Active Learning And Creative Thinking

This work examines the ability of a special type of smart antenna array known as Switched Active Switched Parasitic Antenna (SASPA) to produce a directive and electronically steerable radiation pattern. The SASPA array consists of antenna elements that are switchable between active and parasitic states by using P-Intrinsic-N (PIN) diodes. The active element is the element that is supplied by the radio frequency while short-circuiting the terminals of an element in the array results in a parasitic element. Due to the strong mutual coupling between the elements, a directional radiation pattern with high gain and a small beamwidth can be produced with only one active element operating at a time. By changing the parasitic state to the active

أن عملية التعلم لازالت تسير بنفس الاسلوب المتبع الذي لا يعتبر المتعلمة محور اساسي في عملية التعلم مما سبب ظهور الملل وانخفاض الرغبة لدى المتعلمات للتعلم لغياب الحافز, ولكون المهارات الاساسية بكرة السلة كالمناولة الصدرية والطبطبة بتغير الاتجاه والتصويب السلمي تعد من المهارات المهمة في اللعبة تم اجراء هذه الدراسة الذي يهدف الى اعداد  منهج تعليمي قائم على انموذج التعلم البنائي والتعرف على تأثيره في بعض ا

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

Abstract

The current research aims to identify the level of E-learning among middle school students, the level of academic passion among middle school students, and the correlation between e-learning and academic passion among middle school students. In order to achieve the objectives of the research, the researcher developed two questionnaires to measure the variables of the study (e-learning and study passion) among students, these two tools were applied to the research sample, which was (380) male and female students in the first and second intermediate classes. The research concluded that there is a relationship between e-learning and academic passion among students.

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

      تبنت العديد من المؤسسات الأكاديمية التعلم الإلكتروني منذ سنوات ، وقد أثبت فاعليته في كثير من هذه المؤسسات لاسيما تلك المهتمة بتعلم اللغات الاجنبية. الا انه  مع انتشار جائحة كورونا اصبح التعليم الالكتروني  ضرورة ملحة في الجامعات في جميع أنحاء العالم ، بما في ذلك الجامعات العراقية.  تهدف الدراسة الحالية إلى تقصي أثر هذا الوباء على التعلم الإلكتروني في أحدى الكليات العراقية . يفترض الباحث أن تقبل ال

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Buildings such as malls, offices, airports and hospitals nowadays have become very complicated which increases the need for a solution that helps people to find their locations in these buildings. GPS or cell signals are commonly used for positioning in an outdoor environment and are not accurate in indoor environment. Smartphones are becoming a common presence in our daily life, also the existing infrastructure, the Wi-Fi access points, which is commonly available in most buildings, has motivated this work to build hybrid mechanism that combines the APs fingerprint together with smartphone barometer sensor readings, to accurately determine the user position inside building floor relative to well-known lan

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l