The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on the understanding of thermodynamics, group work and self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq, for academic year 2011-2012. In this study, the pre and posttest were done and the instruments were administered to the students for data collection. Inferential statistics were employed to analyze data. The independent variables were the PBL, the PBL with lecture method, and the conventional teaching. Dependent variables of statistical analysis were posttest scores on the understanding of thermodynamics, group work skills, and self-directed learning skills. Covariates of statistical analysis were pretest scores of the understanding of thermodynamics, group work skills, and self-directed learning skills. The data were analyzed using statistical package social sciences (SPSS) version 19. Overall, the statistical results rejected all null hypotheses of this study. Thus, the use of PBL with lecture method enhances the understanding of thermodynamics better than using the PBL alone or using conventional teaching method. Using the PBL without or with lecture method promotes the skills of group work, and self-directed learning better than using the conventional teaching, among physics undergraduate.
Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
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Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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The research aims to identify the level of psychological burnout among the professors of Sana’a University in light of the armed conflicts in Yemen. The research sample consisted of (104) faculty members. A descriptive-analytical approach was adopted. The results of the research showed that university professors suffer from psychological burnout at a very high level in the overall score of the scale. There were no statistically significant differences in terms of gender, academic degree, teaching experience, marital status, number of family members, or salary. In light of the results, the researcher presented a number of relevant recommendations and suggestions.
Background: Dental anomalies might occur due to abnormal events during teeth development caused by environmental or genetic factors during histo differentiation or morph differentiation stages of embryological development. Aims of the study: To evaluate the distribution of developmental dental anomalies according to age and gender in relation to nutritional status in children attending College of Dentistry /University of Baghdad. Materials and method: After examination 5760 children aged 5-12 years of both genders only 147child with dental anomalies were found, all developmental dental anomalies that were clinically observable were recorded. The developmental dental anomalies which diagnosed in this study were supernumerary, missing teeth,
... Show MoreIntroduction: Although it is discouraged, community pharmacy customers can obtain oral corticosteroids (OCSs) without prescriptions from some community pharmacies in Iraq. Medication abuse is defined as the use of medication for non-medical reasons. Objectives: The study aimed to determine demographics, beliefs, and perceptions associated with the abuse of oral corticosteroids for non-illness reasons among community pharmacy customers. Methods: This cross-sectional study was conducted in fall 2018 in four provinces in Iraq. Customers of 19 community pharmacies asking for OCSs for themselves without a prescription were administered a paper survey. This study used the Theory of Reasoned Action (TRA) to measure the relation
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Background: The individual differences in emotional and behavioral style can be examined through personality instruments. These differences may explain the health status of the individuals. The purpose of the present study was to assess the influence of Personality Types on gingival and periodontal health status among teachers in Baghdad city in relation to selected salivary hormone (Dehydroepiandrosterone). Materials and methods: Females teachers 534 of randomly selected schools were subjected to personality questionnaire using The Riso-Hudson Enneagram Type Indicator. Teachers were examined to estimate the periodontal status according to the Community Periodontal Index (CPI). A group of teachers were selected for salivary analysis of Dehy
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