• 천문학회지
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• 제52권6호
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• pp.217-225
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• 2019

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.

• 대한원격탐사학회지
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• 제40권1호
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• pp.115-122
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• 2024

Multi-object tracking (MOT) is a vital component in understanding the surrounding environments. Previous research has demonstrated that MOT can successfully detect and track surrounding objects. Nonetheless, inaccurate classification of the tracking objects remains a challenge that needs to be solved. When an object approaching from a distance is recognized, not only detection and tracking but also classification to determine the level of risk must be performed. However, considering the erroneous classification results obtained from the detection as the track class can lead to performance degradation problems. In this paper, we discuss the limitations of classification in tracking under the classification uncertainty of the detector. To address this problem, a class update module is proposed, which leverages the class uncertainty estimation of the detector to mitigate the classification error of the tracker. We evaluated our approach on the VisDrone-MOT2021 dataset,which includes multi-class and uncertain far-distance object tracking. We show that our method has low certainty at a distant object, and quickly classifies the class as the object approaches and the level of certainty increases.In this manner, our method outperforms previous approaches across different detectors. In particular, the You Only Look Once (YOLO)v8 detector shows a notable enhancement of 4.33 multi-object tracking accuracy (MOTA) in comparison to the previous state-of-the-art method. This intuitive insight improves MOT to track approaching objects from a distance and quickly classify them.

• 한국전자파학회논문지
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• 제22권12호
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• pp.1060-1068
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• 2011

본 논문에서는 900 MHz 대역에서 동작하는 전류 모드 Class-D(Current-Mode Class-D: CMCD) 전력 증폭기를 설계 및 제작하고 특성을 분석하였다. 차동 구조에 의해 짝수차 고조파 성분이 제거된다는 점에 착안하여 출력단의 일반적인 CMCD 회로의 병렬 공진기를 제거하고 inverse class-F 전력 증폭기를 push-pull 구조로 연결하여 CMCD 전력 증폭기를 설계하였다. 로드-풀 기법을 이용하여 GaN 소자 기반의 inverse class-F 및 이를 적용한 CMCD 전력 증폭기를 설계 및 제작하였다. 제작한 CMCD는 34.2 dBm의 출력과 64.5 %의 드레인 효율을 가지며, 이는 출력측에 공진기 구조를 가지는 일반적인 CMCD 전력 증폭기의 드레인 효율과 비교했을 때 13.6 %의 효율 향상을 가진다.

• 한국초등과학교육학회지:초등과학교육
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• 제38권3호
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• pp.406-425
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• 2019

The purpose of this study is to analyze The Effect of Teacher Participation-oriented Education Program (TPEP) centered on Multi-Faceted Analysis of Elementary Science Classes on the Class Expertise of novice teacher. First, in order to develop the TPEP, lectures and exploratory science classes were analyzed using imaging and eye-tracking techniques. In this study, the TPEP was developed in five stages: image analysis, eye analysis, teaching language analysis, gesture analysis, and class development. Participants directly analyzed the classes of experienced and novice teachers at each stage. The TPEP developed in this study is different from the existing teacher education program in that it reflected the human performance technology aspects. The participants analyzed actual elementary science classes in a multi-faceted way and developed better classes based on them. The results of this study are as follows. First, at the teacher training institutions and the school sites, pre-service teachers and novice teachers should be provided with various experiences in class analysis and multi-faceted analysis of their own classes. Second, through this study, we were able to identify the limitations of existing class observations and video analysis. Third, the TPEP should be developed to improve the novice teachers' class expertise. Finally, we hope that the results of this study are used as basic data in developing programs to improve teachers' class expertise in teacher training institutions and education policy institutions.

• 한국안전학회지
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• 제32권5호
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• pp.88-95
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• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

• 대한수학회지
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• 제47권1호
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• pp.63-70
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• 2010

In this paper, we develop a nonmonotone spectral memory gradient method for unconstrained optimization, where the spectral stepsize and a class of memory gradient direction are combined efficiently. The global convergence is obtained by using a nonmonotone line search strategy and the numerical tests are also given to show the efficiency of the proposed algorithm.

• 한국과학교육학회지
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• 제24권6호
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• pp.1094-1105
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• 2004

이 연구는 중학교 8학년 과학 '지구의 역사와 지각 변동' 단원에서 ICT 활용 수업 과정안을 개발 적용하여 ICT 활용 수업이 학생의 과학 탐구 능력과 과학에 관련된 정의적 특성에 미치는 효과를 알아보는 데 그 목적이 있다. 이 연구를 위해 충청남도에 소재한 D 중학교 2학년 2개 학급을 선정하고 교수-학습 방법을 달리하여 약 6주간 수업하였다. 1개 학급은 실험집단으로 ICT 수업 과정 안을 개발하여 lCT를 활용한 수업을 실시하였으며, 1개 학급은 통제집단으로 교과서 위주의 전통적 방법으로 수업하였다. 학습을 하기 1주일 전에 두 집단을 대상으로 과학 탐구 능력과 과학에 관련된 정의적 특성에 대한 사전 검사를 실시하였으며, 수업이 끝난 뒤에 사후 검사를 실시하였다. 그 결과, lCT를 활용한 실험집단과 전통적 학습을 실시한 통제집단의 과학 탐구 능력 검사에서는 실험 집단에서 유의미한 차이가 나타났다. 또한, 과학에 관련된 정의적 특성에 대한 검사에서 실험집단에서 통계적으로 유의미한 차이가 나타나지는 않았지만, 3개의 과학에 관련된 특성 범위 중에서 흥미 범위에서는 통계적으로 유의미한 차이가 나타났다. 이는 lCT 활용 수업이 학생들의 과학에 관련된 정의적 특성에도 긍정적인 효과가 있음을 시사하는 것이다.

• 대한인간공학회지
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• 제33권3호
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• pp.215-227
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• 2014

Objective: The purpose of this study was to evaluate Korea's Honam express train's first- and second-class seat discomfort by using pressure measurement, subjective discomfort rating, and physical compatibility. Background: Over the years, the demand for an express train service is continually increasing. A comfortable ride is important to achieving passenger satisfaction. A train seat plays a significant role in fulfilling passenger seating comfort. With this in view, a field survey and pressure measurements were performed on the selected train seat. Method: The pressure ratio at the body-seat interface (thigh and buttock regions) was measured by the pressure mat system. The interface pressure ratio was calculated and compared. The subjective discomfort rating scale was used to evaluate the subjects' overall feeling. The dimensions of train seats were analysed according to the anthropometric and demographic characteristics of the population data from Size Korea. Results: The results highlighted that the interface pressure ratio was greater while participants sat on the second-class seat than the first-class seat in the left- and right-side thigh regions. Also the pressure ratio was greater for the participants in the 1st~25th percentile height groups (149.8~160.8cm). The subjects rated higher discomfort for the second-class seat than the first-class seat. The physical compatibility results showed that the second-class seat's breadth was inadequate for the 95th and 99th percentile male. Conclusion: Overall, interface pressure measurement, subjective discomfort score and physical compatibility results showed that the second-class seat was more uncomfortable for the passengers than the first-class seat. Application: The adopted methodologies could be used to measure the seating comfort of the train seats.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4106-4106
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• 2001

A method to discriminate human gallstones by nea. infrared(NIR) spectrometry using a soft independent modeling of class analogy (SIMCA) has been studied. The fifty NIR spectra of gallstones in the wavenumber range from 4500 to 10,000 cm$\^$-1/ were measured. The forty samples were classified to three classes, cholesterol stone, calcium bilirubinate stone and calcium carbonate stone according to the contents of major components in each gallstone. The training set which contained objects of the different known class was constructed using forty NIR spectra and the test set was made with ten different gallstone spectra. The number of important principal components(PCs) to describe the class was determined by cross validation in order to improve the decision criterion of the SIMCA for the training set. The score plots of the class training set whose objects belong to the other classes were inspected. The critical distance of each class was computed using both the Euclidean distance and the Mahalanobis distance at a proper level of significance(${\alpha}$). Two methods were compared with respect to classification and their robustness towards the number of PCs selected to describe different classes.

• 대한수학회지
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• 제42권2호
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• pp.203-222
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• 2005

Thompson series is a Hauptmodul for a genus zero group which lies between $\Gamma$o(N) and its normalizer in PSL2(R) ([1]). We construct explicit ring class fields over an imaginary quadratic field K from the Thompson series $T_g$($\alpha$) (Theorem 4), which would be an extension of [3], Theorem 3.7.5 (2) by using the Shimura theory and the standard results of complex multiplication. Also we construct various class fields over K, over a CM-field K (${\zeta}N + {\zeta}_N^{-1}$), and over a field K (${\zeta}N$). Furthermore, we find an explicit formula for the conjugates of Tg ($\alpha$) to calculate its minimal polynomial where $\alpha$ (${\in}{\eta}$) is the quotient of a basis of an integral ideal in K.