• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.839-852
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• 2014

This study analyzed the applicability of a rainfall downscaling algorithm in space-time multifractal framework (RDSTMF) in Korean Peninsula. To achieve this purpose, the 8 heavy rainfall events that occurred in Korea during the period between 2008 and 2012 were analyzed using the radar rainfall imagery. The result of the analysis indicated that there is a strong tendency of the multifractality for all 8 heavy rainfall events. Based on the multifractal exponents obtained from the analysis, the parameters of the RDSTMF were obtained and the relationship between the average intensity of the rainfall events and the parameters of the RDSTMF was developed. Based on this relationship, the synthetic space-time rainfall fields were generated using the RDSTMF. Then, the generated synthetic space-time rainfall fields were compared to the observation. The result of the comparison indicated that the RDSTMF can accurately reproduce the multifractal exponents of the observed rainfall field up to 3rd order and the cumulative density function of the observed space-time rainfall field with a reasoable accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.363-371
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• 1999

In this paper proposes the optimal fuzzy controller design method using the genetic algorithm. Proposed method is that fuzzy rules and input - output scaling factors of the fuzzy controller are determined by using genetic algorithm that is very effectively in the optimization problem. The optimal fuzzy rules of servo system uses the fitness function which are the performance index in fuzzy controller. In order to verify excellent control performances of the proposed control method, we compare the control performance and characteristics about the proposed control method with a conventional fuzzy control method through a lot of simulations and experiments with one link manipulator.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.91-94
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• 2001

본 논문에서는 멀티웨이브릿 필터뱅크를 이용한 임베디드 제로 트리 구조(embedded zero tree structure)의 영상 압축방법을 제안한다. 본 논문에서 사용한 멀티웨이브릿 함수는 근사화 차수가 2인 새로운 방법의 DGHM 멀티웨이브릿을 사용하였으며, 영상을 부호화하기 위하여 임베디드 제로 트리 구조의 코딩기법을 사용한다. 높은 근사화 차수를 갖는 멀티웨이브릿 필터는 보다 우수한 에너지 압축 효과를 가지게 된다. 따라서 본 논문에서는 우수한 에너지 압축 효과는 내기 위하여 수학적으로 정립이 된 근사화 차수가 2인 DGHM 멀티웨이브릿을 영상압축에 사용한다. 또한 기존의 멀티웨이브릿 필터들보다 높은 성능을 갖는 DGHM 멀티스케일링 및 멀티웨이브릿 필터를 구성하여 영상을 완전복원이 되도록 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.316-321
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• 2005

A new HBT current source model and the corresponding direct parameter extraction methods are presented. Exact analytical expressions for the current source model parameters are derived. This method is applied to scalable modeling of HBT, Some techniques to reduce redundancy of the parameters are introduced. The model based on this method can accurately predict the measured data for the change of ambient temperature, size, and bias.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1374-1383
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• 2001

In the fuzzy control method behaves more robustness than conventional control method, we propose a intelligent control method that membership functions and scaling factor of the fuzzy logic controller are optimized by genetic algorithm under off-line, and then fuzzy logic controller is constructed by the optimization parameters under on-line. In order to verify the usefulness of the proposed control method, we are applied to one link manipulator, and confirmed that the proposed control method is reduced the fuzzy rule base and is the better performance than the conventional fuzzy control method.

• Journal of the Korea Computer Graphics Society
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• v.11 no.1
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• pp.21-30
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• 2005

그래픽, 오디오, 텍스트 정보 등의 저작권 보호를 위해 사용되어오던 디지털 워터마킹은 이제 기하 정보의 저작권을 보호하는데에도 중요하게 쓰이게 되었다. 스펙트랄 영역에서의 다각형 모델에 대한 워터마킹은 여러가지 공격에 대하여 강건함을 갖는다. 우리는 기존의 스펙트랄 영역에서의 워터마킹 기법을 일반화하고 이에 기반한 새로운 방법을 제시한다. 워터마크를 삽입 할 때에 라플라시안 행렬의 고유값과 고유벡터를 찾지 않는다. 대신 스케일링 함수로 부터 얻어진 선형 작용소를 사용한다. 테스트 결과는 서로 상충되는 워터마크를 삽입하고 추출하는데 드는 비용과 공격에 대한 강건성을 어떻게 조정하였는지 보여준다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.661-662
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• 2021

본 논문에서는 인공신경망 기반의 슈퍼 해상도(Super-resolution, SR) 기법을 이용하여 저해상도(Low-resolution, LR) 헤어 시뮬레이션을 고해상도(High-resolution, HR)로 노이즈 없이 표현할 수 있는 기법을 제안한다. LR과 HR 머리카락 간의 쌍은 헤어 시뮬레이션을 통해 얻을 수 있으며, 이렇게 얻어진 데이터를 이용하여 HR-LR 데이터 쌍을 설정한다. 학습할 때 사용되는 데이터는 머리카락의 위치를 지오메트리 이미지로 변환하여 사용한다. 우리가 제안하는 헤어 네트워크는 LR 이미지를 HR 이미지로 업스케일링 시키는 이미지 합성기를 위해 사용된다. 테스트 결과로 얻어진 HR 이미지가 HR 머리카락으로 다시 변환되면, 하나의 매핑 함수로 표현하기 어려운 머리카락의 찰랑거리는(Elastic) 움직임을 잘 표현할 수 있다. 합성 결과에 대한 성능으로는 전통적인 물리 기반 시뮬레이션보다 빠른 성능을 보였으며, 복잡한 수치해석을 몰라도 쉽게 실행이 가능하다.

• Communications of Mathematical Education
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• v.36 no.4
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• pp.559-587
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• 2022

The purpose of this study is to derive implications for the development of the next curriculum and textbooks by comparing and analyzing the textbooks of the 2015 revised high school mathematics curriculum <Mathematics for Economics> and social studies curriculum <Economics>. In the <Mathematics for Economics> textbooks, economic terms and function notations should be introduced. Additionally, the use of graphs for economic-related functions is different from the use of graphs in mathematics in the <Mathematics for Economics> textbooks. For these reasons, the usage of economic terms, function notations, and function graphs covered in the <Mathematics for Economics> textbooks were compared and analyzed with the usage in the <Economics> textbooks. In the <Mathematics for Economics> textbooks, economic terms that are highly related to mathematics are defined and presented. Contrary to the conventions of mathematics and economics, the function notations in the <Mathematics for Economics> textbooks were used inconsistently because uppercase and lowercase letters were mixed in the function notations. Function graphs in the <Mathematics for Economics> textbooks had differences in the range of values represented by the variables regarding axes and scaling. The <Mathematics for Economics> textbooks did not provide a mathematical interpretation of the translation or slope. In the course of <Mathematics for Economics>, it is necessary to specify considerations for teaching and learning, and assessment in the curriculum to promote students' understanding of mathematics and economics. The descriptions in the curriculum document and textbooks of <Mathematics for Economics> should be supplemented to provide learning opportunities for mathematical interpretation of economics-related contents.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.409-419
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• 2007

Database community focuses on the similar music retrieval systems for music database when a humming query is given. One of the approaches is converting the midi data to time series, building their indices and performing the similarity search on them. Queries based on humming can be transformed to time series by using the known pitch detection algorithms. The recently suggested algorithm, scaled and warped matching, is based on dynamic time warping and uniform scaling. This paper proposes Humming BIRD(Humming Based sImilaR mini music retrieval system) using sliding window and center-aligned scaled and warped matching. Center-aligned scaled and warped matching is a mixed distance measure of center-aligned uniform scaling and time warping. The newly proposed measure gives tighter lower bound than previous ones which results in reduced search space. The empirical results show the superiority of this algorithm comparing the pruning power while it returns the same results.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.441-446
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• 2020

In this paper, we propose the α-Feature Map Scaling (α-FMS) method which extends the FMS method that was designed to enhance the discriminative power of feature maps of deep neural networks in Speaker Verification (SV) systems. The FMS derives a scale vector from a feature map and then adds or multiplies them to the features, or sequentially apply both operations. However, the FMS method not only uses an identical scale vector for both addition and multiplication, but also has a limitation that it can only add a value between zero and one in case of addition. In this study, to overcome these limitations, we propose α-FMS to add a trainable parameter α to the feature map element-wise, and then multiply a scale vector. We compare the performance of the two methods: the one where α is a scalar, and the other where it is a vector. Both α-FMS methods are applied after each residual block of the deep neural network. The proposed system using the α-FMS methods are trained using the RawNet2 and tested using the VoxCeleb1 evaluation set. The result demonstrates an equal error rate of 2.47 % and 2.31 % for the two α-FMS methods respectively.