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.
A Raman spectroscopy method was optimised to examine the chemical changes of aspirin tablets after interaction with helium temperatures. Several aspirin tablets were exposed to plasma-assisted desorption ionisation flame for different times (10, 30, 50, 60, 180 and 300s) and then analysed by Raman spectroscopy using optimal conditions. The changes in chemistry between exposed and fresh (without exposure to plasma) tablets were compared. The vibrational peaks of the aspirin molecule in the Raman spectrum were identified by checking the peak position. The results showed clear spectra with increases in intensity of vibrational peaks until 30s, whereas no spectra were measured for the exposed tablets to plasma flame after 50s. It can, the
... Show MoreA novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh
... Show MoreA field-pilot scale slow sand filter (SSF) was constructed at Al-Rustamiya Sewage Treatment Plant (STP) in Baghdad city to investigate the removal efficiency in terms of Biochemical Oxygen Demand (BOD5), Chemical oxygen demand (COD), Total Suspended Solids (TSS) and Chloride concentrations for achieving better secondary effluent quality from this treatment plant. The SSF was designed at a 0.2 m/h filtration rate with filter area 1 m2 and total filter depth of 2.3 m. A filter sand media 0.35 mm in size and 1 m depth was supported by 0.2 m layer of gravel of size 5 mm. The secondary effluent from Al-Rustamiya STP was used as the influent to the slow sand filter. The results showed that the removal of BOD5, COD, TSS, and Chloride were
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreDue to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi
... Show MoreKeys for 22 species representing 10 genera of Thripidae were provided collection of
samples carried out during 1999-2001 in different localities in the middle of Iraq. Of them
four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips
bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another
fourteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.);
Microcephalothrips abdominils (Crawford Scolothrips sexmaculatus (Pergande),);Scolothrips
pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella
schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Marchal; Retithrips
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Background: Although underdeveloped in Iraq, telehealth was one tool used to continue health service provision during the COVID-19 pandemic. Aim: To assess women’s experiences and satisfaction with gynaecological and obstetric telehealth services in Iraq during the COVID-19 pandemic. Methods: Free telehealth services were provided by 4 obstetrician-gynaecologists associated with private clinics in 2020–2021. All patients who accessed the services between June 2020 and February 2021 were invited to complete a postconsultation survey on their experience and satisfaction with services. Results were analysed using descriptive statistics and logistic regression conducted using SPSS version 25. Results: A total of 151 (30.2%) women re
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