Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

The current research aims to know the effect of teaching using multiple intelligences theory on academic achievement for students of primary school. The sample search of pupils . The research sample was divided into two groups where the first group represented the experimental group which studied the use of multiple intelligences and the second group represented the control group which studied the use of the traditional way . The search tool consisted of achievement test. Showed search results, there are statistically significant differences(0.05) between the average scores of students who have studied according to multiple intelligences between the average scores of students who have studied in accordance with the tradition way in the p

The authentic traditional architecture proved that it is very convenient to the environmental and social regulations where it appeared and lasted for hundred of years.

This traditional architecture got the intelligence in providing thermal comfort for their occupants by the intelligent usage of the building materials and the intelligent planning and designs which took in consideration the climatic condition and the aerodynamics of the whole city as one ecological system starting from the cold breeze passing through its narrow streets till it enters the dwelling units and glides out through the wind catchers.

This architecture had been neglected and replaced by modern imported architecture which had collap

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme