946 resultados para Databases as Topic


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This publication is a support and resource document for the "National Action Plan for Promotion, Prevention and Early Intervention for Mental Health 2000". It includes indicators, measurement tools and databases relevant to assessing the implementation of the outcomes and strategies identified in the action plan.

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The changing incidence of adenocarcinomas, particularly in the oesophagus and gastric cardia, has led to the rapid expansion of screening programmes aimed at detecting the precursor lesion of dysplasia before adenocarcinoma develops. The pathologist now has an important role in first diagnosing patients at risk for developing dysplasia, and then correctly classifying dysplasia when it occurs. Barrett's oesophagus has had different diagnostic criteria in previous years but is currently diagnosed by the presence of intestinal metaplasia of any length in the true oesophagus. Intestinal metaplasia confined only to the gastro-oesophageal junction or cardia is of uncertain significance but is probably common, with less risk of progressing to dysplasia or malignancy. In the stomach, patients with autoimmune atrophic gastritis and Helicobacter-associated multifocal atrophic gastritis have an increased risk of adenocarcinoma, but screening protocols are not well-developed compared with those used for Barrett's oesophagus. Dysplasia of glandular epithelium can be classified using well-described criteria. Low grade dysplasia is the most common type and regresses or remains stable in the majority of patients. High grade dysplasia is more ominous clinically, with a propensity to coexist with or progress to adenocarcinoma.

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This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License.

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This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

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The changes introduced into the European Higher Education Area (EHEA) by the Bologna Process, together with renewed pedagogical and methodological practices, have created a new teaching-learning paradigm: Student-Centred Learning. In addition, the last few years have been characterized by the application of Information Technologies, especially the Semantic Web, not only to the teaching-learning process, but also to administrative processes within learning institutions. On one hand, the aim of this study was to present a model for identifying and classifying Competencies and Learning Outcomes and, on the other hand, the computer applications of the information management model were developed, namely a relational Database and an Ontology.

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The clinical content of administrative databases includes, among others, patient demographic characteristics, and codes for diagnoses and procedures. The data in these databases is standardized, clearly defined, readily available, less expensive than collected by other means, and normally covers hospitalizations in entire geographic areas. Although with some limitations, this data is often used to evaluate the quality of healthcare. Under these circumstances, the quality of the data, for instance, errors, or it completeness, is of central importance and should never be ignored. Both the minimization of data quality problems and a deep knowledge about this data (e.g., how to select a patient group) are important for users in order to trust and to correctly interpret results. In this paper we present, discuss and give some recommendations for some problems found in these administrative databases. We also present a simple tool that can be used to screen the quality of data through the use of domain specific data quality indicators. These indicators can significantly contribute to better data, to give steps towards a continuous increase of data quality and, certainly, to better informed decision-making.

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Mental practice is an internal reproduction of a motor act (whose intention is to promote learning and improving motor skills). Some studies have shown that other cognitive strategies also increase the strength and muscular resistance in healthy people by the enhancement of the performance during dynamic tasks. Mental training sessions may be primordial to improving muscle strength in different subjects. The aim of this study was to systematically review and meta-analiyze studies that assessed whether mental practice is effective in improving muscular strength. We conducted an electronic-computed search in Pub-Med/Medline and ISI Web of Knowledge, Scielo and manual searchs, searching papers written in English between 1991 and 2014. There were 44 studies in Pub-Med/Medline, 631 in ISI Web of Knowledge, 11 in Scielo and 3 in manual searchs databases. After exclusion of studies for duplicate, unrelated to the topic by title and summary, different samples and methodologies, a meta-analysis of 4 studies was carried out to identify the dose-response relationship. We did not find evidence that mental practice is effective in increasing strength in healthy individuals. There is no evidence that mental practice alone can be effective to induce strength gains or to optimize the training effects.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Cuidar de um familiar com doença avançada e/ou em fim de vida pode representar uma grande sobrecarga emocional, física e financeira que afeta a qualidade de vida dos cuidadores. O presente estudo teve como objetivo realizar uma revisão sistemática da literatura sobre a sobrecarga no cuidar, os fatores relacionados e suas consequências nos cuidadores de pacientes com câncer avançado em fim de vida ou em cuidados paliativos. Foi realizada uma busca de artigos científicos publicados nas bases de dados EBSCO, Web of Knowledge e Bireme, desde os primeiros registros nas respectivas bases de dados sobre o tema até março de 2014. Dos 582 artigos encontrados, apenas 27 foram selecionados. A maioria dos artigos afirma que os cuidadores familiares estão sobrecarregados. Em alguns estudos, a sobrecarga no cuidar aparece associada a características do paciente e da sua doença; em outros, a um pior estado de saúde do cuidador, a uma maior sintomatologia psicopatológica (ansiedade, depressão, distress emocional) e também ao desenvolvimento de complicações no luto. Porém, a esperança, o apoio social, a capacidade do cuidador de atribuir um significado à experiência de cuidar e se sentir confortável com as tarefas de cuidar foram associados a menores níveis de sobrecarga.

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Current computer systems have evolved from featuring only a single processing unit and limited RAM, in the order of kilobytes or few megabytes, to include several multicore processors, o↵ering in the order of several tens of concurrent execution contexts, and have main memory in the order of several tens to hundreds of gigabytes. This allows to keep all data of many applications in the main memory, leading to the development of inmemory databases. Compared to disk-backed databases, in-memory databases (IMDBs) are expected to provide better performance by incurring in less I/O overhead. In this dissertation, we present a scalability study of two general purpose IMDBs on multicore systems. The results show that current general purpose IMDBs do not scale on multicores, due to contention among threads running concurrent transactions. In this work, we explore di↵erent direction to overcome the scalability issues of IMDBs in multicores, while enforcing strong isolation semantics. First, we present a solution that requires no modification to either database systems or to the applications, called MacroDB. MacroDB replicates the database among several engines, using a master-slave replication scheme, where update transactions execute on the master, while read-only transactions execute on slaves. This reduces contention, allowing MacroDB to o↵er scalable performance under read-only workloads, while updateintensive workloads su↵er from performance loss, when compared to the standalone engine. Second, we delve into the database engine and identify the concurrency control mechanism used by the storage sub-component as a scalability bottleneck. We then propose a new locking scheme that allows the removal of such mechanisms from the storage sub-component. This modification o↵ers performance improvement under all workloads, when compared to the standalone engine, while scalability is limited to read-only workloads. Next we addressed the scalability limitations for update-intensive workloads, and propose the reduction of locking granularity from the table level to the attribute level. This further improved performance for intensive and moderate update workloads, at a slight cost for read-only workloads. Scalability is limited to intensive-read and read-only workloads. Finally, we investigate the impact applications have on the performance of database systems, by studying how operation order inside transactions influences the database performance. We then propose a Read before Write (RbW) interaction pattern, under which transaction perform all read operations before executing write operations. The RbW pattern allowed TPC-C to achieve scalable performance on our modified engine for all workloads. Additionally, the RbW pattern allowed our modified engine to achieve scalable performance on multicores, almost up to the total number of cores, while enforcing strong isolation.

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Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

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O aumento da quantidade de dados gerados que se tem verificado nos últimos anos e a que se tem vindo a dar o nome de Big Data levou a que a tecnologia relacional começasse a demonstrar algumas fragilidades no seu armazenamento e manuseamento o que levou ao aparecimento das bases de dados NoSQL. Estas estão divididas por quatro tipos distintos nomeadamente chave/valor, documentos, grafos e famílias de colunas. Este artigo é focado nas bases de dados do tipo column-based e nele serão analisados os dois sistemas deste tipo considerados mais relevantes: Cassandra e HBase.

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Dissertação de Mestrado em Engenharia Informática