This research aims to underscore the significance of women's emotional intelligence in enhancing the effectiveness of the Board of Directors, a crucial component of internal governance, particularly during crises. Despite strides made in recent decades in appointing women to senior roles in government, business, and education, challenges persist in improving women's leadership opportunities, especially in developing countries. The study utilizes statistical methods, including Pearson's correlation, to analyze the relationships between variables within a sample of banks listed on the Iraqi securities market, comparing periods before and during the COVID-19 pandemic (2019 and 2020). The goal is to measure the impact of female emotional intelligence on the Board of Directors' ability to manage crises, focusing on variables such as conservative accounting policies, Board compensation and benefits, meeting frequency, the ratio of external auditor fees to enterprise capital, enterprise capital, share profitability, and the market-to-share profitability ratio. Findings indicate that emotional intelligence (measured by the number of females on the Board) positively influences conservative accounting policies and meeting frequency during crisis periods. Conversely, the pre-crisis period showed a negative relationship, suggesting a proactive and risk-responsive stance by women during crisis. Additionally, the study observed an inverse relationship between crisis periods and both Board compensation and external auditor fee ratios, implying a cost-reduction strategy facilitated by female emotional intelligence. The crisis period also saw an increase in the profitability of individual shares and the market-to-share profitability ratio. The research recommends expanding the study to compare the role of emotional intelligence in Boards between developing and developed economies.
The aim of this research is to study and test the impact of the policy of open-book accounting as one of the cost management mechanisms in achieving the competitive advantage in Jordanian industrial public companies, to achieve the objectives of the study, a field study was conducted by surveying the views of a sample of the accountants of the Jordanian industrial public companies. Hence the arithmetical Means, the Standard Deviations, the Significant Value and the Simple Linear Regression are used to test the research hypotheses and to achieve the research goals. The results of the study showed that there is a statistically significant effect of the policy of open-book accounting as one of the cost management mechanisms in achieving the
... Show MoreDue to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info
... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
... Show MoreGiven the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University
... Show Moreبسمة الأوقاتي/ أكاديمية وباحثة في العلاقات الدولية تولي الرئيس الأمريكي دونالد ترامب منصبه لولاية ثانية في العشرين من كانون الثاني / يناير من هذا العام (2025) وهو أكثر تمسكاً بعقيدته السياسية التي كان عنوانها في ولايته الأولى (أمريكا أولا / America First) وحاملا لتوجهات جيوسياسية جديدة ومثيرة للجدل
المستخلص
يعد تقييم اداء العاملين احد اهم الركائز الاساسية التي يتوقف عليها نجاح أي منظمة تسعى بأن تتطور وتتميز بأنشطتها واداءها وبالأخص المنظمات التي لها خصوصية في عملها كالأجهزة الرقابية التي تعتمد في اداء انشطتها ومسؤولياتها على كفاءة مواردها البشرية, ومن هذا المنطلق يهدف هذا البحث الى تصميم انموذج ثلاثي المحاور (المؤهلات والقدرات، الاداء والانجاز، التعاون والالتزام الوظيفي) ثُماني المستويات
... Show MoreMalaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f
... Show MoreGrey system theory is a multidisciplinary scientific approach, which deals with systems that have partially unknown information (small sample and uncertain information). Grey modeling as an important component of such theory gives successful results with limited amount of data. Grey Models are divided into two types; univariate and multivariate grey models. The univariate grey model with one order derivative equation GM (1,1) is the base stone of the theory, it is considered the time series prediction model but it doesn’t take the relative factors in account. The traditional multivariate grey models GM(1,M) takes those factor in account but it has a complex structure and some defects in " modeling mechanism", "parameter estimation "and "m
... Show MoreThe Korteweg-de Vries equation plays an important role in fluid physics and applied mathematics. This equation is a fundamental within study of shallow water waves. Since these equations arise in many applications and physical phenomena, it is officially showed that this equation has solitary waves as solutions, The Korteweg-de Vries equation is utilized to characterize a long waves travelling in channels. The goal of this paper is to construct the new effective frequent relation to resolve these problems where the semi analytic iterative technique presents new enforcement to solve Korteweg-de Vries equations. The distinctive feature of this method is, it can be utilized to get approximate solutions for travelling waves of
... Show MoreAbstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.