Dijlah Publisher House
Not a member yet
259 research outputs found
Sort by
تأثير حوكمة الشركات على الميزة التنافسية في المصارف العراقية: بحث ميداني
No full textيهدف هذا البحث إلى دراسة تأثير تطبيق مبادئ حوكمة الشركات على تعزيز الميزة التنافسية في المصارف العراقية. تكمن أهمية هذه الدراسة في تناولها لبيئة الأعمال الحالية التي تتسم بمنافسة شديدة، مما يفرض على المصارف ضرورة تبني آليات إدارية حديثة مثل الحوكمة لضمان استدامتها. حيث تمحورت مشكلة البحث حول الكيفية التي يمكن بها للحوكمة أن تؤثر ايجاباً على الأداء المصرفي وأن تسهم في خلق ميزة تنافسية مستدامة. وللإجابة على هذا التساؤل، اتبع البحث المنهج الوصفي التحليلي. وتم جمع البيانات الأولية من خلال استبيان وُزع على عينة من الأكاديميين والمختصين في القطاع المصرفي، وقد بلغت نسبة الاستجابة 100%. كما تم الاعتماد على البيانات الثانوية المأخوذة من الكتب والأبحاث المتخصصة لبناء إطار نظري متكامل.
أكدت النتائج الإحصائية، التي جرى تحليلها باستخدام مقياس ليكرت ومعاملات الارتباط والثبات، وجود علاقة إيجابية وقوية بين تطبيق مبادئ الحوكمة وتعزيز الميزة التنافسية. وأظهرت الدراسة أن أفراد العينة يتبنون وجهة نظر إيجابية للغاية بشأن أهمية الحوكمة كأداة استراتيجية لتحقيق التفوق المصرفي. بناءً على هذه النتائج، يوصي البحث بضرورة وضع استراتيجية واضحة لتطبيق الحوكمة في المصارف العراقية، مع التركيز بشكل خاص على مبدأي الشفافية والإفصاح. كما يشدد على أهمية الترويج لهذه المفاهيم الحديثة لجذب الزبائن وزيادة ثقتهم، مما يساهم في نهاية المطاف في تعزيز الأداء المالي وسمعة المصرف في السوق
Classification of types of data passing through the network using deep learning
No full textNetwork traffic classification is crucial for network security and management. Traditional methods often struggle with accuracy and scalability. This paper proposes a deep learning-based approach to classify various data types traversing a network. By leveraging the powerful feature extraction capabilities of deep neural networks, we aim to improve classification accuracy and adaptability to evolving network traffic patterns. We explore the application of convolutional neural networks (CNNs) to capture both spatial and temporal dependencies within network packets. Experimental results demonstrate the effectiveness of our proposed method in accurately classifying different data types, surpassing traditional techniques in terms of precision, recall, and overall accuracy.
Our CNN model is designed to capture the underlying patterns and characteristics of network traffic. By processing raw traffic data as images, the model can learn to identify distinctive features that differentiate various traffic types
Characterization of Synthesized Zeolite from Iraqi Metakaolin and its application in dye removal from wastewater
No full textThe present work aims to synthesise and characterise Zeolite using Iraqi metakaolin and to study their performance in the removal of dye from wastewater. Techniques such as scanning electron microscope SEM, X-ray diffractometer XRD, and FTIR Fourier transmission infrared spectrometer were used to synthesise zeolite characterisation. A UV spectrometer determined zeolite\u27s efficiency in removing RB dye from wastewater. The X-ray diffraction result for the zeolite prepared showed that the zeolite was identical in structure to the commercial zeolite Type A. The prepared zeolite was examined as an adsorbent to remove RB dye from wastewater. The adsorption Experiment revealed that approximately 13 ppm of dye could be removed per 2 grams of zeolite, which was deemed unsatisfactory and compatible with similar studies. Additionally, adsorption isotherms modelling indicated that the Langmuir model best described the adsorption behaviour, suggesting a monolayer adsorption process.
Mechanical Properties of welded steel pipes type 213 Gr T5 used in heat exchangers
No full text
This work is concerned to the welding process for joining pipes made from alloy steel which is widely used in heat exchangers structures. The chemical composition analysis of this steel type close to 213 Gr T5 according to ASTM standard. This work show that this metal has a good weldability and high level of weld metal integrity.
Weld filler type ER 502 of 2.4 mm diameter is used in this welding method to join sections of pipes by using Tungsten Inert Gas welding (TIG) process. This investigation is covered the approving of weld integrity assessments and mechanical prosperities by doing a number of tests for weld joint, for example, tensile testing, bending, hardness, x-ray and Liquid penetrant tests). Eventually it was confirmed that, the weld metal has a reasonable joint mechanical property and no series weld defects.
Predicting Heart Attacks using Machine Learning with Multiple Models and Hard Voting to Improve Accuracy
No full textSince heart attacks continue to be a leading cause of mortality globally, these numbers should encourage scientists to develop more effective methods of prevention and early detection. Using clinical data as a starting point, we train and verify a model to forecast the likelihood of a heart attack using machine learning techniques. Indicators of a patient\u27s health form the basis of this concept. The best classification model was chosen after extensive testing and evaluation of many models, such as logistic regression, decision trees, random forest, support vector machines (SVM), k-nearest neighbours (kNN), Naïve Bayes, and Extreme Gradient Boosting (XGBoost). Feature scaling and encoding were applied to all 303 patients in the sample, who possessed a total of 14 distinct characteristics. Two sets of data were created: one for training and one for testing, so that the models could be tested. For every model, we determined the following metrics: ROC-AUC, F1-score, recall, accuracy, precision**, and precision. By a wide margin, XGboost outperformed kNN and SVM classifiers with its 90.2% prediction accuracy. Furthermore, we were able to train an ensemble voting classifier that achieved somewhat better results than the top individual model as well as its individual components. According to feature significance analysis, the two most essential criteria in determining the likelihood of a heart attack are the "which type" of chest pain and the "what kind" of exercise-induced angina. We go deeply into the models\u27 inner workings, discussing the consequences of our discoveries and possible future enhancements. By utilizing machine learning algorithms, medical professionals may improve their ability to foretell the likelihood of a cardiac event, which might result in more timely and effective treatment. Future efforts to improve prediction performance could make advantage of more complete ensemble techniques, bigger datasets, and other characteristics
Improving Wireless Network Routing Performance Using Stingless Bee Foraging Behavior Algorithm
No full textBecause stingless bees forage in a unique way, an optimization algorithm needs to account for this behavior. Stingless bees, whether they forage in groups or alone, have a particular way of doing so. Within bee groups, foraging behavior differs from group to group. Based on the unique behaviors of stingless bees, we created an optimization algorithm in this study. The proposed stingless bee algorithm was then put to the test in order to tackle the challenge of wireless network routing optimization while accounting for residual energy. The calculation time of the stingless bee algorithm was examined by varying the number of nodes used in this work—5, 10, 15, 20, and 25. There are more potential solutions when there are more nodes. The most crucial elements of the designed stingless bee algorithm are the reduction and early termination procedures. The algorithm differs from other bee-swarm-based algorithms due to these two principles
Influence of Holes in Vortex Generators on the Thermal Performance of Flat Plate
No full textVortex generators (VGs) are used in aviation to delay boundary layer separation, which is crucial for increasing the critical angle of attack and, as a result, delaying the aircraft\u27s entry into stall. This is because the vortex generators (VGs) increase the flow energy within the boundary layer. In this paper, the impact of punched triangular vortex generators on convective heat transfer was investigated on a flat plate. Using a wind tunnel (DUC), four pairs of triangular vortex generators were placed on a flat plate, with nine thermocouples implanted in it to measure the temperature change. Three experiments were conducted: the first with a flat plate without a VG, the second VG without holes, and the last VG with holes. The results showed that the presence of the holes had a positive effect on improving heat transfer
Immunohistochemical Expression of the Estrogen Receptor in Oral Pemphigus Vulgaris
No full textThe current study sought to assess the immunohistochemical expression of estrogen receptors (ER-α) in oral PV biopsies. The study was conducted from May 10, 2020, to February 9, 2021. 44 paraffin embedded oral PV tissue blocks were taken. Each block was sliced with a microtome. Antibodies were applied to each sample using the IHC technique to observe the expression of ER. The first was dependent on the intensity of the stain, and the second on the percentage of cells with positive stain. All results were statistically analyzed using the SPSS application. The Chi-square and Spearman tests were used. Results: The intensity of ER-α in all silds was studied and found to be negative in 29 cases and mild in 15 cases. According to the percentage of the cells with positive stains, the results were as follows: The 30 cases registered as negative for ER-α, the scoring for 11 cases was weak, and finally 3 cases showed a moderate score. The current study showed that activation of ER- doesn\u27t play a role in the story of PV, but more research was needed to figure out and clarify the role of EH in autoimmune blistering conditions
The Difficulty in Diagnosis Orf Disease with Erythema Multiform The Difficulty in Diagnosis Orf Disease with Erythema Multiform
No full text Orf is a zoonotic disease also known as a sore mouth disease that mostly affects sheep goats and other animals. People can get it too if they have contact with infected animals, people, and animals usually recover without long–term effects. The disease is caused by orf virus, a type of poxvirus. Lesions usually develop on the hands, and around the mouth and can occur anywhere and resolve within (4-6) weeks without treatment. According to (CDC) Centers for Disease Control and Prevention, the disease is not transmitted from human to human