Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. One of the outstanding classifications methods in data mining is support vector machine classification (SVM). It is capable of envisaging results and mostly effective than other classification methods. The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.

One of the human diseases with a high rate of mortality each year is breast cancer (BC). Among all the forms of cancer, BC is the commonest cause of death among women globally. Some of the effective ways of data classification are data mining and classification methods. These methods are particularly efficient in the medical field due to the presence of irrelevant and redundant attributes in medical datasets. Such redundant attributes are not needed to obtain an accurate estimation of disease diagnosis. Teaching learning-based optimization (TLBO) is a new metaheuristic that has been successfully applied to several intractable optimization problems in recent years. This paper presents the use of a multi-objective TLBO algorithm for the selection of feature subsets in automatic BC diagnosis. For the classification task in this work, the logistic regression (LR) method was deployed. From the results, the projected method produced better BC dataset classification accuracy (classified into malignant and benign). This result showed that the projected TLBO is an efficient features optimization technique for sustaining data-based decision-making systems.

The world is witnessing a marked and rapid change in the use of the Internet in all areas of life and this is a natural development. Because the existence of the web has swelled and increased and became a lot in various magazines depend on it and greatly. Our topic today is about Internet applications in libraries and information centers. How has library performance developed in general? What are the challenges facing librarians? What is the benefit of the students and researchers? Thanks to the presence of the Internet there has been a great revolution in the performance of libraries and traditional processes and developed many of them, for example, reference services, document delivery, resource sharing, and others. Librarians and staff in information centers face significant challenges in developing their Web site. And this returned to all those who come to the library benefit, where there is a schedule of dates and official holidays, planning of buildings within the library, information center for easy access to the destination and organization of different memberships in different categories, circulation and acquisition, and easy to announce the activities of various periodicals and seminars and know all the details and special rules. This research tries to introduce the impact of the technology on the libraries in terms of librarian and library visitors and the resources in the libraries.