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

Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.

Arabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo

                                                                                                          Shakh Ali Khan Zangna was a minister of a big state in terms of its wide lan

The research entitled: (The Constructive Mutation of installation Systems in the Artworks of the artist Ali Al-Najar) has dealt with the concept of Mutation and its systematizations in installation in the artworks of (Ali Al-Najjar).
The research has four chapters: The first Chapter deals with the methodological framework represented by the basic problem of the research, that is concerned with the constructive mutation of installation systems.
The research aims at finding out the constructive mutation of installation systems in the artwork of ( Ali al-Najar). The research is limited by analyzing visual samples of (Ali Al-Najjar) artworks betwen (1967-1991)
The second chapter deals with the theoretical framework, it has five s

The amicus curiae is one of the judicial procedures adopted in many judicial and legal systems around the world, under which a person who is not a party to the case, and without having a personal and direct interest in it, intervenes to draw the court’s attention to many factual and legal aspects

God bestowed upon the Imams of the Ahl al-Bayt (peace be upon them) knowledge and wisdom, in addition to give them virtue as long as it was not given to anyone from the worlds. knowledge have been enriched from them that cause pride.

  The political system during the reign of Imam Ali (peace be upon him) was based on explicit openness in its features and objectives away from misinformation, and built its foundations and foundations on the Koranic legislation, and enacted by the Prophet (peace be upon him), and the decent legislation required by humanity

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p