910 resultados para Classification of causes of death


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Az egyes nemzetek számviteli szabályozásának vizsgálatánál az adott ország sajátosságaiból eredően részben eltérő szabályozások alakultak ki. Az induktív megközelítésű vizsgálatok jellemzően a szabályozási kérdések széles körét fogják át, de csak néhány tényező mentén közelítve. A cash flow-kimutatások témakörénél a legtöbbször csak azt nézték, hogy van-e előírás a kimutatás elkészítésére, de a részletekkel már kevésbé foglalkoztak. Ebből adódóan e területen viszonylag kis különbséget mutattak ki ezek a felmérések. A szerző kutatása szerint a nemzeti cash flow-kimutatások szabályozásának részleteiben eltérések tapasztalhatók, és ezek alapján a nemzetek klaszterelemzéssel hierarchikusan csoportokba rendezhetők. _____ Research has found that as a result of their particularities, different countries have established partly different accounting frameworks. Studies with inductive approaches typically encompass a wide range of regulatory issues, but based on a limited number of factors only. In the case of Statements of Cash Flows, most studies have so far only examined the existence of rules governing the presentation of the statement, without an in-depth analysis of the details. Therefore, these studies only found relatively minor differences in this field. The author’s research shows that many differences exist in the details of national Cash Flow Statement regulations, which makes it possible to classify the countries in groups using the method of hierarchical clustering.

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Az utóbbi évtizedekben egyre gyakrabban merült fel a közszolgálati szervezetek értékelésének igénye, és egyre újabb módszerek jelentek meg, amelyek felvetették ezek rendszerezésének szükségességét mind a gyakorlatban, mind a kutatásokban. A szerző a szakirodalomban fellelhető osztályozási kísérleteknek és az értékelés szakterülete szempontjainak figyelembevételével javaslatot tesz a közszolgálati szervezetek értékelési módszereinek osztályozási keretrendszerére. Az osztályozási szempontok között szerepel az értékelő helyzete, az értékelés szerepe és a megismerés módszere. Az osztályozási keretrendszer tartalmát a szerző példákkal is illusztrálja, amely jelzi a modell gyakorlati alkalmazhatóságát. Ugyanakkor a keretrendszer a kutatások fókuszának és érvényességi körének meghatározásában is segítséget nyújthat. _____ In the last decades the need of the evaluation of public sector organizations has emerged more and more often, and many new methods have shown up that has raised the need of their classification in practice and in research, as well. Based on literature review and the literature of evaluation the author makes a proposal on the classification framework of the evaluation methods of public sector organizations. The dimensions of the classification include the situation of evaluator, the role of evaluation and the approach of knowledge. The author illustrates the content of the framework with examples referring to the applicability of the model in practice. At the same time, the framework is also useful in determining the focus or the scope of research projects.

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Death qualification is a part of voir dire that is unique to capital trials. Unlike all other litigation, capital jurors must affirm their willingness to impose both legal standards (either life in prison or the death penalty). Jurors who assert they are able to do so are deemed “death-qualified” and are eligible for capital jury service: jurors who assert that they are unable to do so are deemed “excludable” or “scrupled” and are barred from hearing a death penalty case. During the penalty phase in capital trials, death-qualified jurors weigh the aggravators (i.e., arguments for death) against the mitigators (i.e., arguments for life) in order to determine the sentence. If the aggravating circumstances outweigh the mitigating circumstances, then the jury is to recommend death; if the mitigating circumstances outweigh the aggravating circumstances, then the jury is to recommend life. The jury is free to weigh each aggravating and mitigating circumstance in any matter they see fit. Previous research has found that death qualification impacts jurors' receptiveness to aggravating and mitigating circumstances (e.g., Luginbuhl & Middendorf, 1988). However, these studies utilized the now-defunct Witherspoon rule and did not include a case scenario for participants to reference. The purpose of this study was to investigate whether death qualification affects jurors' endorsements of aggravating and mitigating circumstances when Witt, rather than Witherspoon, is the legal standard for death qualification. Four hundred and fifty venirepersons from the 11 th Judicial Circuit in Miami, Florida completed a booklet of stimulus materials that contained the following: two death qualification questions; a case scenario that included a summary of the guilt and penalty phases of a capital case; a 26-item measure that required participants to endorse aggravators, nonstatutory mitigators, and statutory mitigators on a 6-point Likert scale; and standard demographic questions. Results indicated that death-qualified venirepersons, when compared to excludables, were more likely to endorse aggravating circumstances. Excludable participants, when compared to death-qualified venirepersons, were more likely to endorse nonstatutory mitigators. There was no significant difference between death-qualified and excludable venirepersons with respect to their endorsement of 6 out of 7 statutory mitigators. It would appear that the Furman v. Georgia (1972) decision to declare the death penalty unconstitutional is frustrated by the Lockhart v. McCree (1986) affirmation of death qualification. ^

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Cardiac troponin I (cTnI) is one of the most useful serum marker test for the determination of myocardial infarction (MI). The first commercial assay of cTnI was released for medical use in the United States and Europe in 1995. It is useful in determining if the source of chest pains, whose etiology may be unknown, is cardiac related. Cardiac TnI is released into the bloodstream following myocardial necrosis (cardiac cell death) as a result of an infarct (heart attack). In this research project the utility of cardiac troponin I as a potential marker for the determination of time of death is investigated. The approach of this research is not to investigate cTnI degradation in serum/plasma, but to investigate the proteolytic breakdown of this protein in heart tissue postmortem. If our hypothesis is correct, cTnI might show a distinctive temporal degradation profile after death. This temporal profile may have potential as a time of death marker in forensic medicine. The field of time of death markers has lagged behind the great advances in technology since the late 1850's. Today medical examiners are using rudimentary time of death markers that offer limited reliability in the medico-legal arena. Cardiac TnI must be stabilized in order to avoid further degradation by proteases in the extraction process. Chemically derivatized magnetic microparticles were covalently linked to anti-cTnI monoclonal antibodies. A charge capture approach was also used to eliminate the antibody from the magnetic microparticles given the negative charge on the microparticles. The magnetic microparticles were used to extract cTnI from heart tissue homogenate for further bio-analysis. Cardiac TnI was eluted from the beads with a buffer and analyzed. This technique exploits banding pattern on sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) followed by a western blot transfer to polyvinylidene fluoride (PVDF) paper for probing with anti-cTnI monoclonal antibodies. Bovine hearts were used as a model to establish the relationship of time of death and concentration/band-pattern given its homology to human cardiac TnI. The final concept feasibility was tested with human heart samples from cadavers with known time of death. ^

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This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gaussian distributions through a novel concept that relates the Fisher distance to the percentage of data overlap. The derivations are expanded to provide a generalized mathematical platform for determining an optimal separating boundary of Gaussian distributions in multiple dimensions. Real-world data used for implementation and in carrying out feasibility studies were provided by Beckman-Coulter. It is noted that although the data used is flow cytometric in nature, the mathematics are general in their derivation to include other types of data as long as their statistical behavior approximate Gaussian distributions. ^ Because this new figure of merit is heavily based on the statistical nature of the data, a new filtering technique is introduced to accommodate for the accumulation process involved with histogram data. When data is accumulated into a frequency histogram, the data is inherently smoothed in a linear fashion, since an averaging effect is taking place as the histogram is generated. This new filtering scheme addresses data that is accumulated in the uneven resolution of the channels of the frequency histogram. ^ The qualitative interpretation of flow cytometric data is currently a time consuming and imprecise method for evaluating histogram data. This method offers a broader spectrum of capabilities in the analysis of histograms, since the figure of merit derived in this dissertation integrates within its mathematics both a measure of similarity and the percentage of overlap between the distributions under analysis. ^

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Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^

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South Florida’s watersheds have endured a century of urban and agricultural development and disruption of their hydrology. Spatial characterization of South Florida’s estuarine and coastal waters is important to Everglades’ restoration programs. We applied Factor Analysis and Hierarchical Clustering of water quality data in tandem to characterize and spatially subdivide South Florida’s coastal and estuarine waters. Segmentation rendered forty-four biogeochemically distinct water bodies whose spatial distribution is closely linked to geomorphology, circulation, benthic community pattern, and to water management. This segmentation has been adopted with minor changes by federal and state environmental agencies to derive numeric nutrient criteria.

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A comprehensive, broadly accepted vegetation classification is important for ecosystem management, particularly for planning and monitoring. South Florida vegetation classification systems that are currently in use were largely arrived at subjectively and intuitively with the involvement of experienced botanical observers and ecologists, but with little support in terms of quantitative field data. The need to develop a field data-driven classification of South Florida vegetation that builds on the ecological organization has been recognized by the National Park Service and vegetation practitioners in the region. The present work, funded by the National Park Service Inventory and Monitoring Program - South Florida/Caribbean Network (SFCN), covers the first stage of a larger project whose goal is to apply extant vegetation data to test, and revise as necessary, an existing, widely used classification (Rutchey et al. 2006). The objectives of the first phase of the project were (1) to identify useful existing datasets, (2) to collect these data and compile them into a geodatabase, (3) to conduct an initial classification analysis of marsh sites, and (4) to design a strategy for augmenting existing information from poorly represented landscapes in order to develop a more comprehensive south Florida classification.

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The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

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Acknowledgements The authors thank the crews, fishers, and scientists who conducted the various surveys from which data were obtained. This work was supported by the Government of South Georgia and South Sandwich Islands. Additional logistical support provided by The South Atlantic Environmental Research Institute, with thanks to Paul Brickle. PF receives funding from the MASTS pooling initiative (TheMarine Alliance for Science and Technology for Scotland), and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. SF is funded by the Natural Environment Research Council, and data were provided from the British Antarctic Survey Ecosystems Long-term Monitoring and Surveys programme as part of the BAS Polar Science for Planet Earth Programme. The authors also thank the anonymous referees for their helpful suggestions on an earlier version of this manuscript.

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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

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This dissertation focuses on two vital challenges in relation to whale acoustic signals: detection and classification.

In detection, we evaluated the influence of the uncertain ocean environment on the spectrogram-based detector, and derived the likelihood ratio of the proposed Short Time Fourier Transform detector. Experimental results showed that the proposed detector outperforms detectors based on the spectrogram. The proposed detector is more sensitive to environmental changes because it includes phase information.

In classification, our focus is on finding a robust and sparse representation of whale vocalizations. Because whale vocalizations can be modeled as polynomial phase signals, we can represent the whale calls by their polynomial phase coefficients. In this dissertation, we used the Weyl transform to capture chirp rate information, and used a two dimensional feature set to represent whale vocalizations globally. Experimental results showed that our Weyl feature set outperforms chirplet coefficients and MFCC (Mel Frequency Cepstral Coefficients) when applied to our collected data.

Since whale vocalizations can be represented by polynomial phase coefficients, it is plausible that the signals lie on a manifold parameterized by these coefficients. We also studied the intrinsic structure of high dimensional whale data by exploiting its geometry. Experimental results showed that nonlinear mappings such as Laplacian Eigenmap and ISOMAP outperform linear mappings such as PCA and MDS, suggesting that the whale acoustic data is nonlinear.

We also explored deep learning algorithms on whale acoustic data. We built each layer as convolutions with either a PCA filter bank (PCANet) or a DCT filter bank (DCTNet). With the DCT filter bank, each layer has different a time-frequency scale representation, and from this, one can extract different physical information. Experimental results showed that our PCANet and DCTNet achieve high classification rate on the whale vocalization data set. The word error rate of the DCTNet feature is similar to the MFSC in speech recognition tasks, suggesting that the convolutional network is able to reveal acoustic content of speech signals.

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There is a large gap between life expectancy and healthy life years at age 65. To reduce this gap, it is necessary that people with medical concerns perceived at higher risk of adverse outcomes are readily identified and treated. The same goes for the need to implement prevention plans. The main objectives of this study are to, in a first step, (a) estimate the percentage of medical concerns, (b) identify factors associated with this concern; in a second step, (c) estimate the perceived risk of death, and (d) evaluate the ability of medical concerns to predict this risk. Results show that the existence and severity of medical concerns are crucial in the prediction of perceived risk of death. Early identification of severity of medical concerns and the availability and adequacy of informal caregiving should allow healthcare professionals to promptly initiate an appropriate assessment and treatment of older patients.

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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

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Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3 m resolution) with coarse-scale (upto 30 m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes.