The research aims to know the traits or characteristics of woman in terms of her external
appearance, motives for her behavior, feelings, mood and ability.
It, moreover, seeks woman’s relationship with others as it is presented by the Iraqi
satirical television show “ State of Melon “.
The researcher adopted for that survey approach using the method of content analysis
to study the research sample represented by “ State of Melon “ show which was
exposed through the screen of a group of channels:
“Hona Baghdad Satellite Channel, then Asia Satellite Channel, Dijla Satellite Channel,
and UTV Satellite Channel.”For this, the researcher used Margaret Gallagher’s Model to analyze the image of
woman in

Tumor necrosis factor-alpha (TNF-α) antagonists’ therapy are expensive and has a non-responsive rate between 30% to 40% in rheumatoid arthritis patients. Genetic variation plays a vital role in the responsiveness to this type of therapy.The aim of this study is to investigate if the presence of genetic polymorphism in the TNF-α gene promoter region at locations -376 G/A (rs1800750), -806 C/T (rs4248158), and -1031 T/C (rs1799964) affects rheumatoid arthritis patient's tendency to be a non-responder to etanercept.

Eighty RA patients on etanercept (ETN) for at least six months were recruited from the Rheumatology Unit at Baghdad Teaching Hospital. Based on The European League Against Rheumatism response (EULAR) criteria, patient

Emotion could be expressed through unimodal social behaviour’s or bimodal or it could be expressed through multimodal. This survey describes the background of facial emotion recognition and surveys the emotion recognition using visual modality. Some publicly available datasets are covered for performance evaluation. A summary of some of the research efforts to classify emotion using visual modality for the last five years from 2013 to 2018 is given in a tabular form.

     In this review paper, several research studies were surveyed to assist future researchers to identify available techniques in the field of infectious disease modeling across complex networks. Infectious disease modelling is becoming increasingly important because of the microbes and viruses that threaten people’s lives and societies in all respects. It has long been a focus of research in many domains, including mathematical biology, physics, computer science, engineering, economics, and the social sciences, to properly represent and analyze spreading processes. This survey first presents a brief overview of previous literature and some graphs and equations to clarify the modeling in complex networks, the detection of soc

     In this review paper, several research studies were surveyed to assist future researchers to identify available techniques in the field of infectious disease modeling across complex networks. Infectious disease modelling is becoming increasingly important because of the microbes and viruses that threaten people’s lives and societies in all respects. It has long been a focus of research in many domains, including mathematical biology, physics, computer science, engineering, economics, and the social sciences, to properly represent and analyze spreading processes. This survey first presents a brief overview of previous literature and some graphs and equations to clarify the modeling in complex networks, the detection of soc

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

Abstract

       Although the subject of biofuels industry is linked directly to the energy sector, but has links and numerous indirect effects, in particular effects on the environment and agriculture, this study (opportunities and challenges of biofuels industry and impact on the development of the agricultural sector in developing countries) a modest step to identify the industry in detail and identify the types of products and raw materials entering, then define or limit the positive and negative impacts of this industry in General and for specific products In particular, detailed, and then flip all those effects on the agricultural sector in developing countries can benef