A personalized and context-aware news offer for mobile devices

For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer

Classifying urban public spaces according to their soundscape

Cities are composed of many types of outdoor spaces, each with their distinct soundscape. Some of these soundscapes can be extraordinary, others are often less memorable. However, most locations in a city are not visited with the purpose of experiencing the soundscape. Consequently, the soundscape will not necessarily attract attention. Existing methods based on the circumplex model of affect classify soundscapes according to the pleasure and arousal they evoke, but do not fully take into account the goals and expectations of the listener. Therefore, in earlier work, a top-level hierarchical classification method was developed, which distinguishes between spaces based on the degree to which the soundscape creates awareness of the acoustical environment, matches expectations and arouses the listener. This paper presents the results of an immersive laboratory experiment, designed to validate this classification method. The experiment involved 40 participants and 50 audiovisual recordings drawn from the Urban Soundscapes of the World database. It is shown that the proposed classification method results in clearly distinct classes, and that membership to these classes can be explained well by physical parameters, extracted from the acoustical environment as well as the visual scene

Cognitive Profile of Students Who Enter Higher Education with an Indication of Dyslexia

For languages other than English there is a lack of empirical evidence about the cognitive profile of students entering higher education with a diagnosis of dyslexia. To obtain such evidence, we compared a group of 100 Dutch-speaking students diagnosed with dyslexia with a control group of 100 students without learning disabilities. Our study showed selective deficits in reading and writing (effect sizes for accuracy between d = 1 and d = 2), arithmetic (d≈1), and phonological processing (d>0.7). Except for spelling, these deficits were larger for speed related measures than for accuracy related measures. Students with dyslexia also performed slightly inferior on the KAIT tests of crystallized intelligence, due to the retrieval of verbal information from long-term memory. No significant differences were observed in the KAIT tests of fluid intelligence. The profile we obtained agrees with a recent meta-analysis of English findings suggesting that it generalizes to all alphabetic languages. Implications for special arrangements for students with dyslexia in higher education are outlined

Application of Quality of Experience in Networked Services: Review, Trend & Perspectives

Full text embargoed until 17.10.2019 (publisher's embargo period, 12 months

Incentivise Me: Smartphone-Based Mobility Detection for Pervasive Games

Part 10: Designing Serious Mobile Location-Based Augmented Reality GamesInternational audienceThe ubiquity of smartphones with a plethora of sensors made it possible to develop context-based pervasive games playable by most people without any additional equipment required. However, popular games like Pokémon GO or Zombie, Run! show the minimal influence context has on the gameplay besides the user’s position. Furthermore, in the context of movement and mobility the distinction between different modes of transport becomes necessary both for security and for environmental reasons.In this paper we present a system that uses location information combined with public transport data to detect different types of mobility, especially vehicular mobility and uses this information for adaptation purposes in a prototypical location-based game. Our evaluation shows that our system can be used to reliably differentiate between public transport and driving a car within minutes and is able to adapt content in pervasive games according to the context surrounding the current user

Offshore windmill and substation maintenance planning with Distance, Fuel consumption and Tardiness optimisation

Despite a lot of research about predictive maintenance for onshore and offshore windmill farms, nearly no investigation has been performed to obtain the optimal sequence in which windmills are to be served in a predefined time frame. The higher fuel costs and the increasing time pressure on maintenance jobs urge the need for optimisation, so offshore windmills can be serviced at minimal costs and within a limited time frame. To minimise distance travelled, fuel consumption and average tardiness of all maintenance tasks to be carried out, a multi-objective, non-dominated sorting island model of genetic algorithms is used.The following novel contributions are realised: (i) A multi-objective island model is used, where on each island a different genetic algorithm is used to minimise a separate cost function per island. (ii) A set of non-dominated maintenance sequences, shown as a Pareto plane, are computed and (iii) these optimal solutions can be used by the planner to select the route to be followed by the CTV when travelling from windmill to windmill during a maintenance sequence.Tests on two of the islands have resulted in a relative improvement of around 65 to 70% on fuel consumption and distance in relation to a random sequence, while the third island has generated a relative gain of 69% in average weighed tardiness. The three islands combined have resulted in a set of Pareto optimal sequences for offshore windmill maintenance