The aim of the present research is to know the following : What are the Science and technology, society and environment issues (S.T.S.E) which included in the content of thechemistry Book second grade intermediate ? And to achieve the objective of search The two researchers has prepares a list of science and technology, society and environment issues (STSE) consisted of (9) key issues namely (Air quality and the atmosphere, sustainable development, water security, health and preventive security, mineral resources investment, pollution of various kinds, energy, food industry, production of weapons technology) and from which (70) sub-issues emerge,Arbitrators competent agreement has been received . Then, thetwo researchers analyzed the content of the chemistry booksecond grade intermediate in the academic year (2015-2016) depending on the prepared list of the(S.T.S.E), was assured of the validity and reliability, The results showedThe chemistry booksecond grade intermediate achieved (17) sub-issue with percentage of (24.29%) . In the light of the search results, the two researchers recommend Including chemistry booksecond grade intermediate with main and sub- main issues of the (S.T.S.E) issues that have not been included , as one of the important modern attitudes in the scientific education , the researcher suggested to conducting other studies to analyze chemistry books for the other stages, and other subjects such as physicsin the light of the same issues .
A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
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Functional strength is one of the most important elements of physical preparation and an important physical characteristic in our daily life in general and sports training in particular, as it is the most influential characteristic in all sporting events, which the athlete must possess in order to reach the highest levels and achieve the best results. The research aimed to prepare functional strength training exercises According to the gradual increase in load in the development of some physical abilities and achievement for men's 100 meter competition runners , And to identify the effect of functional strength training according to the gradual increase in load in developing some physical abilities and achievement for men’s 100-
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Functional strength is one of the most important elements of physical preparation and an important physical characteristic in our daily life in general and sports training in particular, as it is the most influential characteristic in all sporting events, which the athlete must possess in order to reach the highest levels and achieve the best results. The research aimed to prepare functional strength training exercises According to the gradual increase in load in the development of some physical abilities and achievement for men's 100 meter competition runners , And to identify the effect of functional strength training according to the gradual increase in load in developing some physical abilities and achievement for men’s 100-
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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