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This is a summary of our research, asking God Almighty for success and payment. Our research included two topics, the first of which dealt with an aspect of the biography of Imam Al-Shafi’i and the origins and terminology of his school of thought, as it was built on foundations based on the Book and the Sunnah, then the consensus on what is not in the Book or the Sunnah, then that some of the companions of the Prophet, may God’s prayers and peace be upon him, say and we do not know of him opposing them, then the analogy is based on Some layers, and nothing becomes to it other than the Book and the Sunnah, and they exist, but knowledge is taken from above.” Then we give preference according to the strongest and most correct evidence, with an indication of the approval of the weighting of the fatwa saying or not.This lies the importance of the issues that we study and we intend to collect them in one place

Background and Aim: Smartphones become a part of today’s life. In spite of the convenience, it contributes to our daily lives and activities, one of the most important problems is smartphone addiction. As known, smartphone addiction is a type of technological addiction or non-substance addiction. The present study is to investigate the association between smartphone addiction and physical activity, sleeping hours among medical science students in Duhok City.Subjects and Methods: A cross-sectional study design carried out with 295 students in medical science colleges in the Duhok City of both gender. Self-reported data collected from December 15, 2019, to January 22, 2020. Structured questionnaire has been used to gather data related to sociodemographic, physical activity, sleeping hours, and smartphone addiction.Results: The study found most students, 78.3% have smartphone addiction, 78% of medical science students are at low physical activity range, and only 2% of students are at normal physical activity range, also revealed 20% of students were inactive. According to daily sleeping hours, more than half of them, 61.7% were in a healthy range of sleeping; however, no statistically significant association found between smartphone addiction with physical activity, sleeping hours while finding a highly statistically significant association between smartphone addiction with gender.Conclusion: The current study figure out smartphone addiction prevalence was very high among medical science college students. Smartphone addiction showed an effect in increasing sedentary health behavior like low physical activity and poor sleeping quality with no statistically significant association.

The effect of variation in cement content, initial water content, void ratio, and curing time on wave velocity (low-strain property) and unconfined compressive strength (large-strain property) of a cemented sand is examined in this paper. The measured pulse velocity is compared with predictions made using empirical and analytical models, which are mostly based on the published results of resonant column tests. All specimens are made by mixing silica sand and gypsum cement (2.5–20% by weight) and tested under atmospheric pressure. The wave velocity reaches a maximum at optimum water content, and it is mostly affected by the number of cemented contacts; whereas compressive strength is governed not only by the number of contacts but also by the strength of contacts. Experimental relationships are developed for wave velocity and unconfined compressive strength as functions of cement content and void ratio. Available empirical models underpredict the wave velocity (60% on average), likely because of the effect of microfractures induced by confinement during the testing. Wave velocity is found to be a good indicator of cement content and unconfined compressive strength for the conditions of this study.Key words: wave velocity, low-strain stiffness, cemented sands, elastic moduli, unconfined compressive strength.

Segmentation is an important step in medical image analysis and classification for radiological evaluation or computer aided diagnosis. This paper presents the problem of inaccurate lung segmentation as observed in algorithms presented by researchers working in the area of medical image analysis. The different lung segmentation techniques have been tested using the dataset of 19 patients consisting of a total of 917 images. We obtained datasets of 11 patients from Ackron University, USA and of 8 patients from AGA Khan Medical University, Pakistan. After testing the algorithms against datasets, the deficiencies of each algorithm have been highlighted., {"references":["Hoffman, E. A, and McLennan, G., \"Assessment of the pulmonary\nstructure-function relationship and clinical outcomes measures:\nQuantitative volumetric CT of the lung\", Academic Radiology, vol. 4,\nno. 11, pp. 758-776, 1997.","Hedlund, L.W., Anderson, R.F., Goulding, P.L., Beck, J. W., Effmann,\nE.L.and Putman, C.E, \"Two methods for isolating the lung area of a CT\nscan for density information\", Radiology, vol. 144, pp. 353-357, 1982.","Uppaluri, R., Mitsa, T., Sonka, M., Hoffman, E. A., and Mclemman, G.,\n\"Quatification of pulmonary emphysema from lung CT images using\ntexture analysis\", Amer. J. Resp. Crit. Care Med. vol. 156, no. 1 pp.\n248-254, 1997.","Julian Kerr, \"The TRACE method for Segmentation of Lungs from\nChest CT images by Deterministic Edge Linking\", University of New\nSouth Wales, Department of Artificial Intelligence, Australia, May\n2000.","Shiying Hu, Eric A.Huffman, and Joseph M. Reinhardt, \"Automatic\nLung Segementation for Accurate Quantitiation of Volumetric X-Ray\nCT images\", IEEE Transactions on Medical Imaging, vol. 20, No. 6,\nJune 2001.","Manzoor Ahmed Khawaja, Muhammed Zaheer Aziz, Nadeem Iqbal,\n\"Effectual Lung Segmentation for CAD System Using CT Scan\nImages\",IEEE Transactions, INMIC, National Univeristy of Emerging\nSciences, FAST Lahore, Pakistan, 2004.","Riccardo Boscolo, Mathew S. Brown, Michael F. McNitt-Gray,\n\"Medical Image Segmentation with Knowledge-guided Robust Active\nContours\", Radiographics, vol. 22, pp. 437-448, 2002.","Binsheng Zhao, Gordon Gamsu, Michelle S. Ginsberg, \"Automatic\ndetection of small lung nodules on CT utilizing a local density\nmaximum algorithm\", Journal of Applied Clinical Medical Physics, vol.\n4, No. 3, summer 2003.","Samuel G. Armato III, Maryellen L. Giger and Catherine J. Moran,\n\"Computerized Detection of Pulmonary Nodules on CT Scans\",\nRadioGraphics, vol. 19, pp. 1303-1311, 1999.\n[10] Ayman El-Baz, Aly A. Farag, Robert Falk, Renato La Rocca,\n\"Detection, Visualization and identification of Lung Abnormalities in\nChest Spiral CT Scan: Phase-I\", International Conference on\nBiomedical Engineering, Cairo, Egypt, 12-01-2002.\n[11] Ayman El-Baz, Aly A. Farag, Robert Falk, Renato La Rocca, \"A\nUnified Approach for Detection, Visualization and Identification of\nLung Abnormalities in Chest Spiral CT Scan\", Proceedings of\nComputer Assisted Radiology and Surgery, London 2003."]}