The design workshop was created to figure out the needs and wishes people have forsmart watches. In the cultural probe, the focus was on figuring out natural interactions with smart watches. Finally, the focus group interview aimed to gain more insights from the results of the cultural probe in terms of natural user interaction with particular functions. Results - To address the needs and wishes of the users toward wearable smartwatches, we made a subdivision into three categories, such as functions, input measures, and notification (feedback) methods. According to the results, participants wanted weather notification, health monitoring, and identification as expected functions. Regarding the methodof input, voice command and touch screen were preferred. In order to get feedback, most of the participantswanted vibrations, particularly as a reaction tocompleting the commands or inputs. There was also a suggestion to customize their smart watch. For example, users can select the functions and build their own command system, and even choose the notificationmethods. Considering natural user interface with respect to functions (weather, answering a call, navigation, health monitoring, taking a picture and messaging), specific natural user interfaces were mentioned for particular functions. Conclusions - Throughout the study, people???s needs and wishes and their perceptions about natural interaction were identified and the characteristics of natural user interfacesweredetermined. Based on the results, tenperceptions were specifically defined to provide a better understanding of smart watches in terms of natural interaction: user affinity of form, awareness by familiarity, reality correspondence, behavioral extension, purpose orientation, easiness of performance, timeliness, routine acceptance, generality, and rule of thumb. In addition to that, natural user interfaces were categorized into five groups: user familiarity, realistic interaction, accomplishment assistance, contextual appropriateness, and social awareness. In this study,we tried to identify what constitutes anatural interaction and how it should be created. The limitations and further study are discussed at the end.ope

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Seamless Interactions Between Humans and Mobility Systems

As mobility systems, including vehicles and roadside infrastructure, enter a period of rapid and profound change, it is important to enhance interactions between people and mobility systems. Seamless human—mobility system interactions can promote widespread deployment of engaging applications, which are crucial for driving safety and efficiency. The ever-increasing penetration rate of ubiquitous computing devices, such as smartphones and wearable devices, can facilitate realization of this goal. Although researchers and developers have attempted to adapt ubiquitous sensors for mobility applications (e.g., navigation apps), these solutions often suffer from limited usability and can be risk-prone. The root causes of these limitations include the low sensing modality and limited computational power available in ubiquitous computing devices. We address these challenges by developing and demonstrating that novel sensing techniques and machine learning can be applied to extract essential, safety-critical information from drivers natural driving behavior, even actions as subtle as steering maneuvers (e.g., left-/righthand turns and lane changes). We first show how ubiquitous sensors can be used to detect steering maneuvers regardless of disturbances to sensing devices. Next, by focusing on turning maneuvers, we characterize drivers driving patterns using a quantifiable metric. Then, we demonstrate how microscopic analyses of crowdsourced ubiquitous sensory data can be used to infer critical macroscopic contextual information, such as risks present at road intersections. Finally, we use ubiquitous sensors to profile a driver’s behavioral patterns on a large scale; such sensors are found to be essential to the analysis and improvement of drivers driving behavior.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163127/1/chendy_1.pd

Towards a Unified Framework for Media Capacity Characterization: Inferences from Critical Analysis of Media Capacity Theories, Buzzwords and Web History

As the Web enters its third decade of existence, I draw attention to the need to better understand the Web as a potential reference case for how an information system transforms through incremental innovations, with particular focus on the Web’s advancement as a communication media platform. As a necessary research step in this quest, I critically examine whether one can use existing media capacity theories and media-related buzzwords (such as rich media, multimedia, hypermedia, social media) to characterize Web innovations as media. I examine and clarify these buzzwords’ origins, meanings, and relationship with media capacity theories. I also elucidate discrepancies between them. Via inductive reasoning, I synthesize three media capacity dimensions (sensibility support, interactivity support and logistical support) as potential framework for objective media characterization. Each dimension could metamorphize into individual theories or one theory (e.g., sensibility interactivity and logistical support theory (SILST)). I present these dimensions’ indicators and demonstrate three-dimensional typology of Web innovation milestones anchored on the three dimensions—a step forward in substantiating the framework’s applicability to media capacity characterization