Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

The effects of air pollution on cardiovascular diseases: lag structures

OBJECTIVE: To assess the lag structure between air pollution exposure and elderly cardiovascular diseases hospital admissions, by gender. METHODS: Health data of people aged 64 years or older was stratified by gender in São Paulo city, Southeastern Brazil, from 1996 to 2001. Daily levels of air pollutants (CO, PM10, O3, NO2, and SO2) , minimum temperature, and relative humidity were also analyzed. It were fitted generalized additive Poisson regressions and used constrained distributed lag models adjusted for long time trend, weekdays, weather and holidays to assess the lagged effects of air pollutants on hospital admissions up to 20 days after exposure. RESULTS: Interquartile range increases in PM10 (26.21 mug/m³) and SO2 (10.73 mug/m³) were associated with 3.17% (95% CI: 2.09-4.25) increase in congestive heart failure and 0.89% (95% CI: 0.18-1.61) increase in total cardiovascular diseases at lag 0, respectively. Effects were higher among female group for most of the analyzed outcomes. Effects of air pollutants for different outcomes and gender groups were predominately acute and some "harvesting" were found. CONLUSIONS: The results show that cardiovascular diseases in São Paulo are strongly affected by air pollution.

Economic burden of expected epidemiological changes in diseases related to tobacco, Mexico

OBJECTIVE: To determine health care costs and economic burden of epidemiological changes in diseases related to tobacco consumption. METHODS: A time-series analysis in Mexico (1994-2005) was carried out on seven health interventions: chronic obstructive pulmonary diseases, lung cancer with and without surgical intervention, asthma in smokers and non-smokers, full treatment course with nicotine gum, and full treatment course with nicotine patch. According with Box-Jenkins methodology, probabilistic models were developed to forecast the expected changes in the epidemiologic profile and the expected changes in health care services required for selected interventions. Health care costs were estimated following the instrumentation methods and validated with consensus technique. RESULTS: A comparison of the economic impact in 2006 vs. 2008 showed 20-90% increase in expected cases depending on the disease (p<0.05), and 25-93% increase in financial requirements (p<0.01). The study data suggest that changes in the demand for health services for patients with respiratory diseases related to tobacco consumption will continue showing an increasing trend. CONCLUSIONS: In economic terms, the growing number of cases expected during the study period indicates a process of internal competition and adds an element of intrinsic competition in the management of preventive and curative interventions. The study results support the assumption that if preventive programs remain unchanged, the increasing demands for curative health care may cause great financial and management challenges to the health care system of middle-income countries like Mexico.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

Comparing the content of instruments assessing environmental factors using the International Classification of Functioning, Disability and Health

Purpose: To describe and compare the content of instruments that assess environmental factors using the International Classification of Functioning, Disability and Health (ICF). Methods: A systematic search of PubMed, CINAHL and PEDro databases was conducted using a pre-determined search strategy. The identified instruments were screened independently by two investigators, and meaningful concepts were linked to the most precise ICF category according to published linking rules. Results: Six instruments were included, containing 526 meaningful concepts. Instruments had between 20% and 98% of items linked to categories in Chapter 1. The highest percentage of items from one instrument linked to categories in Chapters 2–5 varied between 9% and 50%. The presence or absence of environmental factors in a specific context is assessed in 3 instruments, while the other 3 assess the intensity of the impact of environmental factors. Discussion: Instruments differ in their content, type of assessment, and have several items linked to the same ICF category. Most instruments primarily assess products and technology (Chapter 1), highlighting the need to deepen the discussion on the theory that supports the measurement of environmental factors. This discussion should be thorough and lead to the development of methodologies and new tools that capture the underlying concepts of the ICF.

Factores psicossociais preditivos de ajustamento à vida de pessoas com doenças crónicas

Doenças crónicas são de longa duração, de progressão lenta e induzem alterações na vida das pessoas, que são confrontadas com um conjunto de fatores que exercem um impacto negativo na sua qualidade de vida (QdV). A QdV é um conceito envolvendo componentes essenciais da qualidade humana: físicas, psicológicas, sociais, culturais e espirituais. Após o diagnóstico e com a doença estabilizada, os doentes procuram novas formas de lidar com esta. Este estudo teve como objetivo identificar fatores psicossociais preditivos (otimismo, afeto positivo e negativo, adesão aos tratamentos, suporte social e espiritualidade) da QdV (bem-estar geral, saúde física, saúde mental) e bem-estar subjetivo (BES) em pessoas com doenças crónicas. Amostra constituída por 774 indivíduos [30% diabetes, 27,1% cancro, 17,2% diabetes, 12% epilepsia, 11,5% esclerose múltipla e 2,2% miastenia, 70,5% do sexo feminino, idade M(DP)=42,9(11,6), educação M(DP)=9,6(4,7), anos diagnóstico M(DP)=12,8(9,7), classificação da doença M(DP)=6,6 (2,8)], recrutados nos hospitais centrais portugueses. Aplicando Modelos de Equações Estruturais e ajustando para variáveis sociodemográficas e clínicas, verificou-se que, pessoas mais otimistas, mais ativas e com uma melhor adesão aos tratamentos apresentam um melhor bem-estar geral, uma melhor saúde mental e um melhor bem-estar subjetivo; uma melhor adesão aos tratamentos contribui para uma melhor saúde física; melhor suporte social reflete-se numa melhor saúde mental; pessoas com mais espiritualidade apresentam uma melhor saúde física e uma melhor saúde mental. Estas conclusões contribuem para a definição de uma terapia que pode ajudar a uma melhor adaptação dos protocolos de tratamento para atender às necessidades dos doentes.

Avaliação da torção miocárdica, por Spekle Tracking, em doentes com HTA

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular - Ramo de especialização: Ultrassonografia Cardiovascular

Gender and racial inequalities in trends of oral cancer mortality in Sao Paulo, Brazil

OBJECTIVE:To analyse recent trends in oral cancer mortality, focusing specifically on differences concerning gender and race.METHODS:Official information on deaths and population in the city of Sao Paulo, 2003 to 2009, were used to estimate mortality rates from oral cancer (C00 to C10, International Classification of Diseases, 10th Revision), adjusted for age and stratified by gender (females and males) and race (blacks and whites). The Prais-Winsten auto-regression procedure was used to analyse the time series.RESULTS:During the study period, 8,505 individuals living in the city of Sao Paulo died of oral cancer. Rates increased for females (rate of yearly increase = 4.4%, 95%CI 1.4;7.5), and levelled off for men, which represents an inversion of previous trends among genders in the city. Increases were identified for blacks, with a high rate of yearly increase of 9.1% (95%CI 5.5;12.9), and levelled off for whites. Oral cancer mortality in blacks almost doubled during the study period, and surpassed mortality in whites for almost all categories.CONCLUSIONS:Mortality presented a higher increase among women than in men, and it doubled among backs. The surveillance of trends of oral cancer mortality across gender and racial groups may contribute to implementing socially appropriate health policies, which concurrently reduce the burden of disease and the attenuation of unfair, avoidable and unnecessary inequalities in health.

Effect of eliminating chronic diseases among elderly individuals

OBJECTIVE: To determine whether the elimination of certain chronic diseases is capable of leading to the compression of morbidity among elderly individuals.METHODS: A population-based, cross-sectional study was carried out with official data for the city of Sao Paulo, Southeastern Brazil in 2000 and data from the SABE (Health, Wellbeing and Ageing) study. Sullivan's method was used to calculate disability-free life expectancy. Cause-deleted life tables were used to calculate the probabilities of death and disabilities with the elimination of health conditions.RESULTS: The largest gains in disability-free life expectancy, with the elimination of chronic illness, occurred in the female gender. Among individuals of a more advanced age, gains in disability-free life expectancy occurred as result of a relative compression of morbidity. Among men aged 75 years, all conditions studied, except heart disease and systemic arterial pressure, led to an absolute expansion of morbidity and, at the same time, to a relative compression of morbidity upon being eliminated.CONCLUSIONS: The elimination of chronic diseases in the elderly could lead to the compression of morbidity in elderly men and women.