Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

Background: Plantar heel pain is a clinical syndrome characterized by pain and tenderness beneath the heel which is typically worse in the morning and improves after the first few steps in the day. It is a common and frequently disabling clinical complaint that may be caused by a broad spectrum of osseous or soft tissue disorders. Objective: To evaluate the effectiveness of an operation of multiple drilling of calcaneum for resistant plantar heel pain syndrome. Methods: During the period from November 2012 to August 2016, 17 patients (17heels) were enrolled in a cohort clinical study at the orthopedic unit in AL-Sheikh Zayed and AlWassity Hospitals. Result: Drilling of the calcaneum is a simple procedure achieving 70.6% cure in resistant as

Background: Plantar heel pain is a clinical syndrome characterized by pain and tenderness beneath the heel which is typically worse in the morning and improves after the first few steps in the day. It is a common and frequently disabling clinical complaint that may be caused by a broad spectrum of osseous or soft tissue disorders^.

Objective: To evaluate the effectiveness of an operation of multiple drilling of calcaneum for resistant plantar heel pain syndrome.

Methods: During the period from November 2012 to August 2016, 17 patients (17heels) were enrolled in a cohort clinical study at the orthopedic unit in AL-Sheikh Zayed and Al-Wassity Hospitals.

يشهد العالم تقدما في كافة مجالات الحياة المختلفة وتزداد الحياة صعوبة يوما بعد يوم, ويزداد البحث في كافة المجالات التي تعمل على خدمة الإنسان ولقد طال هذا التقدم النشاط الرياضي ,فقد يكون لتطور التدريب الرياضي وتنوع أساليبه الدور الكبير في تحقيق اللياقة البدنية التي تعد إحدى أهم الأهداف التي يرمي إليها الدرس في كلية التربية الرياضية . واللياقة البدنية تستمد أهميتها من كونها إحدى مكونات اللياقة الشاملة التي بدو

A tungsten inert gas (TIG) welding is one of the most popular kinds of welding used to join metals mainly for aluminum alloys.  However, many challenges may be met with this kind of joining process; these challenges arise from decay of mechanical properties of welded materials. In the present study, an attempt was made to enhancing the mechanical properties of TIG weld joint of 6061-T6 aluminum alloy by hardening the surfaces using shoot peening technique. To optimize the shoot peening process three times of exposure (5, 10, and 15) min. was used. All peened and unpeened, and welded and unwelded samples were  characterized by metallographic test to indicate the phase transformation and modification in microstructure occurring d

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach