Shilpa:一种新的基于神经的方法来测量人类的压力水平

B.T.N Perera, B. Jayarathne, T.G.G.M Dharmakeerthi, K.T.D.D.K Thanthilage, Y. Priyadarshana
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引用次数: 0

摘要

21世纪远比20世纪先进,因为它的创新和相关的技术映射。科技使我们的日常工作变得容易。然而,这已经导致我们简单的生活变得非常复杂。我们变得非常忙碌,金钱至上,最重要的是,我们没有时间和家人在一起,也没有时间考虑自己。作为千禧一代的童年,我们所经历的是成为最好的压力。我们周围和我们之间产生的竞争是无法处理的;所以,人们一直很沮丧,这甚至会让他们自杀。因此,针对高水平学生的学习助手,被称为“Shilpa”,将是克服这些困难的一种实用的补救措施和伴侣。Shilpa已经被用来监测学生的压力水平,并帮助他们根据特定科目的课程了解自己的薄弱环节。一旦确定了一个特别薄弱的领域,Shilpa将用户导航到一个弱识别的课程内容的总结版本,其中用户不必通过整个课程课程来改进他/她的薄弱领域。对所实现的系统进行了考虑所有新组件的测试,根据精度,实验的总体值为0.81。可以得出结论,这种新颖的方法在现有的最先进的基线上达到了81%的总体精度。
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Shilpa: A Novel Neural Based Approach for Measuring Human Stress Level
21st century is far more advanced than the 20th century because of its new innovations along with the relevant technological mappings. Technology makes our day to day work easy. However, this has been led our simple life to be very complex. We have become really busy, money minded and most importantly we don't have time to spend with our families or thinking about ourselves. As Millennials form our childhood what we have experienced is the stress to be the best. The competition which has been generated around and among us cannot be handled; so, people have been depressed and this would let them even committing suicide. Therefore, a Learning Assistant for advanced level students, which has been named as “Shilpa”, would be a practical remedy and a companion to overcome such difficulties. Shilpa has been stepped forward to monitor students' stress levels and to help them understand their weak areas considering the curriculum of a particular subject. Once identifying a particularly weak area, Shilpa navigates the user to the summarized version of a weakly identified content of a lesson in which the user doesn't have to go through the entire course curriculum to improve his/her weak areas. The implemented system has been tested considering all the novel components, and an overall value of 0.81 has been experimented as per the precision. It can be concluded that this novel approach has achieved an overall 81% accuracy over the existing state-of-the-art baselines.
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