This research study proposes a comprehensive Crop Recommendation System that uses advanced machine learning to boost agricultural productivity. By analyzing key environmental and soil factors, including soil compositi...
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In the rapidly evolving landscape of cybersecurity, the menace of phishing attacks looms large, necessitating innovative solutions to safeguard users and organizations alike. MalwareGuard is a cutting-edge Python-base...
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Retinal disease diagnosis is one of the crucial step for preventing vision loss, especially in conditions such as Diabetic Retinopathy(DR), Glaucoma, and Age-related Macular Degeneration(AMD). In this paper, we propos...
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The proposed work presents the development process of a personalized AI assistant, leveraging advanced technologies like Azure OpenAI Services. The project entails significant development effort, adaptable from large ...
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The intense increase in the installed capacity of wind farms has required a computationally efficient dynamic equivalent model of wind *** types of wind-farm modelling aim to identify the accuracy and simulation time ...
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The intense increase in the installed capacity of wind farms has required a computationally efficient dynamic equivalent model of wind *** types of wind-farm modelling aim to identify the accuracy and simulation time in the presence of the power *** this study,dynamic simulation of equivalent models of a sample wind farm,including single-turbine representation,multiple-turbine representation,quasi-multiple-turbine representation and full-turbine representation models,are performed using a doubly-fed induction generator wind turbine model developed in DIgSILENT *** developed doubly-fed induction generator model in DIgSILENT is intended to simulate inflow wind turbulence for more accurate *** wake effects between wind turbines for the fullturbine representation and multiple-turbine representation models have been considered using the Jensen *** developed model improves the extraction power of the turbine according to the layout of the wind *** accuracy of the mentioned methods is evaluated by calculating the output parameters of the wind farm,including active and reactive powers,voltage and instantaneous flicker *** study was carried out on a sample wind farm,which included 39 wind *** simulation results confirm that the computational loads of the single-turbine representation(STR),the multiple-turbine representation and the quasi-multiple-turbine representation are 1/39,1/8 and 1/8 times the full-turbine representation model,*** the other hand,the error of active power(voltage)with respect to the full-turbine representation model is 74.59%(1.31%),43.29%(0.31%)and 7.19%(0.11%)for the STR,the multiple-turbine representation and the quasi-multiple representation,respectively.
Heart disease remains a leading cause of global mortality, necessitating effective predictive tools. As per the World Heart Federation, it was found that over a billion people globally continue to be affected by heart...
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There is a huge rise in the number of USB devices available these days, so is the need to access these devices remotely. This motivates the development of USB/IP (USB over Internet Protocol) solutions. However, the ne...
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Nowadays, the application of information technology worldwide is accelerating the digital transformation of the healthcare sector. Incorporating blockchain technology into healthcare provides better and more innovativ...
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Smart agriculture leverages cutting-edge information and communication technologies to optimize agricultural practices, and machine learning plays a significant role in achieving this goal. However, due to the convent...
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This data analytics project is designed for the real estate industry, with the primary aim of predicting property prices, including lands, buildings, and houses linear regression model and also by carefully analyzing ...
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