Abstract

Abstract
The academy can and should have a major role in the promotion of software accessibility. To try to clarify a number of empirical arguments and certainties regarding the usage of accessible, but not assistive, software, the answers to a survey given to 15 blind or low vision people are depicted. To demonstrate how under addressed this topic is by the academy an experiment was made, and its results are portrayed. The novel contribution that this paper offers is the relation between relevant accessibility documentation to its appropriate type of user interface, which is intended to encourage the introduction of the topic of software accessibility implementation. Also, a proposal for a first slide, regarding accessibility implementation in software meant to be shown to software engineering students, who should produce accessible software in their future, is presented. As a conclusion, some insights are given and new possible research avenues are depicted.

Abstract
This study translates how the potential exists for ICT and Web 2.0 to promote and improve the quality and efficiency of the supply of health services. The segmented and personalized access to individual clinical records is considered in the context of basic support information which simultaneously facilitates an initial screening by a health professional, to all those who fit in a universe of clients and patients of Private Healthcare Organizations - PHO. The context is of excellent customized health care which builds trusting relationships with the target market. The project does however recognize barriers to this change namely by making the health system more transparent clinicians who hitherto have gone mainly unquestioned and unnoticed will subsequently possibly be subject to more scrutiny and possible judicial action in case of mal practice. Nonetheless, with this work we aim to present an initial position relative to the need for the existence of information systems which support the process of creation of customer loyalty in private organizations delivering health care services.

Abstract
Dealing with missing data is a crucial step in the preprocessing stage of most data mining projects. Especially in healthcare contexts, addressing this issue is fundamental, since it may result in keeping or loosing critical patient information that can help physicians in their daily clinical practice. Over the years, many researchers have addressed this problem, basing their approach on the implementation of a set of imputation techniques and evaluating their performance in classification tasks. These classic approaches, however, do not consider some intrinsic data information that could be related to the performance of those algorithms, such as features’ distribution. Establishing a correspondence between data distribution and the most proper imputation method avoids the need of repeatedly testing a large set of methods, since it provides a heuristic on the best choice for each feature in the study. The goal of this work is to understand the relationship between data distribution and the performance of well-known imputation techniques, such as Mean, Decision Trees, k-Nearest Neighbours, Self-Organizing Maps and Support Vector Machines imputation. Several publicly available datasets, all complete, were selected attending to several characteristics such as number of distributions, features and instances. Missing values were artificially generated at different percentages and the imputation methods were evaluated in terms of Predictive and Distributional Accuracy. Our findings show that there is a relationship between features’ distribution and algorithms’ performance, although some factors must be taken into account, such as the number of features per distribution and the missing rate at state.

Abstract
Social network analysis (SNA) is a widely studied research topics, which has been increasingly being applied for solving different kind of problems, including industrial manufacturing ones. This paper focuses on the application of SNA on an industrial plant layout problem. The study aims at analyzing the importance of using SNA techniques to analyze important relations between entities in a manufacturing environment, such as jobs and resources in the context of industrial plant layout analysis. The study carried out enabled to obtain relevant results for the identification of relations among these entities for supporting to establish an appropriate plant layout for producing the jobs.

Abstract
There is a remarkable potential for implementing demand response (DR) strategies for several purposes, such as peak load reduction, frequency regulation, etc., by using thermostatically controllable appliances. In this paper, an enduser comfort violation minimization oriented DR strategy for residential heating, ventilation, and air conditioning (HVAC) units is proposed. The proposed approach manipulates the temperature set-point of HVAC thermostats aiming to minimize the average discomfort among end-users enrolled in an DR program, while satisfying the DR event related requirements of the load serving entity. Besides, the fairness of the allocation of the comfort violation among the enrolled end-users is also taken into account. Moreover, maintaining the load factor during the contracted DR period compared to a base case in order to reduce the load rebound effect due to shifting the use of HVAC units is also considered within the proposed strategy. Last but not least, the heat index that considers the impact of humidity is utilized instead of using ambient dry-bulb temperature through a spatio-temporal forecasting approach.