• Title/Summary/Keyword: feedback error learning

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A controller Design using Immune Feedback Mechanism (인체 면역 피드백 메카니즘을 활용한 제어기 설계)

  • Park, Jin-Hyun;Kim, Hyun-Duck;Choi, Young-Kiu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.701-704
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    • 2005
  • PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They are difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

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An Evaluation Method for the Musculoskeletal Hazards in Wood Manufacturing Workers Using MediaPipe (MediaPipe를 이용한 목재 제조업 작업자의 근골격계 유해요인 평가 방법)

  • Jung, Sungoh;Kook, Joongjin
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.2
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    • pp.117-122
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    • 2022
  • This paper proposes a method for evaluating the work of manufacturing workers using MediaPipe as a risk factor for musculoskeletal diseases. Recently, musculoskeletal disorders (MSDs) caused by repeated working attitudes in industrial sites have emerged as one of the biggest problems in the industrial health field while increasing public interest. The Korea Occupational Safety and Health Agency presents tools such as NIOSH Lifting Equations (NIOSH), OWAS (Ovako Working-posture Analysis System), Rapid Upper Limb Assessment (RULA), and Rapid Entertainment Assessment (REBA) as ways to quantitatively calculate the risk of musculoskeletal diseases that can occur due to workers' repeated working attitudes. To compensate for these shortcomings, the system proposed in this study obtains the position of the joint by estimating the posture of the worker using the posture estimation learning model of MediaPipe. The position of the joint is calculated using inverse kinetics to obtain an angle and substitute it into the REBA equation to calculate the load level of the working posture. The calculated result was compared to the expert's image-based REBA evaluation result, and if there was a result with a large error, feedback was conducted with the expert again.

Case of Non-face-to-face Teaching-learning in the subject of "Research and Guidance on Early Childhood Materials" in the Pre-service Early Childhood Teacher Training Program (예비유아교사 양성과정의 '유아 교재교구 연구 및 지도법' 교과목의 비대면 교수-학습 사례)

  • Kim, Ji-hyun
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.227-238
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    • 2022
  • This study is the case of non-face-to-face teaching-learning in the subject of "Research and Guidance on Early Childhood Materials" in the pre-child teacher training program. The study conducted a non-face-to-face teaching-learning model for 18 students at B University in region C who took lectures on 'Research and Guidance on Early Childhood Materials' in the first semester of 2021. As a non-face-to-face teaching-learning model, it consisted of video lectures, real-time zoom classes, and various forms of 'communication' through frequent feedback and interaction and 'participation'. As a teaching-learning strategy for the participation of pre-service early childhood teachers, comment on questions related to early childhood materials, in-depth reflection on early childhood materials through writing reflective journals and observation reports, and step-by-step presentation of making childhood materials plans, processes, and results were carried out. As a result of exploring the experience of making early childhood materials for pre-service early childhood teachers, factors such as "growth experience through trial and error," "thinking from child's point of view", "Increase efficiency and reduce burden through communication", "Process rather than result" and "The importance of communication and interaction in non-face-to-face classes"

Error analysis on factorization and the effect of online individualization classes (인수분해에 대한 오류 분석과 온라인 개별화 수업의 효과)

  • Choi, Dong-won;Heo, Haeja
    • Journal of the Korean School Mathematics Society
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    • v.24 no.1
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    • pp.83-105
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    • 2021
  • In this paper, we analyzed the misconceptions and errors incurred during factorization learning. We also examined whether online individualization classes had a positive effect on students' mathematical achievement. The experiment was conducted for 4 weeks (16 times in total) on middle school juniors in rural areas of Gyeonggi Province, where the influence of private extra education was small. In the class, the 'Google Classroom' was used as a LMS, the video lecture was uploaded to YouTube, and the teacher interacted with the students through "Zoom" and "Facetalk". In the online class situation, students' assignments and test answers were checked in real time through 'Google Classroom', and immediate feedback was provided to the experimental class group's students. However, for the control group students, feedback was provided only to those who desired. A total of 7 achievement evaluations were conducted in the order of pre-test, formative evaluation (5 times), and post-test to confirm the change in students' ability improvement and achievement. Through the formative evaluation analysis, it was possible to grasp the types of errors and misconceptions that occured during the factorization process. Students' errors were divided into four types: theorem or definition distortion error, functional errors such as calculation, operation, and manipulation, errors that do not verify the solution, and no response. As a result of ANCOVA, the two groups did not show any difference from the 1st to 4th formative assessment. However, the 5th formative assessment and post-test showed statistically significant differences, confirming that online individualization classes contributed to improvemed achievement.

An Analysis and Evaluation of Current Cyber Home Learning Contents - Focused on the Earth Science Area of Science Course for the 10th Grade- (현행 사이버가정학습 콘텐츠의 분석 및 평가 -고등학교 1학년 과학과정의 지구과학 영역을 중심으로-)

  • Na, Jae-Joon
    • Journal of Science Education
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    • v.34 no.2
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    • pp.225-236
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    • 2010
  • The purpose of this study is to analyze and evaluate the Cyber Home Learning contents of Earth science area in the basic course of the $10^{th}$ grade. For this purpose, we applied the 'Cyber Home Study Content Quality Control Tool' presented in Elementary Secondary Education e-Learning Quality Management Guidelines (Ver.2.0)' of Korea Education & Research Information Service(2008). The results of Cyber home learning contents analysis are as follow: First, it was presented that the study guide introduced the contents which should be studied for one class, properly. And it was not analyzed that the diagnosis assesment was not completed in the initiative study; Second, it was possible to study choosing the contents fitting the learner's level of learning in the main study, it was comprised of about 10 minutes. Third, it was performed without feedback for incorrect answers in the learning assessment, just the number of wrong questions. And the learning arrangement present the important contents learned in that class, summarizing and arranging again. The results of evaluating the contents in Cyber Home Learning are as follows: First, in evaluation section of instructional design, many text materials which were so difficult for learners to read were explained, being provided. Besides, the systematic structures leaves much to be desired, in view of learners' learning experience, contents, and environment. And in evaluation section of learning contents, the error of contents caused the learning contents not to appear, the amount of learning in each section was found too much. Second, in evaluation section of the strategy for Teaching and Learning, when we mention the strategy of Self Directed Learning, the environment to make learners search for information free and self-study possible was not possessed well. And in evaluation section of interaction, it was found that a simple click caused the learning to go on. Third, in evaluation section of evaluating, it was evaluated that there was wanting in consistency in learning aims, contents, evaluation contents.

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A Vector-Controlled PMSM Drive with a Continually On-Line Learning Hybrid Neural-Network Model-Following Speed Controller

  • EI-Sousy Fayez F. M.
    • Journal of Power Electronics
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    • v.5 no.2
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    • pp.129-141
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    • 2005
  • A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

A Study on the Development of Emotional Content through Natural Language Processing Deep Learning Model Emotion Analysis (자연어 처리 딥러닝 모델 감정분석을 통한 감성 콘텐츠 개발 연구)

  • Hyun-Soo Lee;Min-Ha Kim;Ji-won Seo;Jung-Yi Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.687-692
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    • 2023
  • We analyze the accuracy of emotion analysis of natural language processing deep learning model and propose to use it for emotional content development. After looking at the outline of the GPT-3 model, about 6,000 pieces of dialogue data provided by Aihub were input to 9 emotion categories: 'joy', 'sadness', 'fear', 'anger', 'disgust', and 'surprise'. ', 'interest', 'boredom', and 'pain'. Performance evaluation was conducted using the evaluation indices of accuracy, precision, recall, and F1-score, which are evaluation methods for natural language processing models. As a result of the emotion analysis, the accuracy was over 91%, and in the case of precision, 'fear' and 'pain' showed low values. In the case of reproducibility, a low value was shown in negative emotions, and in the case of 'disgust' in particular, an error appeared due to the lack of data. In the case of previous studies, emotion analysis was mainly used only for polarity analysis divided into positive, negative, and neutral, and there was a limitation in that it was used only in the feedback stage due to its nature. We expand emotion analysis into 9 categories and suggest its use in the development of emotional content considering it from the planning stage. It is expected that more accurate results can be obtained if emotion analysis is performed by additionally collecting more diverse daily conversations through follow-up research.

Examine the Features of Evidence Based Instruction in Elementary Mathematics Teacher's Guidebook For Students with Math Learning Disabilities and Students with Underachievement - Only about Number and Operations (초등 수학 교사용지도서의 학습장애 학생 및 학습부진학생을 위한 증거기반교수 요인 포함수준 분석 - 수와 연산 영역을 중심으로)

  • Kim, Byeong-Ryong
    • Journal of Elementary Mathematics Education in Korea
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    • v.20 no.2
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    • pp.353-370
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    • 2016
  • This study examined elementary mathematics teacher's guidebook to determine the inclusion level of 11 critical features of evidence based instruction. And the inclusion level of the features in teacher's guidebook were interpreted as 'Low', 'Middle' and 'High'. The results are as followings. First, The overall inclusion level of the features in teacher's guidebook is 'Middle' The inclusion level of the features in teacher's guidebook for 1st, 2nd, 3rd and 4th were 'Middle' but for 5th and 6th were 'Low'. Second, the inclusion level of the features 'Clarity of Objective', 'Single Concepts and Skill Taught', 'Use of Manipulatives and Representation', 'Explicit Instruction', 'Provision of Examples for new concepts and skill', 'Adequate Independent Practice Opportunities' and 'Progress Monitoring' were 'Middle' The inclusion level of the features 'Review of Prerequisite Mathematical Skills', 'Error correction and Corrective Feedback' and 'Instruction of Strategies' were 'Low'. And discussed the results.