• Journal of Communications and Networks
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• 제11권2호
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• Nuclear Engineering and Technology
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• 제52권9호
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• pp.1998-2008
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• 2020

Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

• 대한수학교육학회지:수학교육학연구
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• 제9권2호
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• pp.419-438
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• 1999

This paper explored the impact of dynamic geometry software such as CabriII, GSP on student's understanding deductive justification, on the assumption that proof in school mathematics should be used in the broader, psychological sense of justification rather than in the narrow sense of deductive, formal proof. The following results have been drawn: Dynamic geometry provided positive impact on interacting between empirical justification and deductive justification, especially on understanding the necessity of deductive justification. And teacher in the computer environment played crucial role in reducing on difficulties in connecting empirical justification to deductive justification. At the beginning of the research, however, it was not the case. However, once students got intocul-de-sac in empirical justification and understood the need of deductive justification, they tried to justify deductively. Compared with current paper-and-pencil environment that many students fail to learn the basic knowledge on proof, dynamic geometry software will give more positive ffect for learning. Dynamic geometry software may promote interaction between empirical justification and edeductive justification and give a feedback to students about results of their own actions. At present, there is some very helpful computer software. However the presence of good dynamic geometry software can not be the solution in itself. Since learning on proof is a function of various factors such as curriculum organization, evaluation method, the role of teacher and student. Most of all, the meaning of proof need to be reconceptualized in the future research.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2142-2153
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• 2014

Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.

• 한국도서관정보학회지
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• 제40권1호
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• pp.363-384
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• 2009

학교도서관이 운영하는 프로그램은 자원과 이용자를 연결하는 구체적인 전략이다. 따라서 사서교사는 학교도서관 활성화를 위해서, 교내 외 자원 간의 관계를 구축할 수 있는 파트너십을 형성할 필요가 있다. 그러나 현재 중학교도서관이 운영하는 프로그램에 대한 파트너십 분석 결과, 대부분의 프로그램이 교내 독서 행사 중심으로 운영되고 있다. 그리고 교과교사와 교외 인적자원의 참여가 부족한 것으로 나타났다. 이러한 문제점을 극복하기 위해서는 학습 공동체에서 학교도서관의 교육적 위상을 강화할 수 있는 사서교사의 리더십과 협동적 네트워크를 개발하는 것이 매우 중요하다.

• 디지털콘텐츠학회 논문지
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• 제18권1호
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• pp.17-23
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• 2017

IT기술과 디바이스를 결합한 디지털콘텐츠 제작은 기존 서비스 제공방식의 혁신과 새로운 커뮤니케이션 수단으로 다양하게 활용되고 있다. 본 연구는 자동차 회사에서 신차 구매 시 고객들에게 제공되는 종이형태 자동차 사용 매뉴얼을 태블릿PC에 디지털콘텐츠를 비교하여, 증강현실로 이루어진 콘텐츠가 사용자 학습에 미치는 효과를 규명하고자 한다. 이를 위해 3D 증강현실 기술을 국내 자동차 업계 최초로 적용하여 실제 차량 내 다양한 버튼 및 기능들을 앱에서 구현해 볼 수 있는 K9 매뉴얼앱을 분석하였다. 이를 바탕으로 증강현실 콘텐츠의 적용으로 다양한 학습의 상황에서 가상현실의 적용이 학습에 도움을 줄 수 있음을 시사한다.

• 한국치위생학회지
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• 제20권5호
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• pp.561-569
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• 2020

Objectives: The purpose of this study is to investigate the interaction and satisfaction of with web-based lectures. In addition, it seeks identify their correlations as well as the factors that influence satisfaction. Methods: The study subjects consisted of 139 college students taking up dental hygiene from Suncheon. ANOVA, correlation analysis, and regression analysis were used on the data collected. The Cronbach's alpha for interaction and satisfaction were 0.949 and 0.921, respectively. Results: The interaction recorded was moderate compared to face-to-face lectures. In particular, interaction between students was higher among 3rd grade students compared to those in the 1st grade (p=0.002). Satisfaction with the appropriateness of lecture content and duration was high, but relatively low in terms of the quality of the lecture and the desire to broaden its scope. In particular, satisfaction was higher among students in higher grade levels than their more junior counterparts (p<0.05). It was also found to be positively correlated with interaction (p<0.01). Their respective presence on the educational platform had the greatest impact on satisfaction (β=0.495, p<0.001). Conclusions: Increased interaction results in greater levels of satisfaction. Furthermore, an improvement in the quality of the lectures and the students' perception of them would enable lectures to be conducted more effectively in situations wherein face-to-face lectures cannot be done.

• 인터넷정보학회논문지
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• 제20권6호
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• pp.29-36
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• 2019

When dealing with outdoor images in a variety of computer vision applications, the presence of shadow degrades performance. In order to understand the information occluded by shadow, it is essential to remove the shadow. To solve this problem, in many studies, involves a two-step process of shadow detection and removal. However, the field of shadow detection based on CNN has greatly improved, but the field of shadow removal has been difficult because it needs to be restored after removing the shadow. In this paper, it is assumed that shadow is detected, and shadow-less image is generated by using original image and shadow mask. In previous methods, based on CGAN, the image created by the generator was learned from only the aspect of the image patch in the adversarial learning through the discriminator. In the contrast, we propose a novel method using a discriminator that judges both the whole image and the local patch at the same time. We not only use the residual generator to produce high quality images, but we also use joint loss, which combines reconstruction loss and GAN loss for training stability. To evaluate our approach, we used an ISTD datasets consisting of a single image. The images generated by our approach show sharp and restored detailed information compared to previous methods.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• 디지털융복합연구
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• 제19권12호
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• pp.353-358
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• 2021

노년기에 접어들면서 알츠하이머 다음으로 흔한 퇴행성 뇌 질환은 파킨슨병이다. 파킨슨병의 증상은 손 떨림, 행동의 느려짐, 인지기능의 저하 등 일상생활의 삶의 질을 저하시키는 요인이 된다. 파킨슨병은 조기진단을 통하여 병의 진행 속도를 늦출 수 있는 질환이다. 파킨슨병의 조기진단을 위해 오디오 음성 파일 입력으로 wav2vec을 이용하여 특징을 추출하고 딥러닝(ANN)으로 파킨슨병의 유무를 진단하는 알고리즘을 구현하였다. 오디오 음성 파일을 이용하여 파킨슨병을 진단하는 실험 결과 정확도는 97.47%로 나타났다. 기존의 뉴럴네트워크를 이용하여 파킨슨병을 진단하는 결과보다 좋은 결과를 나타냈다. 오디오 음성 파일을 wav2vec 이용으로 간단하게 실험을 과정을 줄일 수 있었으며, 실험 결과 향상된 결과를 얻을 수 있었다.