In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a

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

Pharmaceutical-instigated pollution is a major concern, especially in relation to aquatic environments and drugs such as meropenem antibiotics. Adsorbents, such as multi-walled carbon nanotubes, offer potential as means of removing polluting meropenem antibiotics and other similar compounds from water. In order to evaluate the effectiveness of multi-walled carbon nanotubes in this capacity, various experimental parameters, including contact time, initial concentration, pH, temperature and the dose of adsorbent have been investigated. The Langmuir and the Freundlich isotherm models have been used. The data obtained using a modified Langmuir model have been consistent with the experimental ones; the best pH value has been obtained to have the

Future wireless communication systems must be able to accommodate a large number of users and simultaneously to provide the high data rates at the required quality of service. In this paper a method is proposed to perform the N-Discrete Hartley Transform (N-DHT) mapper, which are equivalent to 4-Quadrature Amplitude Modulation (QAM), 16-QAM, 64-QAM, 256-QAM, … etc. in spectral efficiency. The N-DHT mapper is chosen in the Multi Carrier Code Division Multiple Access (MC-CDMA) structure to serve as a data mapper instead of the conventional data mapping techniques like QPSK and QAM schemes. The proposed system is simulated using MATLAB and compared with conventional MC-CDMA for Additive White Gaussian Noise, flat, and multi-path selective fa

Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

   The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun

This paper proposes a completion that can allow fracturing four zones in a single trip in the well called “Y” (for confidential reasons) of the field named “X” (for confidential reasons). The steps to design a well completion for multiple fracturing are first to select the best completion method then the required equipment and the materials that it is made of. After that, the completion schematic must be drawn by using Power Draw in this case, and the summary installation procedures explained. The data used to design the completion are the well trajectory, the reservoir data (including temperature, pressure and fluid properties), the production and injection strategy. The results suggest that multi-stage hydraulic fracturing can

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different