Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

The aim of the current study is to identify the effectiveness of cognitive conflict strategy in comprehending reading among literary fifth students in literature and literature texts. The researcher uses experimental method with partial control. The sample consisted of (80) students distributed into control and experimental groups. The scientific material, the behavioral goals, the teaching plans, and the instrument of the research have been prepared (reading comprehension test) by the researcher.

The instrument's validity and reliability have been calculated and then applied to the sample. After treating the data statistically by using SPSS, the results have revealed that there is a statistically significant difference at the si

Abstract The current study is a theoretical study that aims to underline the role of picture books as a serious genre of children's literature in raising children's understanding of English literature and life concepts; especially for non-English speakers. Unfortunately, most Iraqi people have developed a social phobia of learning English since childhood. This phobia is resulted from the heavy traditional reading and writing assignments as well as hard exams. Therefore, this study suggests incorporating more interesting literary material like picture books that would bring pleasure and help in raising children's love and cognition of English Language. More significantly, it calls to replace the old curriculum with a more vital

Abstract

The study aims to build a training program based on the Connectivism Theory to develop e-learning competencies for Islamic education teachers in the Governorate of Dhofar, as well as to identify its effectiveness. The study sample consisted of (30) Islamic education teachers to implement the training program, they were randomly selected. The study used the descriptive approach to determine the electronic competencies and build the training program, and the quasi-experimental approach to determine the effectiveness of the program. The study tools were the cognitive achievement test and the observation card, which were applied before and after. The study found that the effectiveness of the training program

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Obesity is disorder in a foremost nutritional health it’s developed with countries developing. Also is known as increasingin fat accumulation that lead toproblem in health, besidesmay coin one of the reasons lead toloss of life,the obesity not effect on adults just but effect onoffspringand juveniles. In some ofinhabitants the incidence of obesity is superior in female than in male; on the other hand, the variation degree of the between the genderdifferby country.Obesity is generally measured by body mass index and waist circumference, Obesity are classified according to body mass index into:Pre obesity sort 1 : (25 - 29.9) kg/m2, Obesity sort 2 : (30 - 34.9 kg/m2) and extreme obesity sort 3: (40 kg/m2) or greater. Obesity is described by