Ground Penetration Radar (GPR) is a modern and promising geophysical technique for near-subsurface exploring and observing because of its characteristic working scheme (instantaneous underground radargram displaying and subsurface features preserving during the detection tests). In this technique a very high and/ or ultra-high electromagnetic radiation frequencies were utilized to be transmitted to the targeted underground area, then the reflected ones which occur because of the sudden changes in the medium electric properties or texture would be recorded and processed to achieve the final GPR radargram.

     The main goal of this study is to find out the GPR radiation extension which is suitable for concrete

Sediment samples were collected from main water processing and supply plants in Baghdad, and tested for radioactivity from both natural and artificial sources. These stations are: East Dijla (Tigris), Al-Kadisia, Al-Karama, Al-Rasheed, Al-Sader, Al-Wathba, and Al-Wihda supply stations. Qualitative measurements were made, and the results showed that most sediments exhibited natural radioactive level and sometimes less than the international regular standards. Specially, K-40 and Ra-226 results were much less than the standards for radioactive concentrations. Ac-228 concentration was found rather than Th-232 (in Al-Sader and Al-Wihda samples) but with low concentrations of about 10-15 Bg/kg and detection confidence ~45% , and Ce-141 and Be

     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s

Sedimentary structures of Gercus Formation in NE Iraq was little studied in the last decades. In this study the identified sedimentary structures display alternative graded and fining upward cycles, load and flute casts, submarine channels, sand and clay balls and pillow structures, convolute and slump beddings, of marine turbidity origin. The foreland part of Tethys basin characterized by deep marine Tanjero and Kolosh Formations followed by the Gercus formation with conformable relationships. The Eocene aged Flysch comprises predominantly litharenitic sandstones and interbedded mudstones, both of turbiditic affinities and most likely derived from a NE Arabian Plate source. The sediments provide excellent examples of distal fan sands as

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

Establishing coverage of the target sensing field and extending the network’s lifetime, together known as Coverage-lifetime is the key issue in wireless sensor networks (WSNs). Recent studies realize the important role of nature-inspired algorithms in handling coverage-lifetime problem with different optimization aspects. One of the main formulations is to define coverage-lifetime problem as a disjoint set covers problem. In this paper, we propose an evolutionary algorithm for solving coverage-lifetime problem as a disjoint set covers function. The main interest in this paper is to reflect both models of sensing: Boolean and probabilistic. Moreover, a heuristic operator is proposed as a local refinement operator to improve the quality

Phishing is an internet crime achieved by imitating a legitimate website of a host in order to steal confidential information. Many researchers have developed phishing classification models that are limited in real-time and computational efficiency.  This paper presents an ensemble learning model composed of DTree and NBayes, by STACKING method, with DTree as base learner. The aim is to combine the advantages of simplicity and effectiveness of DTree with the lower complexity time of NBayes. The models were integrated and appraised independently for data training and the probabilities of each class were averaged by their accuracy on the trained data through testing process. The present results of the empirical study on phishing websi

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

    Today the Genetic Algorithm (GA) tops all the standard algorithms in solving complex nonlinear equations based on the laws of nature. However, permute convergence is considered one of the most significant drawbacks of GA, which is known as increasing the number of iterations needed to achieve a global optimum. To address this shortcoming, this paper proposes a new GA based on chaotic systems. In GA processes, we use the logistic map and the Linear Feedback Shift Register (LFSR) to generate chaotic values to use instead of each step requiring random values. The Chaos Genetic Algorithm (CGA) avoids local convergence more frequently than the traditional GA due to its diversity. The concept is using chaotic sequences with LFSR to gene

     Ground penetrating radar (GPR) technology is used to determine the extent to which this technique can detect with a high-frequency range from 10 MHz to 1000 MHz into the ground by a transmitting antenna and A graveyard was found beneath the depth of the three meters under Surface of the earth in the shrine of the Prophet Houd and Saleh in Al-Najaf Governorate surveyed by through 4 tracks. Ground Penetrating Radar (GPR) is a device that transmits short pulses of electromagnetic energy with pulse duration about 1 ns to 20 ns. applying the filter Time- Zero to the same profile at a depth (3m) , Two types of antennas were used in this study, with two different frequencies antennas (250, 500 )MHz Three tracks (23,25,2