The current study aims to investigate the second cycle students’ motives for using electronic games in Oman. The sample consisted of (570) students, (346 males and 224 females). The participants completed an open-ended question which was analyzed based on ground theory. The results showed that (46.820%) of the males and (77.678) of the females played electronic games for pleasure, entertainment, and fun. This first category of motivation got the highest percentage of frequency (58.947%). The motive to become a hacker, a popular YouTuber got the lowest percentage (2.280%). Other students’ motives toward playing electronic games included: filling the leisure time, overcoming boredom, feeling adventures, getting science fiction and challenges, developing mental skills, overcoming loneliness, learning new languages, providing movement, enthusiasm, pleasure & comfort, getting prizes, making friends and exchanging experience. The researchers recommended paying attention to the students’ motives toward electronic games and utilizing them in raising their motivation towards learning.
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The most hazardous class of pharmaceuticals for soil and aquatic ecosystems are antibiotics, which include prescription medications and cancer treatments. Hospital effluents are usually produced by all parts of medical facilities, including hospitals. This study's specific goal was to provide a quick, affordable, and accurate analytical technique for determining the levels of amoxicillin, azithromycin, and penicillin in wastewater from Medical City, Al-Mahmudiya, and Al-Yarmouk hospitals (Iraq, Baghdad). An HPLC with a receptive ODS C18 column was used. It was equipped with UV and pulsed amperometric detectors with wavelengths of 230 nm and 210-240 nm, respectively. The correlation coefficients for each drug are greater than 0.9999,
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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