1000 resultados para data muling


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This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment. Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

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O presente trabalho cujo Título é técnicas de Data e Text Mining para a anotação dum Arquivo Digital, tem como objectivo testar a viabilidade da utilização de técnicas de processamento automático de texto para a anotação das sessões dos debates parlamentares da Assembleia da República de Portugal. Ao longo do trabalho abordaram-se conceitos como tecnologias de descoberta do conhecimento (KDD), o processo da descoberta do conhecimento em texto, a caracterização das várias etapas do processamento de texto e a descrição de algumas ferramentas open souce para a mineração de texto. A metodologia utilizada baseou-se na experimentação de várias técnicas de processamento textual utilizando a open source R/tm. Apresentam-se, como resultados, a influência do pré-processamento, tamanho dos documentos e tamanhos dos corpora no resultado do processamento utilizando o algoritmo knnflex.

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The aim of this paper is to analyse the impact of university knowledge and technology transfer activities on academic research output. Specifically, we study whether researchers with collaborative links with the private sector publish less than their peers without such links, once controlling for other sources of heterogeneity. We report findings from a longitudinal dataset on researchers from two engineering departments in the UK between 1985 until 2006. Our results indicate that researchers with industrial links publish significantly more than their peers. Academic productivity, though, is higher for low levels of industry involvement as compared to high levels.

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Sampling of an industrial drill string from the northeastern Paris Basin (Montcornet, France) provides early Jurassic magnetostratigraphic data coupled with biochronological control. About 375 paleomagnetic samples were obtained from a 145 m thick series of Pliensbachian rocks. A composite demagnetization thermal up to 300 C and an alternating field up to 80 mT were used to separate the magnetic components. A low unblocking temperature component (<250degreesC) with an inclination of about 64 is interpreted as a present-day field overprint. The characteristic remanent component with both normal and reversed antipodal directions was isolated between 5 and 50 mT. Twenty-nine polarity intervals were recognized. Correlation of these new results from the Paris Basin with data from the Breggia Gorge section (Ticino, southern Alps, Switzerland), which is generally considered as the reference section for Pliensbachian magnetostratigraphy, reveals almost identical patterns of magnetic polarity reversals. However, the correlation implies significant paleontological age discrepancies. Revised age assignments of biostratigraphic data of Breggia as well as an objective evaluation of the uncertainties on zonal boundaries in both Breggia and Moncornet resolve the initial discrepancies between magnetostratigraphic correlations and biostratigraphic ages. Hence, the sequence of magnetic reversals is significantly strengthened and the age calibration is notably improved for the Pliensbachian, a stage for which sections combining adequate magnetic signal and biostratigraphic constraints are still very few. (C) 2002 Elsevier Science B.V. All rights reserved.

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The NRS state data quality standards identify the policies, processes and materials that states and local programs should have in place to collect valid and reliable data for the National Reporting System (NRS). The Division of Adult Education (DAEL) within the Office of Vocational and Adult Education developed the standards to define the characteristics of high quality state and local data collection systems for the NRS. The standards provide an organized way for DAEL to understand the quality of NRS data collection within the states and also provide guidance to states on how to improve their systems. States are to complete this checklist, which incorporates the standards, with their annual NRS data submission to rate their level of implementation of the standards. The accompanying policy document describes DAEL’s requirements for state conformance to the standards and explains the use of the information from this checklist.

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This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

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The passage of the Workforce Investment Act (WIA) of 1998 [Public Law 105-220] by the 105th Congress has ushered in a new era of collaboration, coordination, cooperation and accountability. The overall goal of the Act is “to increase the employability, retention, and earnings of participants, and increase occupational skill attainment by participants, and, as a result improve the quality of the workforce, reduce welfare dependency, and enhance the productivity and competitiveness of the Nation.” The key principles inculcated in the Act are: • Streamlining services; • Empowering individuals; • Universal access; • Increased accountability; • New roles for local boards; • State and local flexibility; • Improved youth programs. The purpose of Title II, The Adult Education and Family Literacy Act (AEFLA), of the Workforce Investment Act of 1998 is to create a partnership among the federal government, states, and localities to provide, on a voluntary basis, adult education and literacy services in order to: • Assist adults become literate and obtain the knowledge and skills necessary for employment and self-sufficiency; • Assist adults who are parents obtain the educational skills necessary to become full partners in the educational development of their children; • Assist adults in the completion of a secondary school education. Adult education is an important part of the workforce investment system. Title II restructures and improves programs previously authorized by the Adult Education Act. AEFLA focuses on strengthening program quality by requiring States to give priority in awarding funds to local programs that are based on a solid foundation of research, address the diverse needs of adult learners, and utilize other effective practices and strategies. To promote continuous program involvement and to ensure optimal return on the Federal investment, AEFLA also establishes a State performance accountability system. Under this system, the Secretary and each State must reach agreement on annual levels of performance for a number of “core indicators” specified in the law: • Demonstrated improvements in literacy skill levels in reading, writing, and speaking the English language, numeracy, problem solving, English language acquisition, and other literacy skills. • Placement in, retention in, or completion of postsecondary education, training, unsubsidized employment or career advancement. • Receipt of a secondary school diploma or its recognized equivalent. Iowa’s community college based adult basic education program has implemented a series of proactive strategies in order to effectively and systematically meet the challenges posed by WIA. The Iowa TOPSpro Data Dictionary is a direct result of Iowa’s pro-active efforts in this educational arena.

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The purpose of the Iowa TOPSpro Data Dictionary is to provide a statewide-standardized set of instructions and definitions for coding Tracking Of Programs And Students (TOPSpro) forms and effectively utilizing the TOPSpro software. This document is designed to serve as a companion document to the TOPS Technical Manual produced by the Comprehensive Adult Student Assessment System (CASAS). The data dictionary integrates information from various data systems to provide uniform data sets and definitions that meet local, state and federal reporting mandates. The sources for the data dictionary are: (1) the National Reporting System (NRS) Guidelines, (2) standard practices utilized in Iowa’s adult literacy program, (3) selected definitions from the Workforce Investment Act of 1998, (4) input from the state level Management Information System (MIS) personnel, and (5) selected definitions from other Iowa state agencies.

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Yosemite Valley poses significant rockfall hazard and related risk due to its glacially steepened walls and approximately 4 million visitors annually. To assess rockfall hazard, it is necessary to evaluate the geologic structure that contributes to the destabilization of rockfall sources and locate the most probable future source areas. Coupling new remote sensing techniques (Terrestrial Laser Scanning, Aerial Laser Scanning) and traditional field surveys, we investigated the regional geologic and structural setting, the orientation of the primary discontinuity sets for large areas of Yosemite Valley, and the specific discontinuity sets present at active rockfall sources. This information, combined with better understanding of the geologic processes that contribute to the progressive destabilization and triggering of granitic rock slabs, contributes to a more accurate rockfall susceptibility assessment for Yosemite Valley and elsewhere.

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Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.

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since 1999 data from pulmonary hypertension (PH) patients from all PH centres in Switzerland were prospectively collected. We analyse the epidemiological aspects of these data. PH was defined as a mean pulmonary artery pressure of >25 mm Hg at rest or >30 mm Hg during exercise. Patients with pulmonary arterial hypertension (PAH), PH associated with lung diseases, PH due to chronic thrombotic and/or embolic disease (CTEPH), or PH due to miscellaneous disorders were registered. Data from adult patients included between January 1999 and December 2004 were analysed. 250 patients were registered (age 58 +/- 16 years, 104 (41%) males). 152 patients (61%) had PAH, 73 (29%) had CTEPH and 18 (7%) had PH associated with lung disease. Patients <50 years (32%) were more likely to have PAH than patients >50 years (76% vs. 53%, p <0.005). Twenty-four patients (10%) were lost to followup, 58 patients (26%) died and 150 (66%) survived without transplantation or thrombendarterectomy. Survivors differed from patients who died in the baseline six-minute walking distance (400 m [300-459] vs. 273 m [174-415]), the functional impairment (NYHA class III/IV 86% vs. 98%), mixed venous saturation (63% [57-68] vs. 56% [50-61]) and right atrial pressure (7 mm Hg [4-11] vs. 11 mm Hg [4-18]). PH is a disease affecting adults of all ages. The management of these patients in specialised centres guarantees a high quality of care. Analysis of the registry data could be an instrument for quality control and might help identify weak points in assessment and treatment of these patients.