Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

Quality assessment of a landslide inventory map and its application to land���use planning. A case study in the Northern Apennines (Emilia���Romagna region, Italy)

Landslide hazard and risk are growing as a consequence of climate change and demographic pressure. Land���use planning represents a powerful tool to manage this socio���economic problem and build sustainable and landslide resilient communities. Landslide inventory maps are a cornerstone of land���use planning and, consequently, their quality assessment represents a burning issue. This work aimed to define the quality parameters of a landslide inventory and assess its spatial and temporal accuracy with regard to its possible applications to land���use planning. In this sense, I proceeded according to a two���steps approach. An overall assessment of the accuracy of data geographic positioning was performed on four case study sites located in the Italian Northern Apennines. The quantification of the overall spatial and temporal accuracy, instead, focused on the Dorgola Valley (Province of Reggio Emilia). The assessment of spatial accuracy involved a comparison between remotely sensed and field survey data, as well as an innovative fuzzylike analysis of a multi���temporal landslide inventory map. Conversely, long��� and short���term landslide temporal persistence was appraised over a period of 60 years with the aid of 18 remotely sensed image sets. These results were eventually compared with the current Territorial Plan for Provincial Coordination (PTCP) of the Province of Reggio Emilia. The outcome of this work suggested that geomorphologically detected and mapped landslides are a significant approximation of a more complex reality. In order to convey to the end���users this intrinsic uncertainty, a new form of cartographic representation is needed. In this sense, a fuzzy raster landslide map may be an option. With regard to land���use planning, landslide inventory maps, if appropriately updated, confirmed to be essential decision���support tools. This research, however, proved that their spatial and temporal uncertainty discourages any direct use as zoning maps, especially when zoning itself is associated to statutory or advisory regulations.

Citizen science as a tool for the environmental quality assessment of the Mediterranean coastal habitats

The growing need to assess the environmental status of the Mediterranean coastal marine habitats and the large availability of data collected by Reef Check Italia onlus (RCI) volunteers suggest the possibility to develop innovative and reliable indices that may support decision makers in applying conservation strategies. The aims of this study were to check the reliability of data collected by RCI volunteers, analyse the spatial and temporal distribution of RCI available data, resume the knowledge on the biology and ecology of the monitored species, and develop innovative indices to asses the ecological quality of Mediterranean subtidal rocky shores and coralligenous habitats. Subtidal rocky shores and coralligenous were chosen because these are the habitats more attractive for divers; therefore mlst data are referring to them, moreover subtidal rocky bottom are strongly affected by coastal urbanisation, land use, fishing and tourist activities, that increase pollution, turbidity and sedimentation. Non-indigenous species (NIS) have been recognized as a major threat to the integrity of Mediterranean native communities because of their proliferation, spread and impact on resident communities. Monitoring of NIS��� spreading dynamics at the basin spatial scale is difficult but urgent. According to a field test, the training provided by RCI appears adequate to obtain reliable data by volunteers. Based on data collected by RCI volunteers, three main categories of indices were developed: indices based on species diversity, indices on the occurrence non-indigenous species, and indices on species sensitive toward physical, chemical and biological disturbances. As case studies, indices were applied to stretches of coastline defined according to management criteria (province territories and marine protected areas). The assessments of ecological quality in the Tavolara Marine Protected Area using the species sensitivities index were consisten with those previously obtained with traditional methods.

Data Quality Assessment of Ungated Flow Cytometry Data in High

Background: The recent development of semi-automated techniques for staining and analyzing flow cytometry samples has presented new challenges. Quality control and quality assessment are critical when developing new high throughput technologies and their associated information services. Our experience suggests that significant bottlenecks remain in the development of high throughput flow cytometry methods for data analysis and display. Especially, data quality control and quality assessment are crucial steps in processing and analyzing high throughput flow cytometry data. Methods: We propose a variety of graphical exploratory data analytic tools for exploring ungated flow cytometry data. We have implemented a number of specialized functions and methods in the Bioconductor package rflowcyt. We demonstrate the use of these approaches by investigating two independent sets of high throughput flow cytometry data. Results: We found that graphical representations can reveal substantial non-biological differences in samples. Empirical Cumulative Distribution Function and summary scatterplots were especially useful in the rapid identification of problems not identified by manual review. Conclusions: Graphical exploratory data analytic tools are quick and useful means of assessing data quality. We propose that the described visualizations should be used as quality assessment tools and where possible, be used for quality control.

Monitoring and data quality assessment of the ATLAS liquid argon calorimeter

The liquid argon calorimeter is a key component of the ATLAS detector installed at the CERN Large Hadron Collider. The primary purpose of this calorimeter is the measurement of electron and photon kinematic properties. It also provides a crucial input for measuring jets and missing transverse momentum. An advanced data monitoring procedure was designed to quickly identify issues that would affect detector performance and ensure that only the best quality data are used for physics analysis. This article presents the validation procedure developed during the 2011 and 2012 LHC data-taking periods, in which more than 98% of the proton-proton luminosity recorded by ATLAS at a centre-of-mass energy of 7���8 TeV had calorimeter data quality suitable for physics analysis.

Using Provenance for Quality Assessment and Repair in Linked Open Data

As the number of data sources publishing their data on the Web of Data is growing, we are experiencing an immense growth of the Linked Open Data cloud. The lack of control on the published sources, which could be untrustworthy or unreliable, along with their dynamic nature that often invalidates links and causes conflicts or other discrepancies, could lead to poor quality data. In order to judge data quality, a number of quality indicators have been proposed, coupled with quality metrics that quantify the ���quality level��� of a dataset. In addition to the above, some approaches address how to improve the quality of the datasets through a repair process that focuses on how to correct invalidities caused by constraint violations by either removing or adding triples. In this paper we argue that provenance is a critical factor that should be taken into account during repairs to ensure that the most reliable data is kept. Based on this idea, we propose quality metrics that take into account provenance and evaluate their applicability as repair guidelines in a particular data fusion setting.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Water-quality assessment of the Lower Susquehanna River Basin, Pennsylvania and Maryland : sources, characteristics, anaylsis, and limitations of nutrient and suspended-seditment data, 1975-90 /

"National Water-Quality Assessment Program"

Data warehouse para el Centro de Documentaci��n Regional "Juan Bautista V��zquez"

El proceso de toma de decisiones en las bibliotecas universitarias es de suma importancia, sin embargo, se encuentra complicaciones como la gran cantidad de fuentes de datos y los grandes vol��menes de datos a analizar. Las bibliotecas universitarias est��n acostumbradas a producir y recopilar una gran cantidad de informaci��n sobre sus datos y servicios. Las fuentes de datos comunes son el resultado de sistemas internos, portales y cat��logos en l��nea, evaluaciones de calidad y encuestas. Desafortunadamente estas fuentes de datos s��lo se utilizan parcialmente para la toma de decisiones debido a la amplia variedad de formatos y est��ndares, as�� como la falta de m��todos eficientes y herramientas de integraci��n. Este proyecto de tesis presenta el an��lisis, dise��o e implementaci��n del Data Warehouse, que es un sistema integrado de toma de decisiones para el Centro de Documentaci��n Juan Bautista V��zquez. En primer lugar se presenta los requerimientos y el an��lisis de los datos en base a una metodolog��a, esta metodolog��a incorpora elementos claves incluyendo el an��lisis de procesos, la calidad estimada, la informaci��n relevante y la interacci��n con el usuario que influyen en una decisi��n bibliotecaria. A continuaci��n, se propone la arquitectura y el dise��o del Data Warehouse y su respectiva implementaci��n la misma que soporta la integraci��n, procesamiento y el almacenamiento de datos. Finalmente los datos almacenados se analizan a trav��s de herramientas de procesamiento anal��tico y la aplicaci��n de t��cnicas de Bibliomining ayudando a los administradores del centro de documentaci��n a tomar decisiones ��ptimas sobre sus recursos y servicios.

Desenho e implementa����o de um data warehouse para a empresa AdClick

Esta disserta����o incide sobre a problem��tica da constru����o de um data warehouse para a empresa AdClick que opera na ��rea de marketing digital. O marketing digital �� um tipo de marketing que utiliza os meios de comunica����o digital, com a mesma finalidade do m��todo tradicional que se traduz na divulga����o de bens, neg��cios e servi��os e a angaria����o de novos clientes. Existem diversas estrat��gias de marketing digital tendo em vista atingir tais objetivos, destacando-se o tr��fego org��nico e tr��fego pago. Onde o tr��fego org��nico �� caracterizado pelo desenvolvimento de a����es de marketing que n��o envolvem quaisquer custos inerentes �� divulga����o e/ou angaria����o de potenciais clientes. Por sua vez o tr��fego pago manifesta-se pela necessidade de investimento em campanhas capazes de impulsionar e atrair novos clientes. Inicialmente �� feita uma abordagem do estado da arte sobre business intelligence e data warehousing, e apresentadas as suas principais vantagens as empresas. Os sistemas business intelligence s��o necess��rios, porque atualmente as empresas det��m elevados volumes de dados ricos em informa����o, que s�� ser��o devidamente explorados fazendo uso das potencialidades destes sistemas. Nesse sentido, o primeiro passo no desenvolvimento de um sistema business intelligence �� concentrar todos os dados num sistema ��nico integrado e capaz de dar apoio na tomada de decis��es. �� ent��o aqui que encontramos a constru����o do data warehouse como o sistema ��nico e ideal para este tipo de requisitos. Nesta disserta����o foi elaborado o levantamento das fontes de dados que ir��o abastecer o data warehouse e iniciada a contextualiza����o dos processos de neg��cio existentes na empresa. Ap��s este momento deu-se in��cio �� constru����o do data warehouse, cria����o das dimens��es e tabelas de factos e defini����o dos processos de extra����o e carregamento dos dados para o data warehouse. Assim como a cria����o das diversas views. Relativamente ao impacto que esta disserta����o atingiu destacam-se as diversas vantagem a n��vel empresarial que a empresa parceira neste trabalho retira com a implementa����o do data warehouse e os processos de ETL para carregamento de todas as fontes de informa����o. Sendo que algumas vantagens s��o a centraliza����o da informa����o, mais flexibilidade para os gestores na forma como acedem �� informa����o. O tratamento dos dados de forma a ser poss��vel a extra����o de informa����o a partir dos mesmos.

External quality assessment in the voluntary counseling and testing centers in the Brazilian Amazon using dried tube specimens: results of an effectiveness evaluation

INTRODUCTION : In 2011, the Brazilian Ministry of Health rolled out a program for the external quality assessment of rapid human immunodeficiency virus (HIV) tests using the dried tube specimen (DTS) method (EQA-RT/DTS-HIV). Our objective was to evaluate the implementation of this program at 71 voluntary counseling and testing centers (VCTCs) in the Brazilian Legal Amazonian area one year after its introduction. METHODS : Quantitative and qualitative study that analyzed secondary data and interviews with healthcare workers (HCWs) (n=39) and VCTC coordinators (n=32) were performed. The assessment used 18 key indicators to evaluate the three dimensions of the program's logical framework: structure, process, and result. Each indicator was scored from 1-4, and the aggregate results corresponding to the dimensions were expressed as proportions. The results were compared to the perceptions of the HCWs and coordinators regarding the EQA-RT/DTS-HIV program. RESULTS: The aggregate scores for the three dimensions of structure, process, and result were 91.7%, 78.6%, and 95%, respectively. The lowest score in each dimension corresponded to a different indicator: access to Quali-TR online system 39% (structure), registration in Quali-TR online system 38.7% (process), and VCTC completed the full process in the program's first round 63.4% (result). Approximately 36% of the HCWs and 52% of the coordinators reported enhanced trust in the program for its rapid HIV testing performance. CONCLUSIONS: All three program dimensions exhibited satisfactory results (>75%). Nevertheless, the study findings highlight the need to improve certain program components. Additionally, long-term follow-ups is needed to provide a more thorough picture of the process for external quality assessment.

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.

Using balanced scorecards to evaluate the data warehouse system utility

Disserta����o de mestrado em Systems Engineering

Integra����o da ��rea de neg��cio de retalho do grupo Riopele no Data Warehouse corporativo

Disserta����o de mestrado integrado em Engenharia e Gest��o de Sistemas de Informa����o

Development and validation of a clinical decision rule for the diagnosis of influenza.

INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.