Actuellement, les moyens et les méthodes de mesure et de contrôle des procédés de mise en forme, en particulier pour le forgeage, restent limités. Ils ne sont pas systématiques et sont très souvent développés pour des cas particuliers. La robustesse de ces procédés de mise en forme dépend de la capacité à mettre en œuvre des méthodes de maîtrise du processus et des contrôles efficaces. Des méthodologies existantes, comme la DMAIC, permettent de déterminer les paramètres à contrôler et leur influence sur les variables produit, cependant cette démarche possède des inconvénients rendant difficile son application, par exemple, la dépendance de cette méthode aux experts décidant des choix des paramètres. L'idée est de mettre en place une méthodologie générique permettant aux forgerons de maîtriser leur processus de fabrication de manière efficace et efficiente. La méthodologie consiste à mettre en place deux systèmes en amont et en aval du processus de forgeage. Le premier système, en amont, est un système d'aide à la décision reliant les spécifications sur le produit (géométrie, absence de défauts…) et sur les moyens de production aux paramètres processus. Ce premier système doit permettre de déterminer les paramètres clés à surveiller pour éviter des déviations au niveau des variables produit. Le deuxième système, en aval, est un système d'apprentissage dont le but est d'aider dans la compréhension du processus, renseigner le système d'aide à la décision et déterminer la pertinence de contrôle. / The mastering of the forging process is one of the principal objectives of the forging industry. To master a forging process, the key process parameters must be identified and controlled through a specified methodology. Some controlled parameters exist, like the stroke length or the lubrication, which are identified and controlled through a systematic approach. Their control depends on the part to produce or on customer's constraints, rather than a rational approach. A methodology is proposed to master the forging process and to avoid a process deviation. There are some methodologies that already exist such as the DMAIC, but it has certain drawbacks. The aim is to develop a generic methodology to improve the forging process monitoring. The methodology uses two systems in the upstream and the downstream of the forging process. The first system is a decision support system that connects product specifications (geometry, absence of defects…) or other forging process specifications (tool wear, energy…) to the process parameters, using the empirical rules and physical laws. The first system determinates the key parameters to control in order to avoid product variable deviations. The second system is a learning system, this latter helps in process understanding, supply the decision support system with laws and determinate the control pertinence.

An excellent transportation system is integral for Shanghai as it aims for sustainable development. Decision-making has a far-reaching impact on transportation, which should be improved and supplied with assistance. This thesis aims to design a tool based on a Decision Support System (DSS) named the Transportation Sustainability Decision Support System (TSDSS). The Framework for Strategic Sustainable Development (FSSD) is a key element that was integrated in the TSDSS which will guide the users to backcast from sustainability principles to be strategic in moving transportation in Shanghai towards sustainability. The TSDSS has 3 modules based on the ABCD method and 4 base systems including a Database System, a Model Base System, a Method Base System and a Knowledge Base System, which are designed to help Shanghai’s transportation system move in the right direction towards sustainability.

Cheap and reliable electricity is an essential stimulus for economic and social development. Currently fossil fuels are used for the majority of global electricity generation, but energy shortages and pressure on all industries to reduce CO2 emissions provide incentives for growing emphasis on the development of alternative energy-generation methods. Presently hydropower contributes about 17% of global energy generation, which is only a fraction of its total potential. In Africa only 5% of its estimated hydropower potential has been exploited, making it the most underdeveloped continent in terms of hydropower. An often overlooked source of hydropower energy is found in conduits, where pressure-reducing stations (PRSs) are installed to dissipate excess energy. The energy dissipated by these devices can instead be captured as hydroelectricity if turbines are installed in the conduits, either by replacing pressure-reducing valves (PRVs) with a turbine, or by installing the turbine in parallel with the PRV. An initial scoping investigation indicated that significant potential exists for small-scale hydropower installations in water-distribution systems in South Africa. Almost all of the country’s municipalities and water-supply utilities have pressure-dissipating stations in their water-distribution systems, where hydropower potential may exist. This dissertation reflects the development of a Conduit Hydropower Decision Support System (CHDSS), summarised in a series of flow diagrams that illustrate the developmental process (Figure i(a) provides an example). A Conduit Hydropower Development (CHD) Tool was developed to facilitate the calculation of necessary factors (the Phase 1 Economic Analysis is shown in Figure i(b)). The objective of this CHDSS was to assist municipalities and engineers in identifying conduit hydropower potential in South Africa and to provide proper guidance for the development of potential sites. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Civil Engineering / Unrestricted

Early blight (Alternaria solani Sorauer)is a major foliar disease of potatoes in most growing regions of the world and is underestimated in South Africa. This project studies the epidemiology and control of the disease in South Africa. A decision support system (DSS) for early blight in South Africa was developed and evaluated in field trials. This early blight DSS is the first such system to be developed in South Africa and once incorporated with the late blight model, will represent innovative technology for use in the South African potato industry. Trends in weather variables and concentrations of airborne conidia of A. solani were monitored. Distinct seasonal variation was noted. Peaks in spore concentration coincided with periods favourable for spore formation and dispersal; most notable was diurnal periodicity and interrupted wetting periods. The results obtained from these measurements will be useful in improving early blight DSSs for southern Africa. Isolates of A. solani from various potato-growing regions in South Africa were characterized using virulence, vegetative compatibility (VC) and random amplified microsatellite (RAMS) primers. Neither the virulence assays nor VC tests sufficiently characterised the population. Analysis of RAMS profiles revealed 27% genetic diversity among the isolates. This value is similar to diversity values obtained by previous authors studying A. solani, however, it is relatively high for an asexually reproducing fungus. There was no evidence for geographical clustering of isolates, indicating that isolates are widespread across South Africa. A survey on control practices and grower perceptions of early blight in South Africa was conducted using a questionnaire. These questionnaires were distributed to growers from 10 potato-growing regions in South Africa. Results highlighted the most popular control methods and cultivars in the South African potato industry. The majority of respondents indicated that they would use an accurate, cost-effective early blight DSS, and that more research is necessary on early blight in South Africa. A survey on control practices and grower perceptions of early blight in South Africa was conducted using a questionnaire. These questionnaires were distributed to growers from 10 potato-growing regions in South Africa. Results highlighted the most popular control methods and cultivars in the South African potato industry. The majority of respondents indicated that they would use an accurate, cost-effective early blight DSS, and that more research is necessary on early blight in South Africa. Estimated crop losses ranged from 1% - 60%, with an average of approximately 20%. This is the first comprehensive epidemiological study to be conducted on early blight in South Africa and has highlighted the need for further research. / Thesis (DPhil (Plant Pathology))--University of Pretoria, 2006. / Microbiology and Plant Pathology / unrestricted

Multiple Myeloma (MM) is a treatable, yet incurable, malignancy of bone marrowplasma cells. This cancer affects many patients and many succumb to relapse of tumor burden despite a large number of available chemotherapeutic agents developed for therapy. This is because MM tumors are heterogeneous and receive protection from therapeutic agents by the microenvironment and other mechanisms including homologous MM-MM aggregation. Therefore, therapy failure and frequent patient relapse is due to the evolution of drug resistance, not a lack of available drugs. To analyze and understand this problem, the evolution of drug resistance has been explored and presented herein. We seek to describe the methods through which MM cells become resistant to therapy, and how this resistance evolves throughout a patient’s treatment history. We achieve this in five steps. First we review the patient’s clinical history, including treatments and changes in tumor burden. Second, we trace the evolutionary tree of sub-clones within the tumor burden using standard of care fluorescence in situ hybridization (FISH). Thirdly, immunohistochemistry slides are stained and aligned to quantify the level of environmental protection received by surrounding cells and plasma in the bone marrow microenvironment (coined environment mediated drug resistance score [EMDR]). The fourth analysis type is produced through a novel 384-well plate ex vivo chemosensitivity assay to quantify sensitivity of primary MM cells to chemotherapeutic agents and extrapolate these findings to 90-day clinical response predictions. In addition to direct clinical application in the choice of best treatment, this tool was also used to study changes in sensitivity of patient tumors to other drugs, and it was observed that, upon relapse, in addition to developing resistance to the current line of therapy, tumors become cross-resistant to agents that they were never exposed to. Finally, MM-MM homologous aggregation is quantified to assess the level of drug resistance contributed by clustering of patient tumor cells, which causes upregulation of Bcl-2 expression and other resistance mechanisms1. The findings of such experimentation improve comprehension of the driving factors that contribute to drug resistance evolution on a personalized treatment basis. The aforementioned factors all contribute in varying degrees for unique patient cases, seven of which are presented in depth for this project. In summary: Environmental protection plays a critical initial role in drug resistance, which is followed by increase in tumor genetic heterogeneity as a result of mutations and drug-induced Darwinian selection. Eventually, environment-independent drug resistant subpopulations emerge, allowing the tumor to spread to unexplored areas of the bone marrow while maintaining inherited drug resistant phenotype2. It is our hope that these findings will help in shifting perspective regarding optimal management of MM by finding new therapeutic procedures that address all aspects of drug resistance to minimize chance of relapse and improve quality of life for patients.

The thesis focuses on requirements, which must be established when business intelligence is chosen, from user point of view. Business intelligence je decision support system and it is very important, that system must be ease of use and provide expected information for analyst and managers. During the process of choosing the software, they are the one, who provide requirements and expectation of the system. The thesis focuses on mapping those requirements and their importance using survey among analyst and managers, who uses business intelligence or want to use it.

Around ten percent of patients admitted to National Health Service (NHS) hospitals have experienced a patient safety incident, and an important reason for the high rate of patient safety incidents is medical errors. Research shows that appropriate increase in the use of clinical decision support systems (CDSSs) could help to reduce medical errors and result in substantial improvement in patient safety. However several barriers continue to impede the effective implementation of CDSSs in clinical settings, among which representation of and reasoning about medical knowledge particularly under uncertainty are areas that require refined methodologies and techniques. Particularly, the knowledge base in a CDSS needs to be updated automatically based on accumulated clinical cases to provide evidence-based clinical decision support. In the research, we employed the recently developed belief Rule-base Inference Methodology using the Evidential Reasoning approach (RIMER) for design and development of an online belief rule-based group CDSS prototype. In the system, belief rule base (BRB) was used to model uncertain clinical domain knowledge, the evidential reasoning (ER) approach was employed to build inference engine, a BRB training module was developed for learning the BRB through accumulated clinical cases, and an online discussion forum together with an ER-based group preferences aggregation tool were developed for providing online clinical group decision support.We used a set of simulated patients in cardiac chest pain provided by our research collaborators in Manchester Royal Infirmary to validate the developed online belief rule-based CDSS prototype. The results show that the prototype can provide reliable diagnosis recommendations and the diagnostic performance of the system can be improved significantly after training BRB using accumulated clinical cases.

The current guideline for culverts design account for hydrologic, hydraulic, and geomorphological conditions at the construction site. Less attention is given to the assessment of the potential for sedimentation within and in the culvert vicinity. Sedimentation becomes an increasing concern for regions where the soil erodibility is historically high (such as the US Midwest) as the recent changes in the land use and climate exacerbate the problem. Culvert design is based on a wide variety of data sources typically stored in various formats in multiple data provider repositories. Assembly of the data needed for design as currently conducted is time consuming and inefficient while the wealth of information garnered through post-construction monitoring is not used to inform the construction of new culverts in the same geographical area. This thesis presents a solution to the issues above using Hydroinformatics approaches. The end product of the thesis is a geo-platform designed to achieve automated culvert design, sediment mitigation design, and digital culvert inspection. The platform has two primary workflows: culvert design and culvert monitoring. All the functions and tools inside the platform are developed using information and GIS technologies. The platform is web assessable, light weighted, and user friendly.

The purpose of this study is to investigate the use of decisions support systems (DSS) by critical care physicians and to address the following questions: Does the use of a decision support system during diagnosis reduce diagnostic error and how are decision support systems used by critical care physicians? There are no studies that address these research questions in a clinical setting. The information assessment method (IAM) was used to guide the development of the survey questions. Critical care physicians from the University of Oklahoma Health Sciences Center were surveyed. Chi squared test for independence was used to determine the relationship between DSS use and diagnostic error rates. There were three main findings of the study: (1) use of a DSS by a critical care physician can decrease diagnostic error by up to 60%; (2) 56% of critical care physicians are using a DSS during diagnosis to learn something new, confirm something they already knew, and/or to reassure themselves; and (3) the increased use of a DSS by critical care physicians can lead to a decrease in the belief of the ability of a DSS to reduce diagnostic error.

The diploma thesis deals with the evaluation of the quality of customers using fuzzy logic based on the evaluation of their orders. The thesis consists of three parts. The first part is the theoretical basis of the thesis, which explains the issue of fuzzy logic. The second is the analytical part, in which the company ZKN METAL s.r.o. was introduced, for which a specific solution is subsequently proposed in the third and last part of the thesis. This solution is processed in the form of two models. The first of the models is processed in the MS Excel program and the second is modeled using the MATLAB programming environment. Both models are set in a user-intuitive environment and they are compared with each other afterwards.