Modern education requires solutions that can handle large datasets, effectively evaluate students' performance, and reduce teachers' manual workload. This paper addresses these challenges by automating repetit...
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Nowadays, energy buildings have a huge impact in society regarding the active role in the management of energy consumption. Hence, building owners are required to avoid energy losses and improve energy efficiency as h...
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ISBN:
(纸本)9783031820724;9783031820731
Nowadays, energy buildings have a huge impact in society regarding the active role in the management of energy consumption. Hence, building owners are required to avoid energy losses and improve energy efficiency as high as possible. Therefore, it is required to plan an optimization strategy to buy and sell energy in the market ahead of time. To formulate this optimization plan, building owners require the work of specialists responsible for processing, training, forecasting, and evaluation tasks regarding the prediction of energy consumption data from a building for a specific target of time. Therefore, a multiagent-system is needed to allow the cooperation of various agents including the building owner, forecast provider, data structurer and error analysis. Moreover, forecasting algorithms such as artificial neural networks should be taken into consideration in order to process large quantities of energy consumption data during the training and forecasting phases.
Agriculture is vital to food security and economic stability, but weeds reduce crop yields by competing for sunlight, water, and nutrients. Manual weeding and herbicides are often ineffective and environmentally harmf...
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Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice...
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ISBN:
(纸本)9798400707018
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined with showing learning analytics on skill mastery and visual what-if explanations, can support students in practice contexts requiring high degrees of self-regulation, such as homework. Semi-structured interviews with six middle school students revealed three key insights: (1) participants highly valued learner control for an enhanced learning experience and better self-regulation, especially because most wanted to avoid losses in skill mastery;(2) only seeing their skill mastery estimates often made participants base problem selection on their weaknesses;and (3) what-if explanations stimulated participants to focus more on their strengths and improve skills until they were mastered. These findings show how explainable learning analytics could shape students' selection strategies when they have control over what to practice. They suggest promising avenues for helping students learn to regulate their effort, motivation, and goals during practice with tutoring systems.
This paper examines the adaptive prescribed-time dynamic surface control (PTDSC) problem for uncertain nonlinear systems with unknown control gains and time-varying parameter uncertainties. The spatiotemporal transfor...
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This article examines the enhancement of power system network topology reconstruction algorithm using edge computing to increase intelligence and responsiveness of the power system. Through the implementation of an ed...
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Urban traffic congestion is still a major problem that causes delays, collisions, and wasteful use of resources. Conventional fixed-schedule systems, which frequently exacerbate problems at junctions, U-turns, and ped...
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Biometric authentication offers enhanced security and user convenience. However, variations in biometric sample quality and changes in biometric traits over time present significant challenges to maintaining accurate ...
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The Real-Time Traffic Prediction and Optimization System may be described as enriched, spacious, algorithm-oriented, and designed to help contribute to the anti-symptomatic deprievement of increasingly congested urban...
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As emerging technologies advance, intelligent Transportation systems (ITS) are transitioning to Autonomous Transportation systems (ATS). This paper comprehensively outlines and compares the hierarchical mechanisms of ...
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