The organization uses many techniques and methods to ensure that they will succeed and adapted with velocity change in the internal and external environment by decision taking, especially strategic decisions.

Strategic decisions are very important for organization success because it can predict the future and deal with uncertainty, in this circumstances they need accurate and comprehensive information to make effective strategic decision.

To achieve that purpose it must owned successful Strategic Information System ( SIS ) and determined the critical success factors for this system ,which can assisted the worker to focus on the important activities to develop it.

This research dealt with shedding light on the nature of material misrepresentations, in addition to knowing the extent to which the quality of accounting information systems contributes to reducing material misrepresentations On the theoretical side, a number of sources were relied upon in dealing with the research problem and presentation of the topic, while in the practical side, it was relied on the questionnaire form, where the research sample was (accountants and auditors), where 50 forms were distributed and 50 were received, and the data was analyzed and hypotheses tested through the program Statistical spss to show the relationship between the variables. The research reached a number of conclusions, the most important of which is t

The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re