The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests

Autorías: Nuha Mohsin Dhahi, Muhammad Hamza Shihab. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

إحدى أهم الطرق لتقصي توزيع المجرات عبر الزمن الكوني هي دالة اللمعان LF بدلالة كتلة القرص الباريوني ψS(Mb)، القدر . لقد درسنا تقديرًا لكثافة كتلة الباريون في عينة من المجرات الحلزونية القضيبية وغير القضيبية من الادبيات السابقة، والتي تتضمن فعليًا، لكل صنف من الاجرام السماوية ذات المحتوى الباريون المرئي، جزءًا لا يتجزأ من ناتج دالة الضيائية (LF) ونسبة الكتلة إلى الضوء. استخدمت تقنية الانحدار المتعدد لحزمة الب

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Background: Breast cancer is the first one among Iraqi females. Most of them present later for diagnosis. Early detection center in tertiary hospital practice uses FNAB for early diagnosis. Publications on accuracy of this detection are scarce.

Objective:  To test the accuracy of FNAB in breast lump diagnosis.

Methods: Diagnostic test accuracy study, on 204 women with breast lump, attending the oncology department in 2017.

Results: Fine-needle aspiration biopsy diagnosis of histologically malignant cases were, malignant in 89 (87.3%), suspicious of malignancy in 5 (4.9%), and benign in 4 (3.9%). Complete sensitivity was 87.3%, and specificity

Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality

This study was conducted from February 2010 to December 2010. Water Samples were collected every two months in three stations in Baghdad city. The study involved the assessment of concentrations of some heavy metals such as: Chromium, Cadmium, Copper, Iron, Lead, Manganese, Nickel and Zinc. the values of chromium were undetected for the entire of the study, while the rest of the heavy metal were ranged between 0.001 -0.438 mg / l, ND -0.077 mg / L, ND -0.778 mg / l, 0.36 - 0.011 mg / l, 0.011-0 .08mg/ l, ND - 0.1985 mg / l, ND -0.0416 mg / l, respectively. The results showed that the concentrations of heavy metals were fluctuated during the study period, except Lead which have high concentrations and exceeded the permit limits in all statio