52 resultados para Empirical Algorithm Analysis
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The comparative analysis of air quality control policies provides an interesting field for studies of comparative policy analysis including program formulation and implementation processes. In European countries, the problem is comparable, whereas implementation structures, programs and policy impacts vary to a considerable extent. Analysis testing possibilities and constraints of air control policies under varying conditions are likely to contribute to a further development of a theory of policy analysis. This paper presents the analytical framework applied in a continuing empirical study explaining program formulation and implementation processes with respect to the different actors involved. Concrete emitter behavior can be explained by interaction processes at the very local level, by program elements of national legislation, and by structural constraints under which such programs are produced.
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A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .
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Even though architecture principles were first discussed in the 1990s, they are still perceived as an underexplored topic in enterprise architecture management research. By now, there is an increasing consensus about EA principles' nature, as well as guidelines for their formulation. However, the extant literature remains vague about what can be considered suitable EA design and evolution guidance principles. In addition, empirical insights regarding their role and usefulness in practice are still lacking. Accordingly, this research seeks to address three questions: (1) What are suitable principles to guide EA design and evolution? (2) What usage do EA principles have for practitioners? (3) Which propositions can be derived regarding EA principles' role and application? Opting for exploratory research, we apply a research process covering critical analysis of current publications as well as capturing experts' perceptions. Our research ontologically distinguishes between principles from nonprinciples, proposes a validated set of meta-principles, and clarifies principles' application, role, and usefulness in practice. The explored insights can be used as guidelines in defining suitable principles and turning them into an effective bridge between strategy and design and a guide in design decisions.
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This paper aims to provide empirical support for the use of the principal-agent framework in the analysis of public sector and public policies. After reviewing the different conditions to be met for a relevant analysis of the relationship between population and government using the principal-agent theory, our paper focuses on the assumption of conflicting goals between the principal and the agent. A principal-agent analysis assumes in effect that inefficiencies may arise because principal and agent pursue different goals. Using data collected during an amalgamation project of two Swiss municipalities, we show the existence of a gap between the goals of the population and those of the government. Consequently, inefficiencies as predicted by the principal-agent model may arise during the implementation of a public policy, i.e. an amalgamation project. In a context of direct democracy where policies are regularly subjected to referendum, the conflict of objectives may even lead to a total failure of the policy at the polls.
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Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.
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Until recently, the hard X-ray, phase-sensitive imaging technique called grating interferometry was thought to provide information only in real space. However, by utilizing an alternative approach to data analysis we demonstrated that the angular resolved ultra-small angle X-ray scattering distribution can be retrieved from experimental data. Thus, reciprocal space information is accessible by grating interferometry in addition to real space. Naturally, the quality of the retrieved data strongly depends on the performance of the employed analysis procedure, which involves deconvolution of periodic and noisy data in this context. The aim of this article is to compare several deconvolution algorithms to retrieve the ultra-small angle X-ray scattering distribution in grating interferometry. We quantitatively compare the performance of three deconvolution procedures (i.e., Wiener, iterative Wiener and Lucy-Richardson) in case of realistically modeled, noisy and periodic input data. The simulations showed that the algorithm of Lucy-Richardson is the more reliable and more efficient as a function of the characteristics of the signals in the given context. The availability of a reliable data analysis procedure is essential for future developments in grating interferometry.
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We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.
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According to most political scientists and commentators, direct democracy seems to weaken political parties. Our empirical analysis in the 26 Swiss cantons shows that this thesis in its general form cannot be maintained. Political parties in cantons with extensive use of referendums and initiatives are not in all respects weaker than parties in cantons with little use of direct democratic means of participation. On the contrary, direct democracy goes together with more professional and formalized party organizations. Use of direct democracy is associated with more fragmented and volatile party systems, and with greater support for small parties, but causal interpretations of these relationships are difficult.
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Background:¦Infection after total or partial hip arthroplasty (HA) leads to significant long-term morbidity and high healthcare cost. We evaluated reasons for treatment failure of different surgical modalities in a 12-year prosthetic hip joint infection cohort study.¦Method:¦All patients hospitalized at our institution with infected HA were included either retrospectively (1999-‐2007) or prospectively¦(2008-‐2010). HA infection was defined as growth of the same microorganism in ≥2 tissues or synovialfluid culture, visible purulence, sinus tract or acute inflammation on tissue histopathology. Outcome analysis was performed at outpatient visits, followed by contacting patients, their relatives and/or treating physicians afterwards.¦Results:¦During the study period, 117 patients with infected HA were identified. We excluded 2 patients due to missing data. The average age was 69 years (range, 33-‐102 years); 42% were female. HA was mainly performed for osteoarthritis (n=84), followed by trauma (n=22), necrosis (n=4), dysplasia(n=2), rheumatoid arthritis (n=1), osteosarcoma (n=1) and tuberculosis (n=1). 28 infections occurred early(≤3 months), 25 delayed (3-‐24 months) and 63 late (≥24 months after surgery). Infected HA were¦treated with (i) two-‐stage exchange in 59 patients (51%, cure rate: 93%), (ii) one-‐stage exchange in 5 (4.3%, cure rate: 100%), (iii) debridement with change of mobile parts in 18 (17%, cure rate: 83%), (iv) debridement without change of mobile¦parts in 17 (14%, cure rate : 53% ), (v) Girdlestone in 13 (11%, cure rate: 100%), and (vi) two-‐stage exchange followed by¦removal in 3 (2.6%). Patients were followed for an average of 3.9 years (range, 0.1 to 9 years), 7 patients died unrelated to the infected HA. 15 patients (13%) needed additional operations, 1 for mechanical reasons(dislocation of spacer) and 14 for persistent infection: 11 treated with debridement and retention (8 without change; and 3 with change of mobile parts) and 3 with two-‐stage exchange. The average number of surgery was 2.2 (range, 1 to 5). The infection was finally eradicated in all patients, but the functional outcome remained unsatisfactory in 20% (persistent pain or impaired mobility due to spacer or Girdlestone situation).¦Conclusions:¦Non-‐respect of current treatment concept leads to treatment failure with subsequent operations. Precise analysis of each treatment failure can be used for improving the treatment algorithm leading to better results.
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Background and aim of the study: Genomic gains and losses play a crucial role in the development and progression of DLBCL and are closely related to gene expression profiles (GEP), including the germinal center B-cell like (GCB) and activated B-cell like (ABC) cell of origin (COO) molecular signatures. To identify new oncogenes or tumor suppressor genes (TSG) involved in DLBCL pathogenesis and to determine their prognostic values, an integrated analysis of high-resolution gene expression and copy number profiling was performed. Patients and methods: Two hundred and eight adult patients with de novo CD20+ DLBCL enrolled in the prospective multicentric randomized LNH-03 GELA trials (LNH03-1B, -2B, -3B, 39B, -5B, -6B, -7B) with available frozen tumour samples, centralized reviewing and adequate DNA/RNA quality were selected. 116 patients were treated by Rituximab(R)-CHOP/R-miniCHOP and 92 patients were treated by the high dose (R)-ACVBP regimen dedicated to patients younger than 60 years (y) in frontline. Tumour samples were simultaneously analysed by high resolution comparative genomic hybridization (CGH, Agilent, 144K) and gene expression arrays (Affymetrix, U133+2). Minimal common regions (MCR), as defined by segments that affect the same chromosomal region in different cases, were delineated. Gene expression and MCR data sets were merged using Gene expression and dosage integrator algorithm (GEDI, Lenz et al. PNAS 2008) to identify new potential driver genes. Results: A total of 1363 recurrent (defined by a penetrance > 5%) MCRs within the DLBCL data set, ranging in size from 386 bp, affecting a single gene, to more than 24 Mb were identified by CGH. Of these MCRs, 756 (55%) showed a significant association with gene expression: 396 (59%) gains, 354 (52%) single-copy deletions, and 6 (67%) homozygous deletions. By this integrated approach, in addition to previously reported genes (CDKN2A/2B, PTEN, DLEU2, TNFAIP3, B2M, CD58, TNFRSF14, FOXP1, REL...), several genes targeted by gene copy abnormalities with a dosage effect and potential physiopathological impact were identified, including genes with TSG activity involved in cell cycle (HACE1, CDKN2C) immune response (CD68, CD177, CD70, TNFSF9, IRAK2), DNA integrity (XRCC2, BRCA1, NCOR1, NF1, FHIT) or oncogenic functions (CD79b, PTPRT, MALT1, AUTS2, MCL1, PTTG1...) with distinct distribution according to COO signature. The CDKN2A/2B tumor suppressor locus (9p21) was deleted homozygously in 27% of cases and hemizygously in 9% of cases. Biallelic loss was observed in 49% of ABC DLBCL and in 10% of GCB DLBCL. This deletion was strongly correlated to age and associated to a limited number of additional genetic abnormalities including trisomy 3, 18 and short gains/losses of Chr. 1, 2, 19 regions (FDR < 0.01), allowing to identify genes that may have synergistic effects with CDKN2A/2B inactivation. With a median follow-up of 42.9 months, only CDKN2A/2B biallelic deletion strongly correlates (FDR p.value < 0.01) to a poor outcome in the entire cohort (4y PFS = 44% [32-61] respectively vs. 74% [66-82] for patients in germline configuration; 4y OS = 53% [39-72] vs 83% [76-90]). In a Cox proportional hazard prediction of the PFS, CDKN2A/2B deletion remains predictive (HR = 1.9 [1.1-3.2], p = 0.02) when combined with IPI (HR = 2.4 [1.4-4.1], p = 0.001) and GCB status (HR = 1.3 [0.8-2.3], p = 0.31). This difference remains predictive in the subgroup of patients treated by R-CHOP (4y PFS = 43% [29-63] vs. 66% [55-78], p=0.02), in patients treated by R-ACVBP (4y PFS = 49% [28-84] vs. 83% [74-92], p=0.003), and in GCB (4y PFS = 50% [27-93] vs. 81% [73-90], p=0.02), or ABC/unclassified (5y PFS = 42% [28-61] vs. 67% [55-82] p = 0.009) molecular subtypes (Figure 1). Conclusion: We report for the first time an integrated genetic analysis of a large cohort of DLBCL patients included in a prospective multicentric clinical trial program allowing identifying new potential driver genes with pathogenic impact. However CDKN2A/2B deletion constitutes the strongest and unique prognostic factor of chemoresistance to R-CHOP, regardless the COO signature, which is not overcome by a more intensified immunochemotherapy. Patients displaying this frequent genomic abnormality warrant new and dedicated therapeutic approaches.
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BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias and outcome reporting bias have been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. METHODOLOGY/PRINCIPAL FINDINGS: In this update, we review and summarise the evidence from cohort studies that have assessed study publication bias or outcome reporting bias in randomised controlled trials. Twenty studies were eligible of which four were newly identified in this update. Only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Fifteen of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7). In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: This update does not change the conclusions of the review in which 16 studies were included. Direct empirical evidence for the existence of study publication bias and outcome reporting bias is shown. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
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ABSTRACT: BACKGROUND: The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. RESULTS: Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. CONCLUSIONS: Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.
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The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.
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This dissertation analyses public opinion towards the welfare state across 29 European countries. Based on an interdisciplinary approach combining social psychological, sociological, and public opinion approaches to political opinion formation, it investigates how social position and shared beliefs shape perceived legitimacy of welfare institutions, and how social contexts impact on the processes of opinion formation. Drawing on social representations theory, as well as socialization and self-interest approaches, the dissertation analyses the role of social position in lay support for institutional solidarity. Normative beliefs-defined as preferred views regarding the organisation of social relations-mediate the effect of social position on welfare support. In addition, drawing on public opinion literature, the dissertation analyses opinion formation as a function of country-level structural (e.g., level of social spending, unemployment) and ideological factors (e.g., level of meritocracy). The dissertation comprises two theoretical and four empirical chapters. Three of the empirical chapters use data from the European Social Survey 2008. Using multilevel and typological approaches, the dissertation contributes to welfare attitude literature by showing that normative beliefs, such as distrust or egalitarianism, function as underlying mechanisms that link social position to policy attitudes (Chapter 3), and that characteristics of the national contexts influence the processes of political opinion formation (Chapters 3 and 4). Chapter 5 proposes and predicts a typology of the relationship between attitudes towards solidarity and attitudes towards control, reflecting the two central domains of government intervention. Finally, Chapter 6 examines welfare support in the realm of action and social protest, using data from a survey on Spanish Indigados activists. The findings of this dissertation inform contemporary debates about welfare state legitimacy and retrenchment. - Cette thèse avait pour but d'analyser l'opinion publique envers l'Etat social dans 29 pays européens. Basée sur une approche interdisciplinaire qui combine des perspectives psycho-sociales, sociologiques et d'opinion publique sur la formation d'opinion politique, la thèse étudie comment la position sociale et les croyances partagées façonnent la légitimité perçue des institutions de l'Etat social, et comment les contextes sociaux influencent les processus de formation d'opinion. Basée sur la théorie des représentations sociales, ainsi qu'une approche de socialisation et d'intérêt propre, cette thèse analyse le rôle des positions sociales dans le soutien envers la solidarité institutionnelle. Les croyances normatives-définies comme les visions préférées de l'organisation des rapports sociaux-médiatisent l'effet de la position sociale sur le soutien pour l'Etat social. De plus, s'inspirant de la littérature sur l'opinion publique, la thèse analyse la formation d'opinion en fonction des facteurs structurels (ex. le taux de dépenses sociales, le chômage) et idéologiques (ex. le degré de méritocratie). Cette thèse est composée de deux chapitres théoriques et quatre chapitres empiriques. Trois chapitres empiriques utilisent des données provenant de l'enquête European Social Survey 2008. Appliquant des approches multi-niveux et typoloqiques, la thèse contribue à la littérature sur les attitudes envers l'Etat social en montrant que les croyances normatives, telles que la méfiance ou l'égalitarisme, fonctionnent comme des mécanismes sous-jacents qui relient la position sociale aux attitudes politiques (Chapitre 3), et que les caractéristiques des contextes nationaux influencent les processus de formation d'opinion politique (Chapitres 3 et 4). Le chapitre 5 propose et prédit une typologie sur le rapport entre les attitudes envers la solidarité et celles envers le contrôle, renvoyant à deux domaines centraux de régulation étatique. Enfin, le chapitre 6 examine le soutien à l'Etat social dans le domaine de l'action protestataire, utilisant des données d'une enquête menée auprès des militants espagnols du mouvement des Indignés. Les résultats de cette thèse apportent des éléments qui éclairent les débats contemporains sur la légitimité de l'Etat social et son démantèlement.
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The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A distance-based discriminant algorithm and a robust multidimensional centroid estimate illustrate the theory, closely connected to the Gaussian kernels of Machine Learning.