841 resultados para research methods and approaches


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A program of A (90 day moist room), B (14 day moist room) and C (7 day moist room and 7 day 50%_humidity) type curing for the R-11-Z program of durability of concrete using the automatic freeze and thaw machine (ASTM C-291) has been used in the Materials Department of the Iowa State Highway Commission since December 6, 1966. A summary of the results obtained from then until March 25, 1968, indicates that the B and C type curing are yielding very little valuable information. However, the A cure exhibits a wide range of durability factors and also groups the aggregates in an order which is related to the service record (there are definite exceptions. The biggest disadvantage to the A cure is the length of time that it takes to complete the test (90 day cure and 38 day test). The Kansas Highway Department has experimented with different cements and aggregates in order to determine which combination offers a concrete with the best durability factor possible. In an experimental test section of highway, concrete made with a Type II cement appeared to have better durability than others made with Type I cements. Because of this, a question has been raised at the Iowa State Highway Commission - Can concrete made with Type II cements, because of a lesser amount of tricalcium aluminate, yield better durability than concrete made with Type I cements?

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BACKGROUND: Methodological research has found that non-published studies often have different results than those that are published, a phenomenon known as publication bias. When results are not published, or are published selectively based on the direction or the strength of the findings, healthcare professionals and consumers of healthcare cannot base their decision-making on the full body of current evidence. METHODS: As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:1. To determine the proportion and/or rate of non-publication of studies by systematically reviewing methodological research projects that followed up a cohort of studies that a. received research ethics committee (REC) approval,b. were registered in trial registries, orc. were presented as abstracts at conferences.2. To assess the association of study characteristics (for example, direction and/or strength of findings) with likelihood of full publication.To identify reports of relevant methodological research projects we will conduct electronic database searches, check reference lists, and contact experts. Published and unpublished projects will be included. The inclusion criteria are as follows:a. RECs: methodological research projects that examined the subsequent proportion and/or rate of publication of studies that received approval from RECs;b. Trial registries: methodological research projects that examine the subsequent proportion and/or rate of publication of studies registered in trial registries;c. Conference abstracts: methodological research projects that examine the subsequent proportion and/or rate of full publication of studies which were initially presented at conferences as abstracts.Primary outcomes: Proportion/rate of published studies; time to full publication (mean/median; cumulative publication rate by time).Secondary outcomes: Association of study characteristics with full publication.The different questions (a, b, and c) will be investigated separately. Data synthesis will involve a combination of descriptive and statistical summaries of the included methodological research projects. DISCUSSION: Results are expected to be publicly available in mid 2013.

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In anticipation of regulation involving numeric turbidity limit at highway construction sites, research was done into the most appropriate, affordable methods for surface water monitoring. Measuring sediment concentration in streams may be conducted a number of ways. As part of a project funded by the Iowa Department of Transportation, several testing methods were explored to determine the most affordable, appropriate methods for data collection both in the field and in the lab. The primary purpose of the research was to determine the exchangeability of the acrylic transparency tube for water clarity analysis as compared to the turbidimeter.

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The driving forces of technology and globalization continuously transform the business landscape in a way which undermines the existing strategies and innovations of organizations. The challenge for organizations is to establish such conditions where they are able to create new knowledge for innovative business ideas in interaction between other organizations and individuals. Innovation processes continuously need new external stimulations and seek new ideas, new information and knowledge locating more and more outside traditional organizational boundaries. In several studies, the early phases of the innovation process have been considered as the most critical ones. During these phases, the innovation process can emerge or conclude. External knowledge acquirement and utilization are noticed to be important at this stage of the innovation process giving information about the development of future markets and needs for new innovative businessideas. To make it possible, new methods and approaches to manage proactive knowledge creation and sharing activities are needed. In this study, knowledge creation and sharing in the early phases of the innovation process has been studied, and the understanding of knowledge management in the innovation process in an open and collaborative context advanced. Furthermore, the innovation management methods in this study are combined in a novel way to establish an open innovation process and tested in real-life cases. For these purposes two complementary and sequentially applied group work methods - the heuristic scenario method and the idea generation process - are examined by focusing the research on the support of the open knowledge creation and sharing process. The research objective of this thesis concerns two doctrines: the innovation management including the knowledge management, and the futures research concerning the scenario paradigm. This thesis also applies the group decision support system (GDSS) in the idea generation process to utilize the converged knowledge during the scenario process.

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BACKGROUND: There is an urgent need to assess and improve the consent process in clinical trials of innovative therapies for neurodegenerative disorders. METHODS: We performed a longitudinal study of the consent of Huntington's disease patients during the Multicenter Fetal Cell Intracerebral Grafting Trial in Huntington's Disease (MIG-HD) in France and Belgium. Patients and their proxies completed a consent questionnaire at inclusion, before signing the consent form and after one year of follow-up, before randomization and transplantation. The questionnaire explored understanding of the protocol, satisfaction with the information delivered, reasons for participating in the trial and expectations regarding the transplant. Forty-six Huntington's disease patients and 27 proxies completed the questionnaire at inclusion, and 27 Huntington's disease patients and 16 proxies one year later. RESULTS: The comprehension score was high and similar for Huntington's disease patients and proxies at inclusion (72.6% vs 77.8%; P > 0.1) but only decreased in HD patients after one year. The information satisfaction score was high (73.5% vs 66.5%; P > 0.1) and correlated with understanding in both patients and proxies. The motivation and expectation profiles were similar in patients and proxies and remained unchanged after one year. CONCLUSIONS: Cognitively impaired patients with Huntington's disease were capable of consenting to participation in this trial. This consent procedure has presumably strengthened their understanding and should be proposed before signing the consent form in future gene or cell therapy trials for neurodegenerative disorders. Because of the potential cognitive decline, proxies should be designated as provisional surrogate decision-makers, even in competent patients.

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Drying is a major step in the manufacturing process in pharmaceutical industries, and the selection of dryer and operating conditions are sometimes a bottleneck. In spite of difficulties, the bottlenecks are taken care of with utmost care due to good manufacturing practices (GMP) and industries' image in the global market. The purpose of this work is to research the use of existing knowledge for the selection of dryer and its operating conditions for drying of pharmaceutical materials with the help of methods like case-based reasoning and decision trees to reduce time and expenditure for research. The work consisted of two major parts as follows: Literature survey on the theories of spray dying, case-based reasoning and decision trees; working part includes data acquisition and testing of the models based on existing and upgraded data. Testing resulted in a combination of two models, case-based reasoning and decision trees, leading to more specific results when compared to conventional methods.

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Our inability to adequately treat many patients with refractory epilepsy caused by focal cortical dysplasia (FCD), surgical inaccessibility and failures are significant clinical drawbacks. The targeting of physiologic features of epileptogenesis in FCD and colocalizing functionality has enhanced completeness of surgical resection, the main determinant of outcome. Electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) and magnetoencephalography are helpful in guiding electrode implantation and surgical treatment, and high-frequency oscillations help defining the extent of the epileptogenic dysplasia. Ultra high-field MRI has a role in understanding the laminar organization of the cortex, and fluorodeoxyglucose-positron emission tomography (FDG-PET) is highly sensitive for detecting FCD in MRI-negative cases. Multimodal imaging is clinically valuable, either by improving the rate of postoperative seizure freedom or by reducing postoperative deficits. However, there is no level 1 evidence that it improves outcomes. Proof for a specific effect of antiepileptic drugs (AEDs) in FCD is lacking. Pathogenic mutations recently described in mammalian target of rapamycin (mTOR) genes in FCD have yielded important insights into novel treatment options with mTOR inhibitors, which might represent an example of personalized treatment of epilepsy based on the known mechanisms of disease. The ketogenic diet (KD) has been demonstrated to be particularly effective in children with epilepsy caused by structural abnormalities, especially FCD. It attenuates epigenetic chromatin modifications, a master regulator for gene expression and functional adaptation of the cell, thereby modifying disease progression. This could imply lasting benefit of dietary manipulation. Neurostimulation techniques have produced variable clinical outcomes in FCD. In widespread dysplasias, vagus nerve stimulation (VNS) has achieved responder rates >50%; however, the efficacy of noninvasive cranial nerve stimulation modalities such as transcutaneous VNS (tVNS) and noninvasive (nVNS) requires further study. Although review of current strategies underscores the serious shortcomings of treatment-resistant cases, initial evidence from novel approaches suggests that future success is possible.

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The objective of this dissertation is to improve the dynamic simulation of fluid power circuits. A fluid power circuit is a typical way to implement power transmission in mobile working machines, e.g. cranes, excavators etc. Dynamic simulation is an essential tool in developing controllability and energy-efficient solutions for mobile machines. Efficient dynamic simulation is the basic requirement for the real-time simulation. In the real-time simulation of fluid power circuits there exist numerical problems due to the software and methods used for modelling and integration. A simulation model of a fluid power circuit is typically created using differential and algebraic equations. Efficient numerical methods are required since differential equations must be solved in real time. Unfortunately, simulation software packages offer only a limited selection of numerical solvers. Numerical problems cause noise to the results, which in many cases leads the simulation run to fail. Mathematically the fluid power circuit models are stiff systems of ordinary differential equations. Numerical solution of the stiff systems can be improved by two alternative approaches. The first is to develop numerical solvers suitable for solving stiff systems. The second is to decrease the model stiffness itself by introducing models and algorithms that either decrease the highest eigenvalues or neglect them by introducing steady-state solutions of the stiff parts of the models. The thesis proposes novel methods using the latter approach. The study aims to develop practical methods usable in dynamic simulation of fluid power circuits using explicit fixed-step integration algorithms. In this thesis, twomechanisms whichmake the systemstiff are studied. These are the pressure drop approaching zero in the turbulent orifice model and the volume approaching zero in the equation of pressure build-up. These are the critical areas to which alternative methods for modelling and numerical simulation are proposed. Generally, in hydraulic power transmission systems the orifice flow is clearly in the turbulent area. The flow becomes laminar as the pressure drop over the orifice approaches zero only in rare situations. These are e.g. when a valve is closed, or an actuator is driven against an end stopper, or external force makes actuator to switch its direction during operation. This means that in terms of accuracy, the description of laminar flow is not necessary. But, unfortunately, when a purely turbulent description of the orifice is used, numerical problems occur when the pressure drop comes close to zero since the first derivative of flow with respect to the pressure drop approaches infinity when the pressure drop approaches zero. Furthermore, the second derivative becomes discontinuous, which causes numerical noise and an infinitely small integration step when a variable step integrator is used. A numerically efficient model for the orifice flow is proposed using a cubic spline function to describe the flow in the laminar and transition areas. Parameters for the cubic spline function are selected such that its first derivative is equal to the first derivative of the pure turbulent orifice flow model in the boundary condition. In the dynamic simulation of fluid power circuits, a tradeoff exists between accuracy and calculation speed. This investigation is made for the two-regime flow orifice model. Especially inside of many types of valves, as well as between them, there exist very small volumes. The integration of pressures in small fluid volumes causes numerical problems in fluid power circuit simulation. Particularly in realtime simulation, these numerical problems are a great weakness. The system stiffness approaches infinity as the fluid volume approaches zero. If fixed step explicit algorithms for solving ordinary differential equations (ODE) are used, the system stability would easily be lost when integrating pressures in small volumes. To solve the problem caused by small fluid volumes, a pseudo-dynamic solver is proposed. Instead of integration of the pressure in a small volume, the pressure is solved as a steady-state pressure created in a separate cascade loop by numerical integration. The hydraulic capacitance V/Be of the parts of the circuit whose pressures are solved by the pseudo-dynamic method should be orders of magnitude smaller than that of those partswhose pressures are integrated. The key advantage of this novel method is that the numerical problems caused by the small volumes are completely avoided. Also, the method is freely applicable regardless of the integration routine applied. The superiority of both above-mentioned methods is that they are suited for use together with the semi-empirical modelling method which necessarily does not require any geometrical data of the valves and actuators to be modelled. In this modelling method, most of the needed component information can be taken from the manufacturer’s nominal graphs. This thesis introduces the methods and shows several numerical examples to demonstrate how the proposed methods improve the dynamic simulation of various hydraulic circuits.

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More and more innovations currently being commercialized exhibit network effects, in other words, the value of using the product increases as more and more people use the same or compatible products. Although this phenomenon has been the subject of much theoretical debate in economics, marketing researchers have been slow to respond to the growing importance of network effects in new product success. Despite an increase in interest in recent years, there is no comprehensive view on the phenomenon and, therefore, there is currently incomplete understanding of the dimensions it incorporates. Furthermore, there is wide dispersion in operationalization, in other words, the measurement of network effects, and currently available approaches have various shortcomings that limit their applicability, especially in marketing research. Consequently, little is known today about how these products fare on the marketplace and how they should be introduced in order to maximize their chances of success. Hence, the motivation for this study was driven by the need to increase our knowledge and understanding of the nature of network effects as a phenomenon, and of their role in the commercial success of new products. This thesis consists of two parts. The first part comprises a theoretical overview of the relevant literature, and presents the conclusions of the entire study. The second part comprises five complementary, empirical research publications. Quantitative research methods and two sets of quantitative data are utilized. The results of the study suggest that there is a need to update both the conceptualization and the operationalization of the phenomenon of network effects. Furthermore, there is a need for an augmented view on customers’ perceived value in the context of network effects, given that the nature of value composition has major implications for the viability of such products in the marketplace. The role of network effects in new product performance is not as straightforward as suggested in the existing theoretical literature. The overwhelming result of this study is that network effects do not directly influence product success, but rather enhance or suppress the influence of product introduction strategies. The major contribution of this study is in conceptualizing the phenomenon of network effects more comprehensively than has been attempted thus far. The study gives an augmented view of the nature of customer value in network markets, which helps in explaining why some products thrive on these markets whereas others never catch on. Second, the study discusses shortcomings in prior literature in the way it has operationalized network effects, suggesting that these limitations can be overcome in the research design. Third, the study provides some much-needed empirical evidence on how network effects, product introduction strategies, and new product performance are associated. In general terms, this thesis adds to our knowledge of how firms can successfully leverage network effects in product commercialization in order to improve market performance.

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The aim of this master’s thesis is to study how Agile method (Scrum) and open source software are utilized to produce software for a flagship product in a complex production environment. The empirical case and the used artefacts are taken from the Nokia MeeGo N9 product program, and from the related software program, called as the Harmattan. The single research case is analysed by using a qualitative method. The Grounded Theory principles are utilized, first, to find out all the related concepts from artefacts. Second, these concepts are analysed, and finally categorized to a core category and six supported categories. The result is formulated as the operation of software practices conceivable in circumstances, where the accountable software development teams and related context accepts a open source software nature as a part of business vision and the whole organization supports the Agile methods.

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In this research, the effectiveness of Naive Bayes and Gaussian Mixture Models classifiers on segmenting exudates in retinal images is studied and the results are evaluated with metrics commonly used in medical imaging. Also, a color variation analysis of retinal images is carried out to find how effectively can retinal images be segmented using only the color information of the pixels.

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Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

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The experiences of several healthcare organizations were considered to distinguish the most frequently used lean tools, the success and failure factors, and the obstacles that may appear while implementing lean. As a result, two approaches to “go lean” were defined, and analyzed from the prospective of the applicability to healthcare processes. Industrialization of healthcare was studied, and the most promising digital technology tools to improve healthcare process were highlighted. Finally, the analysis of healthcare challenges and feasible ways to address them was conducted and presented as the main result of this work. The possible ways of implementation of the findings and limitations were described in the conclusion.

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We compare a broad range of optimal product line design methods. The comparisons take advantage of recent advances that make it possible to identify the optimal solution to problems that are too large for complete enumeration. Several of the methods perform surprisingly well, including Simulated Annealing, Product-Swapping and Genetic Algorithms. The Product-Swapping heuristic is remarkable for its simplicity. The performance of this heuristic suggests that the optimal product line design problem may be far easier to solve in practice than indicated by complexity theory.