Resulted in scientific and technological developments to the emergence of changes in the educational process and methods of teaching modern formats commensurate with the level of mental retardation. Which called for educational institutions, including the University of Baghdad / College of Fine Arts to urge and guide researchers to study and follow-up of recent developments in the educational process in order to develop in the fine arts in general and technical education in particular being play an important role in achieving educational goals. The educational methods of modern educational require effort-intensive and advanced for the development of technical skills among students, and thus worked researcher to employ computer technology

The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes

The current study aims at identifying of the differences of life quality level for the academic instructors at Omar Al-Mukhtar University / Libya according to the city variable that the instructor belong to ( Libya, Iraq, Egypt ), and also according to gender Variable (Male - Female),To achieve the aims of study ,the researcher chose a sample consists of (210) instructors ( 170 males and 40 females) from four colleges at Omar Al- Mukhtar University/ Darna . The researcher built the scale of life quality which consists of (42) items in last version . The researcher has conducted the validity and reliability of the scale. and by using Analysis of Variance via (SPSS program). The research reaches the following results : 1-The life quality o

هدفت الدراسة الحالية الى التعرف ما اذا كان هناك تقبل اجتماعي للتلاميذ بطيئي من قبل اقرانهم العاديين؟ وكذلك معرفة ما اذا كان هناك فروق ذات دلالة في التقبل الاجتماعي بين افراد عينة الدراسة على وفق المتغيرات الاتية:

أ- العمر (9-13)

ب- الجنس (ذكور –اناث)

ج- المرحلة الدراسية

د- الحالة الاقتصادية (جيدة –متوسطة –جيدة جدا)

    ولغرض تحقيق اه

:الملخص/كلية التربية هدف البحث الكشف عن التدريس الفاعل لأساتذة الكيمياء( . /ابن الهيثم، من وجهة نظر الطلبة وتكونت عينة البحث من للعلوم الصرفة80)طالبا( من طلبة قسم الكيمياء وللصفوف الأربعة في القسم، وتم تقويم50)أستاذا جامعيامن أساتذة القسم، واستخدم المنهج الوصفي في تحليل بيانات هذا البحث، وكذلك(علي الأزيرجاوي، استخدم مقياس التدريس الفاعل الذي أعده2010)بعد التحقق منصدقه وثباته، وقد أظهرت نتائج البحث أن متوسط درجا

The 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