Abstract

Abstract
Social networks are a recent phenomenon of communication, with a high prevalence of young users. This concept serves as a motto for a multidisciplinary project, which aims to create a simple communication network, using light as the transmission medium. Mixed team, composed by students from secondary and higher education schools, are partners on the development of an optical transceiver. A LED lamp array and a small photodiode are the optical transmitter and receiver, respectively. Using several transceivers aligned with each other, this configuration creates a ring communication network, enabling the exchange of messages between users. Through this project, some concepts addressed in physics classes from secondary schools (e.g. photoelectric phenomena and the properties of light) are experimentally verified and used to communicate, in a classroom or a laboratory.

Abstract
User modeling and user adaptive interaction has become a central research issue to understand users as they interact with technology. The importance of the development of well adapted interfaces to several kinds of users and the differences that characterize them is the basis of the successful interaction. User Personas is a technique that allows the discovery and definition of the archetype users of a system. With that knowledge, the system should shape itself, inferring the user expertise to provide its users with the best possible experience. In this paper, an architecture that combines User Personas and a dynamic, evolving system is proposed, along with an evaluation by its target users. The proposed system is able to infer the user and its matching Persona, and keeps shaping itself in parallel with the user's discovery of the system.

Abstract
eCall is a car system which automatically calls for help in case of a car accident. The system sends a minimum set of data containing information about the occurrence, such as the geographic location and the vehicle identification. Simultaneously, a 112-voice connection is established. Therefore, the operator at the Public-Safety Answering Point (PSAP) is able to hear what is happening in the vehicle and actually communicate with the occupant(s). However if the occupant(s)'s are deaf or has earing impairments he will not be able to describe the situation using the voice channel established. This paper proposes a solution for this problem extending the SOSPhone concept, developed for enabling universal access to emergency services. A prototype of an application integrated with the eCall that enables the communication with deaf people or earing impaired people is presented. The solution makes use of touch interfaces, embedding the emergency protocols in the user's device, gathering information with an iconographic interface. (C) 2013 The Authors. Published by Elsevier B.V.

Abstract
The creative transition from understanding the customer experience to defining the service solution, from current situation to preferred future, is central to Service Design. However, the incorporation of customer experience factors can change along the different iterative cycles of service design. To address this challenge, this paper presents the results of a study of how the path of customer experience was followed, studied and incorporated along a mobile service development. Three iterative Service Design cycles enabled a holistic vision of the service and raised ‘customer experience’ awareness on the development team. Following a design research approach, experience factors were actively taken into account and incorporated along ideation and implementations cycles involving a total of 61 interviews. The research work contributes to Service Design by providing a global vision of the experiential changes, especially in mobile and technology based services. It describes the reframed situations working with experiences at each cycle of design, and making use of service design tools and methods at each moment.

Abstract
Random key genetic algorithms are heuristic methods for solving combinatorial optimization problems. They represent solutions as vectors of randomly generated real numbers, the so-called random keys. A deterministic algorithm, called a decoder, takes as input a vector of random keys and associates with it a feasible solution of the combinatorial optimization problem for which an objective value or fitness can be computed. We compare three types of random-key genetic algorithms: the unbiased algorithm of Bean (1994); the biased algorithm of Gonçalves and Resende (2010); and a greedy version of Bean's algorithm on 12 instances from four types of covering problems: general-cost set covering, Steiner triple covering, general-cost set k-covering, and unit-cost covering by pairs. Experiments are run to construct runtime distributions for 36 heuristic/instance pairs. For all pairs of heuristics, we compute probabilities that one heuristic is faster than the other on all 12 instances. The experiments show that, in 11 of the 12 instances, the greedy version of Bean's algorithm is faster than Bean's original method and that the biased variant is faster than both variants of Bean's algorithm. © 2014 Brazilian Operations Research Society.