Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Damascus has great importance throughout its history and has increased in the Umayyad period, It was interested the by Caliphs, and became the capital of the Islam, But the late Umayyad era has witness of troubles and political, this led to collapse the Umayyad state and take the Abbasid rule, despite the neglect of the Abbasids for this city and they left to others, but it remains of great concern by some of the Abbasid caliphs.

Damascus has great importance throughout its history and has increased in the Umayyad period, It was interested the by Caliphs, and became the capital of the Islam, But the late Umayyad era has witness of troubles and political, this led to collapse the Umayyad state and take the Abbasid rule, despite the neglect of the Abbasids for this city and they left to others, but it remains of great concern by some of the Abbasid caliphs.

إسهام تطبيقات التكنولوجيا الرقمية في تطوير الكفاءات النحوية لطلبة اللغة الإسبانية في العراق.

Lately great interests have emerged to find educational alternatives to teach and improve motor skills according to modern educational methods that take into account individual differences and speed in learning for the learner through individual learning that the learner adopts by teaching himself by passing through various educational situations to acquire skills and information in the way he is The learner is the focus of the educational process and among these alternatives the interactive video, the researchers noted through the educational training units at the Model Squash School of the Central Union, and that most of the methods and methods used in learning basic skills take a lot of time in the educational program and do not involve

The art of postmodernism has undergone a number of changes in the course of art and art schools, as art has left the traditional means and paved the way for this artistic transformation to change the materials, techniques, methods and visions as a result of the changes that occurred in the thought and this change played an important role in the artist's vision, To demolish and destroy all of the above and to reconsider the formal systems and intellectual contexts and expressive modes, so it is necessary for the whole art to keep up with the variables of the era and its elements. The current research aims to: "Detect the transformations of form in postmodern art in the projects of students of the Department of Art Education".

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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is