• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.2
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• pp.230-241
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• 1995

The purpose of this study was 1) to investigate the effect of male clothing type and facial attractiveness on the subjects' inferences of occupation for the wearers, 2) to investigate the effect of male clothing type on the inferences of occupational characteristics. The stimuli were composed of 24 color photographs which were made of 6 types of clothing and 18 wearers who were made of 3 levels of facial attractiveness in combination with 6 types of clothing. The subjects were 288 male and 288 female university students. The subjects chose an occupation among 19 occupations presented for 6 types of clothing and the wearers. Also the subjects' inferences of occupational characteristics for the clothing were measured by semantic\ulcornerdiffenential scales. The results were as follows: 1) As a whole, the infered occupation for each of the clothing types was consistent with the expected occupations in this study. "Therefore there were stereotypes about male clothing type. At the same time, the halo effect of facial attractiveness appeared when subjects infered wearer's occupation. 2) The subjects' responses to the semantic-differential scales about 6 types of clothing were factor analyzed to identify the underlying constructs of occupational characteristics. At the result, 4 factors were emerged. The first factor was interpreted to Apperance/ Ability, the second, Indi~iduality, the third, Naivety, and the fourth, Dominancy. 3) The male clothing type influenced on the 3 factors except the Dominancy factor.nancy factor.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.23-40
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• 2002

This study is to examine brain regions that are involved in picture encoding in normal adults using fMRI methods. In Scan 1, the picture encoding was studied during a semantic categorization task in comparison with word. In Scan 2 task type effects were studied both during a picture naming task and during a semantic categorization task with pictures. Subjects were asked to make decision either by pressing a mouse button (Scan 1) or by responding subvocally (naming or saying yes/no) (Scan 2). Regardless of stimulus type, left prefrontal, bilateral occipital, and parietal activations were observed during semantic processing in comparison with fixation baseline. Processing of word stimulus relative to picture resulted in activations in prefrontal and parieto-temporal regions in the left side while that of picture stimulus relative to word resultd in activations in bilateral extrastriatal visual cortices and parahippocampal regions. In spite of the same task demands, stimulus-specific information processings were involved and mediated by different neural substrates; the word encoding was associated with more semantic/lexical processings than pictures and the picture processing associated with more perceptual and novelty related information processings than word. Activations of dorsal part of inferior prefrontal region, i.e., Broca's areas were found both during the picture naming and during the semantic tasks subvocally performed Especially, during the picture naming task, greater occipital activations were found bilaterally relative to the semantic categorization task. indicating a possibility that greater and higher visual processing was involved in retrieving the name referred by picture stimuli.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.32-39
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• 2009

Semantically-operated services, which is different from Web services or semantic Web services with semantic markup, can be defined as the services providing search function or reasoning function using ontologies. It performs a pre-defined task by exploiting URI, ontology classes, and ontology properties. This study introduces a method for pipelining semantically-operated services based on a semantic broker which refers to ontologies and service description stored in a service manager and invokes by user constraints. The constraints consist of input instances, an output class, a visualization type, service names, and properties. This method provides automatically-generated service pipelines including composit services and a simple workflow to the user. The pipelines provided by the semantic broker can be executed in a fully-automatic manner to find a set of meaningful semantic pipelines. After all, this study would epochally contribute to develop a portal service by ways of supporting human service planners who want to find specific composit services pipelined from distributed semantically-operated services.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.267-272
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• 2007

One of the roles of the Semantic Web services is to execute dynamic intra-organizational services including the integration and interoperation of business processes. Since different organizations design their processes differently, the retrieval of similar semantic business processes is necessary in order to support inter-organizational collaborations. Most approaches for finding services that have certain features and support certain business processes have relied on some type of logical reasoning and exact matching. This paper presents our approach of using imprecise matching fur expanding results from an exact matching engine to query the OWL MIT Process Handbook. In order to use the MIT Process Handbook for process retrieval experiments, we had to export it into an OWL-based format. We model the Process Handbook meta-model in OWL and export the processes in the Handbook as instances of the meta-model. Next, we need to find a sizable number of queries and their corresponding correct answers in the Process Handbook. We devise diverse similarity algorithms based on values of process attributes and structures of business processes. We perform retrieval experiments to compare the performance of the devised similarity algorithms.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1157-1159
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• 1987

A syntactic and semantic approach is used to make type classification based on feature points(whorl, delta, core) and the shape of flow line around feature points. The image is divided into 30 by 30 subregions which are represented in the average direction and 4-tuple direction component. Next the relaxation process with singularity detection and convergency checking is performed. A set of semantic languages is used to describe the major flow line around the extracted feature points. LR(1) parser and feature transfer function are used to recognize the coded flow patterns. The 72 fingerprint impressions is used to test the proposed approach and the rate of the classification is about 93 percentages.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.255-257
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• 2011

본 연구에서는 각종 웹사이트와 이메일을 통해 전달되는 회의공지에 포함된 회의장소를 나타내는 문자열로부터 실제 위치를 추정하는 시스템을 설계 및 구현하였다. 직접 구현한 NER과 Relation-type Classification 모듈을 사용하였으며, 장소에 대한 모델은 기존의 지리정보시스템들과의 상호 운용성을 위하여 OpenStreetMap[6]과 Geonames[7]의 데이터 구조를 참조하여 설계되었고, 실제 위치를 구하기 위하여 내부자원 외에도, 각종 오픈API들을 외부자원으로 활용하였다.

• Language and Information
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• v.2 no.1
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• pp.157-176
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• 1998

This paper claims that beneficiary adjuncts are best analyzed as involving external predication in a version of grammatical framework called Head-driven Phrase Structure Grammar. This paper also claims that verbal catefories need to include the attribute INDEX among their semantic components in order to account for the external predication proposed in this paper. This paper distinguishes between recipient and beneficiary reles and assumes that the former is a semantic argument of a verb-type relation and that the latter is an adjunct which makes a semantic contribution as a modifier. This approach achives a unified analysis of modification phenomena of nominal and verbal categories and it can also accomodate Parson's(1990) idea that a verbal category denotes a set of events, not just an event.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.150-157
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• 2014

This thesis intends to grasp the degree of utilization of visual images by understanding the relational properties between picture and letter and considering the children as users, through the analysis of currently published books of English vocabulary for children. Accordingly, the types of picture used in the books of English vocabulary for children, the degree of utilization of picture, combination types of picture and letter, and semantic consistency of picture and letter are reviewed. As a result of analysis, the degree of utilization of picture is high in general, in order of illustration, cartoon, and the mix of illustration and cartoon. In the combination form of picture and letter, the degree of utilization appears in order of picture plus vocabulary, letters without illustration, and pictorial symbol. In particular, the higher semantic consistency of picture and letter, it is effective in learning, however, semantic consistency is low, generally. Pictorial symbol type shows the frequency of the highest combination type in the five groups of higher semantic consistency. In conclusion, the presented types of picture and letter, shown in the currently published books of English vocabulary for children, are similar types by the publishing companies, thus, effective design research should be required based on diverse levels of children.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1239-1249
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• 2018

Optical remote sensing sensors provide visually more familiar images than radar images. However, it is difficult to discriminate sea ice types in optical images using spectral information based machine learning algorithms. This study addresses two topics. First, we propose a semantic segmentation which is a part of the state-of-the-art deep learning algorithms to identify ice types by learning hierarchical and spatial features of sea ice. Second, we propose a new approach by combining of semi-supervised and active learning to obtain accurate and meaningful labels from unlabeled or unseen images to improve the performance of supervised classification for multiple images. Therefore, we successfully added new labels from unlabeled data to automatically update the semantic segmentation model. This should be noted that an operational system to generate ice type products from optical remote sensing data may be possible in the near future.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.11-18
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• 2016

Linked Data is a web standard data definition method devised to connect, expand resources with a standardized type. Linked Data built in various areas expands existing knowledge through an open data cloud like LOD(Linked Open Data). A project to link and service existing knowledge through LOD is under way worldwide. However, LOD project in domestic is being participated in a specific field to the level of research. In this paper, we suggests a method to build the area of technical knowledge like legislations in type of Linked Data, and distribute such Linked Data built to LOD. The construction method suggested by this paper divides knowledge of legislations in structural, semantic, and integrated perspective, and builds each of them by converting to Linked Data according to the perspective. Also, such built Linked Legal Data prepares to link knowledge in a standardized type by distributing them onto LOD. Built Linked Legal Data are equipped with schema for link service in various types, and give help increase understand the access type to existing legal information.