In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.
This study investigates the phonotactics of English obstruent clusters in the word-final position from a markedness theory perspective among Iraqi EFL College Students whose native language, Arabic, prefers only two-member word-final obstruent cluster as a maximum. The markedness of clusters is measured depending on Iraqi EFL College Students’ utilization of the simplification strategies. This study tries to answer whether or not word-final obstruent clusters are marked or unmarked for Iraqi EFL College Students, and whether or not the markedness of the obstruent cluster increases as to its length. In order to answer these questions, a test has been distributed among 60 Iraqi EFL Fourth-Year College students, Department of English, Colleg
... Show MoreThis study aimed to identify the role of servant leadership in promoting organizational citizenship behaviors in a sample of faculties of the University of Alqadisiya .It tried to answer several questions represented its problem.
The most important questions are the followings:
1- Is there enough perception among administrative leaders in the aforementioned faculties toward the concept of servant leadership? And under what level? &
... Show MoreThe aim of this research is to construct an educational program in light of the theory of behavioral cognitive and its impact on the development of the efficient response to students affected by crises (centers of your right to education). To achieve the objectives of the research, two scales were developed by the researcher in addition to two equivalent hypotheses were formulated. The scale contains (26) items divided into five fields; for its validity and reliability were derived based on the measure of efficient response, an educational program based on the theory of behavioral cognition. The test and the educational program were applied to a sample of (60) students from the centers of your right to education, divided into experimenta
... Show MoreThis study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, fo
... Show MoreThree N-(hydroxylphenyl) dimethylmaleimides were directly prepared in good yields (81-86)% from the reaction of dimethylmaleic anhydride with amino phenols. The prepared imides were esterified to the corresponding benzoates, methacrylates and cinnamates via their reaction with different acid chlorides in the presence of triethylamine. The prepared esters were tested as plasticizers for PVC via preparing of thirty six samples of PVC with the prepared esters in certain weight ratio followed by recording their softening points. Comparison the results with the universal plasticizers for PVC (DOP) and (DBP) indicated that the prepared esters in general have high plasticizing efficiency.
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c
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