This research aims to know the impact of leadership integrity as explanatory variable including its dimensions (courage, asceticism, justice, rationality, and humanity) on organizational conflict as responding variable. This research depended on the descriptive-constructive approach through the responses of a sample of (79) employees from (Real Estate Office of The State) in Al-Najaf province. The analyzing of the study done by using (Smart PLS) program to calculate (R^2, t, p). Many results have been concluded and one of them, there is significant impact correlation of the leadership integrity on organizational conflict. There are many suggestions have been reached depending on the results reached and one of them is the necess

• Islamic art is applied art that searches for everything that is useful and beneficial and Both are properties of Islamic art. Islamic art has many well-established elements and styles and pictures that distinguish it from the rest of the arts among those elements and methods that were used in the architectural cladding artwork Or mosaic murals and mosaic was known in its first form in Babylon in a primitive style similar to it, but the Muslim artist in the era of the Caliphs made the art of mosaic In mosques and palaces.
  Chapter one: This chapter is concerned with introducing the art of mosaic historically and focusing on it.
  Chapter Two: This chapter deals with contemporary Islamic mosaics, especially in Mecca

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

The seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.

Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c