The research seeks to identify the proposed scenarios to predict and ward off monetary credit risks that the bank is exposed to in the future, using the banking stress tests model, and showing their impact on capital adequacy and profitability ratio,To achieve this purpose, Sumer Commercial Bank was taken as a case study, and mathematical equations were used to extract the results. Low percentage of profits and returns, strictness in the process of granting credit and financing operations in order to reduce credit risks.

The current work aims to evaluate the association between genetic mutations in thymidylate synthetase (TYMS gene in exon1 and partial regions of promotor and intron 1 [877 bp, 657,220–658,096 bp]) and the therapeutic outcomes for rheumatoid arthritis (RA) Iraqi patients. An observational cross-sectional study involving 95 RA patients with established RA patients based on their methotrexate treatment responsiveness. Genetic sequencing of the TYMS gene was performed for all patients according to the instruction manuals of the sequencing company (Macrogen Inc. Geumchen, South Korea). Four polymorphisms were identified by sequencing 95 randomly selected patients in the noncoding region of TYMS

    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

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

Georeferencing process is one of the most important prerequisites for various geomatics applications; for example, photogrammetry, laser scan analysis, remotely sensing, spatial and descriptive data collection, and others. Georeferencing mostly involves the transformation of coordinates obtained from images that are inhomogeneous due to accuracy differences. The georeferencing depends on image resolution and accuracy level of measurements of reference points ground coordinates.  Accordingly, this study discusses the subject of coordinate’s transformation from the image to the global coordinates system (WGS84) to find a suitable method that provides more accurate results. In this study, the Artificial Neural Network (ANN) method wa

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

  Speech is the first invented way of communication that human used age before the invention of writing. In this paper, proposed method for speech analyses to extract features by using multiwavelet Transform (Repeated Row Preprocessing).The proposed system depends on the Euclidian differences of the coefficients of the multiwavelet Transform to determine the beast features of speech recognition. Each sample value in the reference file is computed by taking the average value of four samples for the same data (four speakers for the same phoneme). The result of the input data to every frame value in the reference file using the Euclidian distance to determine the frame with the minimum distance is said to be the "Best Match". Simulatio

This work includes the synthesis and identification of ligand {3-((4-acetylphenyl)amino)-5,5-dimethylcyclohex2-en-1-one} (HL* ) by the treatment of 5,5-dimethylcyclohexane-1,3-dione with 4-aminoacetophenone under reflux. The ligand (HL* ) was identified via FTIR, Mass spectrum, elemental analysis (C.H.N.), 1H and 13C-NMR spectra, UV-Vis spectroscopy, TGA and melting point. The complexes were synthesized from ligand (HL* ) mixed with 3-aminophenol (A) and metal ion M(II), where M(II) = (Mn, Co, Ni, Cu, Zn and Cd) at alkaline medium to produce complexes of general formula [M(L* )(A)] with (1:1:1) molar ratio. These complexes were detected via FT-IR spectra, UV-Vis spectroscopy as well as elemental analysis (A.A) and melting point, conductivit

This study was for searching for Cholera Bacteria serotype which causes epidemiology Cholera in the 2007 in a fast method which contains (Rapid Visual Test) (Crystal V.C.) which was used for the first time in Iraq to diagnosis of Cholera Bacteria & compared with the traditional bacteriology method. The Cholera disease is one of the most dangerous epidemiological diseases which lead to death with a percentage of (50 – 70) % in the severe cases for untreated patients . For this purpose, 100 samples of stool from the patients from a (13) hospitals in Baghdad Governorate in the period from August to the end of December. The Cholera was diagnosis in two methods, 1st method was the fast method using the nitrocellulose which is coated with anti-

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg