Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of ���lessons learned��� and definition of ���modes of action���. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Child abuse monitor system model: a health care critical knowledge monitor system

The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren���t enough to promote the accusation. Besides that, this subject it���s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.

Clustering-based approach for categorizing pregnant women in obstetrics and maternity care

When a pregnant woman is guided to a hospital for obstetrics purposes, many outcomes are possible, depending on her current conditions. An improved understanding of these conditions could provide a more direct medical approach by categorizing the different types of patients, enabling a faster response to risk situations, and therefore increasing the quality of services. In this case study, the characteristics of the patients admitted in the maternity care unit of Centro Hospitalar of Porto are acknowledged, allowing categorizing the patient women through clustering techniques. The main goal is to predict the patients��� route through the maternity care, adapting the services according to their conditions, providing the best clinical decisions and a cost-effective treatment to patients. The models developed presented very interesting results, being the best clustering evaluation index: 0.65. The evaluation of the clustering algorithms proved the viability of using clustering based data mining models to characterize pregnant patients, identifying which conditions can be used as an alert to prevent the occurrence of medical complications.

Connecting free volume with shape memory properties in noncytotoxic gamma-irradiated polycyclooctene

The free volume holes of a shape memory polymer have been analysed considering that the empty space between molecules is necessary for the molecular motion, and the shape memory response is based on polymer segments acting as molecular switches through variable flexibility with temperature or other stimuli. Therefore, thermomechanical analysis (TMA) and positron annihilation lifetime spectroscopy (PALS) have been applied to analyse shape recovery and free volume hole sizes in gamma irradiated polycyclooctene (PCO) samples, as a non-cytotoxic alternative to more conventional PCO crosslinked via peroxide for future applications in medicine. Thus, a first approach relating structure, free volume holes and shape memory properties in gamma irradiated PCO is presented. The results suggest that free volume holes caused by gamma irradiation in PCO samples facilitate the recovery process by improving movement of polymer chains and open t possibilities for the design and control of the macroscopic response.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Benchmarking sobre t��cnicas de otimiza����o para modelos de apoio �� decis��o na medicina intensiva

Disserta����o de mestrado integrado em Engenharia e Gest��o de Sistemas de Informa����o

Text mining na an��lise de sentimentos em contextos de big data

Disserta����o de mestrado integrado em Engenharia e Gest��o de Sistemas de Informa����o

Pervasive patient timeline

Disserta����o de mestrado integrado em Engenharia e Gest��o de Sistemas de Informa����o

Moradias sobredimensionadas dos anos 70���90 na periferia de Braga: processo de transforma����o

According to the latest census (2011) covering the Portuguese housing stock, there is a considerable number of sub-occupied buildings and most of them were built before the first Portuguese Thermal Code (RCCTE). In view of the objectives of the European Union (20-20-20), it is necessary to contribute to the rehabilitation of existing buildings by promoting the densification of oversized houses, while complying with up-to-date comfort standards and codes.����In this sense, this research is aimed to analyse this problem at the outskirts of Braga, by identifying the type-morphology of oversized buildings, assessing the degree of satisfaction and expectations of both owners and inhabitants and developing and testing a systematic design tool.����Through the development of an intervention kit, wich systematizes and priorizes design strategies and solutions, the design team can have the necessary decision-making support tool to improve the spacial design of the building whilst considering energy efficency, sustainability and improvemente of interior environmental quality.

External and internal dynamics in the EU's counter-terrorism policy: a political and legal analysis

Tese de Doutoramento em Ci��ncia Pol��tica e Rela����es Internacionais

Determina����o da medida da pena privativa de liberdade: um olhar cr��tico a partir do direito anglo-sax��nico

Tese de Doutoramento em Ci��ncias Jur��dicas - ��rea de Ci��ncias Jur��dicas P��blicas

Forma����o de professores no programa nacional para a alfabetiza����o na idade certa com uso das TIC: um estudo de caso no ensino fundamental

Disserta����o de mestrado em Ci��ncias da Educa����o (��rea de especializa����o em Tecnologia Educativa)

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child���s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients��� waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.