Methodology for real-time adaptation of tunnels support using the observational method

The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

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.

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.

Benchmarking sobre técnicas de otimização para modelos de apoio à decisão na medicina intensiva

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Sistema de apoio à decisão clínica: quality of life system

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Pervasive patient timeline

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Apoio à decisão na análise inteligente de reclamações

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Plataforma de apoio à decisão nos cuidados de ginecologia e obstetrícia

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

A clinical recommendation system to maternity care

Nowadays in healthcare, the Clinical Decision Support Systems are used in order to help health professionals to take an evidence-based decision. An example is the Clinical Recommendation Systems. In this sense, it was developed and implemented in Centro Hospitalar do Porto a pre-triage system in order to group the patients on two levels (urgent or outpatient). However, although this system is calibrated and specific to the urgency of obstetrics and gynaecology, it does not meet all clinical requirements by the general department of the Portuguese HealthCare (Direção Geral de Saúde). The main requirement is the need of having priority triage system characterized by five levels. Thus some studies have been conducted with the aim of presenting a methodology able to evolve the pre-triage system on a Clinical Recommendation System with five levels. After some tests (using data mining and simulation techniques), it has been validated the possibility of transformation the pre-triage system in a Clinical Recommendation System in the obstetric context. This paper presents an overview of the Clinical Recommendation System for obstetric triage, the model developed and the main results achieved.

Synthesis and characterization of novel 4H-pyran-4-ylidene indole-based heterocyclic systems for several optical applications

The development of organic materials displaying high two-photon absorption (TPA) has attracted much attention in recent years due to a variety of potential applications in photonics and optoelectronics, such as three-dimensional optical data storage, fluorescence imaging, two-photon microscopy, optical limiting, microfabrication, photodynamic therapy, upconverted lasing, etc. The most frequently employed structural motifs for TPA materials are donor–pi bridge–acceptor (D–pi–A) dipoles, donor–pi bridge–donor (D–pi–D) and acceptor–pi bridge-acceptor (A–pi–A) quadrupoles, octupoles, etc. In this work we present the synthesis and photophysical characterization of quadrupolar heterocyclic systems with potential applications in materials and biological sciences as TPA chromophores. Indole is a versatile building block for the synthesis of heterocyclic systems for several optoelectronic applications (chemosensors, nonlinear optical, OLEDs) due to its photophysical properties and donor electron ability and 4H-pyran-4-ylidene fragment is frequently used for the synthesis of red light-emitting materials. On the other hand, 2-(2,6-dimethyl-4H-pyran-4-ylidene)malononitrile (1) and 1,3-diethyl-dihydro-5-(2,6-dimethyl-4H-pyran-4-ylidene)-2-thiobarbituric (2) units are usually used as strong acceptor moieties for the preparation of π-conjugated systems of the push-pull type. These building blocks were prepared by Knoevenagel condensation of the corresponding ketone precursor with malononitrile or 1,3-diethyl-dihydro-2-thiobarbituric acid. The new quadrupolar 4H-pyran-4-ylidene fluorophores (3) derived from indole were prepared through condensation of 5-methyl-1H-indole-3-carbaldehyde with the acceptor precursors 1 and 2, in the presence of a catalytical amount of piperidine. The new compounds were characterized by the usual spectroscopic techniques (UV-vis., FT-IR and multinuclear NMR - 1H, 13C).

Information systems assessment in pathologic anatomy service

Information technologies changed the way of how the health organizations work, contributing to their effectiveness, efficiency and sustainability. Hospital Information Systems (HIS) are emerging on all of health institutions, helping health professionals and patients. However, HIS are not always implemented and used in the best way, leading to low levels of benefits and acceptance by users of these systems. In order to mitigate this problem, it is essential to take measures able to ensure if the HIS and their interfaces are designed in a simple and interactive way. With this in mind, a study to measure the user satisfaction and their opinion was made. It was applied the Technology Acceptance Model (TAM) on a HIS implemented on various hospital centers (AIDA), being used the Pathologic Anatomy Service. The study identified weakness and strengths features of AIDA and it pointed some solutions to improve the medical record.

Analysis of integrated management systems from various perspectives

This article compiles the main topics addressed by management systems (MSs) literature concerningMSs integration by performing a systematic literature review. In this paper, it is intended to present themain limitations of non-integratedmanagement systems (IMSs), the main motivations driving an IMS implementation, the major resistances faced, the most common resultant benefits, the suitable guidelines and standards and the critical success factors. In addition, this paper addresses the issues concerning integration strategies and models, the integration levels or degrees achieved by an IMS and the audit function in an integrated context. The motivations that drive companies to integrate their management subsystems, the obstacles faced and the benefits collected may have internal or external origins. The publishing of standards guiding companies on how to integrate their management subsystems has been done mainly at a national level. There are several models that could be used in order to support companies in their management subsystems integration processes, and a sequential or an all-in strategy may be adopted. Four audit typologies can be distinguished, and the adoption of any of these typologies should consider resource availability and audit team know-how, among other features.