Abstract

Abstract
Transportation modes prediction is a fundamental task for decision making in smart cities and traffic management systems. Traffic policies based on trajectory mining can save money and time for authorities and the public. It may reduce the fuel consumption, commute time, and more pleasant moments for residents and tourists. Since the number of features that may be used to predict a user transportation mode can be substantial, finding a subset of features that maximizes a performance measure is worth investigating. In this work, we explore a wrapper and an information retrieval methods to find the best subset of trajectory features for a transportation mode dataset. Our results were compared with two related papers that applied deep learning methods. The results showed that our work achieved better performance. Furthermore, two types of cross-validation approaches were investigated, and the performance results show that the random cross-validation method may provide overestimated results. © 2019 Copyright held by the owner/author(s).

Abstract
Distance Education (DE) still have some challenges to be considered similar to the face-to-face mode of instruction regarding the quality of learning, including the lack in promoting the sense of presence. This research investigates whether a differentiated media support, complementary to the traditional Virtual Learning Environment (VLE), composed by the integration of 3D Virtual Worlds (3DVW) and Conversational Agents, in the role of a Virtual Companions, can promote the student’s sense of presence in order to contribute with the learning process in DE. A quasi-experiment pilot study was conducted with 36 students enrolled in the Financial Management discipline from a DE formal course. A 3DVW was developed in the light of the pedagogical model of Experiential Learning, in the form of a role-play simulation. The results reveal that although the students positively evaluated the experience in the 3DVW, it did not stimulate the sense of presence as expected. However, better performance rates were diagnosed for students who had the help of the Virtual Companion.

Abstract
Security and quality of supply continue to be major concern of power system operators. Thus, the expansion of transmission grids is certainly one of the major drivers to achieve this goal. In this scope, this paper presents a three-stage approach to solve the multi-year Transmission Expansion Planning (TEP) problem. This approach uses heuristic algorithms coupled with the Harmony Search (HS) metaheuristic and the Branch & Bound (B&B) algorithm. This hybrid method (HS-B&B) aims at finding the optimal multi-stage investment plan avoiding load shedding over the planning horizon. In this work, the AC-Optimal Power Flow (AC-OPF) is used to model the network as a way to consider the real operation conditions of the system. The method was validated using the Garver and the IEEE RTS 24 bus systems. Results demonstrate the reduction of computational effort without compromising the quality of the TEP.

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Workshops are a great opportunity for identifying innovative topics of research that might require discussion and maturation. This paper summarizes the outcomes of the workshops track of the 11th Engineering Interactive Computing Systems conference (EICS 2019), held in Valencia (Spain) on 18-21 June 2019. The track featured three workshops, one half-day, one full-day and one two-days workshop, each focused on specific topics of the ongoing research in engineering usable and effective interactive computing systems. In particular, the list of discussed topics include novel forms of interaction and emerging themes in HCI related to new application domains, more efficient and enjoyable interaction possibilities associated to smart objects and smart environments, challenges faced in designing, developing and using interactive systems involving multiple stakeholders.

Abstract