• 한국수학교육학회지시리즈A:수학교육
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• 제53권2호
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• pp.291-312
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• 2014

This study has to do with creative product in mathematics. We analyze Taylor's creative product according to a different developmental level of creativity, Taylor's creative product inventory, Besemer & Treffinger's creative products analysis matrix, O'Quin & Besemer's creative products semantic scale(CPSS) etc. The purpose of this study is to make creative products semantic scale in mathematics. O'Quin & Besemer's CPSS consists of 55 items, bipolar adjective checklist. We confirm that O'Quin & Besemer's CPSS is not fit to use for mathematics creative products. So we develop Creative Product Semantic Scale in Mathematics(MCPSS) which consists of 33 items, bipolar adjective checklist. Our result will provide convenience to mathematics teacher who guides a student make a creative product.

• ETRI Journal
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• 제29권5호
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• pp.545-558
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• 2007

This paper presents an efficient semantic service discovery scheme called UbiSearch for a large-scale ubiquitous computing environment. A semantic service discovery network in the semantic vector space is proposed where services that are semantically close to each other are mapped to nearby positions so that the similar services are registered in a cluster of resolvers. Using this mapping technique, the search space for a query is efficiently confined within a minimized cluster region while maintaining high accuracy in comparison to the centralized scheme. The proposed semantic service discovery network provides a number of novel features to evenly distribute service indexes to the resolvers and reduce the number of resolvers to visit. Our simulation study shows that UbiSearch provides good semantic searchability as compared to the centralized indexing system. At the same time, it supports scalable semantic queries with low communication overhead, balanced load distribution among resolvers for service registration and query processing, and personalized semantic matching.

• 한국언어정보학회지:언어와정보
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• 제15권2호
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• pp.23-45
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• 2011

This paper proposes a statistical-based linguistic methodology for automatic mapping between large-scale heterogeneous languages resources for NLP applications in general. As a particular case, it treats automatic mapping between two large-scale heterogeneous Korean language resources: Sejong Semantic Classes (SJSC) in the Sejong Electronic Dictionary (SJD) and nouns in KorLex. KorLex is a large-scale Korean WordNet, but it lacks syntactic information. SJD contains refined semantic-syntactic information, with semantic labels depending on SJSC, but the list of its entry words is much smaller than that of KorLex. The goal of our study is to build a rich language resource by integrating useful information within SJD into KorLex. In this paper, we use both linguistic and statistical methods for constructing an automatic mapping methodology. The linguistic aspect of the methodology focuses on the following three linguistic clues: monosemy/polysemy of word forms, instances (example words), and semantically related words. The statistical aspect of the methodology uses the three statistical formulae ${\chi}^2$, Mutual Information and Information Gain to obtain candidate synsets. Compared with the performance of manual mapping, the automatic mapping based on our proposed statistical linguistic methods shows good performance rates in terms of correctness, specifically giving recall 0.838, precision 0.718, and F1 0.774.

• 한국실내디자인학회논문집
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• 제20권6호
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• pp.192-199
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• 2011

The purposes of this study are to present the criteria for a sensibility rating scale for measuring the general women's perception of museums' spatial environment, through an empirical analysis; and to clarify the characteristics of the presented rating scale in terms of each rating element and factor. For this study, a survey was conducted during August 19 - September 16, 2010, and a total of 342 museum visitors participated in the survey. A sensibility rating scale used for the survey consisted of a total of 32 adjectives selected from a literature review of previous studies. To specify the dimensions of semantic space using the semantic adjectives, words with opposite meanings were analyzed with the semantic differential technique developed by Osgood et al. Using SPSS, a reliability analysis, factor analysis were conducted on the data obtained from the survey. The results of this study can be summarized as follows: According to the women's perception of museums' spatial environment, six factors were found from the 25 semantic ratings of the Museum. The summarized criteria were: 'aesthetic', 'pleasant', 'valuable', 'function', 'affinity', and 'material.' The derived criteria were verified through an empirical test using emotional adjectives. In the coming years, the results of this study will serve as valuable data for constructing a sensibility rating scale for evaluating spatial environments of museums.

• 정보과학회 논문지
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• 제42권1호
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• pp.54-67
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• 2015

최근 사물인터넷 환경에서는 발생하는 센서데이터의 가치와 데이터의 상호운용성을 증진시키기 위해 시맨틱웹 기술과의 접목에 대한 연구가 활발히 진행되고 있다. 이를 위해서는 센서데이터와 서비스 도메인 지식의 융합을 위한 센서데이터의 시맨틱화는 필수적이다. 하지만 기존의 시맨틱 변환기술은 정적인 메타데이터를 시맨틱 데이터(RDF)로 변환하는 기술이며, 이는 사물인터넷 환경의 실시간성, 대용량성의 특징을 제대로 처리할 수 없는 실정이다. 따라서 본 논문에서는 사물인터넷 환경에서 발생하는 대용량 스트리밍 센서데이터의 실시간 병렬처리를 통해 시맨틱 데이터로 변환하는 기법을 제시한다. 본 기법에서는 시맨틱 변환을 위한 변환규칙을 정의하고, 정의된 변환규칙과 온톨로지 기반 센서 모델을 통해 실시간 병렬로 센서데이터를 시맨틱 변환하여 시맨틱 레파지토리에 저장한다. 성능향상을 위해 빅데이터 실시간 분석 프레임워크인 아파치 스톰을 이용하여, 각 변환작업을 병렬로 처리한다. 이를 위한 시스템을 구현하고, 대용량 스트리밍 센서데이터인 기상청 AWS 관측데이터를 이용하여 제시된 기법에 대한 성능평가를 진행하여, 본 논문에서 제시된 기법을 입증한다.

• 한국실내디자인학회논문집
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• 제19권6호
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• pp.75-82
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• 2010

The purposes of this study are to present the criteria for a sensibility rating scale for measuring the general public's perception of museums' spatial environment, particularly lobby space, through an empirical analysis; and to clarify the characteristics of the presented rating scale in terms of each rating element and factor. For this study, a survey was conducted during September 11-17, 2010, and a total of 370 museum visitors participated in the survey. A sensibility rating scale used for the survey consisted of a total of 32 adjectives selected from a literature review of previous studies. To specify the dimensions of semantic space using the semantic adjectives, words with opposite meanings were analyzed with the semantic differential technique developed by Osgood et al. Using SPSS, a reliability analysis, factor analysis, and cluster analysis were conducted on the data obtained from the survey. The results of this study can be summarized as follows: According to the general public's perception of museum lobbies, five factors were found from the 19 semantic ratings of the Gyeonggido Museum of Modern Art and the 20 semantic ratings of the Seoul Museum of Art, respectively. In the case of Gyeonggido Museum of Modern Art, three additional semantic words of 'orderly', 'open', and 'original', which did not appear in the case of Seoul Museum of Art, were discovered. In the case of Seoul Museum of Art, more detailed semantic words such as 'restrained', 'ordinary', 'concrete', and 'intellectual (rational)' were obtained. Five semantic elements, which describe the two museums, were: Feelings of 'pleasantness', 'value, 'usage', 'aesthetics', and 'materials'. According to a comparative analysis of the two lobby spaces in terms of semantic rating elements, Gyeonggido Museum of Modern Art was perceived to be an orderly, original, open, soft, and female-like space, whereas Seoul Museum of Art was perceived to be aesthetic, restrained, concrete, realistic, intellectual and rational. In the coming years, the results of this study will serve as valuable data for constructing a sensibility rating scale for evaluating spatial environments of museums.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.3942-3961
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• 2019

Recently, the models of deep super-resolution networks can successfully learn the non-linear mapping from the low-resolution inputs to high-resolution outputs. However, for large scaling factors, this approach has difficulties in learning the relation of low-resolution to high-resolution images, which lead to the poor restoration. In this paper, we propose Stage Generative Adversarial Networks (Stage-GAN) with semantic maps for image super-resolution (SR) in large scaling factors. We decompose the task of image super-resolution into a novel semantic map based reconstruction and refinement process. In the initial stage, the semantic maps based on the given low-resolution images can be generated by Stage-0 GAN. In the next stage, the generated semantic maps from Stage-0 and corresponding low-resolution images can be used to yield high-resolution images by Stage-1 GAN. In order to remove the reconstruction artifacts and blurs for high-resolution images, Stage-2 GAN based post-processing module is proposed in the last stage, which can reconstruct high-resolution images with photo-realistic details. Extensive experiments and comparisons with other SR methods demonstrate that our proposed method can restore photo-realistic images with visual improvements. For scale factor ${\times}8$, our method performs favorably against other methods in terms of gradients similarity.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.321-329
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• 2007

This paper reports on the application of network analysis approaches to investigate the characteristics of graph representations of Japanese word associations. Two semantic networks are constructed from two separate Japanese word association databases. The basic statistical features of the networks indicate that they have scale-free and small-world properties and that they exhibit hierarchical organization. A graph clustering method is also applied to the networks with the objective of generating hierarchical structures within the semantic networks. The method is shown to be an efficient tool for analyzing large-scale structures within corpora. As a utilization of the network clustering results, we briefly introduce two web-based applications: the first is a search system that highlights various possible relations between words according to association type, while the second is to present the hierarchical architecture of a semantic network. The systems realize dynamic representations of network structures based on the relationships between words and concepts.

• 품질경영학회지
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• 제32권3호
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• pp.182-197
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• 2004

In this paper we propose a new method of evaluating customers' service quality using triangle fuzzy numbers and semantic differential scale. These two parameters are useful for quantifying the customers' linguistic variables and subjective judgements. We define the Service Quality(SQ) as the ratio of the expected and perceived service and address the Agreement Rate(AR) calculated from the hamming distance in order to define the Service Rate(SR) as the geometric mean of the SQ and AR. Using the SR in the analysis of service attributes provides more appropriate to measure the customers' service quality and to establish a creative service policy for competitive service quality improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2761-2781
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• 2018

With the continuous growth of data size and the use of compression technology, data reduction has great research value and practical significance. Aiming at the shortcomings of the existing semantic compression algorithm, this paper is based on the analysis of ItCompress algorithm, and designs a method of bidirectional order selection based on interval partitioning, which named An Optimized Iterative Semantic Compression Algorithm (Optimized ItCompress Algorithm). In order to further improve the speed of the algorithm, we propose a parallel optimization iterative semantic compression algorithm using GPU (POICAG) and an optimized iterative semantic compression algorithm using Spark (DOICAS). A lot of valid experiments are carried out on four kinds of datasets, which fully verified the efficiency of the proposed algorithm.