• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.154-165
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• 2012

In this paper, I examine the history of split screens, primarily seek to explain types of them, and explore the narrative meaning of each type in feature films. In short, I try to categorize the types of split screens and present a figure of them according to events and characters, focusing the relations between/among simultaneous images and narrative meanings. In addition, I assert that split screen have altered some methods of filmic storytelling and the ontology of screen. Story lines no longer have to be linear and the screen need not to remain a window through which we can see another world. The screen has come to be a canvas upon which several images can be arranged for narrative purposes.

• Journal of the Korean Society of Earth Science Education
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• v.1 no.1
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• pp.111-118
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• 2008

This study is aimed at analyzing earth conception the nine pre service teachers who are majoring in earth science education and classifying a special feature from the ontological categories. Open ended questionnaires and semi structured interviews which meant to contribute to identifying ontological categories of concepts involving study area were designed. Pre service teachers' ontological category about earth conception most showed to dynamic and proto process. In the results show that many pre service teachers recognize simply the conception to a material, a condition and a conversion of the state changing. Most of the pre service teachers show their intermediate understanding level about the earth inner construction according to the analyzed results of the drawing tasks and interviews. The main alternative conceptions show them through a definition of the plate, a wording definition between lithosphere and asthenosphere, a feature of the plate boundary, a heat convection in the earth inner, the earth inner heat source, the earth inner structure, a physical feature of the mantle.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.337-344
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• 2006

In this paper, we describe the design and the implementation of word clustering system using a definition of an entry word in the dictionary, called a dictionary definition. Generally word clustering needs various features like words and the performance of a system for the word clustering depends on using some kinds of features. Dictionary definition describes the meaning of an entry in detail, but words in the dictionary definition are implicative or abstractive, and then its length is not long. The word clustering using only features extracted from the dictionary definition results in a lots of small-size clusters. In order to make large-size clusters and improve the performance, we need to transform the features into more general words with keeping the original meaning of the dictionary definition as intact as possible. In this paper, we propose two methods for extending the dictionary definition using ontology. One is to extend the dictionary definition to parent words on the ontology and the other is to extend the dictionary definition to some words in fixed depth from the root of the ontology. Through our experiments, we have observed that the proposed systems outperform that without extending features, and the latter's extending method overtakes the former's extending method in performance. We have also observed that verbs are very useful in extending features in the case of word clustering.

• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.253-266
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• 2018

This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.348-353
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• 2008

이미지의 사용이 증가함에 따라 이미지 중 사용자가 원하는 이미지를 효율적으로 검색하기 위한 방법들이 연구되어 왔다. 본 논문에서는 질의 이미지를 분석하여 이미지 특징(feature)을 추출한 후 이미지 특징에 대한 유사도 평가를 통한 이미지 검색 및 온톨로지를 기반으로 검색된 이미지들과 유사하다고 판단된 이미지와 그러한 이미지들의 의미적 정보를 추출하는 방법을 제안한다. 제안된 시스템은 질의 이미지에서 색상, 질감, 모양 등의 특징을 추출하여 유사도 평가를 통해 검색된 이미지를 제공하고, 내용기반 이미지 검색 방식을 통해 이미지를 검색하고, 온톨로지를 이용해 이미지의 의미적 정보를 추출하여 사용자에게 이미지와 관련된 의미적 정보를 제공한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.276-279
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• 2010

소프트웨어 제품 라인 개발 패러다임은 관련 제품들 사이의 공통점과 차이점을 이용해 보다 전략적인 재사용을 가능하게 함으로써 소프트웨어 개발 생산성을 높여 주는 개발 방법론이다. 공통점과 차이점을 분석하고 모델링하기 위해 가장 중요한 모델이 특성 모델이다. 특성 모델은 규모가 커짐에 따라 오류를 포함할 가능성이 커지며 이를 검증하기 위한 자동화된 도구가 필요하다. 본 논문에서는 온톨로지를 자바 언어로 구현 가능하게 해주는 Protege API, OWL기반의 시맨틱 웹 규칙 언어인 SWRL, 규칙 추론 엔진인 Pellet Reasoner 등의 기술을 이용한 특성 모델 검증 도구를 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.409-414
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• 2013

With the increase of multimedia information such as images, researches have been realized on how to extract the high-level semantic information from low-level visual information, and a variety of techniques have been proposed to generate this information automatically. However, most of these technologies extract the semantic information between single images, it's difficult to extract semantic information when a combination of multiple objects within the image. In this paper, we extract the visual features of objects within the image and training images stored in the DB and the features of each object are defined by measuring the similarity. Using ontology reasoner, each object feature within images infers the semantic information by positional relation and associative relation. With this, it's possible to infer semantic information between objects within images, we proposed a method for inferring more complicated and a variety of high-level semantic information.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.73-79
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• 2010

Emotion intelligence computing is able to processing of human emotion through it's studying and adaptation. Also, Be able more efficient to interaction of human and computer. As sight and hearing, music & image is constitute of short time and continue for long. Cause to success marketing, understand-translate of humanity emotion. In this paper, Be design of check system that matched music and image by user emotion keyword(irritability, gloom, calmness, joy). Suggested system is definition by 4 stage situations. Then, Using music & image and emotion ontology to retrieval normalized music & image. Also, A sampling of image peculiarity information and similarity measurement is able to get wanted result. At the same time, Matched on one space through pared correspondence analysis and factor analysis for classify image emotion recognition information. Experimentation findings, Suggest system was show 82.4% matching rate about 4 stage emotion condition.

• Korean Journal of Ichthyology
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• v.32 no.3
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• pp.117-129
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• 2020

The body color pattern in fish is a distinctive feature for species identification. The blass bloched rockfish Sebastes pachycephalus is a commercially important marine fish species, distributed in the central and southern parts of Korea and south Hokkaido of Japan. It has a morphological feature divided into four subspecies according to with or lacking distinct spots on the body surface, and to the location of markings on the body surface. However, the genetic basis of body color pattern of S. pachycephalus is still unknown. Thus we analyzed the transcriptome of S. pachycephalus skin samples using RNA-seq analysis to investigate functional genes related to body color patterns. The experimental skin samples were prepared by classified into 'Wild type' (lacking distinct spots and markings) and 'Color type' (with distinct spots and marking). Two skin sample transcriptomes were compared pairwise and the results revealed that were 164 differentially expressed unigenes in the skin samples of 'Wild type' and 'Color type'. Gene Ontology analysis of 164 differentially expressed unigenes showed that these genes were included in the functional group of molecular function (2 genes), biological process (46 genes), and cellular component (6 genes). There were several genes that body color type skin specific expression and the genes were CTL (Galactose-specific lectin nattectin), CUL1 (Cullin-1), CMAS (N-acylneuraminate cytidylyltransferase), NMRK2 (Nicotinamide riboside kinase 2), ALOXE3 (Hydroperoxide isomerase ALOXE3), SLC4A7 (sodium bicarbonate cotransporter 3). Our study is the first attempt to search for functional genes involved in the formation of body color patterns in S. pachycephalus. The differentially expressed unigenes obtained in this study can be used as candidate genes for functional gene study related to body coloration of fish.