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 CNN infrastructure. Findings: The results acquired through the investigated CBIR system alongside the benchmarked results have clearly indicated that the suggested technique had the best performance with the overall accuracy at 88.29% as opposed to the other sets of data adopted in the experiments. The outstanding results indicate clearly that the suggested method was effective for all the sets of data. Improvements/Applications: As a result of this study, it was found the revealed that the multiple image representation was redundant for extraction accuracy, and the findings from the study indicated that automatically retrieved features are capable and reliable in generating accurate outcomes.
The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l
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At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance pena
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The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
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he assignment model represents a mathematical model that aims at expressing an important problem facing enterprises and companies in the public and private sectors, which are characterized by ensuring their activities, in order to take the appropriate decision to get the best allocation of tasks for machines or jobs or workers on the machines that he owns in order to increase profits or reduce costs and time As this model is called multi-objective assignment because it takes into account the factors of time and cost together and hence we have two goals for the assignment problem, so it is not possible to solve by the usual methods and has been resorted to the use of multiple programming The objectives were to solve the problem of
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Applications of nonlinear, time variant, and variable parameters represent a big challenge in a conventional control systems, the control strategy of the fuzzy systems may be represents a simple, a robust and an intelligent solution for such applications.
This paper presents a design of fuzzy control system that consists of three sub controllers; a fuzzy temperature controller (FC_T), a fuzzy humidity controller (FC_H) and a ventilation control system; to control the complicate environment of the greenhouse (GH) using a proposed multi-choice control system approach. However, to reduce the cost of the crop production in the GH, the first choice is using the ventilation system to control the temperature and humidit
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Abstract
The research aims to identify the level of effectiveness of the teaching practices of science and mathematics teachers in light of the national framework for future skills in Omani schools. To achieve the objectives of the study, the researchers used the descriptive approach, as he designed a note card consisting of (30) phrases distributed on three axes: basic skills, practical skills, and technical skills. After verifying the validity and reliability of the tools, they were applied to a sample of (116) teachers. The results of the research revealed that the level of effectiveness of the teaching practices of mathematics teachers has recorded a medium degree with a mean (3.05). The results a
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