The current study examined the effect of different sample sizes to detect the Item differential functioning (DIF). The study has used three different sizes of the samples (300, 500, 1000), as well as to test a component of twenty polytomous items, where each item has five categories. They were used Graded Response Model as a single polytomous item response theory model to estimate items and individuals’ parameters. The study has used the Mantel-Haenszel (MH) way to detect (DIF) through each case for the different samples. The results of the study showed the inverse relationship between the sample size and the number of items, which showed a differential performer.

In the last few years, there have been a lot of changes in the economy, society, and the environment. This has led to much competition between companies, directly and indirectly affecting production and marketing processes. Most companies are trying to cut production and manufacturing costs by using modern cost techniques such as product life cycle costing and Continuous Improvement (Kaizen) technology, in the method of measuring production costs or service costs, and the need for internal control to keep an eye on how these technologies are being used and how well they work. And to find out the effect of internal control on the implementation of costing techniques in Iraqi companies, 64 questionnaires were given to people who work in the i

The purpose of this research highlight the achievement of the effectiveness of small and medium enterprises dimensions and conformable to analyze the relationship between business strategies and human resources management strategies , and launched search of a dilemma thought provoking fundamental questions revolve around the search is the lack of appropriate strategies in these enterprises to help them continuity and permanence in business and markets , as these enterprises lack the human resources management strategies appropriate , as well as business strategies that make them withstand the changes in the market environment is changing and volatile . It was to

Three hundred and fifty five patients with hepatitis were investigated in this study all cases gave negative result with HBs Ag , IgM-anti HCV , IgM-anti HEV, IgM-anti HDV and anti-HIV tests . The frequency of IgM-anti HAV was 113 and the percentage was 32 % in all ages but when these patients divided into five groups dependent on ages. The highest percentage of IgM-anti HAV was (45%) in age <10 and the percentage declined with age increase till to 9% in age >41 year.

Abstract

The article is devoted to the study of modal framework of the utterance with the semantics of “disappearance” in modern Russian language. The empirical basis of the study was the works of Russian writers, such as M.A. Bulgakov, F.M. Dostoevsky, A.I. Kuprin., L.M. Leonov, B.L. Pasternak, K.G. Paustovsky, L.N. Tolstoy, I.S. Turgenev and others. The author focuses special attention on the role of the modal component in the formation of the sentences and its modal semantics. A lot attention is paid to the analysis of the reasons of productivity / low productivity in the functioning of the temporal forms of the verbs that form these utterances. The nature of the material of study determined the choice of

Objectives: To choose the best mode of delivery
for term, frank or complete, breech presentation
through studying the perinatal outcome of each mode of
delivery decided when managing a group of pregnant
ladies presented with breech delivery in our centre.
Methods: One hundred and fifty pregnant ladies
presented at term with singleton, frank or complete,
breech presentation for delivery in our centre during the
period from May 2004 toAugust 2005.
Mode of delivery, parity, gestational age, maternal age,
maternal medical illness, and birth weight where the
variables that have been tested in each delivery
included in the study to verify their relationship to
perinatal outcome.
Results: No significant

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

The chemical composition of wastes of pressed grapes and found that the main components of wastes of pressed grapes, represented by the percentage of moisture was 6.47%, and the proportions are 3.71%. Either carbohydrates amounted to 85.77 %, either in fat models using petroleum ether Petroleum ether) was the increase of 0.27%. estimated the percentage of ash in the sampls was 3.78%, either fiber reached 69.47 %,, in addition to the test extracts towards the growth of seven types of bacteria, which included Bacillus subtilis, Bacillus cereus, Bacillus stearothermophilus, Escherishia coli, Staphylococcus aureus, Salmonella typhimurium and Pseudomonas fluorescens and yeast Candida albicans and Kluyveromyces marxianus, ( diffusion method ).

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi