Thanks to the exponential growth of the Internet, Distance Education is becoming more and more strategic in many fields of daily life. Its main advantage is that students can learn through appropriate web platforms th...
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ISBN:
(纸本)9789897583308
Thanks to the exponential growth of the Internet, Distance Education is becoming more and more strategic in many fields of daily life. Its main advantage is that students can learn through appropriate web platforms that allow them to take advantage of multimedia and interactive teaching materials, without constraints neither of time nor of space. Today, in fact, the Internet offers many platforms suitable for this purpose, such as Moodle, ATutor and others. Coursera is another example of a platform that offers different courses to thousands of enrolled students. This approach to learning is, however, posing new problems such as that of the assessment of the learning status of the learner in the case where there were thousands of students following a course, as is in Massive On-line Courses (MOOC). The Peer Assessment can therefore be a solution to this problem: evaluation takes place between peers, creating a dynamic in the community of learners that evolves autonomously. In this article, we present a first step towards this direction through a peer assessment mechanism led by the teacher who intervenes by evaluating a very small part of the students. Through a mechanism based on machine learning, and in particular on a modified form of K-NN, given the teacher’s grades, the system should converge towards an evaluation that is as similar as possible to the one that the teacher would have given. An experiment is presented with encouraging results. Copyright 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
Systems are often controlled using feedback loops. Fault diagnosis schemes are usually designed assuming that there is no feedback loop. Therefore fault diagnosis methods need to accommodate for the feedback loop. One...
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This study aims to develop an online Greek language learning platform via a learning management system based on the WordPress platform for primary school pupils with Russian as a mother tongue. The subject was chosen ...
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the interest in robots and their applications has increased recently, and one of the most important applications is using robots in medical applications. This paper shows a prototype robotic system for robot-aided rad...
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The method of detection and localization of design errors in HDL-models of finite state machines with arbitrary output functions was proposed. The diagnostic experiment is carried out bypassing all arcs of the Mealy m...
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ISBN:
(数字)9781728126920
ISBN:
(纸本)9781728126937
The method of detection and localization of design errors in HDL-models of finite state machines with arbitrary output functions was proposed. The diagnostic experiment is carried out bypassing all arcs of the Mealy machine, starting from the initial vertex, including for machines of the "non-exclusive" class. To ensure the return of the machine with a possible design error in the initial state, it is suggested to use synchronizing sequences. Diagnostic experiments were performed in the Active-HDL design environment.
The paper studies the problem of determining the optimal control when singular arcs are present in the solution. In the general classical approach the expressions obtained depend on the state and the costate variables...
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Laboratories are a core part of any engineering degree, but access to laboratories is typically limited due to a combination of timetable, space and equipment restrictions [1]. In more recent years that has been a sig...
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Laboratories are a core part of any engineering degree, but access to laboratories is typically limited due to a combination of timetable, space and equipment restrictions [1]. In more recent years that has been a significant growth in so-called virtual laboratories (VL), that is laboratory like activities that can be accessed via software or even a web interface, e.g. [2], [3], [5]. The advantage of VL is that the accessibility can potentially be improved to 24/7 and often these may be available on a student's own computing device thus also giving no space restrictions. Improvements in accessibility mean that staff can integrate VL far more easily into the curriculum and student independent study schedule with the consequence that, in principle, students can learn more effectively.
Many tracking systems are based on the Global Positioning System (GPS), Global System for Mobile communications (GSM) and smart phones, due to their wide availability and reliability. A moving object to be tracked, it...
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Machine and reinforcement learning (RL) are increasingly being applied to plan and control the behavior of autonomous systems interacting with the physical world. Examples include self-driving vehicles, distributed se...
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ISBN:
(数字)9781728113982
ISBN:
(纸本)9781728113999
Machine and reinforcement learning (RL) are increasingly being applied to plan and control the behavior of autonomous systems interacting with the physical world. Examples include self-driving vehicles, distributed sensor networks, and agile robots. However, when machine learning is to be applied in these new settings, the algorithms had better come with the same type of reliability, robustness, and safety bounds that are hallmarks of control theory, or failures could be catastrophic. Thus, as learning algorithms are increasingly and more aggressively deployed in safety critical settings, it is imperative that control theorists join the conversation. The goal of this tutorial paper is to provide a starting point for control theorists wishing to work on learning related problems, by covering recent advances bridging learning and control theory, and by placing these results within an appropriate historical context of system identification and adaptive control.
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