• International Journal of Precision Engineering and Manufacturing
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• 제4권4호
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• pp.13-18
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• 2003

This paper presents the in-process compensation to control cutter ronout and to improve the machined surface quality. Cutter ronout compensation system consists of the micro-positioning servo system with piezoelectric actuator which is embeded in the sliding table to manipulate radial depth of cut in real-time. Cutting force feedback control was proposed in the angle domain based upon repetitive learning control strategy to eliminate chip load variation in end milling process. Micro-positioning control due to adaptive actuation force response improves the machined surface quality by cutter ronout compensation.

• Journal of information and communication convergence engineering
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• 제21권4호
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• pp.294-299
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• 2023

Micro ribonucleic acids (miRNAs) can regulate the protein expression levels of genes in the human body and have recently been reported to be closely related to the cause of disease. Determining the genes related to miRNAs will aid in understanding the mechanisms underlying complex miRNAs. However, the identification of miRNA-related genes through wet experiments (in vivo, traditional methods are time- and cost-consuming). To overcome these problems, recent studies have investigated the prediction of miRNA relevance using deep learning models. This study presents a method for predicting the relationships between miRNAs and genes. First, we reconstruct a negative dataset using the proposed method. We then extracted the feature using an autoencoder, after which the feature vector was concatenated with the original data. Thereafter, the concatenated data were used to train a long short-term memory model. Our model exhibited an area under the curve of 0.9609, outperforming previously reported models trained using the same dataset.

• 한국정보통신학회논문지
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• 제24권3호
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• pp.364-370
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• 2020

본 논문은 저고도로 비행하는 초소형 무인기에 대한 탐지 및 분류에 대한 기술로써, 단순히 초소형 무인기를 탐지만 하는 것이 아니라 탐지된 무인기의 종류 및 모델까지 인식하는 심화학습 기반 탐지 및 분류 기법을 제안한다. 무인기의 소리 특성으로 MFCC를 사용하였고 탐지 및 분류를 위해 CNN를 사용하였다. 무인기들은 각각 CNN을 통해 구분할 수 있는 MFCC 특성을 가짐을 입증하였고, 또한 총 4가지의 무인기에 대한 dataset을 대상으로 분류를 한 결과 time-related sequence를 가지는 MFCC라 하더라도 RNN 대신 CNN를 사용하면 탐지 및 분류 능력을 갖추면서도 연산량을 줄일 수 있음을 검증하였다. 따라서 본 논문은 간단하면서도 효과적인 초소형 무인기 탐지 및 분류 방법을 제시한다.

• 한국과학교육학회지
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• 제35권4호
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• pp.773-790
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• 2015

Conducted as an ethnographic examination of science teaching and learning in an Innovative Middle School in Korea, this study employs sociocultural theory to examine how structures afford and limit student participation in an innovative school designed to promote student-centered learning. Data includes teacher and student interviews, student responses to a questionnaire, classroom observations, and analysis of video recordings of ten lessons in two in two 8th grade science classes. Using structure|agency dialectic theory, we identify and describe some structures that afford and limit teacher and student agency at the micro (science classrooms), meso (school), and macro (Korean society) levels to raise some questions about current reform measures, such as innovation schools, that seek to position classroom teachers as agents for change in science education reform in Korea. Findings suggest that while teachers and school administrators play an essential role in structuring learning opportunities at the meso and micro levels, they have limited agency to address structural constraints originating at the macro-level, which can negatively impact teaching and learning in the science classroom. We offer implications for policy and practice and argue the need for more qualitative research, informed by sociocultural theory, to inform science education reform efforts in Korea.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2022년도 제34회 한글 및 한국어 정보처리 학술대회
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• pp.47-52
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• 2022

환자와 주변인들에게 다양한 문제를 야기하는 치매와 조현병 진단을 위한 모델을 제안한다. 치매와 조현병 진단을 위해 프로토콜에 따라 녹음한 의사와 내담자 음성 시료를 전사 작업하여 분류 태스크를 수행하였다. 사전 학습한 언어 모델의 MLM Head를 이용해 분류 태스크를 수행하는 Prompt 기반의 분류 모델을 제안하였다. 또한 많은 수의 데이터 수를 확보하기 어려운 의료 분야에 효율적인 Few-Shot 학습 방식을 이용하였다. CLS 토큰을 미세조정하는 일반적 학습 방식의 Baseline과 비교해 Full-Shot 실험에서 7개 태스크 중 1개 태스크에서 macro, micro-F1 점수 모두 향상되었고, 3개 태스크에서 하나의 F1 점수만 향샹된 것을 확인 하였다. 반면, Few-Shot 실험에서는 7개 태스크 중 2개 태스크에서 macro, micro-F1 점수가 모두 향상되었고, 2개 태스크에서 하나의 F1 점수만 향상되었다.

• 융복합기술연구소 논문집
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• 제10권1호
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• pp.31-36
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• 2020

The purpose of this study is to discuss how to introduce micro degree for innovation in convergence education in our university. To this end, the background of the introduction of micro and nano degrees and domestic and foreign applications were reviewed. The reason why the rate of students completing the multi-degree was low was that the credits required for graduation were higher than that of other domestic universities, and the difficulty of the courses offered in the convergence major did not match the students. In order to reduce the burden of students learning convergence subjects while acquiring new knowledge and skills, the introduction of a micro degree is considered to be an alternative to the current convergence education.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.172-176
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• 1989

In this paper, a simple method for designing iterative learning control scheme is proposed. The proposed learning algorithm is designed based on series expansion of inverse plant model. The proposed scheme has simple structure and fast convergency so that it is suitable for implementing it on conventional micro processor based controllers. The effectiveness of the proposed algorithm is investigated through a series of computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.1981-1995
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• 2021

When a person tries to conceal emotions, real emotions will manifest themselves in the form of micro-expressions. Research on facial micro-expression recognition is still extremely challenging in the field of pattern recognition. This is because it is difficult to implement the best feature extraction method to cope with micro-expressions with small changes and short duration. Most methods are based on hand-crafted features to extract subtle facial movements. In this study, we introduce a method that incorporates optical flow and deep learning. First, we take out the onset frame and the apex frame from each video sequence. Then, the motion features between these two frames are extracted using the optical flow method. Finally, the features are inputted into an improved MobileNetV2 model, where SVM is applied to classify expressions. In order to evaluate the effectiveness of the method, we conduct experiments on the public spontaneous micro-expression database CASME II. Under the condition of applying the leave-one-subject-out cross-validation method, the recognition accuracy rate reaches 53.01%, and the F-score reaches 0.5231. The results show that the proposed method can significantly improve the micro-expression recognition performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1105-1108
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• 2003

The micro robot soccer playing system is introduced. Studying and learning, evolving in artificial agents are very difficult problem, but on the other hand we think more powerfully challenging task. In our laboratory, this soccer-system studies mainly centered on single agent learning problem. The construction of such experimental system has involved lots of kinds of challenges such as robot designing, vision processing, motion controlling. At last we will give some results showing that the proposed approach is feasible to guide the design of common agents system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.834-837
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• 1993

This paper describes the implementation of an autonomous fuzzy logic controller. The controller is endowed with basic control principles and learning constructs which enable it to autonomously modify its control policy based on system performance. The controller lies dormant when system response is satisfactory but if rapidly initiates adaptation in real time when adverse performance is observed. The autonomous fuzzy controller is implemented on an Intel MCS-51 series micro-controller board using an inexpensive 8-bit Intel 8031 processor. The 11.06 MHz micro-controller operates at a rate exceeding 200 "global" look-up table reinforcements per second. This is important when developing practical on-line adaptive controllers for fast systems. It is also significant because an initial controller look-up table could be incorrect or non-existent. The relatively high learning rate enables the controller to learn to control a system even while it is controlling it.