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 were 96.5% and 93.47%, respectively, before applying balancing to the data. In addition, 98.59% and 97.18%, respectively, after applying the balancing technique The extreme gradient boosting (XGBoost) technique had been applied to selecting the important features and the Pearson correlation for finding the correlation between features.
The current research aims to measure Generalized Anxiety Disorder among students of the University of Sulaymaniyah / College of Basic Education, and to identify the significance of differences between sex, scientific specialization and age, and for that reason, the research sample of (102) male and female students was chosen in a random manner, and the researcher used the diagnostic criteria for the generalized anxiety disorder contained He mentioned it in the Statistical and Diagnostic Manual of Psychiatry, and the paragraphs of the scale were formulated according to those standards after they verify the conditions of honesty and consistency, and the use of appropriate statistical means. The results of the research indicated that genera
... Show MoreSymptoms of posttraumatic stress disorder are associated with various variables such as the exposure to traumatic events, sex and age. Such events could lead to negative cognitions towards self and the world. These cognitions, in turn, may lead to traumatic related disorders.
The present study aims to identify the percentage of traumatised individuals according to sex and age category variables. It also aims to assess the average of spreading symptoms of posttraumatic stress disorder of traumatised individuals according to sex and age category variables. Likewise, it aims to test variables significance in cognitions towards the world and the self according to the level of the spread of posttraumatic stre
... Show MoreIn this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreBackground: The isthmus is a difficult area in the root canal complex to manage. The research aimed to evaluate the efficiency of three different obturation techniques (lateral condensation, EandQ (thermoplasticized gutta percha system) and Soft Core (thermoplasticized core carrier gutta percha system)) to obturate the isthmus area of roots prepared by two different instrumentation techniques (rotary ProTaper universal and ProTaper Next systems). Material and method: Sixty freshly extracted teeth were randomly divided into two main groups (A and B) of 30 teeth each. Group A was prepared by rotary ProTaper Universal whereas group B was prepared by ProTaper Next system. Each main group was then randomly subdivided into three subgroups of 10 t
... Show MoreThe psychological scientific studies suggest that basic human situations stem from human emotional abilities and those with a lack of emotional intelligence are unable to cope with life, which might lead to anxiety and psychological depression. The current study aimed to investigate this problem by identifying the level of emotional intelligence and psychological depression among the students of the University of Anbar. To achieve the objectives of the study, the researchers created two questionnaires: 1) to measure emotional intelligence. 2) to measure psychological depression and applied these questionnaires on (300) students. The results revealed that the participants showed a high level of emotional intelligence with a low level of p
... Show MoreThe study aims to identify the symptoms of PTSD among displaced Yazidi women according to age, marital status, educational level, and type of status (displaced or survivor). The study also seeks to identify the effect of the relaxation program on reducing PTSD among displaced Yazidi women. The research sample included (60) Yazidis for the statistical analysis sample and (5) for the experimental sample in the Dohuk governorate. For achieving the research objectives, a scale was used from the PTSD Checklist for DSM-5 (PCL-5), as well as a relaxation program was prepared. The researchers reached the following results that there is an average level of PTSD symptoms among displaced Yazidi women, there are no statistically significant differen
... Show MoreSurvival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
... Show More<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show MoreStructure type and disorder have become important questions in catalyst design, with the most active catalysts often noted to be “disordered” or “amorphous” in nature. To quantify the effects of disorder and structure type systematically, a test set of manganese(III,IV) oxides was developed and their reactivity as oxidants and catalysts tested against three substrates: methylene blue, hydrogen peroxide, and water. We find that disorder destabilizes the materialsthermodynamically, making them stronger chemical oxidantsbut not necessarily better catalysts. For the disproportionation of H2O2 and the oxidative decomposition of methylene blue, MnOx-mediated direct oxidation competes with catalytically mediated oxidation, making the most
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