Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

This research aims to find out the extent the reflection of tacit knowledge dimensions (experience, skill, intuition, the ability to think) on Organizational performance of the offices of inspectors general dimensions (internal processes, growth and learning the focus, the focus on the customer) and the measurement and analysis of the type of impact the tacit knowledge of auditors on performance Organizational in inspectors general offices, the research seeks to diagnose the extent of awareness of Office Management knowledge implicit and the attention span of the administration in determining levels and performance levels, and the resolution means the main information-gathering adopted by the researcher, which, as well as his exp

In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

The current study aims to test the impact of green training and development on sustainable performance and explore its effects within and outside the Iraqi Ministry of Environment. The main research problem revolves around the question of the extent of implementing green training and development and sustainable performance in the ministry (What is the nature of the relationship between green training and development and sustainable performance in the ministry?). To clarify the relationship between the research variables, two main hypotheses were formulated along with sub-hypotheses. The study also aims to assess the level of the ministry's interest in the research variables and provide key recommendations to enhance sustainable performan

This work is concerned with the study of the effect of cement types, particularly OPC and SRPC, which are the main cement types manufactured in Iraq. In addition, study the effect of mineral admixtures, which are HRM and SF on the resistance of high performance concrete (HPC) to internal sulphate attack. The HRM is used at (10%) and SF is used at (8 and 10)% as a partial replacement by weight of cement for both types. The percentages of sulphate investigated are (1,2 and 3)% by adding natural gypsum as a partial replacement by weight of fine aggregate. The tests carried out in this work are: compressive strength, flexural strength, ultrasonic pulse velocity, and density at the age of 7, 28, 90 and 120 days.

The r

     The research tagged (Perceived Organizational Support in High Performance) deals with identifying the extent of the impact of perceived organizational support as an explanatory variable on high performance as a response variable for the purpose of reaching appropriate mechanisms that enable colleges of the University of Baghdad to exploit the perceived organizational support in achieving the required high performance and pursuit of its goals. The researcher relied on the descriptive and analytical approach in carrying out the research. An intentional sample was selected and reached (70) persons from the higher leadership of the colleges represented by (deans, assistants deans, heads of departments) that r

The study aims to identify the cognitive bias and the level of emotional thinking among university students, besides, identifying the significant differences between male and female students regarding those two variables, and determine if there is a correlation between cognitive bias and emotional thinking. To this end, two scales were adopted to collect needed data: cognitive bias scale designed by (Al-any, 2015), composed of (14) items, and emotional thinking scale designed by (Abdu Allah, 2017), consisted of (27) items. These two scales were administered to (140) students composed the study sample. They were chosen from four different colleges at Al-mustansiriyah University for the academic year (2017-1018). The findings revealed that

The current research aims to show the correlation between cognitive sharing and perfectionism of Kindergarten pepartment students, to identify the level of cognitive sharing of kindergarten pepartment students and to identify the level of perfectionism among students. The research sample consisted of 100 students from the kindergarten pepartment College of Education for women, Baghdad University for the academic year 2024-2025. They were selected in an accessible manner. In order to achieve the objectives of the research, the scale of cognitive sharing was adopted after verifying its validity and reliability and anolher scale for perfections. The results perfectionism, the research results have shown that the average arithmetic of cognitive

Researchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors. This paper proposes a new nonparametric regression function for the kernel and employs it with the Nadaraya-Watson kernel estimator method and the Gaussian kernel function. The proposed kernel function (AMS) is then compared to the Gaussian kernel and the traditional parametric method, the ordinary least squares method (OLS). The objective of this study is to examine the effectiveness of nonparametric regression and identify the best-performing model when employing the Nadaraya-Watson