It is very well known in the planning publications that when creating spacing development to a region or sub-region, it can be able to make more than an alternative consisting with the strategic directions overtaken from the actual development of region and the situational and developmental objectives needed. However, the difficulty facing the situational planning is in selecting one of these alternatives to be the best in order to make a balanced situational re-structure, and achieving the economic, social and civil objectives. The developmental situation elements in the regions and governorates, including (Karbala) impose themselves as situational power which implies the process of re-structural arrangement where the situational develo

Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f

Cyber security is a term utilized for describing a collection of technologies, procedures, and practices that try protecting an online environment of a user or an organization. For medical images among most important and delicate data kinds in computer systems, the medical reasons require that all patient data, including images, be encrypted before being transferred over computer networks by healthcare companies. This paper presents a new direction of the encryption method research by encrypting the image based on the domain of the feature extracted to generate a key for the encryption process. The encryption process is started by applying edges detection. After dividing the bits of the edge image into (3×3) windows, the diffusions

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy