In this paper, a single-phase boost type ac-dc converter with power factor correction (PFC) technique is designed and implemented. A current mode control at a constant switching frequency is used as a control strategy for PFC converter. The PFC converter is a single-stage singleswitch boost converter that uses a current shaping technique to reshape the non-sinusoidal input current drawn by the bulky capacitor in the conventional rectifier. This technique should provide an input current with almost free-harmonics, comply with the IEC61000-3-2 limits, and a system operates with near unity power factor. The other function of the boost converter that should be
accomplished is to provide a regulated DC output voltage. The complete designed

Liquid electrodes of domperidone maleate (DOMP) imprinted polymer were synthesis based on precipitation polymerization mechanism. The molecularly imprinted (MIP) and non-imprinted (NIP) polymers were synthesized using DOMP as a template. By methyl methacrylate (MMA) as monomer, N,Nmethylenebisacrylamide (NMAA) and ethylene glycol dimethacrylate (EGDMA) as cross-linkers and benzoyl peroxide (BP) as an initiator. The molecularly imprinted membranes were synthesis using acetophenone (APH), di-butyl sabacate (DBS), Di octylphthalate (DOPH) and triolyl phosphate (TP)as plasticizers in PVC matrix. The slopes and limit of detection of l

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

Abstract

In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll

News headlines are key elements in spreading news. They are unique texts written in a special language which enables readers understand the overall nature and importance of the topic. However, this special language causes difficulty for readers in understanding the headline. To illuminate this difficulty, it is argued that a pragmatic analysis from a speech act theory perspective is a plausible tool for a headline analysis. The main objective of the study is to pragmatically analyze the most frequently employed types of speech acts in the news headlines covering COVID-19 in Aljazeera English website. To this end, Bach and Harnish's (1979) Taxonomy of Speech Acts has been adopted to analyze the data. Thirty headlines have been collected f

تتطلب عملية التنمية الاقتصـادية في الدول النامية مبالغ كبيرة من رؤوس الأمـوال اللازمة لتنفيذ البرامج والخطط الاقتصادية، ولما كانت الاسـتثمارات التي تنفذها هذه الدول خلال حقبة معينة، تزيد على ما تم  تحقيقه من موارد مالية محلية، فلابد أنْ يمول الفرق من خلال انسياب صافٍ لرأس المال الأجنبي (قروض ومساعدات) إلى الداخل خلال المدة نفسها، لغـرض سَدّ الفجوة في المـوارد المحلية المعدة للاسـتثمار، وعانت بعض د