• Journal of Conservation Science
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• v.18 s.18
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• pp.89-96
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• 2006

Surface layers of stone cultural properties including the soluble salt need consolidation because they are mostly very weak. There is a lot of research on the penetration depth of consolidant in stone and the effect of consolidant on mechanical stability of deteriorated structure. But some conservation experiences show that consolidation with silicic acid ester is not successful on salt contaminated stone cultural properties. In this study, in order to assess the influence of soluble salts$(CaSO_4\;2H_2O,\;NaNO_3)$ on the efficiency of consolidation on the deteriorated stone cultural properties(Nationalgalerie, Berlin, Germany) sandstone samples have been soaked with the salts solution. The impregnation of consolidant based on ethyl filicate have been afterwards carried out on these samples. As a result, it confirms that the soluble salts act as a preventer or consolidation. They fill up the pores in the stone and prevent that sufficient amount of consolidant enter deeply into the stone. According to this result, if use silicic ethyl ester as a consolidant for the research object which is built by Nebra sandstone, desalination is necessary before the treatment with consolidant. But it is also reported by other researches that some soluble salts improve the consolidation effect. Therefore it should be necessary to pre-study about salt and its harmfulness before the consolidation treatment. In order to consolidate without the aggravative damage in salt contaminated stone cultural heritage, we must first of all study the relations among salt, stone and consolidant.

• The Journal of Korean society of community based occupational therapy
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• v.8 no.3
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• pp.59-67
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• 2018

Objective : This study was conducted to investigate the effects of occupation-based group cooking program on executive function for children in community children's center. Methods : The children who participated in the study were 7 to 9 years old. This study was based on a one-group pre-posttest design, which the group cooking program included making of sandwiches, frog-shaped hamburgers, patbingsu, sausage gimbap, and flowerpot cupcake. This study consisted of five activity sessions, which each session lasted for 120 minutes. Effectiveness of the program was measured by using the STROOP Color and Word Test, Children's Color Trails Test and Assessment of Motor and Process Skills. Results : The differences between pre and posttest scores on STROOP Color and Word Test and the process skill score of Assessment of Motor and Process Skills were statistically significant. There was no difference significantly between pre and posttest scores in Children's Color Trails Test-2. Conclusion : This study demonstrated that the group cooking program intervention has effects on cognitive inhibition executive function and performance executive function of children in the community children's center. This study suggests that occupation-based intervention can be applied to various clients in the community setting.

• Journal of Internet Computing and Services
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• v.2 no.3
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• pp.37-49
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• 2001

Korean auxiliary verbs are often used in Korean sentences in spite of the small number of the auxiliary verbs, However. the incorrect processing of the verbs concept leads to the poor translation quality. To solve the problems of the auxiliary verb processing. the paper proposes a description of the auxiliary verbs based on Conceptual Graph (CG), For the description of the auxiliary verbs within CG. we first collect 40 Korean auxiliary verbs and example sentences from papers and a Korean dictionary, Next, we perform the analysis of the Korean auxiliary verbs through a classification: perfective, progressive, benefactive, attemptive, emphatic, desirable, retentive, and presumptive. Then we depict the eight meanings based on CG. In the experiment. the paper implements the program that translates sentences included in the auxiliary verbs into CG and explains the experimental results.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.267-270
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• 2018

구제역으로 인하여 국내 축산업계 및 관련 산업분야는 매년 막대한 피해를 입고 있다. 구제역과 관련한 다양한 학술적 연구들이 현재 진행되고는 있으나, 구제역의 발병에 따른 사회적 파급효과에 관한 공학적 분석 연구는 매우 제한적이다. 본 연구에서는 구제역에 관한 일반 시민들의 감성적 반응을 텍스트 마이닝 방법론을 사용하여 분석하는 체계적인 방법론을 제안한다. 제안하는 시스템은 먼저, 트위터에 게시된 트윗 중 구제역과 관련된 데이터를 수집한 후, 감성사전을 기반으로 극성탐지 과정을 거친다. 둘째, 토픽 모델링의 대표적인 기법 중 하나인 LDA를 활용하여 트윗으로 부터 키워드들을 추출하고, 추출된 키워드들로부터 극성별 동시출현 키워드 네트워크를 구성한다. 셋째, 키워드 네트워크을 통해 각 구간별 구제역의 사회적 파급효과를 분석한다. 사례 분석으로써, 2010년 7월부터 2011년 12월까지 국내에서 발생한 구제역에 관한 일반 시민들의 감성적 변화를 분석하였다.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.165-172
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• 2010

Sensor network can be applied in many areas in our life, and security is very important in applying sensor network. For secure sensor communication, pairwise key establishment between sensor nodes is essential. In this paper, we cluster the network field in hexagonal shapes and preassign three different kinds of key information for each sensor according to its expected location. We adopt overlapped key string pool concept for our clustered network architecture and every node uses the part of sub-strings for setting up pairwise keys with all neighboring nodes in its own cluster and from different clusters according to respective position with small amount of information. Our proposal decreases the memory requirement and increases security level efficiently.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.49-56
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• 2014

Generally, the tool presetter is utilized to align and measure some specific dimensions of a machine tool. It is classified into two types(contact and contactless) according to the measurement method, and the optical sensor based contactless scheme has the advantages of measurement flexibility and convenience. This paper describes the design and realization of an industrial tool presetter using machine vision and linear scaler. Before measurement, the objective tool is attached to the mechanical mount and is aligned with the optical apparatus. After capturing tool images, the suggested image processing algorithm calculates its dimesions accurately, combining the traversing distance from the linear scaler. Experimental results conforms that the present tool presetter system has the precision within ${\pm}20um$ error.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.1
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• pp.17-23
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• 2004

This paper proposes to determine word senses in Korean language processing by corpus-based ontology learning. Our approach is a hybrid method. First, we apply the previously-secured dictionary information to select the correct senses of some ambiguous words with high precision, and then use the ontology to disambiguate the remaining ambiguous words. The mutual information between concepts in the ontology was calculated before using the ontology as knowledge for disambiguating word senses. If mutual information is regarded as a weight between ontology concepts, the ontology can be treated as a graph with weighted edges, and then we locate the least weighted path from one concept to the other concept. In our practical machine translation system, our word sense disambiguation method achieved a 9％ improvement over methods which do not use ontology for Korean translation.

• Information Systems Review
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• v.16 no.1
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• pp.37-50
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• 2014

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. In order to overcome this problem, some previous researches suggest clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new hybrid case-based reasoning method which dynamically composing a searching pool for each target case. This method is applied to diagnose for the heart disease dataset. The results show that the suggested hybrid method produces statistically the same level of predictive performances with using significantly less computational cost than the CBR method and also outperforms the basic clustering-CBR (C-CBR) method.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.145-153
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• 2020

Recently, keyword extraction from social big data has been widely used for the purpose of extracting opinions or complaints from the user's perspective. Regarding this, our previous work suggested a method to improve accuracy of keyword extraction based on the notion of cohesion scoring, but its accuracy can be degraded when the number of input reviews is relatively small. This paper presents a method to resolve this issue by applying simplified morphological analysis as a postprocessing step to extracted keywords generated from the algorithm discussed in the previous work. The proposed method enables to add analysis rules necessary to process input data incrementally whenever new data arrives, which leads to reduction of a dictionary size and improvement of analysis efficiency. In addition, an interactive rule adder is provided to minimize efforts to add new rules. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that error ratio was reduced from 10% to 1% by applying our method and it took 450 milliseconds to process 5,000 reviews, which means that keyword extraction can be performed in a timely manner in the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.104-104
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• 2022

임진강 수계는 북측 지역이 다수를 차지하는 유역 특성으로 예고 없는 상류 급방류, 강우 등으로 인해 댐 운영에 근본적 어려움이 있으며, 이에 따라 홍수조절지 및 댐 하류 계측 가능 지역의 취득 자료를 고려한 하천 수위 변화에 대한 사전 예측을 필요로 하고 있다. 홍수기 하천 도달시간 및 수위예측 기법으로는 물리 기반 및 데이터 기반 모델들이 다양하게 연구되어 왔으며, 일부 연구성과들은 현업에 활용하고 있다. 물리기반 모델은 하천 지형 변화에 대한 자료 취득 및 분석에 많은 시간을 요하는 단점은 있으나, 설명 가능한 모델을 구현할 수 있을 것으로 사료 된다. 반면, 데이터 기반 인공지능 모델은 짧은 시간 및 비용으로 모델을 개발할 수 있으나, 복잡한 알고리즘구현 시 설명이 불가하여 일관성을 의심 받을 수 있다. 본 논문에서는 홍수 도달시간과 하류 수위 상승에 대하여 설명 가능한 인공지능 알고리즘 및 시뮬레이션 프로그램을 개발하고자 하였다. 홍수 도달시간 예측은 기존 조견표 방식에서 고려하지 않았던 홍수파의 영향을 추가 변수화 하고, 데이터의 전후처리를 통하여 도달시간을 예측하였다. 실시간 하류 수위 예측은 댐 방류량, 주변 강우, 조위 등을 고려하여 도달시간 후 수위를 예측할 수 있도록 구현하였으며, 자료 동화 기술을 일부 적용하였다. 미래 방류조건에 대한 시뮬레이션을 위해서는 미래 방류량, 예상 강우 입력 시 하천 지점별 수위 상승을 예측할 수 있도록 알고리즘 및 프로그램을 개발하였다. 이를 구현하기 위하여 다양한 인공지능 알고리즘을 이용한 학습, 유전자 알고리즘을 이용한 가중치 학습 제한 조건내 최적화, 수위파와 조위파의 중첩의 정리 등을 이용하여 예측 정확도 및 신뢰성을 제고 하였다. 인공지능 분석결과의 현업활용성 제고를 위하여 시뮬레이터 프로그램을 개발하여 현업에 적용하였다.