The importance of incorporating time in databases has been well realized by the community and time varying databases have been extensively studied by researchers. The main idea is to model up-to-date changes to data since it became available. Time information is mostly overlaid on the traditional databases, and extensional time dimension helps in inquiring or past data / this all becomes possible only once the idea is realized and favored by commercial database management systems. Unfortunately, one disadvantage of the temporal database management system is that it has not been commercialized. Firstly XML ,eXtensible Markup Language, is a defacto standard for data interchange and hence integrating XML as the data model is decided. The motivation for the work described in this thesis is two-fold / transferring databases into XML with changing crisp values into fuzzy variables describing fuzzy sets and second bitemporal databases form one interesting type of temporal databases. Thus, purpose is to suggest a complete automated system that converts any bitemporal database to its fuzzy XML schema definition. However, the implemented temporal database operators are database content independent. Fuzzy elements are capable of having different membership functions and varying number of linguistic variables. A scheme for determining membership function parameters is proposed. Finally, fuzzy queries have also been implemented as part of the system.

In this thesis, a requirements traceability model is proposed in order to make efficient and effective change request impact analysis. The proposed model is a requirements &ndash / requirements traceability model. There are several researches regarding software requirements traceability problem. The main problem of these researches is that the proposed solutions can not be applied to software industry with affordable changes. However, current literature begins to see that describing all the software requirements in a huge black box is not so much applicable to today&rsquo / s more dynamic and bigger software projects, especially regarding change management. The proposed traceability model tries to be a solution to these problems. Change requests and business rules are two important and popular terms for today&rsquo / s software industry. The traceability model consists of three types of software requirements: data definitions, business rules and use cases. The traceability model proposes bidirectional traces between these types. Data definitions, business rules and use cases are related to each other and they all should be seen as parts of a software system which should work together to make the software system work properly. Empirical investigation is made on a real industrial software project. These types were configured in order to match to the project specific needs in a reconfigurable way. Experimental results show that the traceability model has an acceptable degree of correctness.

Information integration over distributed and heterogeneous resources has been challenging in many terms: coping with various kinds of heterogeneity including data model, platform, access interfaces / coping with various forms of data distribution and maintenance policies, scalability, performance, security and trust, reliability and resilience, legal issues etc. It is obvious that each of these dimensions deserves a separate thread of research efforts. One particular challenge among the ones listed above that is more relevant to the work presented in this thesis is coping with various forms of data distribution and maintenance policies. This thesis aims to provide a service-oriented data integration solution over data Grids for cases where distributed data sources are partitioned with overlapping sections of various proportions. This is an interesting variation which combines both replicated and partitioned data within the same data management framework. Thus, the data management infrastructure has to deal with specific challenges regarding the identification, access and aggregation of partitioned data with varying proportions of overlapping sections. To provide a solution we have extended OGSA-DAI DQP, a well-known service-oriented data access and integration middleware with distributed query processing facilities, by incorporating UnionPartitions operator into its algebra in order to cope with various unusual forms of horizontally partitioned databases. As a result / our solution extends OGSA-DAI DQP, in two points / 1 - A new operator type is added to the algebra to perform a specialized union of the partitions with different characteristics, 2 - OGSA-DAI DQP Federation Description is extended to include some more metadata to facilitate the successful execution of the newly introduced operator.

The results of seismic hazard analysis (SHA) play a crucial role in assessing seismic risks and mitigating seismic hazards. SHA calculations generally involve magnitude and distance distribution models, and ground motion prediction models as components. Many alternatives have been proposed for these component models. SHA calculations may be demanding in terms of processing power depending on the models and analysis parameters involved, and especially the size of the site for which the analysis is to be performed. In this thesis, we develop a grid-based SHA application which provides the necessary computational power and enables the investigation of the effects of applying different models. Our application not only includes various already implemented component models but also allows integration of newly developed ones.

Suffix Tree Clustering (STC) is a search result clustering (SRC) algorithm focused on generating overlapping clusters with meaningful labels in linear time. It showed the feasibility of SRC but in time, subsequent studies introduced description-first algorithms that generate better labels and achieve higher precision. Still, STC remained as the fastest SRC algorithm and there appeared studies concerned with different problems of STC. In this thesis, semantic relations between cluster labels and documents are exploited to filter out noisy labels and improve merging phase of STC. Wikipedia is used to identify these relations and methods for integrating semantic information to STC are suggested. Semantic features are shown to be effective for SRC task when used together with term frequency vectors. Furthermore, there were no SRC studies on Turkish up to now. In this thesis, a dataset for Turkish is introduced and a number of methods are tested on Turkish.

In this thesis, the focus is on the development of scheduling algorithms for Sim-PETEK which is a framework for parallel and distributed execution of simulations. Since it is especially designed for running parameter sweep applications in a heterogeneous distributed computational environment, multi-round and adaptive scheduling approaches are followed. Five different scheduling algorithms are designed and evaluated for scheduling purposes of Sim-PETEK. Development of these algorithms are arranged in a way that a newly developed algorithm provides extensions over the previously developed and evaluated ones. Evaluation of the scheduling algorithms is handled by running a Wireless Sensor Network (WSN) simulation over Sim-PETEK in a heterogeneous distributed computational system formed in TUBITAK UEKAE ILTAREN. This evaluation not only makes comparisons among the scheduling algorithms but it also and rates them in terms of the optimality principle of divisible load theory which mentions that in order to obtain optimal processing time all the processors used in the computation must stop at the same time. Furthermore, this study adapts a scheduling approach, which uses statistical calibration, from literature to Sim-PETEK and makes an assessment between this approach and the most optimal scheduling approach among the five algorithms that have been previously evaluated. The approach which is found to be the most efficient is utilized as the Sim-PETEK scheduler.

One view to cognition is that the symbol manipulating brain interprets the symbols of language based on the sensori-motor experiences of the agent. Such symbols, for example, what we refer to as nouns and verbs, are generalizations that the agent discovers through interactions with the environment. Given that an important subset of nouns correspond to objects (and object concepts), in this thesis, how function and appearance-based object concepts can be created through affordances has been studied. For this, a computational system, which is able to create object concepts through simple interactions with the objects in the environment, is proposed. Namely, the robot applies a set of built-in behaviors (such as pushing, lifting, grasping) on a set of objects to learn their aordances, through which objects affording similar functions are grouped into object concepts. Moreover, the thesis demonstrates that the discovered object concepts are beneficial for learning new tasks by analyzing the learning performance of learning a new task with and without object concepts.

This thesis presents a preliminary goal oriented modeling of situation awareness in a command and control system. Tropos, an agent oriented software development methodology, has been used for modeling. Use of Tropos allows us to represent, at the knowledge level, the Command and Control actors along with their goals and interdependencies. Through refinement we aim to derive an architectural design for the Situation Awareness component of an Air Defense Command and Control system. This work suggests that goal oriented methodologies can be successfully used in the modeling of the complex systems at the requirement analysis phase. By analyzing dependencies between Command and Control entities, it should be possible to improve the modularity of the Command and Control system architecture.

We propose a developmental framework that enables the robot to learn affordances through interaction with the environment in an unsupervised way and to use these affordances at different levels of robot control, ranging from reactive response to planning. Inspired from Developmental Psychology, the robot&rsquo / s discovery of action possibilities is realized in two sequential phases. In the first phase, the robot that initially possesses a limited number of basic actions and reflexes discovers new behavior primitives by exercising these actions and by monitoring the changes created in its initially crude perception system. In the second phase, the robot explores a more complicated environment by executing the discovered behavior primitives and using more advanced perception to learn further action possibilities. For this purpose, first, the robot discovers commonalities in action-effect experiences by finding effect categories, and then builds predictors for each behavior to map object features and behavior parameters into effect categories. After learning affordances through self-interaction and self-observation, the robot can make plans to achieve desired goals, emulate end states of demonstrated actions, monitor the plan execution and take corrective actions using the perceptual structures employed or discovered during learning. Mobile and manipulator robots were used to realize the proposed framework. Similar to infants, these robots were able to form behavior repertoires, learn affordances, and gain prediction capabilities. The learned affordances were shown to be relative to the robots, provide perceptual economy and encode general relations. Additionally, the affordance-based planning ability was verified in various tasks such as table cleaning and object transportation.

Visibility analysis is an important GIS tool that is used in a diverse array of disciplines ranging from earth sciences to telecommunications. Multi-visibility, as a cumulative type of visibility, combines many point-to-point results into a multi-value array. Points, lines, or areas can be used as sources or targets / and the combined values can be calculated in both ways. Through multi-visibility, a special 2.5D visibility value surface can be constructed over a digital elevation model. The effectiveness of multi-visibility can be increased with weighted target zones. Other types of weighting criteria can be defined, such as distance and angle. Open source GIS tools offer a limited amount of support for that type of multivisibility analysis. In this study, a weighted multi-visibility methodology has been developed which accepts a path as the source. The path can have a specific direction to account for moving subjects that have a specific view angle based on their direction. A software tool has been developed to apply the methodology in a practical and automated way. The tool was written in Python programming language and can be run as a plugin to the open source Quantum GIS software. The proposed weighted multi-analysis methodology and its software tool can be used to assess the quality of visibility through the generation of value surfaces and calculation of a combined quantitative visibility value for the full path.