E-learning has recently become of great importance, especially after the emergence of the Corona pandemic, but e-learning has many disadvantages. In order to preserve education, some universities have resorted to using blended learning. Currently, the Ministry of Higher Education and Scientific Research in Iraq has adopted e-learning in universities and schools, especially in scientific disciplines that need laboratories and a spatial presence. In this work, we collected a dataset based on 27 features and presented a model utilizing a support vector machine with regression that was enhanced with the KNN method, which identifies factors that have a substantial influence on the model for the type of education, whether blended or traditional.
Furthermore, the dataset used was primarily focused on three key factors: personal information, the impact of e-Learning platforms, and the influence of the Corona virus. The attributes that were measured revealed that social status, computer skills, and the basic platform gave the user enough tools to continue the learning process. The size of the classrooms and laboratories that meet the health safety conditions is the most significant. The goal of our work is to discover a model that predicts how blended learning will be used during and after the coronavirus pandemic and to produce a model with minimal errors.
In present study 74 specimens of urine were collected from patients suffering from urinary tract infections.Fifty (67.56%) isolates were identified as Escherichia coli. 78% of isolates were identified as extendedspectrum beta lactamases (ESBL) producer. Antibiotic susceptibility t est was done and ceftazidime wasselected to complete this study by implying stress at sub-MIC on isolate harbor high number of resistancegenes (N11) and compared with sensitive isolate (S). Only four β-lactamase coding genes were detected;blaTEM, blaPER, blaVIM and blaCTX-M-2 and N11 had blaTEM, blaPER, and blaVIM. It was found that the resistantisolate did not form biofilm when compared with the sensitive one, which formed moderate biofilm. Inaddition, ceftazidi
... Show MoreThis study aims at identifying the reality of alternative assessment for teachers of the first cycle of the basic education in the Sultanate of Oman with respect to the degree of teachers' use of alternative assessment strategies, level of self-efficacy for alternative assessment strategies, and attitude towards alternative assessment, and their relationship with other variables. To achieve the aims of the study, a descriptive research approach was utilized. A 5-point self-rated questionnaire was developed. It consists of three sections: Actual use of alternative assessment strategies (21 items), self-efficacy for alternative assessment strategies (21 items), and attitude towards alternative assessment (27 items). The psychometric proper
... Show MoreThe problem of this research lies in the fact that there is a lack of accurate scientific perceptions about the size of the use of Iraqi women’s social networking sites and the motives behind this use and the expectations generated by them.
The goals of the research are as follows:
1- Determine the extent of Iraqi women’s use of social networking sites (Facebook, YouTube, twitter, and Instagram).
2- Investigative the motives behind the use of social networking sites by Iraqi women.
3- Detecting the repercussions of Iraqi women’s use of social networking sites (Facebook, you tube, twitter, and Instagram).
The research is classified as a descriptive one. The researchers use the survey methodology. The research commu
HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023
The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreInvestigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016. the researcher setup two scales based on the previous studies: one to measure the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data