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

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

Objectives: This study aims to assess the quality of life of cerebral palsy children less than 12 years old reported by
parents in Erbil city/Iraq.
Methodology: A descriptive study was conducted during 2014, to describe the quality of life of cerebral palsy
children. One hundred mothers have cerebral palsy children were participated in this study. The study took place at
Helena Center for handicapped children in Erbil City. Questionnaire was used to collect data, which consists of two
main parts. The first part is divided into two sections; section one was described the mothers’ demographic
characteristics, while the second section was for identifying the demographical characteristics of cerebral palsy
children. Th

The aim of the research is the knowing of the academic Scientific Journals of the colleges of University of Baghdad , through searching in the University of Baghdad website and the websites of colleges and thus studying the presentation of these journals in those website , and this is done by surfing the main pages of the websites for the colleges included in the research , and by analyzing the research made a menu for all the academic Scientific Journals for all institutes of the University of Baghdad , which simplifies the way for the researchers to publish these researches in the specific journals for their specialties .

     Two field experiments were performed to study the response of two species , Nigella sativa L. and Nigella arvensis L. within different sowing dates at spring and autumn seasons which included 1^st and 20^th March, 10^th April and 1^st May for spring season, while the sowing dates for the autumn season were, 2^nd November, 21^st November, 11^th December, 31^stDecember and 20^thJanuary. Both experiments conducted according to the Completely Randomized Block Design (CRBD) within three replications at hallabja/Kurdistan Region, located [35^°12'48.7^"N; 45^°57'34.4^"