Dia L. Ali

Fuzzy spatial relationships and mobile agent technology in geospatial information systems

This chapter discusses an integrated work in the definition and implementation of sets of fuzzy spatial relationships concerning topology and direction. We present our basic approach to defining these relationships as an extension to previous work in temporal relations. We also discuss several extensions to this approach that include refinements and alternate definitions. Two implementations are also described, one in a C++, Oracle database environment and another utilizing the expert system shell Fuzzy Clips. Finally we discuss the integration of this querying approach in an agent-based framework. Agent technology has become a leading implementation paradigm for distributed and complex systems, and has recently garnered much interest from researchers in the area of spatial databases. Agents offer many advantages with respect to intelligence abilities and mobility that can provide solutions for issues related to uncertainty in spatial data, such as those of spatial relationships.

Performance evaluation of SDIAGENT, a multi-agent system for distributed fuzzy geospatial data conflation

A rapid growth of available geospatial data requires development of systems capable of autonomous data retrieval, integration and validation. Mobile agents may provide the suitable framework for developing such systems since this technology, in a natural way, can deal with the distributed heterogeneous nature of such data. In this paper, we evaluate SDIAGENT our, recently introduced, multi-agent architecture for geospatial data integration and conflation, and compare its model performance with that of client/server and single-agent approaches. Experimental results for several realistic scenarios, under varying conditions, are presented for these three system architectures. We analyze the performance alteration for various numbers of participating nodes, varying amount of database accesses, processing loads, and network loads.

Integrating heterogeneous distributed database system

Abstract This paper demonstrates various aspects of resolving possible data conflicts occurring in the database integration process. A general model of a Heterogeneous Distributed Database System (HDDBS) based on a relational data model is presented. We also discuss the problems of heterogeneous database integration and the principal user requirements, together with design and implementation issues. The HDDBS suppresses differences of DBMS, language, and data models among the databases and provides users with a unified global schema and a single high-level query language. There are three principal research goals of the paper. The first goal is to develop appropriate language constructs for accessing and integrating heterogeneous databases. The Second goal is to discover effective global and local optimization techniques. The final goal is to design methods for handling incompatible data representations and inconsistent data.

Preliminary performance evaluation of an agent-based geospatial data conflation system

A rapid growth of available geospatial data requires development of systems capable of autonomous data retrieval, integration and validation. Mobile agent technology may provide a suitable framework for developing such systems since this technology can deal, in a natural way, with the distributed heterogeneous nature of the data. We evaluate our novel multi-agent architecture for geospatial data integration and compare its performance with a client/server and a single-agent architecture. We analyze the performance alteration for various numbers of participating nodes, amount of database accesses, processing loads, and network loads.

Fuzzy spatial querying with inexact inference

The issue of spatial querying accuracy has been viewed as critical to the successful implementation and long-term viability of the GIS technology. In order to improve the spatial querying accuracy and quality, the problems associated with the areas of fuzziness and uncertainty are of great concern in the spatial database community. There has been a strong demand to provide approaches that deal with inaccuracy and uncertainty in GIS. In this paper, we are dedicated to develop an approach that can perform fuzzy spatial querying under uncertainty. An inexact inferring strategy is investigated. The study shows that the fuzzy set and the certainty factor can work together to deal with spatial querying. Querying examples implemented by FuzzyClips are also provided.

A practical guide for implementing data warehousing

Data warehousing is a method by which an organization stores its data so that the information contained in that data can be ascertained, accessed and analyzed more quickly and efficiently than would be possible when using a conventional architecture. Multidimensional databases (MDD) provide an efficient means to analytical processing, but the cost is prohibitive for many small and mid-sized organizations. This paper addresses the need for an inexpensive solution to an information management problem that can be solved by database application developers using conventional tools. A relational database management system (RDBMS) can be used to emulate a MDD and still maintain an acceptable performance level in a client server environment.

An inexact inferencing strategy for spatial objects with determined and indeterminate boundaries

For many years, spatial querying has been of interest for the researchers in the GIS community. Any successful implementation and long-term viability of the GIS technology depends on the issue of accuracy of spatial queries. In order to improve the accuracy and quality of spatial querying, the problems associated with the areas of fuzziness and uncertainty need to be addressed. There has been a strong demand to provide approaches that deal with inaccuracy and uncertainty in GIS. In this paper, we develop an approach that can perform fuzzy spatial querying under uncertainty. An inexact inferencing strategy for objects with determined and indeterminate boundaries is investigates using type-2 fuzzy set theory.

Neural network approach to digital control

This paper starts with an overview of a classical PID controller design. An account of how Neural Networks may be incorporated to provide control is such a setup. The example used in this paper is the problem of controlling a High Frequency Acoustics Platform (HFAP) in-flight. The HFAP is towed by a ship and flown in the water behind the ship to acquire acoustic data reflected from the sea floor. The stability of such a platform is of prime importance to the accuracy of data collected. Using fight data from previous runs of the platform, a Neural Network is trained. The trained network is then used to predict the behavior of the platform. These predictions may then be directly translated to control signals minimizing the platforms spatial deviations. In this paper results form the trained Neural Network on predicting the behavior of the platform are displayed. Network prediction results illustrating the ability of the network to operate with partial input are displayed. Displaying these results in contrast with conventional controller results given the same input parameters emphasizes the importance of such a feature. Finally the use of different network architectures and the cost of using these network, in terms of computing power is investigated.

Distributing data to the user: a distributed user querying interface standard for the future distributed database

The variety of user interfaces of existing database querying tools made the interfaces unfriendly to the database users. The users are forced to shift between different application environments to pass information between applications. The diverse interface definitions and command sets of the different applications prevent the users from having high productivity. In this paper we propose a new standard querying interface, whose querying power is distributed to applications throughout the operating system. The proposed querying interface would improve the data accessibility of the databases. This new standard is called Distributed Querying Interface Standard(DQIS) by the authors.

The undeterministic manipulation of solid models for robot program synthesis

Abstract In automatic robot program synthesis the number of variables that should be taken into consideration become prohibitively numerous. Due to the ambiguity and sheer size of items to be considered conventional computation methods cannot satisfactorily solve the problem. A Neural Network model that acquires data from a Solid Modeling data base, combines the completeness of information provided by solid modeling with the uncertainty encountered in the grouping process to perform geometrical classification of objects. The capabilities of Neural Networks to learn non-geometrical patterns in the grasping process, are yet to be achieved. Much progress needs to be made in both the neural model complexity and the computing machinery power before real intelligent program synthesis can be achieved.