تحديات العولمة للشباب ومواجهتها في ضوء السيرة النبوية

Challenges are part of the ways of life, and the Islamic world is suffering of the rupture and differentiates internal conflicts, and the chaos of thought and delayed civilization. The most prominent of these challenges, which the Islamic world is facing, is the phenomenon of globalization. Which included the three worlds, and sought to dominate them, and melt the people’s properties and this is what precipitated the emergence of numerous drawbacks, and the researcher specially mentioned, negative aspects of identity, ethics and the environment. Young people who are the hope and asset of this nation are able to turn dreams into realities, and hopes to practical projects, and ambitions to the visible achievements. They are worthwhile, and the most capable and powerful to meet these challenges. If they grasp the necessary requirements that qualify and stables them to face it and take advantage of its goodness, and avoid disadvantage. But if they stationed, and failed to do their duty, they offered loss and destruction to themselves and nation. Curriculum should be prepared in accordance with the system of Islamic values, which are the individual configuration integrated, in belief, thought, and behavior, and attention to the development of the curriculum, and make it combines tradition and modernity, and the distinction between fixed and variable, and have superior mental abilities. All these issues are addressed in this research the negative impact of globalization on the environment, ethics and then showed the importance of taking care of the human development of young people, through various training programs that earn young people skills, science, and sophisticated learning methodical thinking, proper planning, and positive participation in society, and carry responsibility, and foster in them the ability to dialogue and to develop in them the spirit of creativity and scientific research and rational dealing with crises, and tribulations, and the ability to solve problems and meet the challenges of globalizatio

Efficient Computer Diagnostic System for Early Detection of Cancer

Breast cancer is considered to be one of the most fatal types of cancer among women. The early detection of breast cancer increases the survival probability. Computer Aided Diagnosis (CAD) system for detection and classifying of masses in mammograms is essential. In this thesis, new pre-processing techniques for mammograms have been proposed. First, an improved segmentation technique using image pre-processing and modified reaction diffusion based level set method is developed. The mammogram is passed through morphological operations, contrast enhancement and interpolation algorithm. The pre-processed image is then passed through a modified reaction diffusion based level set algorithm for accurate breast boundary segmentation. In Second pre-processing technique, pectoral muscle is suppressed by the proposed technique based on geometry and contrast variance between the breast tissues and pectoral muscles. Simulation results verify the significance of proposed schemes visually and quantitatively as compared to state of art existing schemes. Three class classification based on deep learning techniques i.e. CNN and RBMs is proposed. In the CNN-DW method, enhanced mammogram images are decomposed as its four subbands by means of two-dimensional discrete wavelet transform (2D-DWT), while in the second method discrete curvelet transform (DCT) is used. Proposed methods have been compared with existing methods in terms of accuracy rate, error rate, and various validation assessment measures. Simulation results clearly validate the significance and impact of our proposed model as compared to other well-known existing techniques. Last but not the least, a novel three-class classification technique for a large dataset of mammograms using a deep-learning method of restricted Boltzmann machine (RBM) is proposed. The augmented dataset is generated using mammogram patches. The dataset is filtered using a non-local means (NLM) filter to enhance the contrast of patches. These patches are decomposed using (2D-DWT) and (CT). The proposed method is compared with existing methods in terms of ROC curve, accuracy rate and various validation assessment measures. The simulation results clearly demonstrate the significance and impact of our proposed model compared to other well-known existing techniques.