ICTERI 2020: ІКТ в освіті, дослідженнях та промислових застосуваннях. Інтеграція, гармонізація та передача знань 2020: Матеріали 16-ї Міжнародної конференції. Том II: Семінари. Харків, Україна, 06-10 жовтня 2020 р.

This volume represents the proceedings of the Workshops co-located with the 16th International Conference on ICT in Education, Research, and Industrial Applications, held in Kharkiv, Ukraine, in October 2020. It comprises 101 contributed papers that were carefully peer-reviewed and selected from 233 submissions for the five workshops: RMSEBT, TheRMIT, ITER, 3L-Person, CoSinE, MROL. The volume is structured in six parts, each presenting the contributions for a particular workshop. The topical scope of the volume is aligned with the thematic tracks of ICTERI 2020: (I) Advances in ICT Research; (II) Information Systems: Technology and Applications; (III) Academia/Industry ICT Cooperation; and (IV) ICT in Education.Цей збірник представляє матеріали семінарів, які були проведені в рамках 16-ї Міжнародної конференції з ІКТ в освіті, наукових дослідженнях та промислових застосуваннях, що відбулася в Харкові, Україна, у жовтні 2020 року. Він містить 101 доповідь, які були ретельно рецензовані та відібрані з 233 заявок на участь у п'яти воркшопах: RMSEBT, TheRMIT, ITER, 3L-Person, CoSinE, MROL. Збірник складається з шести частин, кожна з яких представляє матеріали для певного семінару. Тематична спрямованість збірника узгоджена з тематичними напрямками ICTERI 2020: (I) Досягнення в галузі досліджень ІКТ; (II) Інформаційні системи: Технології і застосування; (ІІІ) Співпраця в галузі ІКТ між академічними і промисловими колами; і (IV) ІКТ в освіті

Strategic Management in Converging Industries

This paper provides a discussion of the consequences of digital convergence on strategic management. The process of digital convergence was initiated a few years ago by the rapid progress in digital technologies and has gained increased practical importance since then. In order to show its multiple effects on strategic management we choose a three-steps approach for this analysis

Desk-mates (stable matching) with privacy of preferences, and a new distributed csp framework

The desk-mates matcher application places students in pairs of two for working in projects (similar to the well known problems of stable matchings or stable roommates). Each of the students has a (hopefully stable) secret preference between every two colleagues. The participants want to find an allocation satisfying their secret preferences and without leaking any of these secret preferences, except for what a participant can infer from the identity of the partner that was recommended to her. The peculiarities of the above problem require solvers based on old distributed CSP frameworks to use models whose search spaces are higher than those in centralized solvers, with bad effects on efficiency. Therefore we introduce a new distributed constraint satisfaction (DisCSP) framework where the actual constraints are secrets that are not known by any agent. They are defined by a set of functions on some secret inputs from all agents. The solution is also kept secret and each agent learns just the result of applying an agreed function on the solution. The expressiveness of the new framework is shown to improve the efficiency (O(2 m3 −log(m)) times) in modeling and solving the aforementioned problem with m participants. We show how to extend our previous techniques to solve securely problems modeled with the new formalism, and exemplify with the problem in the title. An experimental implementation in the form of an applet-based solver is available