The study aims at evaluating the penalty of semi- intentional killing felony in the Egyptian and Algerian criminal law following the Islamic Law (Shari'a). The study used the descriptive, evalutive and analytical methodology to reach the topic in question. To meet the theoretical significance of the study, much data has been collected to give a comprehensive picture about the topic under examination. As for the practical significance of the study, it helps the juridical power to reconsider and phrase the legal materials of the semi-intentional killing penalty based on the Islamic law. The study has come to the conclusions that the Islamic Law (Shari'a) imposes a compensation (blood-money) to be given to the deceased family and an act of expiation as a penalty against those who proved committed of intentional killing felony. However, the Egyptian Penal Law imposes hard labor/imprisonment as an alternative penalty against this felony. On the other hand, the Algerian Criminal law imposes imprisonment as an alternative penalty to this felony. Consequently, the penalties prescribed by both Egyptian and Algerian Laws contradict with what Islamic Law (Shari'a) necessitates. The study recommended that the Egyptian and the Algerian Criminal laws to activate the Islamic law represented by the compensation (blood-money) and act of expiation as a penalty to this crime.
Ottoman Empire created in the state of Algeria staff who manage its affairs on behalf of the Ottomans, who identified their functions and was mostly soldiers Alancksharien, but these soon engaged in Algerian society and coexist with him, and became them their own interests and participated people there in their business and their trades until it became their property and provinces and the interests they manage to order provide for a living.
عرص كتاب البرلمان في العراق (دراسة للواقع .. وتأملات في المستقبل)
The aim of this study is to propose mathematical expressions for estimation of the flexural strength of plain concrete members from ultrasonic pulse velocity (UPV) measurements. More than two hundred pieces of precast concrete kerb units were subjected to a scheduled test program. The tests were divided into two categories; non-destructive ultrasonic and bending or rupture tests. For each precast unit, direct and indirect (surface) ultrasonic pulses were subjected to the concrete media to measure their travel velocities. The results of the tests were monitored in two graphs so that two mathematical relationships can be drawn. Direct pulse velocity versus the flexural strength was given in the first relationship while the second equation des
... Show MoreThe aim of this study is to propose mathematical expressions for estimation of the flexural strength of plain concrete members from ultrasonic pulse velocity (UPV) measurements. More than two hundred
pieces of precast concrete kerb units were subjected to a scheduled test program. The tests were divided into two categories; non-destructive ultrasonic and bending or rupture tests. For each precast unit, direct and indirect (surface) ultrasonic pulses were subjected to the concrete media to measure their travel velocities. The results of the tests were mointered in two graphs so that two mathematical relationships can be drawn. Direct pulse velocity versus the flexural strength was given in the first relationship while the second equati
The extraction of iron from aqueous chloride media in presence of aluminum was studied at different kinds of extractants(cyclohexanone, tributyl phosphate, diethyl ketone), different values of normality (pH of the feed solution), agitation time, agitation speed, operating temperature, phase ratio (O/A), iron concentration in the feed, and extractant concentration]. The stripping of iron from organic solutions was also studied at different values of normality (pH of the strip solution) and phase ratio (A/O). Atomic absorption spectrophotometer was used to measure the concentration of iron and aluminum in the aqueous phase throughout the experiments.The best values of extraction coefficient and stripping coefficient are obtained under the
... Show MoreFour new species of Thrips (Thripidae) Chirothrips imperatus sp. nov.; Frankliniella megacephala sp. nov.; Retithrips bagdadensis sp. nov; Taeniothrips tigridis sp. Nov.; from middle of Iraq, are described and illustrated with their hosts.
Nineteen thrips species recorded in center of Iraq during 1999-2001, four of them was recorded by El-Haidari & Daoud, 1967; Thrips tabaci Lindeman, Retithrips syriacus (Mayet), Parascolothrips prieseri Mound, Anaphthrips sudanensis Trybom. Fifteen species are recorded for the first time in Iraq, Thrips meridionalis (Priesner), Microcephalothrips abdominals (Crawford), Scolothrips pallidus (Beach), Scolothrips sexmaculatus (Pergande), Scritothrips mangiferae Priesner, Frankliniella schultzie Trybom, Frankliniella unicolor Morgan, Frankliniella Tritici Bagnall, Retithrips aegypticus Marchal, Retithrips javanicus
... Show MoreIn the present research, the chemical washing method has been selected using three chelating agents: citric acid, acetic acid and Ethylene Diamine Tetraacetic Acid (EDTA) to remove 137Cs from two different contaminated soil samples were classified as fine and coarse grained. The factors that affecting removal efficiency such as type of soil, mixing ratio and molarity have been investigated. The results revealed that no correlation relation was found between removal efficiency and the studied factors. The results also showed that conventional chemical washing method was not effective in removing 137Cs and that there are further studies still need to achieve this objective.
Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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