Single Nucleotide Polymorphisms (SNPs) are the most frequent genomic variations and the main basis for genetic differences among individuals and many diseases. As genotyping millions of SNPs at once is now possible with the microarrays and advanced sequencing technologies, SNPs are becoming more popular as genomic biomarkers. Like other high-throughput research techniques, genome wide association studies (GWAS) of SNPs usually hit a bottleneck after statistical analysis of significantly associated SNPs, as there is no standardized approach to prioritize SNPs or to select representative SNPs that show association with the conditions under study. In this study, a java based integrated system that makes use of major public databases to prioritize SNPs according to their biological relevance and statistical significance has been constructed. The Analytic Hierarchy Process, has been utilized for objective prioritization of SNPs and a new emerging methodology for second-wave analysis of genes and pathways related to disease associated SNPs based on a combined p-value approach is applied into the prioritization scheme. Using the subset of SNPs that is most representative of all SNPs associated with the diseases reduces the required computational power for analysis and decreases cost of following association and biomarker discovery studies. In addition to the proposed prioritization system, we have developed a novel feature selection method based on Simulated Annealing (SA) for representative SNP selection. The validity and accuracy of developed model has been tested on real life case control data set and produced biologically meaningful results. The integrated desktop application developed in our study will facilitate reliable identification of SNPs that are involved in the etiology of complex diseases, ultimately supporting timely identification of genomic disease biomarkers, and development of personalized medicine approaches and targeted drug discoveries.

Web Service technology is one of the most rapidly developing contemporary technologies. Nowadays, Web Services are being used by a large number of projects and academic studies all over the world. As the use of Web service technology is increasing, it becomes harder to find the most suitable web service which meets the Quality of Service (QoS) as well as functional requirements of the user. In addition, quality of the web services (QoS) that take part in the software system becomes very important. In this thesis, we develop a method to track the QoS primitives of Web Services and an algorithm to automatically calculate QoS values for Web Services. The proposed method is realized within a domain specific web service discovery system, namely DSWSD-S, Domain Specific Web Service Discovery with Semantics. This system searches the Internet and finds web services that are related to a domain and calculates QoS values through some parameters. When a web service is queried, our system returns suitable web services with their QoS values. How to calculate, keep track of and store QoS values constitute the main part of this study.

In the last decade, with the extensive use of mobile electronic and wireless communication devices, there is a growing need for context aware applications and many pervasive computing applications have become integral parts of our daily lives. Context aware recommender systems are one of the popular ones in this area. Such systems surround the users and integrate with the environment / hence, they are aware of the users&#039 / context and use that information to deliver personalized recommendations about everyday tasks. In this manner, predicting user&rsquo / s next activity preferences with high accuracy improves the personalized service quality of context aware recommender systems and naturally provides user satisfaction. Predicting activities of people is useful and the studies on this issue in ubiquitous environment are considerably insufficient. Thus, this thesis proposes an activity prediction model to forecast a user&rsquo / s next activity preference using past preferences of the user in certain contexts and current contexts of user in ubiquitous environment. The proposed model presents a new approach for activity prediction by taking advantage of ontology. A prototype application is implemented to demonstrate the applicability of this proposed model and the obtained outputs of a sample case on this application revealed that the proposed model can reasonably predict the next activities of the users.

In this thesis work, a certificate based authentication model supported by mobile devices is provided for ubiquitous computing environments. The model primarily aims to create an infrastructure for controlling and regulating access requests through mobile devices to local resources and services. The model also allows users from different domains to use local resources and services within the scope of agreements between domains. In addition to conceptual description of the model, a real prototype implementation is developed and successful application of the model is demonstrated. Within the prototype implementation, a mobile application is developed for access requests and sensors are used as representative local resources. Sample cases applied on the prototype demonstrate applicability and feasibility of the model.

This thesis presents a two step automatic transformation of Field Artillery Mission Space Conceptual Models (ACMs) into High Level Architecture (HLA) Federation Architecture Models (FAMs) into executable distributed simulation code. The approach followed in the course of this thesis adheres to the Model-Driven Engineering (MDE) philosophy. Both ACMs and FAMs are formally defined conforming to their metamodels, ACMM and FAMM, respectively. ACMM is comprised of a behavioral component, based on Live Sequence Charts (LSCs), and a data component based on UML class diagrams. Using ACMM, the Adjustment Followed by Fire For Effect (AdjFFE) mission, which serves as the source model for the model transformation case study, is constructed. The ACM to FAM transformation, which is defined over metamodel-level graph patterns, is carried out with the Graph Rewriting and Transformation (GReAT) tool. Code generation from a FAM is accomplished by employing a model interpreter that produces Java/AspectJ code. The resulting code can then be executed on an HLA Run-Time Infrastructure (RTI). Bringing a fully fledged transformation approach to conceptual modeling is a distinguishing feature of this thesis. This thesis also aims to bring the chart notations to the attention of the mission space modeling community regarding the description of military tasks, particularly their communication aspect. With the experience gained, a set of guidelines for a domainindependent transformer from any metamodel-based conceptual model to FAM is offered.

In this thesis the main objective is to design a machine vision system that classifies aflatoxin contaminated chili peppers from uncontaminated ones in a rapid and non-destructive manner via hyperspectral imaging and machine learning techniques. Hyperspectral image series of chili pepper samples collected from different regions of Turkey have been acquired under halogen and UV illuminations. A novel feature set based on quantized absolute difference of consecutive spectral band features is proposed. Spectral band energies along with absolute difference energies of the consecutive spectral bands are utilized as features and compared with other feature extraction methods such as Teager energy operator and 2D wavelet Linear Discriminant Bases (2D-LDB). For feature selection, Fisher discrimination power, information theoretic Minimum Redundancy Maximum Relevance (mRMR) method and proposed Multi Layer Perceptron (MLP) based feature selection schemes are utilized.Finally, Linear Discriminant Classifier (LDC), Support Vector Machines (SVM) and MLP are used as classifiers. It is observed that MLP outperforms other learning models in terms of predictor performance. We verified the performance and robustness of our proposed methods on different real world datasets. It is suggested that to achieve high classification accuracy and predictor robustness, a machine vision system with halogen excitation and quantized absolute difference of consecutive spectral band features should be utilized.

High performance computer clusters have become popular as they are more scalable, affordable and reliable than their centralized counterparts. Database management systems are particularly suitable for distributed architectures / however distributed DBMS are still not used widely because of the design difficulties. In this study, we aim to help overcome these difficulties by implementing a simulation testbed for a distributed query plan processor. This testbed works on our departmental HPC cluster machine and is able to perform select, project and join operations. A data generation module has also been implemented which preserves the foreign key and primary key constraints in the database schema. The testbed has capability to measure, simulate and estimate the response time of a given query execution plan using specified communication network parameters. Extensive experimental work is performed to show the correctness of the produced results. The estimated execution time costs are also compared with the actual run-times obtained from the testbed to verify the proposed estimation functions. Thus, we make sure that these estimation iv functions can be used in distributed database query optimization and distributed database design tools.

In recent years, many Personal Health Record (PHR) systems have been developed to retrieve patients&rsquo / Electonic Health Records (EHRs) from external sources. However, current PHRs can provide access to only a small number of EHR systems, since there are many dierent interfaces, data formats and medical terminologies among dierent systems. When this is the case, all these diversity yields high integration costs. Development of such systems is dicult and expensive because of the reasons such as accessing to evidence based medical information, utilization of social networks to share information, incorporation of available medical knowledge models, etc. Due to the technical diversity of external information systems, a developer of a PHR system faces a dicult integration process when he wants to integrate a new source or service. Integration of medical devices is also important and necessary in a PHR system. However, most of the medical device vendors use proprietary formats and protocols for communicating their devices with external systems / again, causing high integration eorts and costs. In this thesis, these problems and challenges are addressed by providing an on-line personal iv healthcare management platform, i.e. eSaglikKaydim which is built on top of a highly modular architecture and provides services based on worldwide standards. In this way, eSaglikKaydim platform can be integrated with any external health information service and medical device so that it maximizes the data variety retrieved from all kinds of external health data sources. The work presented in this thesis is part of the OSAmI project supported by European ITEA and funded by the TU&uml / BI

Enterprises require an information security solution that provides privacy, integrity, authentication and access controls for processes. License management systems are developed to be a solution for process authorization in different platforms. However, security threats on processes cannot be controlled with existing license management mechanisms. The need is a complete system that is independent from implementation, platform, and application. In this thesis, we design a complete system for process authorization based on Public Key Infrastructure (PKI) technology.

This research first defines money and lists its functions and properties. Among these properties, the anonymity and off-line capability of money are pointed out. Then the history of money is briefly discussed, to show that money has evolved similarly to the Lamarckian evolution of species. The examination of the history of money helps us justify why electronic money is necessary, and to point out that money will continuously evolve towards Pure Money. The definition of electronic money conducted afterwards, draws the lines within which the model will be proposed. The proposed model is formally constructed and evaluated accordingly with the use of micropayment evaluation frameworks. The model is a hardware based model considering as baseline smart cards with secure co-processors, and allows transactions with cross-challenging. The model is evaluated with respect to technologic, social and economic dimensions, and taking into account the associated computational and storage costs.