• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.175-180
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• 2018

In this paper, a feature extraction and object recognition algorithm using only morphological operations is proposed. The morphological operations used in feature extraction are erosion and dilation, opening and closing combining erosion and dilation, and morphological edge and skeleton detection operation. In the process of recognizing an object based on features, a pooling operation is applied to reduce the dimension. Among various structuring elements, $3{\times}3$ rhombus, $3{\times}3$ square, and $5{\times}5$ circle are arbitrarily selected in morphological operation process. It has confirmed that the proposed algorithm can be applied in object recognition fields through experiments using Internet images.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.119-124
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• 2015

Speech enhancement has been required as a preprocessor for a noise robust speech recognition system. Codebook-based Speech Enhancement (CBSE) is highly robust in nonstationary noise environments compared with conventional noise estimation algorithms. However, its performance is severely degraded for the codevector combinations that have lower correlation with the input signal since CBSE depends on the trained codebook information. To overcome this problem, only the reliable codevector combinations are selected to be used to remove the codevector combinations that have lower correlation with input signal. The proposed method produces the improved performance compared to the conventional CBSE in terms of Log-Spectral Distortion (LSD) and Perceptual Evaluation of Speech Quality (PESQ).

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.402-410
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• 2004

In this paper, an optimal design method of clonal selection based Fuzzy-Neural Networks (FNN) model for complex and nonlinear systems is presented. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. Also Advanced Clonal Selection (ACS) is proposed to find the parameters such as parameters of membership functions, learning rates and momentum coefficients. The proposed method is based on an Immune Algorithm (IA) using biological Immune System and The performance is improved by control of differentiation rate. Through that procedure, the antibodies are producted variously and the parameter of FNN are optimized by selecting method of antibody with the best affinity against antigens such as object function and limitation condition. To evaluate the performance of the proposed method, we use the time series data for gas furnace and traffic route choice process.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.23-43
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• 2022

In order to apply AI (Artificial Intelligence) in various industries, interest in algorithm selection is increasing. Algorithm selection is largely determined by the experience of a data scientist. However, in the case of an inexperienced data scientist, an algorithm is selected through meta-learning based on dataset characteristics. However, since the selection process is a black box, it was not possible to know on what basis the existing algorithm recommendation was derived. Accordingly, this study uses k-means cluster analysis to classify types according to data set characteristics, and to explore suitable classification algorithms and methods for resolving class imbalance. As a result of this study, four types were derived, and an appropriate class imbalance resolution method and classification algorithm were recommended according to the data set type.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.204-204
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• 2018

수문 기상레이더는 강우량을 바로 추정하지 못하고 여러 단계의 정량적 강우량 추정과정을 거치게 되므로 많은 불확실성 발생요소가 존재한다. 불확실성 관련한 기존 연구들은 정량적 레이더 기반 강우량 추정과정에서 보정방법을 이용하여 각 단계별 불확실성을 줄이는 연구들을 수행하였다. 하지만 기존 연구들은 전체 과정에 대한 포괄적인 불확실성을 나타내지 못하고 각 단계별 불확실성의 상대적인 비율도 제시하지 못하는 단점이 있다. 본 연구에서는 정량적 레이더강우량 추정과정의 각 단계별 불확실성을 정량화하고 불확실성 전파를 나타낼 수 있는 적합한 방법을 제시하였다. 첫 번째로 초기와 최종 불확실성, 각 단계별 불확실성의 변동과 상대적인 비율을 나타낼 수 있는 새로운 개념을 제안하였다. 두 번째로 레이더기반 추정과정의 불확실성 정량화와 전파과정을 분석하기 위해 Maximum Entropy Method (MEM), Uncertainty Delta Method (UMD), Modified-Narrow Uncertainty Method (M-NUM)를 적용하였다. 세 번째로 레이더기반 강우량 추정과정의 불확실성 정량화를 위해 2개 품질관리 알고리즘, 2개 강우량 추정방법, 2개 후처리 강우량 보정방법을 2012년 여름철 18개 사례에 대하여 사용하였다. 적용결과, 최종 불확실성(후처리 강우량 보정 불확실성)이 초기 불확실성(품질관리 불확실성)보다 작게 나타나 불확실성이 감소하는 것으로 나타났다. 하지만 레이더강우량 추정단계의 불확실성은 증가하는 것으로 나타났다. 또한 레이더강우량 추정과정에서 각 단계별로 적합한 방법을 선정하는 것이 각 단계별로 불확실성이 감소시킬 수 있음을 확인하였다. 따라서 본 연구는 새로운 방법이 명확히 불확실성을 정량화할 수 있으며 정확한 정량적 레이더 강우추정에 기여할 것으로 판단한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.97-99
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• 2014

This study aims to suggest development model for ICT Teaching and Learning System adopting collective intelligence. First, we defined program modules according to functions which multimedia online encyclopedia-type e-textbook should have. Then, we also specified content information creating rules and procedures and content information searching methods. Finally, we developed the prototype which suggests user interface to collect and search information adopting information visualizing techniques. This study has significance in suggesting advanced form of ICT system in which qualified teachers can create, accumulate, and share information and students can explore information and expand search in self-directed manner.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.105-114
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• 2017

Because the concepts and components of computational thinking included in the Information Education Curriculum and the Software Education Guidelines are different, it has been difficult to establish computational thinking-based software education in schools. Therefore, this study, which is based on the Delphi survey results from 39 experts, we defined computational thinking as 'computing thinking' and separated the components of computational thinking into five main categories: (1) problem definition, (2) data analysis, (3) abstraction, (4) automation, and (5) generalization. In addition, we selected software areas that are strongly related to computational thinking in the KAIE's information Curriculum Standard Model and surveyed experts to decide which computing thinking components are related to the achievement criteria of the software areas.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.73-81
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• 2012

In this paper, we propose a high-speed synchronization method for Digital Radio Mondiale (DRM) receivers. In order to satisfy the high-speed synchronization requirement of DRM receivers, the proposed method eliminate the initial sampling frequency synchronization process in conventional synchronization methods. In the proposed method, sampling frequency tracking is performed after integer frequency synchronization and frame synchronization. Different correlation algorithms are applied to detect the first frame of the Orthogonal Frequency Division Multiplexing (OFDM) demodulation symbol with sampling frequency offset (SFO). A frame detection algorithm that is robust to SFO is selected based on the performance analysis and simulation. Simulation results show that the proposed method reduces the time spent for initial sampling frequency synchronization even if SFO is present in the DRM signal. In addition, it is verify that inter-cell differential correlation used between reference cells is roubst to the effect of initial SFO.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.413-422
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• 2012

Many researchers have been studied to reveal human natural language to let machine understand its meaning by text based, page rank based or more. Particularly, it has been considered that URL and HTML Tag information in web documents are attracting people' attention again to analyze huge amount of web document automatically. In this paper, we propose a STW (Semantic Term Weight) approach based on syntactic and linguistic structure of web documents in order to classify what genres are. For the evaluation, we analyzed more than 1,000 documents from 20-Genre-collection corpus for training the documents based on SVM algorithm. Afterwards, we tested KI-04 corpus to evaluate performance of our proposed method. This paper measured their accuracy by classifying them into an experiment using STW and one without u sing STW. As the results, the proposed STW based approach showed approximately 10.2% which Is higher than one without use of STW.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.321-331
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• 2006

Recently, runoff characteristics of urban area are changing because of the increase of impervious area by rapidly increasing of population and industrialization, urbanization. It needs to extract the accurate topologic and hydrologic parameters of watershed in order to manage water resource efficiently. Thus, this study developed more precise input data and more improved parameter estimating procedures using GIS(Geographic Information System) and GA(Genetic Algorithm). For these purposes, XP-SWMM (EXPert-Storm Water Management Model) was used to simulate the urban runoff. The model was applied to An-Yang stream basin that is a typical Korean urban stream basin with several tributaries. The rules for parameter estimation were composed and applied based on quantity parameters that are investigated through the sensitivity analysis. GA algorithm is composed of these rules and facts. The conditions of urban flows are simulated using the rainfall-runoff data of the study area. The data of area, slope, width of each subcatchment and length, slope of each stream reach were acquired from topographic maps, and imperviousness rate, land use types, infiltration capacities of each subcatchment from land use maps, soil maps using GIS. Also we gave the management scheme of urbanization runoff using XP-SWMM. The parameters are estimated by GA from sensitivity analysis which is performed to analyze the runoff parameters.