The use of information and communication technologies has been increasing day-today throughout the world since the 1980s, as these technologies seem to reduce the complexity of issues for governments and at the same time reduce the context. Provided for the complex interdependencies between governments. This dual function of information and communication technologies has caused security problems for countries, especially underdeveloped countries, in terms of lower access or, in other words, the digital divide of advanced countries. The growing challenge in the security of nations is a major concern for everyone, in order to tackle this challenge a great amount of effort must be dedicated. Multiple related questions are asked in this article: Are we capable of IT and Ensure Homeland Security Strategy in Different Countries Do Intelligence Agencies Have the Right IT Infrastructure for the Purposes of Collecting, Sharing, and Disseminating Information? Is there Enough Monitoring Equipment? Information technology plays a significant role and will continue to strengthen the national security against future upcoming threats and cyber-attacks. Particularly, information technology can help countries to identify potential threats, share information easily, and protect mechanisms in them. Provide and develop capabilities.
Blood cells are composed of erythrocytes (Red Blood Cells (RBCs)), the shape of RBC changes when the body suffers from different diseases such as Anemia. Classification of such diseases helps the medical technician to decide the type of Anemia in Laboratory analyzes in the hospitals. This paper proposed an automatic classification algorithm, which discriminates the different types of Anemia using Principal Component Analysis (PCA) algorithm and Decision tree. The proposed algorithm consists of four steps, at the first step preprocessing steps are applied on the RBC image, these RBC images then segmented in the second step, features are extracted using moment invariant in third step, this features are considered input to PCA so as to produced features vectors, at a final step features vector are inputted to Decision Tree to classify RBC image. Best classifications rates are (92%) obtained when using PCA algorithm compared with (74.1 %) which are obtained without applying PCA algorithm.
This paper include the problem of segmenting an image into regions represent (objects), segment this object by define boundary between two regions using a connected component labeling. Then develop an efficient segmentation algorithm based on this method, to apply the algorithm to image segmentation using different kinds of images, this algorithm consist four steps at the first step convert the image gray level the are applied on the image, these images then in the second step convert to binary image, edge detection using Canny edge detection in third Are applie the final step is images. Best segmentation rates are (90%) obtained when using the developed algorithm compared with (77%) which are obtained using (ccl) before enhancement.
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