Abstract Political power in Lebanon is a fundamental objective of any political organization, whether political party or political group. Thus, there is a conflict of power. There are two kinds of political conflict that are differentiated by the idea of legitimacy. The competition is in the political system when the agreement between the social forces is considered legitimate, and the conflict is on the political system when the agreement between these forces ceases to be legitimate and Are working to topple it and seek to establish an alternative system. Therefore, the succession of power in Lebanon is a result of the competition and political conflict, which is in turn a result of the large number of regional and international players

Leaching scheduling techniques are one of the suggested solutions for water scarcity problems .The aim of the study is to show the possibility of using leaching scheduling, when applying the irrigation scheduling program for a certain irrigation project, which was prepare by Water Resources Engineering –University of Baghdad with some modifications to generalized it and it make applicable to various climatic zone and different soil types.
The objectives of this research is to build a system that concerns the prediction of the leaching scheduling (depth and date of leaching water), illustrating the main problems (soil salinity, save the amount of leaching requirement, and to maintain crops growth).The other objective is to compare be

Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

Photocatalytic materials are being investigated as effective bactericides due to their superior ability to inactivate a broad range of dangerous microbes. In this study, the following two types of bacteria were employed for bactericidal purposes: Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus). The shape, crystal structure, element percentage, and optical properties of Ag9(SiO4)2NO3 were examined after it was successfully synthesized by a standard mixing and grinding processing route. Bactericidal efficiency was recorded at 100% by the following two types of light sources: solar and simulated light, with initial photocatalyst concentration of 2 µg/mL, and 97% and 95% of bactericidal acti

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from