• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.349-361
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• 2008

There has been abundant empirical research undertaken on the technical efficiency of Korean ports. Most studies have focused on the use of parametric and non-parametric techniques to analyse overall technical efficiency. This paper utilizes data for the period 2000-07 to offer a heterogeneous perspective on the overall efficiency of Korean ports. The framework assumes that ports use one input to produce one output; the output and input include port export(import) and regional export(import). This paper also employs panel analysis and heteroscedastic Tobit model to show the effect of the explanatory variables on the port efficiencies. The panel analysis shows that the regional export/total export has negative effect on the export efficiency while the regional import/total import has not any relations with the import efficiency. The heteroskedastic Tobit model shows that both regional export ratio and regional import ratio have negative effects on the efficiency while the gross regional domestic product has not any significant relations with the import efficiency.

• Proceedings of the Korean Vacuum Society Conference
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• 1998.02a
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• pp.108-108
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• 1998

최근의 GaN에 관한 연구는 주로 MOCVD법과 MBE법이 이용되고 있으며 대부분 800¬1$\alpha$)()t 정도의 고옹에서 이루어지고 었다. 그러나 이러한 고온 성장은 GaN 성장 과청에서 질 소 vacancy를 생성시켜 광특성을 저하시키고 청색 발광충인 InGaN 화합물에 In의 유입울 어 렵게 하며 저온에서보다 탄소 오염이 증가하는 동의 문제캠을 가지고 있다. 이러한 고온 생장 의 문제점을 해결하기 위한 방법중의 한 가지로 제시되고 있는 것이 저온 성장법이다. 본 연구 에 사용된 RPE-UHVCVD법은 Nz률 rf plasma로 $\sigma$acking하여 공급함으로써 NI-h롤 질소원으 로 사용하는 고온 성장의 청우와는 다르게 온도에 크게 의존하지 고 질소원올 공급할 수 있 어 저옹 성장이 가능하였다. 기판으로는 a - Alz03($\alpha$)()1)를 사용하였고 3족원은 TEGa(triethylgallium)이며,5족원으로는 6 6-nine Nz gas를 rf plasma로 cracking하여 활성 질소원올 공급하였다 .. Nz plasma로 질화처리 를 한 sapphire 표면 위에 G따애 핵생성충을 성장 옹도(350 t, 375 t, 400 t)와 성장시간(30 분,50 분) 그리고 VIllI비(1$\alpha$)(), 2뼈)둥을 변화시키면서 성장시킨 후 GaN 에피택시충을 450 $^{\circ}C$에서 120 분 동안 성장시켰다 .. XPS(x-ray photoelectron spectroscopy), XRD(x-ray d diffraction), AFM(atomic force microscope)둥올 이용하여 표면의 조성 및 morphology 변화와 결정성을 관찰하였다. X XPS 분석 결과 질화처리를 한 sapphire 표면에는 AlN가 형성되었다는 것을 확인 할 수 있 었으며 질화처리를 한 후 G따J 핵생성충올 성장시킨 경우에 morphology 변화를 AFM으로 살 펴본 결과 표면에 facet shape의 island가 형성되었고 이러한 결파는 질화처리 과청이 facet s shape의 island 형성을 촉진시킨다는 것을 알 수 있었다. 핵생성충의 성장온도가 중가함에 따 라 island의 모양은 round shape에서 facet shape으로 변화하였다. 이러한 표면의 morphology 변화와 GaN 에피택시충의 결정성과의 관계를 살펴보면 GaN 에피택시충 표면의 rms(root m mean square) roughness가 중가하는 경 우 XRD (j -rocking curve의 FWHM(full width half m maximum) 값이 감소하는 것으로 나타났다. 이러한 현상은 결정성의 향상이 columnar 성장과 관계가 었다는 것올 알 수 있었다 .. columnar 성장은 결함의 밀도가 낮은 column의 형생과 G GaN 에피택시충의 웅력 제거로 인해 G값{의 결정성을 향상시킬 수 있는 것으로 생각된다. 톡 히 고온 성장의 경우와는 달리 rms roughness의 중가가 100-150 A청도로 명탄한 표면올 유 지하면서 결정성을 향상시킬 수 있었다. 본 실험에서는 핵생성충올 375 t에서 30 분 생장시킨 경우에 hexagonal 모양의 island로 columnar 성장을 하였고 GaN 에피태시충의 결정성도 가장 향상되었다 이상의 결과로부터 RPE-UHVCVD법용 이용한 GaN 저온 성장에서도 GaN의 결청성올 향 상시킬 수 있음융 확인할 수 있었다.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.639-643
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• 2022

한글이 우수한 글자라는 의견에 세계 대부분의 학자들이 동의하고 있다. 한글 자모의 단순성과 직교성(규칙성)으로 인해 표현할 수 있는 발음의 수도 제일 많고 읽고 쓰고 배우기도 쉽다는 점을 누구나 인정하기 때문이다. 구한말과 1950년대에 중국도 한글표기를 사용할 뻔 했다는 이야기도 있다. 그러나 그들은 한자를 사용하되 단순화 하는 방법과 병음을 사용하는 것으로 결론이 났고 현재 그렇게 사용하고 있다. 그런데 중국인들이 외래어를 다루는 것을 보면 많이 고생한다는 생각이 든다. 외래어 표기를 한글로 사용한다면 외래어를 위한 한자 단어를 만들 필요가 없고 외래어를 표현하고 배우고 읽고 쓰는데 훨씬 더 효과적으로 할 수 있고, 원음 재현율이 매우 개선된다. 또한' 글자의 길이가 짧아지고 더 멀리서도 인식되는 장점도 있다. 본 논문은 그것을 보여준다. 본 논문에서는 영어 원단어, 한국어 표기, 중국어 표기, 병음 표기, 중국어 발음 한글 표기 등을 비교해서 한글이 유리함을 보여주고자 한다. 결론적으로 외국단어를 한자나 한자의 병음으로 표현하는 것보다 한글로 표현하는 것이 중국어를 사용하는 모든 사람들에게 큰 도움이 될 것이다. 물론 그들이 한글을 읽고 쓰는 것을 배우는 부담은 있지만 몇일만 배우면 평생의 문제를 해결하게 되는 문제이므로 큰 부담은 아니라고 본다.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.99-99
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• 2019

꾸지뽕나무(Cudrania tricuspidata)는 뽕나무과(Moraceae)에 속하는 낙엽활엽 소교목이다. 우리나라와 중국, 일본과 같은 동아시아에 주로 분포하며 척박한 땅에서도 잘자라고 병충해에 강하다고 알려져 있다. 예로부터 꾸지뽕나무는 항암, 간보호, 눈을 밝게하는 작용이 있다고 동의보감과 신농본초경에 기록되어 있다. 우리나라는 오랫동안 된장 등 발효식품을 자주 접하고 섭취하여 왔다는 점을 고려하여 본 연구를 수행하였다. 발효균을 접종하면 항암활성, 면역체계 개선 등 다양한 생리활성 물질이 증가한다고 알려져 있다. 본 연구는 가시가 없고 잎이 커 작업성이 용이한 대품 품종을 2018년 9월에 전남 신안군에서 채취하여 분석 시료로 사용하였다. 항산화활성 측정은 프리라디칼(DPPH, ABTS) 소거능을 측정하여 농도(EC50)별 측정결과 $100{\mu}g/mL$ ext. 이하로 항산화 활성이 열매보다 잎이 높다는 것을 확인하였다. 황국균(Aspergillus oryae)을 꾸지뽕나무 잎과 열매에 접종시켜 페놀성화합물을 스크리닝 한 결과 기존에 발견되지 않은 Salicylic acid, Naringenin, Vanilic acid, Oxyresveratrol 등 기능성 물질이 발견되었고, 잎의 경우 36시간 발효물(355mg/g)은 무처리군(179mg/g)에 비해 2배정도 상승하였다. 열매의 경우 48시간 발효시켰을 경우(472mg/g)으로 무처리군(156mg/g)보다 3배정도 상승하였다. 발효를 통해 꾸지뽕나무 잎과 열매의 최적의 추출조건을 확립하고 생리활성 물질 분석을 이용한 효능탐색 등을 진행하였다. 향후 꾸지뽕나무를 활용한 식품 소재개발 등 사업화에 기초적인 자료를 제공하여 임업인의 새로운 소득품목 육성에 기어코자 한다.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.375-382
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• 2008

A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.125-134
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• 2008

We implemented a system being able to suggest example sentences for multiple choice tests, considering the level of students. To build the system, we designed an automatic method for sentence generation, which made it possible to control the difficulty degree of questions. For the proper evaluation in the multiple choice tests, proper size of question pools is required. To satisfy this requirement, a system which can generate various and numerous questions and their example sentences in a fast way should be used. In this paper, we designed an automatic generation method using a linguistic resource called WordNet. For the automatic generation, firstly, we extracted keywords from the existing sentences with the morphological analysis and candidate terms with similar meaning to the keywords in Korean WordNet space are suggested. When suggesting candidate terms, we transformed the existing Korean WordNet scheme into a new scheme to construct the concept similarity matrix. The similarity degree between concepts can be ranged from 0, representing synonyms relationships, to 9, representing non-connected relationships. By using the degree, we can control the difficulty degree of newly generated questions. We used two methods for evaluating semantic similarity between two concepts. The first one is considering only the distance between two concepts and the second one additionally considers positions of two concepts in the Korean Wordnet space. With these methods, we can build a system which can help the instructors generate new questions and their example sentences with various contents and difficulty degree from existing sentences more easily.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.