Petrophysical characterization is the most important stage in reservoir management. The main purpose of this study is to evaluate reservoir properties and lithological identification of Nahr Umar Formation in Nasiriya oil field. The available well logs are (sonic, density, neutron, gamma-ray, SP, and resistivity logs). The petrophysical parameters such as the volume of clay, porosity, permeability, water saturation, were computed and interpreted using IP4.4 software. The lithology prediction of Nahr Umar formation was carried out by sonic -density cross plot technique. Nahr Umar Formation was divided into five units based on well logs interpretation and petrophysical Analysis: Nu-1 to Nu-5. The formation lithology is mainly

In this study, a new adsorbent derived from sunflower husk powder and coated in CuO nanoparticles (CSFH) was investigated to evaluate the simultaneous adsorption of Levofloxacin (LEV), Meropenem (MER), and Tetracycline (TEC) from an aqueous solution. Significant improvements in the adsorption capacity of the sunflower husk were identified after the powder particles had been coated in CuO nanoparticles. Kinetic data were correlated using a pseudo-second-order model, and was successful for the three antibiotics. Moreover, high compatibility was identified between the LEV, MER, and TEC, isotherm data, and the Langmuir model, which produced a better fit to suit the isotherm curves. In addition, the spontaneous and exothermic nature of the adsor

    When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona

Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

In the current endeavor, a new Schiff base of 14,15,34,35-tetrahydro-11H,31H-4,8-diaza-1,3(3,4)-ditriazola-2,6(1,4)-dibenzenacyclooctaphane-4,7-dien-15,35-dithione was synthesized. The new symmetrical Schiff base (Q) was employed as a ligand to produce new complexes comprising Co(II), Ni(II), Cu(II), Pd(II), and Pt(II) metal-ions at a ratio of 2:1 (Metal:ligand). There have been new ligands and their complexes validated by (FTIR), (UV-visible), 1H-NMR, 13C-NMR, CHNS, and FAA spectroscopy, Thermogravimetric analysis (TG), Molar conductivity, and Magnetic susceptibility. The photostabilization technique to enhance the polymer was also used. The ligand Q and its complexes were mixed in 0.5% w/w of polyvinyl chloride in tetrahydrofuran

         Stream ciphers are an important class of encryption algorithms. There is a vast body of theoretical knowledge on stream ciphers, and various design principles for stream ciphers have been proposed and extensively analyzed. This paper  presents a new method of stream cipher, that by segmenting the plaintext into number of register then any of them combined to any other by using combination logic circuit (And, OR, JK, NOT, XOR), then using variant register in length as a key which provides security enhancement against attacks and then compare the strength of this method with RSA by calculaing the time necessary to get the original text by using the genetic algorithm. And the way that ha

The object of the presented study was to monitor the changes that had happened
in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To
fulfill this goal, different satellite images had been used in different times, MSS
1973, TM 1990, ETM+ 2000 and MODIS 2010. K-Means which is unsupervised
classification and Neural Net which is supervised classification was used to classify
the satellite images 0Tand finally by use 0Tadaptive classification 0Twhich is0T3T 0T3Tapply
s0Tupervised classification on the unsupervised classification. ENVI soft where used
in this study.

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

The diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced n

Urban morphological approach (concepts and practices) plays a significant role in forming our cities not only in terms of theoretical perspective but also in how to practice and experience the urban form structures over time. Urban morphology has been focused on studying the processes of formation and transformation of urban form based on its historical development. The main purpose of this study is to explore and describe the existing literature of this approach and thus aiming to summarize the most important studies that put into understanding the city form. In this regard, there were three schools of urban morphological studies, namely: the British, the Italian, and the French School. A reflective comparison between t