Background: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o

Despite Iraq's possession of the energies material, human and agricultural resources and great economic but that contribution of the agricultural sector in the total gross fixed capital formation and gross domestic product in the Iraqi economy remained low and declining continuously since the nineties of the last century, as well as the inability of agricultural production to meet the country's needs of food . The food gap increased strategic food crops until it reached 1049 thousand tons in 2010. On this basis, there is a need to study and analysis the behavior of the function of  gross fixed capital format

Hepatitis B and Hepatitis C viruses are the major health problem in the worldwide. In the Middle East, the prevalence of HBV in general population with the chronic infectionsis 2-5%,whereas the prevalence of HCV is about 1% in Arabian Gulf countries. World Health Organization (WHO) revealed that the risks of HBV and HCV transmissionas well as human immunodeficiency virus (HIV) through the transfusion of contaminated blood and blood products is high, because of the fragility of health services in these countries. Several viral diseases are transportby different modes like bloodtransfusion, sexual contact, and unsafe injections. The mostcommon blood-transmitted viruses are hepatitis B virus(HBV), hepatitis C virus (HCV) and humanimmunodeficie

Antimicrobial resistance (AMR) is a global concern, especially in low- and middle-income countries, threatening food production, healthcare, and life expectancy. Antimicrobial stewardship (AMS) programs can optimize antibiotic use, improve patient outcomes, lower AMR, and save healthcare costs. This observational-retrospective study in Dhi Qar Governorate aimed to assess antimicrobial prescribing patterns in Al-Nasiriya public hospitals. Dhi Qar Health Directorate comprises ten hospitals, and only one hospital was excluded from the study. The study used data from antibiotic stewardship committees, including antibiogram, antibiotic, and meropenem surveys, hospital pharmacies’ medical files, and the directorate statistics from 1/1/2

اهمية البحث والحاجة اليه :

ان القياس ضروري في دراسة كل فعالية يقوم بها الكائن الحي ، فلغة العلم ، هي رموز ومصطلحات وتعبيرات احصائية ( العيسى ، 1973 : 3 ) .

والقياس بشكل عام مهم في كل العلوم ، فهي على اختلاف انواعها تقوم بتوجيه اهتمامها نحو دراسة العلاقة بين المتغيرات ( Variables ) ، في الميادين التي تبحثها لذلك يجب ان تكون هذه المتغيرات قابلة للقياس بشكل دقيق لنتمكن من در

Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.