Among many issues that the world faces, cybersecurity holds the position of the most fundamental one due to the formation of conniving methods for the breaches of data and security by smart people literally every day....
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Emerging critical illnesses pose substantial problems, including breast cancer, which can be efficiently treated if found early. Many instances of breast cancer are managed through early discovery, which reduces the d...
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The upcoming era of Wireless communication systems is about to make significant use of deep learning and machinelearning technology. Compared to traditional ground-based systems, the evolution of communication-based ...
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Predictive maintenance is revolutionizing the management of autonomous vehicles by proactively addressing potential component failures before they occur. This paper presents a predictive maintenance approach using mac...
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This paper presents the design and implementation of a web-based application for managing vehicle operating costs. The application is intended to help vehicle users control and optimize the money spent on the maintena...
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ISBN:
(数字)9783031564673
ISBN:
(纸本)9783031564697;9783031564673
This paper presents the design and implementation of a web-based application for managing vehicle operating costs. The application is intended to help vehicle users control and optimize the money spent on the maintenance of both a single vehicle and a group of vehicles (fleet) for the company. Moreover this application aims to collect data that will then serve as sample files that will then be used in a machinelearning application. At the beginning of the work, the methodology and requirements to be met by the web application were discussed. In the following parts of the work, the implementation of the web application and tests of the application are presented. At the end of the work, proposals for further development of the application and conclusions of the work are presented. In the era of electric vehicles, such applications will play an increasingly important role, including as journey calculators (charging plans, etc., taking into account journey times, distance covered, stopping times, minimizing energy consumption, etc.), hence the role of machinelearning (ML) will grow, as, for example, as a route is covered, the software will recalculate data and alternative options in real time, which can be reflected in ERP logistics and enterprise fleet management systems for sustainability.
Crop disease distinguishing and treatment suggestion utilizing CNN revolutionizes rural hones by joining progressed innovation with conventional cultivating strategies this think about saddles the capabilities of prof...
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This research paper examines several soil qualities, such as texture, structure, density, porosity, wetness, and pH, and how these affect agricultural productivity and soil management. It discusses how to analyze soil...
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The proliferation of distributed low-inertia generators combined with the large number of power transactions ruled by complex electricity market dynamics and the increased penetration of non-linear loads make modern e...
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ISBN:
(纸本)9798350386509;9798350386493
The proliferation of distributed low-inertia generators combined with the large number of power transactions ruled by complex electricity market dynamics and the increased penetration of non-linear loads make modern electrical grids more vulnerable to dynamic perturbations. Hence, to enhance the power system resilience to these perturbations, it is incumbent to develop enhanced tools for Dynamic Security Assessment (DSA), which try inferring from large aggregated datasets actionable information helpful in defining corrective actions to mitigate the dynamic impacts of severe perturbation phenomena. In this context, the curtailment of renewable power generators is one of the most critical actions that DSA should identify for enhancing the power system stability after severe grid contingencies. To face this challenging issue, this paper explores the potential role of machinelearning-based surrogate modeling in discovering the hidden relationships between aggregated grid data describing the electricity market clearing and the corresponding wind power curtailment identified by a real DSA tool. Experimental results obtained by processing the Italian electricity market data are presented and discussed to assess the performance of the analyzed techniques, outlining the most revealing future research paths of this research.
The incidence of heart disease is concerning, and timely detection is essential for improving the health of patients. machinelearning has shown potential in assisting in the prognosis of heart conditions. This resear...
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The current secondary circuit is an important component of new advanced power systems, and the determination of its abnormal state has always been of great concern. The measurement anomaly detection of current seconda...
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