Online examination is an integral and vital component of online learning. Student authentication is going to be widely seen when one of these major challenges within the online assessment. This study aims to investigate potential threats to student authentication in the online examinations. Adopting cheating in E-learning in a university of Iraq brings essential security issues for e-exam . In this document, these analysts suggested a model making use of a quantitative research style to confirm the suggested aspects and create this relationship between these. The major elements that might impact universities to adopt cheating electronics were declared as Educational methods, Organizational methods, Teaching methods, Technical methods. In order to verify that the design of the questionnaire, has been followed up with two steps of verification. First of all, a approval stage within that , the list of questions examined by the section of specialists in this subject in computer technology and teaching in universities, the feedback received was implemented before proceeding in order in order to this second stage . Second of all, the pilot research has been carried out to check the dependability of the factors . The gathered data has been examined using the Cronbach’s Alpha coefficient dependability test in SPSS 18 software package. This final results demonstrated this all factors are dependable as they acquired a value of 0.9126 and above inside test.
The present paper describes and analyses three proposed cogeneration plants include back pressure steam-turbine system, gas turbine system, diesel-engine system, and the present Dura refinery plant. Selected actual operating data are employed for analysis. The same amount of electrical and thermal product outputs is considered for all systems to facilitate comparisons. The theoretical analysis was done according to 1st and 2nd law of thermodynamic. The results demonstrate that exergy analysis is a useful tool in performance analysis of cogeneration systems and permits meaningful comparisons of different cogeneration systems based on their merits, also the result showed that the back pressure steam-turbine is more efficient than other pro
... Show MoreA case-control study was designed to find out the association between rs2234671 polymorphism of cxcr1 and rUTI in a sample of Iraqi women by polymerase chain reaction- sequence-specific primer (PCR-SSP) method. The current findings revealed that the genotype GC (OR= 7.86, 95% CI = 2.82-21.87, P= 7.7 × 10-5) and the C allele (OR= 3.93, 95% CI = 1.97 - 7.83, P = 9.8×10-5) are significantly associated with rUTI. However, the genotype GG played as a protective factor (OR= 0.12, 95% CI = 10.05 - 0.34, P = 4.0 ×10-5). Depending on these findings, the genotype GC is significantly associated with rUTI.
A reduplicative word is an important phenomenon in all language studies because it reflects many functions in language communication such as plurality, emphasis, contrast, imitation. The various instances of reduplicative words in a particular language reflect the richness and uniqueness of that language. Moreover, such variation gives insights into both culture and thought. A reduplicative word is a linguistic phenomenon found in the syntactic, morphological, phonological and semantic levels. The current study aims at investigating the illocutionary force of English reduplicative words in some selected English colloquial utterances. To achieve this aim, an analytical -pragmatic approach has been used by adopting Searle’s (1979)
... Show MoreSince the nineties of the last century, Iraqi youth have been exposed to Mexican soap operas dubbed into classical Arabic, and the stories and ideas presented by these series were almost new to all the minds of the youth at that time, a culture completely different from the culture we have of social relations, and since the number of episodes was more than Of the 100 episodes, exposure to these series has left young people confused by the addiction to all their ideas and stories. They differ from the foreign films (mostly American) that we used to watch, and they only take two hours (at most). These films contain diverse stories and may be forgotten. Memory includes events and characters in their entirety at times, and you may remember th
... Show MoreThe convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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Abstract
Leadership has now become a process for applying methods and techniques that make the Organization at the top of its competitive pyramid a greater market share. Leadership has become a focus for all leaders and managers، and leaders and managers are increasingly seeking to develop their skills and leadership skills. The research started with a clear problem of specific questions to ensure that the general objective of the research is to describe the characteristics of the leader and to clarify the dimensions of empowering the workers and to highlight the role of the leader in empowering the workers. The study examines the relation between the role of the leader in
... Show MoreWhenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
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