• Journal of Korean Society of Environmental Engineers
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• v.38 no.7
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• pp.387-394
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• 2016

Commercial 28 algae removal technologies that have been applied in domestic rivers and lakes with green tide were investigated, analyzed and classified. The classification of algae removal technologies was based on the three criteria (i.e., principle, flow rate of water body, and application period). Also, algae removal technologies were evaluated in terms of cost effectiveness, field applicability, effect durability, and eco friendliness. From the analysis results, technologies using physical, chemical, biological, and convergent controls were 32.2%, 25%, 21.4%, and 21.4%, respectively. The 75% of technologies have been applied to stagnant water body (${\leq}0.2m/s$). Also, algae harvesting ship with dissolved air flotation, conveyor belt and filtration processes and natural floating coagulant were found to have better field applicability, compared to other technologies. However, proper algae removal technology in specific rivers and lakes should be chosen after the evaluation of long-term pilot scale field test. Also, development of energy and resource recovery technologies from algae biomass is warranted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.702-708
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• 2018

3D printing technology is attracting increasing attention as a key technology of the fourth industrial revolution that can change the production paradigm of existing industries. The introduction of construction 3D printing technology has been slower than other industries because of the characteristics of the construction field. On the other hand construction automation using 3D printing is required to reduce the production population, as well as improve productivity and safety. In this study, a construction 3D printing work breakdown structure and link method to a standard estimation system were developed as a preliminary preparation for introducing 3D printing to construction. Based on expert consultation on construction and 3D printing, a hypothetical scenario was developed based on existing construction 3D printing technology. According to the scenario, 16 kinds of works required for 3D printing construction work were derived. The existing work breakdown structure and standard estimation system were analyzed, and the 3D printing work was linked. 3D printing works that were the same as the existing breakdown structure were found, and non-existent works were added to the similar breakdown structure. These results are expected to be helpful for future 3D printing construction management and cost estimation. The actual standard estimation system through 3D printing work will need to be calculated.

• Journal of Korean Society for Geospatial Information Science
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• v.9 no.2 s.18
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• pp.37-46
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• 2001

Spectral pattern recognition techniques are most used in classification of remotely sensed data. Yet, in any real image, adjacent pixels are related, because imaging sensors acquire significant portions of energy from adjacent pixels. And, with the continued improvement in the spatial resolution of remote sensing systems, another spatial pattern recognition approach is must considered. In this study, we aim to show the potentiality of spatial classification methods through comparing the accuracies of spectral classification methods and those of spectral classification methods. By the comparisons between the two methods, classification accuracies of 6 different spatial classification methods are higher than that of spectral classification method by 2-6% or so. Additionally, we can show it statistically through the classification experiments with different band combinations.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.115-123
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• 2014

Patent information analysis has been carried out for technological capability analysis of competitors relating to next generation mobile communication. Various analysis methods, such as applicant analysis, technology classification analysis, indicator analysis and the like have been utilized as a method of analyzing patent information. As a first step for the technological capability analysis of competitors, applicants having high patent activity(PA) were selected, and as a second step therefor, technology classifications showing high technological independence (TI) were selected. Furthermore, portfolios for technology classifications showing high technological independence in the patents of main applicants having high patent activity by matching results the first and second steps together were prepared. Through such a process, portfolios for important technologies which have been concentrically researched by competitors could be analyzed. Accordingly, the present analysis results will help to carry out strategic R&D management, such as the establishment of company R&D plans and patent strategies.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.218-227
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• 2022

This study attempted classification through deep learning-based image training for land cover classification in river spaces which is one of the important data for efficient river management. For this purpose, land cover classification analysis with the RGB image of the target section based on the category classification index of major land cover map was conducted by using the learning outcomes from the result of labeling. In addition, land cover classification of the river spaces was performed by unsupervised and supervised classification from Sentinel-2 satellite images provided in an open format, and this was compared with the results of deep learning-based image classification. As a result of the analysis, it showed more accurate prediction results compared to unsupervised classification results, and it presented significantly improved classification results in the case of high-resolution images. The result of this study showed the possibility of classifying water areas and wetlands in the river spaces, and if additional research is performed in the future, the deep learning based image train method for the land cover classification could be used for river management.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.239-246
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• 2023

In this paper, we propose an open-loop algorithm to classify speech and music signals using the spectral flux parameters and Mel Frequency Cepstral Coefficients(MFCC) parameters for the audio coder. To increase responsiveness, the MFCC was used as a short-term feature parameter and spectral fluxes were used as a long-term feature parameters to improve accuracy. The overall voice/music signal classification decision is made by combining the short-term classification method and the long-term classification method. The Gaussian Mixed Model (GMM) was used for pattern recognition and the optimal GMM parameters were extracted using the Expectation Maximization (EM) algorithm. The proposed long-term and short-term combined speech/music signal classification method showed an average classification error rate of 1.5% on various audio sound sources, and improved the classification error rate by 0.9% compared to the short-term single classification method and 0.6% compared to the long-term single classification method. The proposed speech/music signal classification method was able to improve the classification error rate performance by 9.1% in percussion music signals with attacks and 5.8% in voice signals compared to the Unified Speech Audio Coding (USAC) audio classification method.

• Annual Conference of KIPS
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• 2006.05a
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• pp.31-34
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• 2006

단백질 구조로부터 단백질 기능을 예측하고자 하는 일은 생명정보학 에서 중요한 이슈 및 연구과제가 되어 왔다. 그 중 단백질의 3 차 구조를 이해하고 분류하는 데에는 계층적인 분류방법을 이용하는 CATH database가 사용되고 있다. 이 논문에서는 CATH database 의 계층적 분류의 특성을 이용하되, 단백질의 3 차 구조가 아닌 단백질 서열로부터 데이터마이닝 기술을 적용, 마이닝 기법 중 순차패턴과 연관적 분류 기법을 이용하여 CATH database 의 계층별 구조 분류 기법을 제안 하였다.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.194-199
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• 1997

본 논문에서는 글꼴의 변화와 잡영을 흡수할 수 있도록 자소의 탐색 영역을 정의 하였으며 이 영역에 나타나는 횡모음과 종모음의 주획을 추출하는 방법을 기술하였다. 종모음 영역에서 추출한 수직획들과 횡모음 영역에서 추출한 수평획들을 각각 종모음과 횡모음의 주획이 될 수 있는 후보들로써 이들로 부터 종모음과 횡모음의 존재를 파악하는 것이 한글 유형 분류의 주된 내용이다. 그러나 다양한 글꼴에 나타나는 수평획들로부터 곧바로 횡모음의 존재를 파악하는 것은 쉬운 문제가 아니다 본 논문에서는 기존의 트리 분류기를 확장하여 복잡하고 다양한 특징을 단계별로 단순화시키고 트리 분류기의 상위 노드에서 결정된 정보와 제약 조건을 이용하여 유형을 분류하는 방법을 제안하였다. 제안된 방법은 한글 상위 빈도 1405자, 3가지 글꼴에 대하여 99.8 %의 유형 분류율을 보이고 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.434-436
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• 2003

DNA칩 기술로 얻어지는 유전자발현데이터(gene expression data)는 생채 조직이나 세포의 수천개에 달하는 유전자의 발현량(expression level)을 측정한 것으로, 유전자발현양상(gene expression pattern)에 기반한 암 종류의 분류 등에 유용하다. 본 논문에서는 확률그래프모델(probabilistic graphical model)의 하나인 베이지안망(Bayesian network)을 발현데이터의 분류에 적응하며, 분류 성능을 높이기 위해 베이지안망의 앙상블(ensemble of Bayesian networks)을 구성한다. 실험은 실제 암 조직에서 추출된 유전자발현데이터에 대해 행해졌다 실험 결과, 앙상블 베이지안망의 분류 정확도는 단일 베이지안망보다 높았으며, naive Bayes 분류기, 신경망, support vector machine(SVM) 등과 대등한 성능을 보였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1690-1697
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• 2006

온톨로지는 사람들 간의 정확한 의사소통을 가능하게 하고 시스템 사이의 상호운용성을 달성하기 위한 도구로서 다양한 분야에서 많은 기대를 받고 있는 기술이다. 온톨로지의 구축은 기존 온톨로지들간의 통합을 통해 더욱 효율적으로 이루어질 수 있다. 그러나 기존 온톨로지들이 표현 언어, 대상 도메인, 온톨로지 구성요소 등의 측면에서 다양한 형태와 특성을 가지므로, 온톨로지 통합이 이루어지기 위해서는 온톨로지들 간의 상호운용성의 확보가 필수적이다. 본 논문에서는 온톨로지를 분류하는 체계적인 프레임워크의 제공을 통해 온톨로지들 간의 상호운용성 확보를 지원하는 온톨로지 아키텍처를 제안한다. 본 논문에서 제안하는 온톨로지 아키텍처는 온톨로지를 바라보는 3가지 관점에 따라 MDA에 기반한 온톨로지 표현 분류축, 시맨틱 도메인 분류축, 온톨로지 구성요소 분류축의 3개 분류축으로 이루어져 있으며, MDA의 4계층 메타모델링을 문법적인 기반으로 하고 있다. 온톨로지 아키텍처의 3개의 분류축은 온톨로지들 간의 문법적인 상호운용성과 의미적인 상호운용성을 향상시키기 위해 조화롭게 설계됨으로써 온톨로지 통합이 유연하게 이루어지도록 지원한다.