Timur Osadchiy

Dinislam Abdulgalimov, Timur Osadchiy

Modern society is going through the transformation under the influence of Information Technologies. Internet of Things as one of the latest facet of it becoming more visible and widely spread. We wish to reflect and discuss the current concerns regarding its expansion. Our particular interests lie in the increasing of usability and comfortability through the unification of the IoT protocols and security measures. As well as addressing the privacy concerns and discussing the possible changings in the perception of privacy and personal space concepts.

Timur Osadchiy, Ivan Poliakov, Patrick Olivier et al.

Recall assistance methods are among the key aspects that improve the accuracy of online dietary assessment surveys. These methods still mainly rely on experience of trained interviewers with nutritional background, but data driven approaches could improve cost-efficiency and scalability of automated dietary assessment. We evaluated the effectiveness of a recommender algorithm developed for an online dietary assessment system called Intake24, that automates the multiple-pass 24-hour recall method. The recommender builds a model of eating behavior from recalls collected in past surveys. Based on foods they have already selected, the model is used to remind respondents of associated foods that they may have omitted to report. The performance of prompts generated by the model was compared to that of prompts hand-coded by nutritionists in two dietary studies. The results of our studies demonstrate that the recommender system is able to capture a higher number of foods omitted by respondents of online dietary surveys than prompts hand-coded by nutritionists. However, the considerably lower precision of generated prompts indicates an opportunity for further improvement of the system.