Abstract: Robotic system is an important area in artificial intelligence that aims at developing the performance techniques of the robot and making it more efficient and more effective in choosing its correct behavior. In this paper the distributed learning classifier system is used for designing a simulated control system for robot to perform complex behaviors. A set of enhanced approaches that support default hierarchies formation is suggested and compared with each other in order to make the simulated robot more effective in mapping the input to the correct output behavior.
Abstract: Representation and description of object shapes by the
slopes of their contours or borders are proposed. The idea is to capture
the essence of the features that make it easier for a shape to be
stored, transmitted, compared and recognized. These features must
be independent of translation, rotation and scaling of the shape. A
approach is proposed to obtain high performance, efficiency and to
merge the boundaries into sequence of straight line segments with
the fewest possible segments. Evaluation on the performance of the
proposed method is based on its comparison with established method
of object shape description.
Abstract: Risk management is an essential fraction of project management, which plays a significant role in project success. Many failures associated with Web projects are the consequences of poor awareness of the risks involved and lack of process models that can serve as a guideline for the development of Web based applications. To circumvent this problem, contemporary process models have been devised for the development of conventional software. This paper introduces the WPRiMA (Web Project Risk Management Assessment) as the tool, which is used to implement RIAP, the risk identification architecture pattern model, which focuses upon the data from the proprietor-s and vendor-s perspectives. The paper also illustrates how WPRiMA tool works and how it can be used to calculate the risk level for a given Web project, to generate recommendations in order to facilitate risk avoidance in a project, and to improve the prospects of early risk management.
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Abstract: The size, complexity and number of databases used
for protein information have caused bioinformatics to lag behind in
adapting to the need to handle this distributed information.
Integrating all the information from different databases into one
database is a challenging problem. Our main research is to develop a
tool which can be used to access and manipulate protein information
from difference databases. In our approach, we have integrated
difference databases such as Swiss-prot, PDB, Interpro, and EMBL
and transformed these databases in flat file format into relational
form using XML and Bioperl. As a result, we showed this tool can
search different sizes of protein information stored in relational
database and the result can be retrieved faster compared to flat file
database. A web based user interface is provided to allow user to
access or search for protein information in the local database.