905 resultados para specialized text
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S.O.
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The aim of this dissertation is to provide a translation from English into Italian of a highly specialized scientific article published by the online journal ALTEX. In this text, the authors propose a roadmap for how to overcome the acknowledged scientific gaps for the full replacement of systemic toxicity testing using animals. The main reasons behind this particular choice are my personal interest in specialized translation of scientific texts and in the alternatives to animal testing. Moreover, this translation has been directly requested by the Italian molecular biologist and clinical biochemist Candida Nastrucci. It was not possible to translate the whole article in this project, for this reason, I decided to translate only the introduction, the chapter about skin sensitization, and the conclusion. I intend to use the resources that were created for this project to translate the rest of the article in the near future. In this study, I will show how a translator can translate such a specialized text with the help of a field expert using CAT Tools and a specialized corpus. I will also discuss whether machine translation can prove useful to translate this type of document. This work is divided into six chapters. The first one introduces the main topic of the article and explains my reasons for choosing this text; the second one contains an analysis of the text type, focusing on the differences and similarities between Italian and English conventions. The third chapter provides a description of the resources that were used to translate this text, i.e. the corpus and the CAT Tools. The fourth one contains the actual translation, side-by-side with the original text, while the fifth one provides a general comment on the translation difficulties, an analysis of my translation choices and strategies, and a comment about the relationship between the field expert and the translator. Finally, the last chapter shows whether machine translation and post-editing can be an advantageous strategy to translate this type of document. The project also contains two appendixes. The first one includes 54 complex terminological sheets, while the second one includes 188 simple terminological sheets.
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A tree-based dictionary learning model is developed for joint analysis of imagery and associated text. The dictionary learning may be applied directly to the imagery from patches, or to general feature vectors extracted from patches or superpixels (using any existing method for image feature extraction). Each image is associated with a path through the tree (from root to a leaf), and each of the multiple patches in a given image is associated with one node in that path. Nodes near the tree root are shared between multiple paths, representing image characteristics that are common among different types of images. Moving toward the leaves, nodes become specialized, representing details in image classes. If available, words (text) are also jointly modeled, with a path-dependent probability over words. The tree structure is inferred via a nested Dirichlet process, and a retrospective stick-breaking sampler is used to infer the tree depth and width.
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S.P.I.R.E., at use at Central Institute for the Deaf, is a comprehensive, multi-sensory systematic reading and language program that targets at risk and struggling students. The purpose of this project was to write additional stories and sentences for students who are hearing impaired through reader 2 that may be used in conjunction with the exiting stories and supplements.
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Real-world text classification tasks often suffer from poor class structure with many overlapping classes and blurred boundaries. Training data pooled from multiple sources tend to be inconsistent and contain erroneous labelling, leading to poor performance of standard text classifiers. The classification of health service products to specialized procurement classes is used to examine and quantify the extent of these problems. A novel method is presented to analyze the labelled data by selectively merging classes where there is not enough information for the classifier to distinguish them. Initial results show the method can identify the most problematic classes, which can be used either as a focus to improve the training data or to merge classes to increase confidence in the predicted results of the classifier.
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Objective. This research study had two goals: (1) to describe resource consumption patterns for Medi-Cal children with cystic fibrosis, and (2) to explore the feasibility from a rate design perspective of developing specialized managed care plans for such a special needs population.^ Background. Children with special health care needs (CSHN) comprise about 2% of the California Medicaid pediatric population. CSHN have rare but serious health problems, such as cystic fibrosis. Medicaid programs, including Medi-Cal, are enrolling more and more beneficiaries in managed care to control costs. CSHN, however, do not fit the wellness model underlying most managed care plans. Child health advocates believe that both efficiency and quality will suffer if CSHN are removed from regionalized special care centers and scattered among general purpose plans. They believe that CSHN should be "carved out" from enrollment in general plans. One alternative is the Specialized Managed Care Plan, tailored for CSHN.^ Methods. The study population consisted of children under age 21 with CF who were eligible for Medi-Cal and California Children's Services program (CCS) during 1991. Health Care Financing Administration (HCFA) Medicaid Tape-to-Tape data were analyzed as part of a California Children's Hospital Association (CCHA) project.^ Results. Mean Medi-Cal expenditures per month enrolled were $2,302 for 457 CF children, compared to about \$1,270 for all 47,000 CCS special needs children and roughly $60 for almost 2.6 million ``regular needs'' children. For CF children, inpatient care (80\%) and outpatient drugs (9\%) were the major cost drivers, with {\it all\/} outpatient visits comprising only 2\% of expenditures. About one-third of CF children were eligible due to AFDC (Aid to Families with Dependent Children). Age group explained about 17\% of all expenditure variation. Regression analysis was used to select the best capitation rate structure (rate cells by age and eligibility group). Sensitivity analysis estimated moderate financial risk for a statewide plan (360 enrollees), but severe risk for single county implementation due to small numbers of children.^ Conclusions. Study results support the carve out of CSHN due to unique expenditure patterns. The Specialized Managed Care Plan concept appears feasible from a rate design perspective given sufficient enrollees. ^
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Auditory conditioning (associative learning) causes reorganization of the cochleotopic (frequency) maps of the primary auditory cortex (AI) and the inferior colliculus. Focal electric stimulation of the AI also evokes basically the same cortical and collicular reorganization as that caused by conditioning. Therefore, part of the neural mechanism for the plasticity of the central auditory system caused by conditioning can be explored by focal electric stimulation of the AI. The reorganization is due to shifts in best frequencies (BFs) together with shifts in frequency-tuning curves of single neurons. In the AI of the Mongolian gerbil (Meriones unguiculatus) and the posterior division of the AI of the mustached bat (Pteronotus parnellii), focal electric stimulation evokes BF shifts of cortical auditory neurons located within a 0.7-mm distance along the frequency axis. The amount and direction of BF shift differ depending on the relationship in BF between stimulated and recorded neurons, and between the gerbil and mustached bat. Comparison in BF shift between different mammalian species and between different cortical areas of a single species indicates that BF shift toward the BF of electrically stimulated cortical neurons (centripetal BF shift) is common in the AI, whereas BF shift away from the BF of electrically stimulated cortical neurons (centrifugal BF shift) is special. Therefore, we propose a hypothesis that reorganization, and accordingly organization, of cortical auditory areas caused by associative learning can be quite different between specialized and nonspecialized (ordinary) areas of the auditory cortex.
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The goal of the project is to analyze, experiment, and develop intelligent, interactive and multilingual Text Mining technologies, as a key element of the next generation of search engines, systems with the capacity to find "the need behind the query". This new generation will provide specialized services and interfaces according to the search domain and type of information needed. Moreover, it will integrate textual search (websites) and multimedia search (images, audio, video), it will be able to find and organize information, rather than generating ranked lists of websites.
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In the article relevance of system development for subject search using computational linguistics is considered. The basic principles of system functioning are defined. The principle of grammar development for information retrieval from the partially structured text in a natural language is considered. The ranging principle of results of information search is defined.
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National Highway Traffic Safety Administration, Washington, D.C.
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National Highway Traffic Safety Administration, Washington, D.C.
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Publication date stamped on t.p.
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"December 1957."
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May 1980.