The main objective of this research is to identify the role of job satisfaction in influencing strategic agility through knowledge sharing. The researcher used the descriptive as well as the analytical approach in the completion of this research by collecting data by means of the questionnaire as the main tool on a sample of the General Company for Food Industries' employees, whose number reached (76) individuals. Moreover, some statistical methods were employed to process the data; including the arithmetic mean, Standard deviation, simple linear correlation coefficient (Pearson), simple linear regression, and the median variable test. It was represented that there is a significant and essential impact of job satisfaction in influen

The research aimed to investigate the level of Organizational Cynicism and Job Engagement of Government Schools teachers in Al Zubair district. To achieve this research was conducted on a random sample of (66) items. The statistical package for social sciences (SPSS) was used to analyze and examine the hypotheses. The researcher used many statistical methods to achieve the research objectives, such as simple, multi regression and the research results showed there is a significant impact to teacher's in the schools of the research sample between Organizational cynicism and Job  Engagement             

A .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr

The use of artificial intelligence (AI) technology is rapidly expanding in nursing and society. However, its use in healthcare comes with a number of challenges and concerns. The authors of this article use the sociotechnical model to consider the expanding use of AI in nursing and healthcare from a global perspective. Select references from the literature are used to support this important discussion for nurses and other healthcare professionals. Artificial intelligence is a major innovation that, if used properly, can reduce errors and improve efficiency and healthcare quality. It has also been shown to increase patient support, healthcare access and patient care. Here the authors address some of the limitations and challenges of

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Abstract. This research examines the role of artificial intelligence (AI) in improving and sustaining agricultural production in the Arab world, with a particular focus on the challenges facing Iraq in implementing this technology. It reviews several developments, such as big data, the Internet of Things (IoT), and drone technology, which improve irrigation, increase soil fertility, and reduce waste. The study highlights the diverse applications of AI in crop production and pest control, while revealing Iraq's infrastructure challenges and the need for better training for farmers, To find effective solutions, the research recommends collaboration between governments and the private sector.

ABSTRACT

      The current research aims at highlighting the role of engagement of a sample of employees who works in some of the Iraqi private banks in terms of their interaction , commitment and enthusiasm and the positive impact they own regarding their job and devote their efforts to achieve the core purpose  which is customer loyalty. The problem was expressed through a number of intellectual and practical questions.

In order to achieve the aim of the research the quantitative analytical method was used depending on a questionnaire as a basic tool to collect research data and the qualitative survey method depending on semi-structured interviews which were distrib

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct