Jorge Ribeiro

A Case-Based Reasoning Approach to GBM Evolution

GlioBastoma Multiforme (GBM) is an aggressive primary brain tumor characterized by a heterogeneous cell population that is genetically unstable and resistant to chemotherapy. Indeed, despite advances in medicine, patients diagnosed with GBM have a median survival of just one year. Magnetic Resonance Imaging (MRI) is the most widely used imaging technique for determining the location and size of brain tumors. Indisputably, this technique plays a major role in the diagnosis, treatment planning, and prognosis of GBM. Therefore, this study proposes a new Case Based Reasoning approach to problem solving that attempts to predict a patient’s GBM volume after five months of treatment based on features extracted from MR images and patient attributes such as age, gender, and type of treatment.

Evolutionary Computation on Road Safety

This study examines the psychological research that focuses on road safety in Smart Cities as proposed by the Vulnerable Road Users (VRUs) sphere. It takes into account qualities such as VRUs’ personal information, their habits, environmental measurements and things data. With the goal of seeing VRUs as active and proactive actors with differentiated feelings and behaviours, we are committed to integrating the social factors that characterize each VRU into our social machinery. As a result, we will focus on the development of a VRU Social Machine to assess VRUs’ behaviour in order to improve road safety. The formal background will be to use Logic Programming to define its architecture based on a Deep Learning approach to Knowledge Representation and Reasoning, complemented with an Evolutionary approach to Computing.

A Deep-Big Data Approach to Health Care in the AI Age

The intersection of these two trends is what we call The Issue and it is helping businesses in every industry to become more efficient and productive. One’s aim is to have an insight into the development and maintenance of comprehensive and integrated health information systems that enable sound policy and effective health system management in order to improve health and health care. Undeniably, different sorts of technologies have been developed, each with their own advantages and disadvantages, which will be sorted out by attending at the impact that Artificial Intelligence and Decision Support Systems have to everyone in the healthcare sector engaged to quality-of-care, i.e., making sure that doctors, nurses, and staff have the training and tools they need to do their jobs.

Quality Management in Training Companies

This study was carried out in training companies and aims to evaluate customer satisfaction. It focusses at the Organizations’ Quality-of-Management (QoM) that is in itself a major competitive advantage to differentiate them. Indeed, the universe of discourse is set in order to consider not only the complex relationships among the entities that populate it, but also to take into account its inner structure, where incomplete, unknown or even self-contradictory information or knowledge are present. One’s goal is at the development of a comprehensive and integrated computational model to ensure the Organizations’ Performance and its QoM in order to fulfill customer’s requirements. It is based on a Logic Programming approach to Knowledge Representation and Reasoning and grounded on an Artificial Neural Networks approach to computing.

Planning, Managing and Monitoring Technological Security Infrastructures

Over the past few decades many different Information Technologies (IT) policies have been introduced, including COSO, ITIL, PMBook, CMM, ISO 2700x, Six Sigma, being COBIT IT (Control Objectives for IT) the framework that encompasses all IT and Information Systems (IS) governance activities at the organization’s level. As part of the applicability of quality services certification (ISO 9001) in all IT services of a public institution, it is presented a case study aimed at planning, managing and monitoring technological security infrastructures. It followed the guidelines for the ISO 2700x family, COBIT, ITIL and other standards and conducted a survey to complement the IT process’s objectives. With regard to an action-research methodology for problem-solving (i.e., a kind of attempt to improve or investigate practice) and according to the issue under analyze, the question is put into the terms, viz. “How can the ISO 2700x, COBIT, ITIL and other guidelines help with the planning, management and monitoring of technological security infrastructures and minimize the risk management of IT and IS?”. Indeed, it may be resolved that it is possible to achieve the goals of planning, managing and monitoring a technological security infrastructure. In the future, we will use Artificial Intelligence based approaches to problem solving such as Artificial Neural Networks and Cased Based Reasoning, to evaluate this issue.

Pocket-cubes, bringing multidimensional data views to mobile platforms

From simple entertainment gadgets to real world based applications, a little bit of everything is in a mobile platform. Thus, its not a surprise that enterprise managers, decision makers or business analytics use it also to support their most regular daily business activities. Following the same fast adoption path of other applications, their analytical needs quickly appeared in their horizon as one of the most useful applications that they could bring in their “pockets”. The data structures of such applications are very large to be received by mobile platforms. Data cubes still are quite out from currently mobile platforms data manipulation boundaries. However, a lot of efforts were developed during the last few years to provide smaller hyper cubes with the same exploitation potentialities, requiring less computational resources as disk storage and processing time, appealing to better data compression techniques or multidimensional views selection. In this paper we present the most usual techniques for compressing and processing data cubes. In order to support such approach we designed and developed the Pocket Cubes system, an application especially oriented to prepare data cubes to be used on mobile platforms.