Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

In the present work, the ternary compound MgxZn7-x O7Wurtzoid with variable Zn and Mg contents was analyzed using density functional theory with B3LYP 6-311G**basis set. The electronic and vibrational properties of MgxZn7-xO7 wurtzoids, were investigated, including energy gaps, bond lengths, spectral properties, such like infrared spectra and Raman. IR and Raman spectra were compared with experimental longitudinal optical modes frequency results. The theoretical results agree well with experiments and previous data. It has been found that the energy gap is increasing with the increased Mg concentration, and that the longitudinal optical position exposes a UV shift movement with an increase in the concentration.

Growth hormone deficiency is a condition that occurs when a limited volume of growth hormone is released by the pituitary gland since growth hormone deficiency causes growth delays, short stature, and overall physical development delays. symptoms differ based on the age at which they occur .Aim of this study Estimating the level of growth hormone serotonin ,IGF-1 and Chromogranin A before and after with treatment recombinant growth hormone and It is the first study in Iraq that sheds light on the relationship between Chromogranin and other variables ( somatostatin, IGF-1,GH) ,also the prediction of Chromogranin A as a newly biochemical marker in children with growth hormone deficiency. In this study, 30 samples were collected from children

The research aims to highlight on the behavioural approach in accounting, and clarify the behavioural implications of the main activities of accounting, and clarify the concept of information inductance within the framework of the behavioural approach and its impact on preparing financial statements. And that the impact of financial information on the behaviour of investment decision-makers, and to achieve the goals of the research, the researcher prepared a questionnaire according to Likert five-step scale, and he took into consideration in preparing it in line with the characteristics of the study community, and that the target community for this questionnaire is the investors in the Iraq Stock Exchange. The researcher reached

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

The issue of peaceful coexistence between societies is the topic of the hour, as it is one of the important issues in this era, especially in days when conflicts and conflicts abound, and even wars in the name of religion, gender, race, language, and the like. The world, so that single-mindedness and adherence to one opinion and intolerance to it became the method of dialogue in our world today, as writing in the field of peaceful coexistence, peace-building, tolerance, pluralism, and acceptance of the other is one of the new fields of knowledge in Iraq in general and in Nineveh Governorate in particular, as peaceful coexistence is one of the basic needs And necessary for the presence of individuals in societies, and it requires the achi