Journal of Al-Qadisiyah for Computer Science and Mathematics

requirements validation techniques (RVTs) play important role to detect possible defects in the requirements (functional, non-functional ). Prototypes are good way to demonstrate the requirements and help stakeholders discover problems. The key advantage of a prototyping-based methodology is that it very quickly provides a system for the users to interact with, even if it is not initially ready for widespread organizational use. The proposed web application has been tested based on the usability, System quality has a considerable effect on ease of use and does directly influence the users' intention to use the TIAS in the future. The analysis indicates that the attractiveness of the user interface, performance and the functionalities are critical success factors of TIAS acceptance. the mean of intention to use and ease of use are respectively 3.77 and 3.54 on a 5-point Likert scale. These results show that TIAS is well accepted in general.

The time series analysis is considered of the important statistics topics which concerned with the study phenomena behavior and interpret them at periods of time. Through a general description of time series and forming a suitable model for time series behavior interpretation for forecasting .
The aim of research is to build a forecasting model to the electricity power consumption in AL - Qadisiya province at the period (2005 - 2012) by using Box Jenkins model in time series and Artificial Neural Networks (ANN) model . The results showed superiority of artificial neural networks by using some error criterion.

Medical image processing is the most challenging field now a days. Processing of CT ovarian images is one of the part of this field.The goal of this work is to present a method for detection of ovarian mass from Computed Tomography Image and determine location as well as calculation area of it. Preprocessing of the CT image includes image resizing, conversion to gray and enhancement makes it ready for applying the processing phase which applied operations on processed image by histogram and marker controlled watershed segmentation to segment it to a set of segment that collectively cover the entire image ,then apply morphological operations to visualize only parts of masses in CT images. Because of the nature of ovarian CT images which contain left and right lobes, a proposed algorithm to division the images after extraction the masses into two images and then apply algorithm to calculate the area of mass in each parts of image. when execute the proposed method, the results obtained are good compared with calculation area of the mass of the ovarian extracted by the region of interest algorithm (ROI) using cursor. A detailed procedure using Matlab (R2010a) software is written to extract mass region in CT Scan ovarian Image.

Image enhancement techniques aim to improve the quality of images. In field of medical image processing, low contrast is considered as one of the main and most important issues. As Histogram Equalization (HE) is an effective and simple technique, it is widely used as contrast enhancement. In this paper, efficient method to enhance the quality of medical images has been proposed. This method depends on Discrete Wavelet Transform (DWT) to decompose an input image as the first step. HE and contrast stretching were carried out on the results of DWT separately. Adaptive Histogram Equalization (AHE) was applied on the main part that is resulted from DWT. Contrast stretching was applied on the remaining parts. The results that been gotten showed goodness and efficiency of the proposed method.

In the field of digital image processing, medical imaging is one of the most important applications areas. However; low contrast and poor quality are the main issues in medical image. So it is essential to enhance images so that the result is more suitable for post processing and diagnosis. Histogram equalization has been proved as an effective and simple technique used as contrast enhancer. This paper presents an efficient method for brain MRI image enhancement. Discrete Wavelet Transform (DWT) has been utilized to decompose MRI image. Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE) applied on the important part of the decomposed image. Finally, inverse of discrete wavelet transform is carried out to get the enhanced image. Experiments results that were obtained showed the effectiveness of proposed method.

Logical Analysis of Data is a technique that used in finding a specific pattern. In Data mining, using this technique through learning process with available data set in order to extract a useful pattern. Then use it in different tasks. So in this paper, we apply this framework in construction a predictive model based on the useful extracted patterns concerned with the pattern sets generation. The practical work testing this predictive model, would be performed based on data set of disease that convenient with the nature of this technique. The data would be obtained from UCI web site for experimented data set.

In this paper we considered the problem of scheduling n jobs on a single machine. Our
aim in this study is to find the near optimal solution to minimize the cost of total flow time
and maximum earliness with unequal ready times.
Different local search methods: (Descent Method, Adjacent Pairwise Interchange
Method, Simulated Annealing, Genetic Algorithm) are developed, compared, and tested for
the problem. We investigate the influence of the parameters variance for these local search
methods, and empirically analyze their starting solutions. Computational experience found
that these local search algorithms can solve the problem up to (23000) jobs with reasonable
time. Also we found that: the Genetic algorithm is the best local search heuristic algorithm
for our problem when the size is less than or equal to (1500) jobs, and for problems of large
size the Simulated Annealing was recommended.

[1]. By constructing appropriate sub- and super-solutions to this system −cu′ = u′′ + f(u, v), −cv′ = ϵ2v′′ + g(u, v), (u, v)(−∞) = S−, (u, v)(∞) = S+ (1) Where, we are interested in component-wise monotone travelling wave solutions of the system of equations ut= uxx+ f(u, v), vt= ϵ2vxx+ g(u, v), (2) for (x, t ) ∈R × R+ for which the asymptotic conditions (u, v)(−∞, t) = S−, (u, v)(∞, t) = S+, t >0 (3) are satisfied. Similar to those introduced in [3] and using essentially identical arguments, itcan be shown that −K ≤ c ≤ Lϵ,(4) whereK and L are positive constants independent of ϵ. One immediate consequenceof this result is that in the limit ϵ → 0 only left travelling waves exist.We investigate the sharpness of these bounds in the special case of CLV kinetics.We show that: the bounds of the wave speed given in [4] are optimal for the given leftand right solutions (sub-solutions and super-solutions).