Abstract: A novel multi-objective antenna optimization method based on the surrogate model-assisted deep reinforcement learning (SADRL) is proposed. The method is divided into three stages: coarse ...
Abstract: Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale ...
ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...
What is a Student Learning Outcome (SLO)? Student Learning Outcomes (SLOs) are clear and concise statements of what students will know or be able to do by the end of a course, program, or educational ...
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Learning a Language Without This Method
This video discusses whether it is possible to learn a language without using one of the most common study methods. It looks at different learning strategies, compares traditional approaches with ...
From the Dean's Desk welcomes guest author Melissa Kaufman, EdD, Associate Dean for Education at Drexel University's Dornsife School of Public Health Universal Design for Learning (UDL) is "a ...
What are the differences between lesson objectives, learning objectives and success criteria and how can we sharpen our lesson planning and pedagogical choices? Helen Webb offers some practical ...
Lizélle Pretorius received funding from UNISA as part of a bursary when completing her PhD. She is currently a member of ISATT (International Study Association of Teachers and Teaching) and the Junior ...
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