The Use of Artificial Intelligence and Robotics -Related Films as a Tool to Introduce the Middle School Students to Artificial Intelligence and Robotics.

تساهم الأفلام القائمة على الذكاء الاصطناعي والروبوتات بشكل كبير في صناعة الأفلام، ومن الواضح أن أعدادها متناسبة مع أعمال السينما التي زادت بسرعة خلال العقد الماضي. وقد لوحظت هذه النسب المتزايدة منها بسبب التطور غير المسبوق في مفاهيم ومشاريع الذكاء الاصطناعي وتكنولوجيا الروبوتات التي اجتذبت طيفًا واسعًا من فئة المجتمعات. لذلك، يهدف هذا البحث إلى التحقق من تأثير هذا النوع من الأفلام على مجموعة من طلاب المرحلة الإعدادية. تم إعداد المنهجية المقترحة لهذه الدراسة لقياس الجوانب المختلفة لطلاب المرحلة الإعدادية على النحو التالي: (1) إدخال مثل هذه الموضوعات التكنولوجية و (2) زيادة مهارات الإبداع والتخيل. تم إجراء استبيان لتقييم الأثر على طلاب المدارس الإعدادية قبل وبعد مشاهدة مقاطع فيلم محددة مسبقًا تتعلق بالذكاء الاصطناعي والروبوتات. أظهرت نتائج الاستبيان أن مثل هذا النوع من الأفلام له آثار إيجابية أولية على دوافع الطلاب وإلهامهم وإبداعهم.Artificial intelligence and robotics-based films contribute significantly to the films industry, it is evidenced that it is proportion as part of the film business was increased rapidly during last decade. This was observed due to the increases in the artificial intelligence and robotics technology which have been attracting wide spectrum of the communities’ category. Therefore, this paper aim to investigate the impact of this type of films on the middle school students’ group. The proposed methodology of this study is made to measure various aspects for the middle school students as follows: (1) Introducing such technological topics and (2) Increasing the creativity and imagination skills. A survey to evaluate the impact on middle school students was conducted that consists of a list questionnaire before and after watching a pre-selected film clips related to artificial intelligence and robotics. It was evidenced that such as films type have initial positive effects on the students’ motivations, inspiration and creativity

A Smart Infrared Microcontroller-Based Blind Guidance System

Blindness is a state of lacking the visual perception due to physiological or neurological factors. The partial blindness represents the lack of integration in the growth of the optic nerve or visual centre of the eye, and total blindness is the full absence of the visual light perception. In this work, a simple, cheap, friendly user, smart blind guidance system is designed and implemented to improve the mobility of both blind and visually impaired people in a specific area. The proposed work includes a wearable equipment consists of head hat and mini hand stick to help the blind person to navigate alone safely and to avoid any obstacles that may be encountered, whether fixed or mobile, to prevent any possible accident. The main component of this system is the infrared sensor which is used to scan a predetermined area around blind by emitting-reflecting waves. The reflected signals received from the barrier objects are used as inputs to PIC microcontroller. The microcontroller is then used to determine the direction and distance of the objects around the blind. It also controls the peripheral components that alert the user about obstacle's shape, material, and direction. The implemented system is cheap, fast, and easy to use and an innovative affordable solution to blind and visually impaired people in third world countries

Identification of Coronary Artery Diseases Using Photoplethysmography Signals and Practical Feature Selection Process

A low-cost, fast, dependable, repeatable, non-invasive, portable, and simple-to-use vascular screening tool for coronary artery diseases (CADs) is preferred. Photoplethysmography (PPG), a low-cost optical pulse wave technology, is one method with this potential. PPG signals come from changes in the amount of blood in the microvascular bed of tissue. Therefore, these signals can be used to figure out anomalies within the cardiovascular system. This work shows how to use PPG signals and feature selection-based classifiers to identify cardiorespiratory disorders based on the extraction of time-domain features. Data were collected from 360 healthy and cardiovascular disease patients. For analysis and identification, five types of cardiovascular disorders were considered. The categories of cardiovascular diseases were identified using a two-stage classification process. The first stage was utilized to differentiate between healthy and unhealthy subjects. Subjects who were found to be abnormal were then entered into the second stage classifier, which was used to determine the type of the disease. Seven different classifiers were employed to classify the dataset. Based on the subset of features found by the classifier, the Naïve Bayes classifier obtained the best test accuracy, with 94.44% for the first stage and 89.37% for the second stage. The results of this study show how vital the PPG signal is. Many time-domain parts of the PPG signal can be easily extracted and analyzed to find out if there are problems with the heart. The results were accurate and precise enough that they did not need to be looked at or analyzed further. The PPG classifier built on a simple microcontroller will work better than more expensive ones and will not make the patient nervous