942 resultados para Projects Analysis


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This paper analyzes and evaluates, in the context of Ontology learning, some techniques to identify and extract candidate terms to classes of a taxonomy. Besides, this work points out some inconsistencies that may be occurring in the preprocessing of text corpus, and proposes techniques to obtain good terms candidate to classes of a taxonomy.

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Morphological descriptors are practical and essential biomarkers for diagnosis andtreatment selection for intracranial aneurysm management according to the current guidelinesin use. Nevertheless, relatively little work has been dedicated to improve the three-dimensionalquanti cation of aneurysmal morphology, automate the analysis, and hence reduce the inherentintra- and inter-observer variability of manual analysis. In this paper we propose a methodologyfor the automated isolation and morphological quanti cation of saccular intracranial aneurysmsbased on a 3D representation of the vascular anatomy.

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[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

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[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

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[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

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The following data was derived from 1391 reports of participating contractors for the annual 2002 through 2011 reporting periods. The workforce data is reflective of one peak work week for highway contractors during the most active time of the season, the last full week of July. The summary data on pages 4 and 5 was compiled by Iowa DOT staff from the 1391 reports received. Interesting changes and trends have been addressed in the written analysis.

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The Bridges Decision Support Model is a geographic information system (GIS) that assembles existing data on archaeological sites, surveys, and their geologic contexts to assess the risk of bridge replacement projects encountering 13,000- to 150-year-old Native American sites. This project identifies critical variables for assessing prehistoric sites potential, examines the quality of available data about the variables, and applies the data to creating a decision support framework for use by the Iowa Department of Transportation (Iowa DOT) and others. An analysis of previous archaeological surveys indicates that subsurface testing to discover buried sites became increasingly common after 1980, but did not become routine until after the adoption of guidelines recommending such testing, in 1993. Even then, the average depth of testing has been relatively shallow. Alluvial deposits of sufficient age, deposited in depositional environments conducive to human habitation, are considerably thicker than archaeologists have routinely tested.

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In response to the mandate on Load and Resistance Factor Design (LRFD) implementations by the Federal Highway Administration (FHWA) on all new bridge projects initiated after October 1, 2007, the Iowa Highway Research Board (IHRB) sponsored these research projects to develop regional LRFD recommendations. The LRFD development was performed using the Iowa Department of Transportation (DOT) Pile Load Test database (PILOT). To increase the data points for LRFD development, develop LRFD recommendations for dynamic methods, and validate the results ofLRFD calibration, 10 full-scale field tests on the most commonly used steel H-piles (e.g., HP 10 x 42) were conducted throughout Iowa. Detailed in situ soil investigations were carried out, push-in pressure cells were installed, and laboratory soil tests were performed. Pile responses during driving, at the end of driving (EOD), and at re-strikes were monitored using the Pile Driving Analyzer (PDA), following with the CAse Pile Wave Analysis Program (CAPWAP) analysis. The hammer blow counts were recorded for Wave Equation Analysis Program (WEAP) and dynamic formulas. Static load tests (SLTs) were performed and the pile capacities were determined based on the Davisson’s criteria. The extensive experimental research studies generated important data for analytical and computational investigations. The SLT measured loaddisplacements were compared with the simulated results obtained using a model of the TZPILE program and using the modified borehole shear test method. Two analytical pile setup quantification methods, in terms of soil properties, were developed and validated. A new calibration procedure was developed to incorporate pile setup into LRFD.

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Accurate prediction of transcription factor binding sites is needed to unravel the function and regulation of genes discovered in genome sequencing projects. To evaluate current computer prediction tools, we have begun a systematic study of the sequence-specific DNA-binding of a transcription factor belonging to the CTF/NFI family. Using a systematic collection of rationally designed oligonucleotides combined with an in vitro DNA binding assay, we found that the sequence specificity of this protein cannot be represented by a simple consensus sequence or weight matrix. For instance, CTF/NFI uses a flexible DNA binding mode that allows for variations of the binding site length. From the experimental data, we derived a novel prediction method using a generalised profile as a binding site predictor. Experimental evaluation of the generalised profile indicated that it accurately predicts the binding affinity of the transcription factor to natural or synthetic DNA sequences. Furthermore, the in vitro measured binding affinities of a subset of oligonucleotides were found to correlate with their transcriptional activities in transfected cells. The combined computational-experimental approach exemplified in this work thus resulted in an accurate prediction method for CTF/NFI binding sites potentially functioning as regulatory regions in vivo.

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Highway Research Project HR-392 was undertaken to evaluate cold in-place asphalt recycled (CIR) projects in the State of Iowa. The research involved assessment of performance levels, investigation of factors that most influence pavement performance and economy, and development of guidelines for CIR project selection. The performance was evaluated in two ways: Pavement Condition Indices (PCI, U.S. Corps of Engineers) were calculated and overall ratings were given on ride and appearance. A regression analysis was extrapolated to predict the future service life of CIR roads. The results were that CIR roads within the State of Iowa, with less than 2000 annual average daily traffic (AADT), have an average predicted service life of fifteen to twenty-six years. Subgrade stability problems can prevent a CIR project from being successfully constructed. A series of Dynamic Cone Penetrometer (DCP) tests were conducted on a CIR project that experienced varying levels of subgrade failure during construction. Based on this case study, and supporting data, it was determined that the DCP test can be used to evaluate subgrades that have insufficient stability for recycling. Overall, CIR roads in Iowa are performing well. It appears that the development of transverse cracking has been retarded and little rutting has occurred. Contracting agencies must pay special attention to the subgrade conditions during project selection. Because of its performance, CIR is a recommended method to be considered for rehabilitating aged low volume (<2000 AADT) asphalt concrete roads in Iowa.

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In response to the mandate on Load and Resistance Factor Design (LRFD) implementations by the Federal Highway Administration (FHWA) on all new bridge projects initiated after October 1, 2007, the Iowa Highway Research Board (IHRB) sponsored these research projects to develop regional LRFD recommendations. The LRFD development was performed using the Iowa Department of Transportation (DOT) Pile Load Test database (PILOT). To increase the data points for LRFD development, develop LRFD recommendations for dynamic methods, and validate the results of LRFD calibration, 10 full-scale field tests on the most commonly used steel H-piles (e.g., HP 10 x 42) were conducted throughout Iowa. Detailed in situ soil investigations were carried out, push-in pressure cells were installed, and laboratory soil tests were performed. Pile responses during driving, at the end of driving (EOD), and at re-strikes were monitored using the Pile Driving Analyzer (PDA), following with the CAse Pile Wave Analysis Program (CAPWAP) analysis. The hammer blow counts were recorded for Wave Equation Analysis Program (WEAP) and dynamic formulas. Static load tests (SLTs) were performed and the pile capacities were determined based on the Davisson’s criteria. The extensive experimental research studies generated important data for analytical and computational investigations. The SLT measured load-displacements were compared with the simulated results obtained using a model of the TZPILE program and using the modified borehole shear test method. Two analytical pile setup quantification methods, in terms of soil properties, were developed and validated. A new calibration procedure was developed to incorporate pile setup into LRFD.

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US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

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Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

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Liikevaihdon orgaaninen kasvu on ensisijainen tekijä ja haaste yritysjohdolle yrityksen omistaja-arvon kasvattamiseksi. Tutkimus tarkastelee suosivatko suomalaisyritykset pääasiallisesti olemassa olevaa liiketoimintaa palvelevia innovaatioita vai tukevatko nykyhetken toimintatavat myös uusia kasvua kiihdyttäviä radikaaleja innovaatioita. Lisäksi työ kartoitti suomalaisyritysten innovaatioprosessien kehitysalueita käyttäen itsearviointitutkimusta.Tulokset johtivat kolmeen johtopäätökseen. Tutkimus osoitti, että vastaajayritykset ovat keskittyneet innovaatiotoiminnassaan vahvasti ydinliiketoimintaansa, jättäen potentiaaliset kasvumahdollisuudet huomioimatta. Yritykset tavoittelevat maksimaalisia tuottoja keskittymällä tuotteidensa korkeaan suorituskykyyn. Lyhyen aikavälin epärealistiset tuotto-odotukset sekä projekteille suunnatut arviointikriteerit rajoittavat liiketoimintaa mullistavien radikaalien innovaatioiden kehittymistä organisaatiossa. Toiseksi, tutkimus osoitti, että suuri osa yrityksistä käyttää perinteisen projektien arviointi- ja kehitysprosessin lisäksi vaihtoehtoisia ja huonosti kontrolloitavissa olevia kehitysprosesseja, mikäli projektille annetaan kielteinen rahoituspäätös standardin prosessin sisällä. Kolmanneksi, suomalaisyritysten innovaatioprosesseissa paljastui merkittäviä puutteita mitattavien elementtien suhteen.

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The topic of this thesis is studying how lesions in retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. Methods for equalizing uneven illumination in fundus images, detecting regions of poor image quality due toinadequate illumination, and recognizing abnormal lesions were developed duringthe work. The developed methods exploit mainly the color information and simpleshape features to detect lesions. In addition, a graphical tool for collecting lesion data was developed. The tool was used by an ophthalmologist who marked lesions in the images to help method development and evaluation. The tool is a general purpose one, and thus it is possible to reuse the tool in similar projects.The developed methods were tested with a separate test set of 128 color fundus images. From test results it was calculated how accurately methods classify abnormal funduses as abnormal (sensitivity) and healthy funduses as normal (specificity). The sensitivity values were 92% for hemorrhages, 73% for red small dots (microaneurysms and small hemorrhages), and 77% for exudates (hard and soft exudates). The specificity values were 75% for hemorrhages, 70% for red small dots, and 50% for exudates. Thus, the developed methods detected hemorrhages accurately and microaneurysms and exudates moderately.