The study aims to measure the level of academic stress in the e-learning environment in three areas, students and their dealing with classmates, dealing with the professor and technical skills, and the nature and content of the curriculum among graduate students in the College of Education at King Khalid University during COVID-19 pandemic. This study was descriptive in nature (survey, comparative). The sample consisted of (512) male and female graduate students in the master's and doctoral programs. The Academic Stress Scale in the E-learning Environment designed by Amer (2021) was used. The results indicated a high level of academic stress among graduate students in the e-learning environment. The study also found that there were statistically significant differences in the level of these stresses based on gender with female students reporting higher score means than male students. Moreover, results revealed that there were statistically significant differences in the level of these stresses between masters and doctoral students in favor of master's students. However, there were no statistically significant differences found based on the variable of specialization.
Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp
... Show MoreThe reaction of 2-amino-benzothiazole with bis [O,O-2,3,O,O – 5,6 – (chloro(carboxylic) methiylidene) ] – L – ascorbic acid (L-AsCl2) gave new product 3-(Benzo[d]Thaizole-2-Yl) – 9-Oxo-6,7,7a,9-Tertrahydro-2H-2,10:4,7-Diepoxyfuro [3,2-f][1,5,3] Dioxazonine – 2,4 (3H) – Dicarboxylic Acid, Hydro-chloride (L-as-am)), which has been insulated and identified by (C, H, N) elemental microanalysis (Ft-IR),(U.v–vis), mass spectroscopy and H-NMR techniques. The (L-as am) ligand complexes were obtained by the reaction of (L-as-am) with [M(II) = Co,Ni,Cu, and Zn] metal ions. The synthesized complexes are characterized by Uv–Visible (Ft –IR), mass spectroscopy molar ratio, molar conductivity, and Magnetic susceptibility techniques. (
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يتضمن البحث تعيين عنصر الزئبق السام بتراكيزنزرة عالية الدقة (نانوغرام) باستخدام منظومة يخار الزئبق البارد لنماذج غذائية (لحوم حمراء ، لحوم بيضاء ) مختلفة ونماذج مائية (ماء النهر، مياه صناعية ، ماء الشرب) وربط المنظومة بتقنية الامتصاص الذري اللهبي.
ان عنصر الزئبق من اشد العناصر سمية وان التراكيز المسموح بها عالميا لايتعدى جزء واحد
A prominent figure such as Yahya bin Khaldoun and a scholar of the moroccan countries in the medieval era, and had a special place in the history of the country and the state of Bani Zayan, and the positions he occupied in it and left his scientific, literary and historical traces, leaving him an imprint in the course of history and its events, and in this study
I dealt with the research: his personal life : his name and lineage, then his upbringing and his family.
The aim of the study is to know this character in the details of his personal and scientific life, according to the historical descriptive research method, including description and presentation of events, and linking them in a
... Show MoreCyberbullying is one of the biggest electronic problems that takes multiple forms of harassment using various social media. Currently, this phenomenon has become very common and is increasing, especially for young people and adolescents. Negative comments have a significant and dangerous impact on society in general and on adolescents in particular. Therefore, one of the most successful prevention methods is to detect and block harmful messages and comments. In this research, negative Arabic comments that refer to cyberbullying will be detected using a support vector machine algorithm. The term frequency-inverse document frequency vectorizer and the count vectorizer methods were used for feature extraction, and the results wer
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Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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ءأرﻘﻟا ةﺎﯾﺣﺑ ًﺎﻘﯾﺛو ًﻻﺎﺻﺗا لﺻﺗﺗ. نﻣ ﮫﺑﺗﺎﮐﻟﻟ ﻲﺻﺧﺷﻟا ﻊﺑﺎطﻟا ﻲﻔﺣﺻﻟا دوﻣﻌﻟا لﻣﺣﯾ ا فﻟﺗﺧﻣﻟ ﮫﻟوﺎﻧﺗ لﻼﺧ وا ﮫﺋارا وا هرظﻧ ﺔﮭﺟو لﻣﺣﺗ ﻲﺗﻟا ﺔﯾﻣوﯾﻟا ثادﺣﻻاو ﺎﯾﺎﺿﻘﻟ ﺢﺿﻔﺑ موﻘﯾو ثادﺣﻻاو ﺔﯾﺑﻟﺳﻟا رھاوظﻟﻟ ىدﺻﺗﯾ وا، ءيرﺎﻘﻟا ﯽﻟا ﮫﺑرﺎﺟﺗ وا هرﺎﮐﻓا ءﺎطﺧﻻا دﺻرﯾ بﯾﻗرﺑ ﮫﺑﺷا وھو، ءيرﺟﻟا دﻘﻧﻟا نﻋ مﻧﯾ بوﻟﺳﺎﺑ ﺔﺋطﺎﺧﻟا تﺎﺳرﺎﻣﻣﻟا ﺎﮭﺣدﻣﯾو تﺎﯾﺑﺎﺟﯾﻻا ﯽﻟﻋ
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