This research deals with the qualitative and quantitative interpretation of Bouguer gravity anomaly data for a region located to the SW of Qa’im City within Anbar province by using 2D- mapping methods. The gravity residual field obtained graphically by subtracting the Regional Gravity values from the values of the total Bouguer anomaly. The residual gravity field processed in order to reduce noise by applying the gradient operator and 1st directional derivatives filtering. This was helpful in assigning the locations of sudden variation in Gravity values. Such variations may be produced by subsurface faults, fractures, cavities or subsurface facies lateral variations limits. A major fault was predicted to extend with the direction NE-

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

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

In the present work, the critical micelle concentration (CMC) of the solution of Sodium dodecyl sulfate (SDS) as anionic surfactant, Cocamidopropyl Betaine (CAPB) as amphoteric surfactant, and their mixture have been determined using surface tension and conductivity measurements at a temperature range 293 -323 K. The adsorption and thermodynamic micellization parameters (?G?m, ?G?ads, ?max ,Amin,?cmc ) for individual surfactants was calculated. Rosen model which is focuses on the adsorbed mixed surfactant film at the air/solution interface was used to calculate the interaction parameter ( ?? ) at the interface and the activity coefficients g1 and g2. The results indicate that the CMC of the individual surfactants was affected by

Simple, sensitive and economical spectrophotometric methods have been developed for the determination of cefixime in pure form. This method is based on the reaction of cefixime as n-electron donor with chloranil to give highly colored complex in ethanol which is absorb maximally at 550 nm. Beer's law is obeyed in the concentration ranges 5-250 µg ml-1 with high apparent molar absorptivities of 1.52×103 L.mole-1. cm-1.

In-vitro biological activities of the free new H4L ( indole-7-thiocarbohydrazone) ligand and its Ni(II), Pd(II) , Pt(II), Cu(II), Ag(I), Zn(II) and Cd(II) complexes are screened against two cancerous cell lines, that revealed significant activity only for [Cu2Cl2(H4L)2(PPh3)2] after 72 h treatment by the highest tested concentrations. The Copper(I) complex was characterized by X-ray Crystallography and the NMR spectra, whereas it has been confirmed to have momentous cytotoxicity against ovarian, breast cancerous cell lines (Caov-3, MCF-7). The apoptosis-inducing properties of the Cu(I) complex have been investigated through fluorescence microscopy visualization, DNA fragmentation analysis and propidium iodide flow cytometry.

The research aims to identify the importance of using analytical procedures in the detection of creative accounting practices. To achieve this goal, (100) questionnaires were prepared and distributed to the auditors in the Federal Financial Supervision Bureau and the authorized auditors' offices and practitioners of the auditing profession in Iraq. For the purpose of testing the research hypothesis and analyzing data, some appropriate statistical methods have been used and the use of the statistical program (SPSS) to analyze the data. The results of the research showed that the analytical procedures and tests applied by the auditor have a role in revealing and limiting creative accounting practices and methods and that auditors u

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system