This study concerned with phytochemical investigation and methods of extraction and separation of active constituents from Valeriana officinalis plant cultivated in Iraq. Due to the large number of active constituents in Valeriana officinalis, it was necessary to make analytical study of its constituents to determine the chemical nature of these constituents and then determine the main classes (terpenes and iridoids) using chemical reagents specific for each class. Different organic solvents like ethanol (70%) used in soxhlet apparatus and hexane, ethyl acetate and methanol were used separately to extract the main active constituents by maceration. Through comparison between these solvents using thin layer chromatograph

This study aims to calculate the percentage of loss and its causes of the horticultural crops tangerines and Seville oranges in Baghdad governorate for the 2020 agricultural season and estimate the economic impacts of losses both crops tangerines and Seville oranges at the study samples level. The research followed both methods descriptive and the quantitative mathematical in estimating the loss of horticultural crops from tangerines and Seville oranges trees and calculating the economic impact of this loss. The results showed that the percentage of losses of tangerines and Seville oranges crops on the level of wholesalers was about 12% and 13% respectively; causing economic losses estimated at about 3184.41 Euro. The results also displayed

This research aims to study the contribution of social costs contribution to achieving social luxury in Al-Furat General Chemical Industries company that has considered second largest contamination in the area after the invasive power  to deal with chemicals in manufacturing and very dangerous to individual society and environment ,this is first to play an effective role by the senior parties related to sense of social responsibility of the internal and external environment of the company to identify costs that are preventing ,reduced and treating damage caused and achieving sustainable development ,to achieve this goal  and what they reached are the difficulty of accounting for the environment and social costs from final accou

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea