• 기술혁신학회지
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• 제8권2호
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• pp.860-885
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• 2005

This study relates to develop a quantitative method through which promising technology-based business items can be discovered and selected. For this study, we utilized patent trend analysis, technology-industry concordance analysis, and keyword co-occurrence analysis of US patents. By analyzing patent trends and technology-industry concordance, we were able to find out the emerging industry trends : prevalence of bio industry, service industry, and B2C business. From the direct and co-occurrence analysis of newly discovered patent keywords in the year, 2000, 28 promising business item candidates were extracted. Finally, the promising item candidates were prioritized using 4 business attractiveness determinants; market size, product life cycle, degree of the technological innovation, and coincidence with the industry trends. This result implicates that reliable discovery and selection of promising technology-based business items can be performed by a quantitative, objective and low- cost process using knowledge discovery method from patent database instead of peer review.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.271-279
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• 2001

Sequential pattern discovery is one of main interests in web usage mining. the technique of sequential pattern discovery attempts to find inter-session patterns such that the presence of a set of items is followed by another item in a time-ordered set of server sessions. In this paper, a tree-based sequential pattern finding method is proposed in order to discover navigation patterns in server sessions. At each learning process, the suggested method learns about the navigation patterns per server session and summarized into the modified Rymon's tree.

• 산업공학
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• 제25권1호
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• pp.31-39
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• 2012

Discovering the suppliers capable of manufacturing the parts that satisfy buyer requirements via current online market places remains difficult due to semantic differences between what the suppliers can produce and what the buyer wants to acquire. One of the promising approaches to overcome the semantic difference is to adopt an ontology to describe the suppliers' manufacturing capabilities and the buyer requirements that range widely from manufacturing costs to eco-friendly design. Such an ontology dedicated to supplier discovery has yet to be developed. MSDL(Manufacturing Service Description Language) provides the basis for defining terms and their relationships in the ontology. Thus, the objective of this paper is to extend MSDL into a new ontology suitable for supplier discovery in mold manufacturing industry. In addition, a new ontology development method for supplier discovery will be proposed. Finally prototype demonstrations are provided to show a feasibility of the proposed ontology in mold manufacturing domains.

• Journal of Preventive Medicine and Public Health
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• 제49권2호
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• pp.129-133
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• 2016

Objectives: The systematic review (SR) is a research methodology that aims to synthesize related evidence. Updating previously conducted SRs is necessary when new evidence has been produced, but no consensus has yet emerged on the appropriate update methodology. The authors have developed a new SR update method called 'adaptive meta-analysis' (AMA) using the 'cited by', 'similar articles', and 'related articles' citation discovery tools in the PubMed and Scopus databases. This study evaluates the usefulness of these citation discovery tools for updating SRs. Methods: Lists were constructed by applying the citation discovery tools in the two databases to the articles analyzed by a published SR. The degree of overlap between the lists and distribution of excluded results were evaluated. Results: The articles ultimately selected for the SR update meta-analysis were found in the lists obtained from the 'cited by' and 'similar' tools in PubMed. Most of the selected articles appeared in both the 'cited by' lists in Scopus and PubMed. The Scopus 'related' tool did not identify the appropriate articles. Conclusions: The AMA, which involves using both citation discovery tools in PubMed, and optionally, the 'related' tool in Scopus, was found to be useful for updating an SR.

• 한국정보과학회논문지:정보통신
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• 제35권1호
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• pp.91-97
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• 2008

Ad hoc 네트워크에서 필요한 서비스를 사용하려면 먼저 원하는 서비스를 어떤 노드가 제공하는지, 또한 이런 서비스를 호출하려면 어떠한 방법을 사용해야 하는지 등의 정보를 알아내야 한다. 본 논문에서는 이러한 문제점들을 해결할 수 있는 DHT(Distributed Hash Table) 기반의 서비스 발견 프로토콜을 제안한다. 제안하는 프로토콜은 중앙 룩업 서버를 요구하지 않고 멀티캐스트나 플러딩을 사용하지 않기 때문에 확장성을 지닌다. 성능평가 결과, 제안하는 프로토콜은 확장성이 있고 기존의 서비스 탐색 프로토콜에 비해 나은 성능을 가짐을 알 수 있었다.

• Journal of Communications and Networks
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• 제16권2호
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• pp.238-244
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• 2014

A key technical challenge in TV white spaces is the efficient spectrum usage without interfering with primary users. This paper considers available spectrum discovery scheme using in-band sensing signal to support super Wi-Fi services effectively. The proposed scheme in this paper adopts non-contiguous orthogonal frequency-division multiplexing (NC-OFDM) to utilize the fragmented channel in TV white space due to microphones while this channel cannot be used in IEEE 802.11af. The proposed solution is a novel available spectrum discovery scheme by exploiting the advantages of a sensing signaling. The proposed method achieves considerable improvement in throughput and delay time. The proposed method can use more subcarriers for transmission by applying NC-OFDM in contrast with the conventional IEEE 802.11af standard. Moreover, the increased number of wireless microphones (WMs) hardly affects the throughput of the proposed method because our proposal only excludes some subcarriers used by WMs. Additionally, the proposed method can cut discovery time down to under 10 ms because it can find available channels in real time by exchanging sensing signal without interference to the WM.

• 한국조리학회지
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• 제23권2호
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• pp.126-134
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• 2017

본 연구의 목적은 우리나라 돈육 선물시장이 현물시장에 대해 가격발견기능을 제대로 수행하고 있는지를 알아보는 것이다. 이러한 분석을 위해 2011년 1월 5일부터 2012년 12월 28일까지 자료가 사용되었다. 연구의 주요 결과는 다음과 같다. 첫째, 돈육 선물과 현물가격은 장기적으로 균형관계가 존재하는 것으로 나타났다. 둘째, 오차수정모형의 오차수정계수를 이용한 분석에서는 돈육 선물시장이 현물시장에 대해 가격발견기능의 역할을 주도적으로 수행하는 것으로 나타났다. 셋째, Gonzalo와 Granger(1995)와 Hasbrouck(1995)가 제시한 방법론에 따라 GG 정보비율과 Hasbrouck 정보비율 분석에 의하면 우리나라의 돈육 선물시장은 현물시장에 대해 가격발견에 있어서 강하지는 않지만, 어느 정도 우월한 역할을 하고 있는 것으로 나타났다.

• Mass Spectrometry Letters
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• 제4권3호
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• pp.47-50
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• 2013

An ultra-fast generic LC-MS/MS method was developed for high-throughput quantification of discovery pharmacokinetic (PK) samples and its reliability was verified. The method involves a simple protein precipitation for sample preparation and the analysis by ultra-fast generic LC-MS/MS with the ballistic gradient program and selected reaction monitoring (SRM) mode. Approximately 290 new chemical entities (NCEs) (over 10,000 samples) from 5 therapeutic programs were analyzed. The calibration curves showed good linearity in the concentration range of 1, 2 or 5 to 2000 ng/mL. No significant ion suppression was observed in the elution region of all the NCEs. When approximately 300 plasma samples were continuously analyzed, the peak area of internal standard was constant and reproducible. In the repeated analysis of samples, the plasma concentrations and the area under the curve (AUC) were consistent with the results from the first analysis. These results showed that the present ultra-fast generic LC-MS/MS method is reliable in terms of selectivity, sensitivity, and reproducibility and could be useful for high-throughput quantification and other bioanalysis in drug discovery.

• 한국수학사학회지
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• 제22권3호
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• pp.255-272
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• 2009

본 연구는 20세기 미국 대학의 수학 교육현장에서 큰 영향을 미쳐온 R. L. 무어 교수법이 학부 수학교육 과정에 효과적으로 적용되기 위해 어떻게 연구되고 변형되어왔는지를 지켜보면서, 교육학적 논의를 통해 우리나라 대학교육에 시사하는 점을 논의하고자 한다.

• Journal of Information Processing Systems
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• 제17권1호
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.