In pattern recognition, &ldquo / bias-variance&rdquo / trade-off is a challenging issue that the scientists has been working to get better generalization performances over the last decades. Among many learning methods, two-layered homogeneous stacked generalization has been reported to be successful in the literature, in different problem domains such as object recognition and image annotation. The aim of this work is two-folded. First, the problems of stacked generalization are attacked by a proposed novel architecture. Then, a set of success criteria for stacked generalization is studied. A serious drawback of stacked generalization architecture is the sensitivity to curse of dimensionality problem. In order to solve this problem, a new architecture named &ldquo / unanimous decision&rdquo / is designed. The performance of this architecture is shown to be comparably similar to two layered homogeneous stacked generalization architecture in low number of classes while it performs better than stacked generalization architecture in higher number of classes. Additionally, a new success criterion for two layered homogeneous stacked generalization architecture is proposed based on the individual properties of the used descriptors and it is verified in synthetic datasets.

In this thesis, the relations between information systems outsourcing success measures and strategic and financial drivers are investigated. After a study of the relevant literature, 14 organizations that belong to four different categories are investigated in terms of IS outsourcing. These categories are: IS vendors, IS outsourcers, firms that both procure and supply IS services, and IS system integrators. Thus, the subject matter is studied from both customers&#039 / and vendors&#039 / points of view. The investigation is realized in three steps: First, general questions were posed in order to gather the characteristics of organizations, then, questionnaires were conducted, and finally, financial data documents were prepared according to the type of the organization. The results show that the number of relations between strategic drivers and information systems outsourcing success measures are more than the number of relations between financial drivers and information systems outsourcing success measures. Besides, strategic drivers influence each of the information system outsourcing success measures, whereas financial drivers affect only two of them.

This thesis emphasizes the importance of software industry within global perspective, in addition, aims to study the economic, social and structural dimensions of Indian, Irish and Turkish software industries. Because of coming from developing countries scale and attaining to significant software export achievements in global software industry, India and Ireland will be in center of this study. In this context, the determination of India and Ireland&rsquo / s industrial and national software strategies and the results and achievement evaluations in application case are accomplished. In consequence of related assessments, Turkish software industry is analyzed and future oriented suggestions are presented via taking into account country dynamics. In theoretical perspective, Indian, Irish and Turkish software industries are analyzed on the basis of Richard Heeks&rsquo / &ldquo / Software Strategies in Developing Countries&rdquo / model with appropriate approaches. Beyond, in this study, which is commenced on the basis of three countries, division of labor of global software industry will be analyzed in &ldquo / core and periphery&rdquo / framework and the suggestions will be presented to developing countries on their national software industries. The findings of the study indicate that, countries which have advanced national software industries keep high value added phases in their home countries, however outsource low value added phases of software development projects to developing countries because of workforce cost, qualified human resources, tax incentives, geographical market position etc. advantages.

A major problem to be solved in health informatics is high quality, structured and timely data collection. Standard terminologies and uniform domain conceptual models are important steps to alleviate this problem which are also proposed to enable interoperability among systems. With the aim of contributing to the solution of this problem, this study proposes novel features for the Archetypes and multi-level modeling technique in health information and knowledge modeling. The study consists of the development of a research prototype for endoscopic data management, and based on that experience, the extension of Minimal Standard Terminology in Digestive Endoscopy (MST). A major contribution of the study consists of significant extensions to the modeling formalism. The proposed modeling approach may be used in the design and development of health information systems based on archetypes for structured data collection, validation and dynamic user interface creation. The thesis work is aimed to make considerable contribution to the emerging Electronic Health Records (EHR) standards and specifications.

The focus of this study is on predicting the subcellular localization of a protein. Subcellular localization information is important for protein function annotation which is a fundamental problem in computational biology. For this problem, a classification system is built that has two main parts: a predictor that is based on a feature mapping technique to extract biologically meaningful information from protein sequences and a client/server architecture for searching and predicting subcellular localizations. In the first part of the thesis, we describe a feature mapping technique based on frequent patterns. In the feature mapping technique we describe, frequent patterns in a protein sequence dataset were identified using a search technique based on a priori property and the distribution of these patterns over a new sample is used as a feature vector for classification. The effect of a number of feature selection methods on the classification performance is investigated and the best one is applied. The method is assessed on the subcellular localization prediction problem with 4 compartments (Endoplasmic reticulum (ER) targeted, cytosolic, mitochondrial, and nuclear) and the dataset is the same used in P2SL. Our method improved the overall accuracy to 91.71% which was originally 81.96% by P2SL. In the second part of the thesis, a client/server architecture is designed and implemented based on Simple Object Access Protocol (SOAP) technology which provides a user-friendly interface for accessing the protein subcellular localization predictions. Client part is in fact a Cytoscape plug-in that is used for functional enrichment of biological networks. Instead of the individual use of subcellular localization information, this plug-in lets biologists to analyze a set of genes/proteins under system view.

This thesis is a study on improving the software requirements management processes of embedded software department of a company. The literature on software process improvement and requirements engineering is reviewed. After determining the problems related to the current requirements management processes of the department, an improved process is proposed addressing these problems. The static process descriptions and the models of the current and improved requirements management processes are formed. A recently proposed pre-enactment model for measuring process quality is used for measuring the quality of the current and improved requirements management processes. Finally, the results of the process quality measurements are compared and evaluated.

The graphics hardware have evolved from simple feed forward triangle rasterization devices to flexible, programmable, and powerful parallel processors. This evolution allows the researchers to use graphics processing units (GPU) for both general purpose computations and advanced graphics rendering. Sophisticated GPUs hold great opportunities for the acceleration of computationally expensive photorealistic rendering methods. Rendering of photorealistic images in real-time is a challenge. In this work, we investigate efficient ways to utilize GPUs for real-time photorealistic rendering. Specifically, we studied uniform grid based ray tracing acceleration methods and GPU friendly traversal algorithms. We show that our method is faster than or competitive to other GPU based ray tracing acceleration techniques. The proposed approach is also applicable to the fast rendering of volumetric data. Additionally, we devised GPU based solutions for real-time stereoscopic image generation which can be used in companion with GPU based ray tracers.

Gait analysis is the process of collecting and analyzing quantitative information about walking patterns of the people. Gait analysis enables the clinicians to differentiate gait deviations objectively. Diagnostic decision making from gait data only requires high level of medical expertise of neuromusculoskeletal system trained for the purpose. An automated system is expected to decrease this requirement by a &lsquo / transformed knowledge&rsquo / of these experts. This study presents a clinical decision support system for the detecting and scoring of a knee disorder, namely, Osteoarthritis (OA). Data used for training and recognition is mainly obtained through Computerized Gait Analysis software. Sociodemographic and disease characteristics such as age, body mass index and pain level are also included in decision making. Subjects are allocated into four OA-severity categories, formed in accordance with the Kellgren-Lawrence scale: &ldquo / Normal&rdquo / , &ldquo / Mild&rdquo / , &ldquo / Moderate&rdquo / , and &ldquo / Severe&rdquo / . Different types of classifiers are combined to incorporate the different types of data and to make the best advantages of different classifiers for better accuracy. A decision tree is developed with Multilayer Perceptrons (MLP) at the leaves. This gives an opportunity to use neural networks to extract hidden (i.e., implicit) knowledge in gait measurements and use it back into the explicit form of the decision trees for reasoning. Individual feature selection is applied using the Mahalanobis Distance measure and most discriminatory features are used for each expert MLP. Significant knowledge about clinical recognition of the OA is derived by feature selection process. The final system is tested with test set and a success rate of about 80% is achieved on the average.

This thesis provides an approach to use feature modeling with a set of guidelines for requirements definition and decomposition activities of the axiomatic design methodology. A tool that supports the development of feature models and modeling of the Axiomatic Design activities is implemented to be utilized for guiding the designer. Axiomatic Design suggested four domains of information in the transformation of the problem definition to the solution, and provided mechanisms for supporting the mapping among some of those domains. The approach suggested in this thesis fills an important gap, which is the transition from the customer needs to functional requirements, in axiomatic design. A case study is carried out in order to analyze advantages and disadvantages of the proposed approach.

The simulation world defines conceptual modeling as a tool that provides a clear understanding of the target domain or problem. Although there are some approaches offering useful insights on conceptual modeling in the simulation development lifecycle, they do not provide adequate guidance on how to develop a conceptual model. This thesis study presents a framework for developing conceptual models for simulation systems that is based on the idea that the modelers will develop conceptual models more effectively by following a defined conceptual modeling method, using a domain specific notation and a tool. The conceptual model development method is defined in a step-by-step manner and explanations about the notation and tool are provided when required. A multiple-case study involving two cases is conducted in order to evaluate the applicability of the method for conceptual modeling and validate the expected benefits.