• ETRI Journal
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• 제21권1호
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• pp.55-71
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• 1999

Recently, the increased handling of on-line standards information has emerged as an important feature of information and communications technology (ICT) standardization. In order to meet market needs for on-time standards deployment, most standards organizations are actively seeking more efficient ways of standardization using electronic means in order to accelerate the standards making process. This paper suggests a virtual standard development environment designed for standards developers to carry out their standards-related activities on-line. In this paper, we outline a conceptual model of a concurrent standardization process and describe the design and implementation of an Extranet-based network system called standards information cooperative network (SICN). The system was created with a view to fostering faster standards development with functionalities such as a virtual management of networked standards developers, collaboration support tools, a workflow-based electronic signature system, and dynamic links for ready retrieval of standards information stored in a database. We conclude this paper with an introduction to the concept of a virtual standards development organization (VSDO) that supports all the features needed by the relevant standards making bodies to carry out their activities in a dynamic on-line environment.

• 한국문헌정보학회지
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• 제35권3호
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• pp.17-34
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• 2001

인터넷 서점에서 이용자를 위한 정보자료의 효율적인 조직화는 매우 중요하다. 그러므로 주제접근을 용이하게 하고 검색 효율성을 높이는 도구로서 분류체계에 대한 관심을 가져야할 시점이다. 본 연구에서는 국내외 인터넷 서점의 분류체계의 대분류 항목 및 접근 방법을 구조적 측면에서 조사하고 이에 대한 비교 분석을 통해 인터넷 서점에서 보다 효과적인 주제별 분류체계 설계 방안에 관해 살펴보았다. 이를 위하여 현재 국내외에서 활발하게 운영 중인 인터넷 서점 9개를 선정하여 주제별 분류의 측면에 중점을 두고 조사 분석하였다. 끝으로 본 연구 결과를 바탕으로 이용자 중심의 효과적인 주제별 검색 기능을 제공할 수 있는 인터넷 서점의 효과적인 주제별 분류체계의 모형을 제안하였다.

• Genomics & Informatics
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• 제11권4호
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• pp.289-291
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• 2013

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The molecular understanding of HPV proteins has significant connotation for understanding their intrusion in the host and designing novel protein vaccines and anti-viral agents, etc. Genomic, proteomic, structural, and disease-related information on HPV is available on the web; yet, with trivial annotations and more so, it is not well customized for data analysis, host-pathogen interaction, strain-disease association, drug designing, and sequence analysis, etc. We attempted to design an online reserve with comprehensive information on HPV for the end users desiring the same. The Human Papillomavirus Proteome Database (hpvPDB) domiciles proteomic and genomic information on 150 HPV strains sequenced to date. Simultaneous easy expandability and retrieval of the strain-specific data, with a provision for sequence analysis and exploration potential of predicted structures, and easy access for curation and annotation through a range of search options at one platform are a few of its important features. Affluent information in this reserve could be of help for researchers involved in structural virology, cancer research, drug discovery, and vaccine design.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.178-184
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• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• 한국문헌정보학회지
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• 제31권2호
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• pp.79-93
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• 1997

동일 분류항목 내에 분류되는 저작들을 개별화하여 배열과 검색을 용이하게 하기 위해 사용되는 도서기호는 크게 입수순기호, 저자기호, 그리고 연대순기호로 나누어 볼 수 있다. 현대의 매우 빠른 학문 발전속도는 최신의 정보가 최상의 가치를 갖도록 만들었고, 이용자들의 이용행태 또한 최신의 자료에 집중되고 있다. 이러한 정보의 가치기준과 이용행태의 변화에 따라 도서관에서는 최신의 자료를 오래된 것과 구분하여 모아줄 필요가 발생하였다. 본고에서는 이러한 요구를 반영하여 고안된 「새 연대순 도서기호법」이 널리 채용되게 하고자 하는 목적으로 그 특징과 기호구성을 살펴보았고, 일부 자모순 도서기호를 적용토록 지시된 항목의 성격에 대해 규명하였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(C)
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• pp.62-65
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• 2010

Image annotations allow users to access a large image database with textual queries. But since the surrounding text of Web images is generally noisy. an efficient image annotation and retrieval system is highly desired. which requires effective image search techniques. Data mining techniques can be adopted to de-noise and figure out salient terms or phrases from the search results. Clustering algorithms make it possible to represent visual features of images with finite symbols. Annotationbased image search engines can obtains thousands of images for a given query; but their results also consist of visually noise. In this paper. we present a new algorithm Double-Circles that allows a user to remove noise results and characterize more precise representative annotations. We demonstrate our approach on images collected from Flickr image search. Experiments conducted on real Web images show the effectiveness and efficiency of the proposed model.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1213-1228
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• 2017

The pitch tracking of music has been researched for several decades. Several possible improvements are available for creating a good t-distribution, using the instantaneous robust algorithm for pitch tracking framework to perfectly detect pitch. This article shows how to detect the pitch of music utilizing an improved detection method which applies a statistical method; this approach uses a pitch track, or a sequence of frequency bin numbers. This sequence is used to create an index that offers useful features for comparing similar songs. The pitch frequency spectrum is extracted using a modified instantaneous robust algorithm for pitch tracking (IRAPT) as a base combined with the statistical method. The pitch detection algorithm was implemented, and the percentage of performance matching in Thai classical music was assessed in order to test the accuracy of the algorithm. We used the longest common subsequence to compare the similarities in pitch sequence alignments in the music. The experimental results of this research show that the accuracy of retrieval of Thai classical music using the t-distribution of instantaneous robust algorithm for pitch tracking (t-IRAPT) is 99.01%, and is in the top five ranking, with the shortest query sample being five seconds long.

• Advances in aircraft and spacecraft science
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• 제7권3호
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• pp.271-290
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• 2020

The paper describes the analysis of deployment strategies and trajectories design suitable for executing the inspection of an operative spacecraft in orbit through re-usable CubeSats. Similar missions have been though indeed, and one mission recently flew from the International Space Station. However, it is important to underline that the inspection of an operative spacecraft in orbit features some peculiar characteristics which have not been demonstrated by any mission flown to date. The most critical aspects of the CubeSat inspection mission stem from safety issues and technology availability in the following areas: trajectory design and motion control of the inspector relative to the target, communications architecture, deployment and retrieval of the inspector, and observation needs. The objectives of the present study are 1) the identification of requirements applicable to the deployment of a nanosatellite from the mother-craft, which is also the subject of the inspection, and 2) the identification of solutions for the trajectories to be flown along the mission phases. The mission for the in-situ observation of Space Rider is proposed as reference case, but the conclusions are applicable to other targets such as the ISS, and they might also be useful for missions targeted at debris inspection.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.45-52
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• 2022

With the development of artificial intelligence analysis methods, especially machine learning, various fields are widely expanding their application ranges. However, in the case of classical music, there still remain some difficulties in applying machine learning techniques. Genre classification or music recommendation systems generated by deep learning algorithms are actively used in general music, but not in classical music. In this paper, we attempted to classify opera among classical music. To this end, an experiment was conducted to determine which criteria are most suitable among, composer, period of composition, and emotional atmosphere, which are the basic features of music. To generate emotional labels, we adopted zero-shot classification with four basic emotions, 'happiness', 'sadness', 'anger', and 'fear.' After embedding the opera libretto with the doc2vec processing model, the optimal number of clusters is computed based on the result of the elbow method. Decided four centroids are then adopted in k-means clustering to classify unsupervised libretto datasets. We were able to get optimized clustering based on the result of adjusted rand index scores. With these results, we compared them with notated variables of music. As a result, it was confirmed that the four clusterings calculated by machine after training were most similar to the grouping result by period. Additionally, we were able to verify that the emotional similarity between composer and period did not appear significantly. At the end of the study, by knowing the period is the right criteria, we hope that it makes easier for music listeners to find music that suits their tastes.

• 한국컴퓨터정보학회논문지
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• 제14권3호
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• pp.51-56
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• 2009

언어에서 명사 및 키워드 추출은 정보처리에서 매우 필수적인 요소이다. 하지만, 한국어 정보처리에서 명사 추출과 키워드 추출은 아직도 많은 문제점을 안고 있다. 본 논문에서는 명사의 등장 특성을 고려한 효율적인 명사 추출 방법에 대해서 제시하였다. 제시한 방법은 대량의 문서를 빠르게 처리해야 하는 정보 검색과 같은 분야에서 유용하게 쓰일 수 있다. 또한 대량의 문제를 자동으로 분류하기 위하여 비감독 학습 기법에 의해 카테고리별 키워드를 구성하기 위한 방법을 제안하였다. 제안된 방법은 감독 학습 기법의 키워드 추출기법 중에서 우수하다고 알려진 X2기법과 DF 기법보다 우수한 분류 성능을 보였다.