Mental health dynamics have also been affected with significant changes by the digital age with the changes in the way people interact, work, or get information. What has emerged over the last decade, while informatio...
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The capacity to get additional patient data, including clinical, behavioral, and self-monitored data, has enhanced by the expanding usage of wearable technology. Large volumes of previously unobtainable data are now a...
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End-to-end training has emerged as a prominent trend in speech recognition, with Conformer models effectively integrating Transformer and CNN architectures. However, their complexity and high computational cost pose d...
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This study investigates the production of high-quality syngas from sewage sludge and its hydrochars through gasification and catalytic gasification processes. The following types of sludge were analyzed: digested (MS1...
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Hyperspectral imaging (HSI) has been proved to be useful in numerous fields because of its ability to acquire the spectral information across the hundreds of contiguous bands. Nevertheless, the vast dimensionality of ...
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作者：
Wanjari, KetanVerma, Prateek
Faculty of Engineering and Technology Department of Computer Science and Engineering Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha442001 India
Skin cancer is the most commonly reported type of cancer globally and one of the few cancers that can be effectively treated if detected in its early stages. Recent advancements in artificial intelligence (AI) have si...
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Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex *** Architecture is one of the recent technique...
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Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex *** Architecture is one of the recent techniques in which Enterprise Systems can be developed as fine-grained smaller components and deployed *** methodology brings numerous benefits like scalability,resilience,flexibility in development,faster time to market,*** the advantages;Microservices bring some challenges *** microservices need to be invoked one by one as a *** most applications,more than one chain of microservices runs in parallel to complete a particular requirement To complete a user’s *** results in competition for resources and the need for more inter-service communication among the services,which increases the overall latency of the application.A new approach has been proposed in this paper to handle a complex chain of microservices and reduce the latency of user requests.A machine learning technique is followed to predict the weighting time of different types of *** communication time among services distributed among different physical machines are estimated based on that and obtained insights are applied to an algorithm to calculate their priorities dynamically and select suitable service instances to minimize the latency based on the shortest queue waiting *** were done for both interactive as well as non interactive workloads to test the effectiveness of the *** approach has been proved to be very effective in reducing latency in the case of long service chains.
The ubiquity of handheld devices and easy access to the Internet help users get easy and quick updates from social media. Generally, people share information with their friends and groups without inspecting the posts...
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Current automatic segment extraction techniques for identifying target characters in videos have several limitations, including low accuracy, slow processing speeds, and poor adaptability to diverse scenes. This paper...
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The solid oxide electrolysis cell(SOEC)holds great promise to efficiently convert renewable energy into ***,traditional modeling methods are limited to a specific or reported SOEC ***,four machine learning models are ...
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The solid oxide electrolysis cell(SOEC)holds great promise to efficiently convert renewable energy into ***,traditional modeling methods are limited to a specific or reported SOEC ***,four machine learning models are developed to predict the performance of SOEC processes of various types,operating parameters,and feed *** impact of these features on the SOEC's outputs is explained by the Shapley additive explanations and partial dependency plot *** preferredmodel is integratedwith a genetic algorithmto determine the optimal values of each input *** show the improved extreme gradient enhanced regression(XGBoost)algorithm is the core of the machine learning model of the process since it has the highest R^(2)(>0.95)in the three *** electrolytic cell descriptors have a greater impact on the system performance,contributing up to 54.5%.The effective area,voltage,and temperature are the three most influential factors in the SOEC system,contributing 21.6%,16.6%,and 13.0%to its *** temperature,high pressure,and low effective area are the most favorable conditions for H_(2)production *** conducting multi-objective optimization,the optimal current intensity and hydrogen production rate were determined to be 1.61 A/cm^(2)and 1.174 L/(h⋅cm^(2)).
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