860 resultados para Data management and analyses


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OBJECTIVE: To investigate whether better management of chronic conditions by family practices reduces mortality risk. DATA: Two random samples of 5 million patients registered with over 8,000 English family practices followed up for 4 years (2004/5-2007/8). Measures of the quality of disease management for 10 conditions were constructed for each family practice for each year. The outcome measure was an indicator taking the value 1 if the patient died during a specified year, 0 otherwise. STUDY DESIGN: Cross-section and multilevel panel data multiple logistic regressions were estimated. Covariates included age, gender, morbidity, hospitalizations, attributed socio-economic characteristics, and local health care supply measures. PRINCIPAL FINDINGS: Although a composite measure of the quality of disease management for all 10 conditions was significantly associated with lower mortality, only the quality of stroke care was significant when all 10 quality measures were entered in the regression. CONCLUSIONS: The panel data results suggest that a 1 percent improvement in the quality of stroke care could reduce the annual number of deaths in England by 782 [95 percent CI: 423, 1140]. A longer study period may be necessary to detect any mortality impact of better management of other conditions.

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The general striving to bring down the number of municipal landfills and to increase the reuse and recycling of waste-derived materials across the EU supports the debates concerning the feasibility and rationality of waste management systems. Substantial decrease in the volume and mass of landfill-disposed waste flows can be achieved by directing suitable waste fractions to energy recovery. Global fossil energy supplies are becoming more and more valuable and expensive energy sources for the mankind, and efforts to save fossil fuels have been made. Waste-derived fuels offer one potential partial solution to two different problems. First, waste that cannot be feasibly re-used or recycled is utilized in the energy conversion process according to EU’s Waste Hierarchy. Second, fossil fuels can be saved for other purposes than energy, mainly as transport fuels. This thesis presents the principles of assessing the most sustainable system solution for an integrated municipal waste management and energy system. The assessment process includes: · formation of a SISMan (Simple Integrated System Management) model of an integrated system including mass, energy and financial flows, and · formation of a MEFLO (Mass, Energy, Financial, Legislational, Other decisionsupport data) decision matrix according to the selected decision criteria, including essential and optional decision criteria. The methods are described and theoretical examples of the utilization of the methods are presented in the thesis. The assessment process involves the selection of different system alternatives (process alternatives for treatment of different waste fractions) and comparison between the alternatives. The first of the two novelty values of the utilization of the presented methods is the perspective selected for the formation of the SISMan model. Normally waste management and energy systems are operated separately according to the targets and principles set for each system. In the thesis the waste management and energy supply systems are considered as one larger integrated system with one primary target of serving the customers, i.e. citizens, as efficiently as possible in the spirit of sustainable development, including the following requirements: · reasonable overall costs, including waste management costs and energy costs; · minimum environmental burdens caused by the integrated waste management and energy system, taking into account the requirement above; and · social acceptance of the selected waste treatment and energy production methods. The integrated waste management and energy system is described by forming a SISMan model including three different flows of the system: energy, mass and financial flows. By defining the three types of flows for an integrated system, the selected factor results needed in the decision-making process of the selection of waste management treatment processes for different waste fractions can be calculated. The model and its results form a transparent description of the integrated system under discussion. The MEFLO decision matrix has been formed from the results of the SISMan model, combined with additional data, including e.g. environmental restrictions and regional aspects. System alternatives which do not meet the requirements set by legislation can be deleted from the comparisons before any closer numerical considerations. The second novelty value of this thesis is the three-level ranking method for combining the factor results of the MEFLO decision matrix. As a result of the MEFLO decision matrix, a transparent ranking of different system alternatives, including selection of treatment processes for different waste fractions, is achieved. SISMan and MEFLO are methods meant to be utilized in municipal decision-making processes concerning waste management and energy supply as simple, transparent and easyto- understand tools. The methods can be utilized in the assessment of existing systems, and particularly in the planning processes of future regional integrated systems. The principles of SISMan and MEFLO can be utilized also in other environments, where synergies of integrating two (or more) systems can be obtained. The SISMan flow model and the MEFLO decision matrix can be formed with or without any applicable commercial or free-of-charge tool/software. SISMan and MEFLO are not bound to any libraries or data-bases including process information, such as different emission data libraries utilized in life cycle assessments.

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In a networked business environment the visibility requirements towards the supply operations and customer interface has become tighter. In order to meet those requirements the master data of case company is seen as an enabler. However the current state of master data and its quality are not seen good enough to meet those requirements. In this thesis the target of research was to develop a process for managing master data quality as a continuous process and find solutions to cleanse the current customer and supplier data to meet the quality requirements defined in that process. Based on the theory of Master Data Management and data cleansing, small amount of master data was analyzed and cleansed using one commercial data cleansing solution available on the market. This was conducted in cooperation with the vendor as a proof of concept. In the proof of concept the cleansing solution’s applicability to improve the quality of current master data was proved. Based on those findings and the theory of data management the recommendations and proposals for improving the quality of data were given. In the results was also discovered that the biggest reasons for poor data quality is the lack of data governance in the company, and the current master data solutions and its restrictions.

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Especially in global enterprises, key data is fragmented in multiple Enterprise Resource Planning (ERP) systems. Thus the data is inconsistent, fragmented and redundant across the various systems. Master Data Management (MDM) is a concept, which creates cross-references between customers, suppliers and business units, and enables corporate hierarchies and structures. The overall goal for MDM is the ability to create an enterprise-wide consistent data model, which enables analyzing and reporting customer and supplier data. The goal of the study was defining the properties and success factors of a master data system. The theoretical background was based on literature and the case consisted of enterprise specific needs and demands. The theoretical part presents the concept, background, and principles of MDM and then the phases of system planning and implementation project. Case consists of background, definition of as is situation, definition of project, evaluation criterions and concludes the key results of the thesis. In the end chapter Conclusions combines common principles with the results of the case. The case part ended up dividing important factors of the system in success factors, technical requirements and business benefits. To clarify the project and find funding for the project, business benefits have to be defined and the realization has to be monitored. The thesis found out six success factors for the MDM system: Well defined business case, data management and monitoring, data models and structures defined and maintained, customer and supplier data governance, delivery and quality, commitment, and continuous communication with business. Technical requirements emerged several times during the thesis and therefore those can’t be ignored in the project. Conclusions chapter goes through these factors on a general level. The success factors and technical requirements are related to the essentials of MDM: Governance, Action and Quality. This chapter could be used as guidance in a master data management project.

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This Master´s thesis explores how the a global industrial corporation’s after sales service department should arrange its installed base management practices in order to maintain and utilize the installed base information effectively. Case company has product-related records, such as product’s lifecycle information, service history information and information about product’s performance. Information is collected and organized often case by case, therefore the systematic and effective use of installed base information is difficult also the overview of installed base is missing. The goal of the thesis study was to find out how the case company can improve the installed base maintenance and management practices and improve the installed base information availability and reliability. Installed base information management practices were first examined through the literature. The empirical research was conducted by the interviews and questionnaire survey, targeted to the case company’s service department. The research purpose was to find out the challenges related to case company´s service department’s information management practices. The study also identified the installed base information needs and improvement potential in the availability of information. Based on the empirical research findings, recommendations for improve installed base management practices and information availability were created. Grounding of the recommendations, the case company is suggested the following proposals for action: Service report development, improving the change management process, ensuring the quality of the product documentation in early stages of product life cycle and decision to improve installed base management practices.

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This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

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Data is the most important asset of a company in the information age. Other assets, such as technology, facilities or products can be copied or reverse-engineered, employees can be brought over, but data remains unique to every company. As data management topics are slowly moving from unknown unknowns to known unknowns, tools to evaluate and manage data properly are developed and refined. Many projects are in progress today to develop various maturity models for evaluating information and data management practices. These maturity models come in many shapes and sizes: from short and concise ones meant for a quick assessment, to complex ones that call for an expert assessment by experienced consultants. In this paper several of them, made not only by external inter-organizational groups and authors, but also developed internally at a Major Energy Provider Company (MEPC) are juxtaposed and thoroughly analyzed. Apart from analyzing the available maturity models related to Data Management, this paper also selects the one with the most merit and describes and analyzes using it to perform a maturity assessment in MEPC. The utility of maturity models is two-fold: descriptive and prescriptive. Besides recording the current state of Data Management practices maturity by performing the assessments, this maturity model is also used to chart the way forward. Thus, after the current situation is presented, analysis and recommendations on how to improve it based on the definitions of higher levels of maturity are given. Generally, the main trend observed was the widening of the Data Management field to include more business and “soft” areas (as opposed to technical ones) and the change of focus towards business value of data, while assuming that the underlying IT systems for managing data are “ideal”, that is, left to the purely technical disciplines to design and maintain. This trend is not only present in Data Management but in other technological areas as well, where more and more attention is given to innovative use of technology, while acknowledging that the strategic importance of IT as such is diminishing.

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The goal of this study is to create a new inventory valuation process for The Switch Drive Systems and to improve its inventory management practices. In the matter of inventories the main problems in the case company are that it doesn’t have consistent valuation methods throughout the company and that information received in ERP system isn’t trustful. The research is qualitative case study. The empirical data is gathered through observing and unstructured interviews. The research shows that material flow process and the inventory valuation must be divided and handled separately but they should interact with each other. The result is a new inventory valuation process which takes many factors of material process under the consideration in order to receive reliable value for inventories.

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Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

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Dental injuries are common and the incidence of maxillofacial injuries has increased over the recent decades in Finland. Accidental injuries are the global leading cause of death among children over the age of one year and among adults under the age of 40 globally. Significant resources and costs are needed for the treatment of these patients. The prevention is the most economical way to reduce trauma rates and costs. For the prevention it is crucial to know the prevalences, incidences and risk factors related to injuries. To improve the quality of treatment, it is essential to explore the causes, trauma mechanisms and management of trauma. The above mentioned was the aim of this thesis. With a large epidemiological cohort study (5737 participants) it was possible to estimate lifetime prevalence of and risk factors for dental trauma in general population (Study I). The prevalence of dental fractures was 43% and the prevalence of dental luxations and avulsions was 14%. Male gender, a history of previous non-dental injuries, mental distress, overweight and high alcohol consumption were positively associated with the occurrence of dental injuries Study II was conducted to explore the differences in type and multiplicity of mandibular fractures in three different countries (Canada, Finland and Kuwait). This retrospective study showed that the differences in mandibular fracture multiplicity and location are based on different etiologies and demographic patterns. This data can be exploited for planning of measures to prevent traumatic facial fractures. The etiology, management and outcome of 63 pediatric skull base fracture (Study III) and 20 pediatric frontobasal fracture patients (Study IV) were explored. These retrospective studies showed that, both skull base fracture and frontobasa fracture are rare injuries in childhood and although intracranial injuries and morbidity are frequent, permanent neurological or neuropsychological deficits are infrequent. A systematic algorithm (Study V) for computer tomography (CT) image review was aimed at clinicians and radiologists to improve the assessment of patients with complex upper midface and cranial base trauma. The cohort study was cross sectional and data was collected in the Turku and Oulu University Hospitals. A novel image-reviewing algorithm was created to enhance the specificity of CT for the diagnosis of frontobasal fractures. The study showed that an image-viewing algorithm standardizes the frontobasal trauma detection procedure and leads to better control and assessment. The purpose of the retrospective subcranial craniotomy study (VI) was to review the types of frontobasal fractures and their management, complications and outcome when the fracture is approached subcranially. The subcranial approach appears to be successful and have a reasonably low complication rate. It may be recommended as the technique of choice in multiple and the most complicated frontal base fractures where the endoscopic endonasal approach is not feasible.

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Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014