Fiber optics technology has shown immense applications in the areas of medicine, telecommunication, and imaging. For these particular applications, it requires fibers with precise cleaving. In this paper, we will demonstrate a quick, simple and efficient cleaving method that can result in a high-quality fiber surface that works well for many fiber-optic applications. The smooth tip and good surface quality obtained on the cleaved surface of optical fiber is demonstrated by using a microscope imaging system and was flat surface with a 900 angle for perpendicular cleavages. The precision cleaver provides smooth and high-quality cleaves on single-fiber surfaces as opposed to the ruby scribe pen. The defects that may occur during the cleaving p

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

أن لعبة كرة السلة في تقدم وتطور مستمر حالها في ذلك حال الألعاب الرياضية الأخرى حيث أن الفضل في ذلك يعود إلى المعرفة بالعلوم المختلفة وكذلك البحث العلمي من اجل تحقيق نتائج متقدمة تنشدها معظم الدول ومنها العراق على الصعيد المحلي والعربي والدولي. ومما لاشك فيه أن متطلبات تطور مستوى نتائج القدرات البدنية في أيُة لعبة مرتبطة بالبرمجة والتخطيط الصحيح للمناهج التدريبية إذ تقودنا هذه الحقيقة إلى إجراء المزيد من الا

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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

Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb

Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit