Maturity models in the hospital information systems management initial research

Os modelos de maturidade são instrumentos facilitadores da gestão das organizações, incluindo a gestão da sua função sistemas de informação, não sendo exceção as organizações hospitalares. Neste artigo apresenta-se uma investigação inicial que visa o desenvolvimento de um abrangente modelo de maturidade para a gestão dos sistemas de informação hospitalares. O desenvolvimento deste modelo justifica-se porque os modelos de maturidade atuais no domínio da gestão dos sistemas informação hospitalares ainda se encontram numa fase embrionária de desenvolvimento, sobretudo porque são pouco detalhados, não disponibilizam ferramentas para determinação da maturidade e não apresentam as características dos estágios de maturidade estruturadas por diferentes fatores de influência.

Non-preemptive and SRP-based fullypreemptive scheduling of real-time Software Transactional Memory

Recent embedded processor architectures containing multiple heterogeneous cores and non-coherent caches renewed attention to the use of Software Transactional Memory (STM) as a building block for developing parallel applications. STM promises to ease concurrent and parallel software development, but relies on the possibility of abort conflicting transactions to maintain data consistency, which in turns affects the execution time of tasks carrying transactions. Because of this fact the timing behaviour of the task set may not be predictable, thus it is crucial to limit the execution time overheads resulting from aborts. In this paper we formalise a FIFO-based algorithm to order the sequence of commits of concurrent transactions. Then, we propose and evaluate two non-preemptive and one SRP-based fully-preemptive scheduling strategies, in order to avoid transaction starvation.

Towards realistic core-failure-resilient scheduling and analysis

Presented at IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

Towards realistic core-failure-resilient scheduling and analysis

Presented at IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

Probabilistic models for mechanical properties of prestressing strands

This study focus on the probabilistic modelling of mechanical properties of prestressing strands based on data collected from tensile tests carried out in Laboratório Nacional de Engenharia Civil (LNEC), Portugal, for certification purposes, and covers a period of about 9 years of production. The strands studied were produced by six manufacturers from four countries, namely Portugal, Spain, Italy and Thailand. Variability of the most important mechanicalproperties is examined and the results are compared with the recommendations of the ProbabilisticModel Code, as well as the Eurocodes and earlier studies. The obtained results show a very low variability which, of course, benefits structural safety. Based on those results, probabilistic modelsfor the most important mechanical properties of prestressing strands are proposed.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Non-linear time series models

The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

A score test for non-nested hypotheses with applications to discrete data models

This paper suggests that a convenient score test against non-nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest.

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Mat`ern models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Tuple-based morphisms for interoperability establishment of financial information models

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

ANIMAL MODELS FOR THE STUDY OF LEISHMANIASIS IMMUNOLOGY

Leishmaniasis remains a major public health problem worldwide and is classified as Category I by the TDR/WHO, mainly due to the absence of control. Many experimental models like rodents, dogs and monkeys have been developed, each with specific features, in order to characterize the immune response to Leishmania species, but none reproduces the pathology observed in human disease. Conflicting data may arise in part because different parasite strains or species are being examined, different tissue targets (mice footpad, ear, or base of tail) are being infected, and different numbers (“low” 1×102 and “high” 1×106) of metacyclic promastigotes have been inoculated. Recently, new approaches have been proposed to provide more meaningful data regarding the host response and pathogenesis that parallels human disease. The use of sand fly saliva and low numbers of parasites in experimental infections has led to mimic natural transmission and find new molecules and immune mechanisms which should be considered when designing vaccines and control strategies. Moreover, the use of wild rodents as experimental models has been proposed as a good alternative for studying the host-pathogen relationships and for testing candidate vaccines. To date, using natural reservoirs to study Leishmania infection has been challenging because immunologic reagents for use in wild rodents are lacking. This review discusses the principal immunological findings against Leishmania infection in different animal models highlighting the importance of using experimental conditions similar to natural transmission and reservoir species as experimental models to study the immunopathology of the disease.

Scalable Intelligence for Scheduling Systems

A personalização é um aspeto chave de uma interação homem-computador efetiva. Numa era em que existe uma abundância de informação e tantas pessoas a interagir com ela, de muitas maneiras, a capacidade de se ajustar aos seus utilizadores é crucial para qualquer sistema moderno. A criação de sistemas adaptáveis é um domínio bastante complexo que necessita de métodos muito específicos para ter sucesso. No entanto, nos dias de hoje ainda não existe um modelo ou arquitetura padrão para usar nos sistemas adaptativos modernos. A principal motivação desta tese é a proposta de uma arquitetura para modelação do utilizador que seja capaz de incorporar diferentes módulos necessários para criar um sistema com inteligência escalável com técnicas de modelação. Os módulos cooperam de forma a analisar os utilizadores e caracterizar o seu comportamento, usando essa informação para fornecer uma experiência de sistema customizada que irá aumentar não só a usabilidade do sistema mas também a produtividade e conhecimento do utilizador. A arquitetura proposta é constituída por três componentes: uma unidade de informação do utilizador, uma estrutura matemática capaz de classificar os utilizadores e a técnica a usar quando se adapta o conteúdo. A unidade de informação do utilizador é responsável por conhecer os vários tipos de indivíduos que podem usar o sistema, por capturar cada detalhe de interações relevantes entre si e os seus utilizadores e também contém a base de dados que guarda essa informação. A estrutura matemática é o classificador de utilizadores, e tem como tarefa a sua análise e classificação num de três perfis: iniciado, intermédio ou avançado. Tanto as redes de Bayes como as neuronais são utilizadas, e uma explicação de como as preparar e treinar para lidar com a informação do utilizador é apresentada. Com o perfil do utilizador definido torna-se necessária uma técnica para adaptar o conteúdo do sistema. Nesta proposta, uma abordagem de iniciativa mista é apresentada tendo como base a liberdade de tanto o utilizador como o sistema controlarem a comunicação entre si. A arquitetura proposta foi desenvolvida como parte integrante do projeto ADSyS - um sistema de escalonamento dinâmico - utilizado para resolver problemas de escalonamento sujeitos a eventos dinâmicos. Possui uma complexidade elevada mesmo para utilizadores frequentes, daí a necessidade de adaptar o seu conteúdo de forma a aumentar a sua usabilidade. Com o objetivo de avaliar as contribuições deste trabalho, um estudo computacional acerca do reconhecimento dos utilizadores foi desenvolvido, tendo por base duas sessões de avaliação de usabilidade com grupos de utilizadores distintos. Foi possível concluir acerca dos benefícios na utilização de técnicas de modelação do utilizador com a arquitetura proposta.

Avaliação dos mecanismos de concorrência na API do Java 8

As plataformas com múltiplos núcleos tornaram a programação paralela/concorrente num tópico de interesse geral. Diversos modelos de programação têm vindo a ser propostos, facilitando aos programadores a identificação de regiões de código potencialmente paralelizáveis, deixando ao sistema operativo a tarefa de as escalonar dinamicamente em tempo de execução, explorando o maior grau possível de paralelismo. O Java não foge a esta tendência, disponibilizando ao programador um número crescente de bibliotecas de mecanismos de sincronização e paralelização de código. Neste contexto, esta tese apresenta e discute um conjunto de resultados obtidos através de testes intensivos à eficiência de algoritmos de ordenação implementados com recurso aos mecanismos de concorrência da API do Java 8 (Threads, Threadpools, ExecutorService, CountdownLach, ExecutorCompletionService e ForkJoinPools) em sistemas com um número de núcleos variável. Para cada um dos mecanismos, são apresentadas conclusões sobre o seu funcionamento e discutidos os cenários em que o seu uso pode ser rentabilizado de modo a serem obtidos melhores tempos de execução.