• Title/Summary/Keyword: pattern discovery

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Discovery Methods of Similar Web Service Operations by Learning Ontologies (온톨로지 학습에 의한 유사 웹 서비스 오퍼레이션 발견 방법)

  • Lee, Yong-Ju
    • The KIPS Transactions:PartD
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    • v.18D no.2
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    • pp.133-142
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    • 2011
  • To ensure the successful employment of semantic web services, it is essential that they rely on the use of high quality ontologies. However, building such ontologies is difficult and costly, thus hampering web service deployment. This study automatically builds ontologies from WSDL documents and their underlying semantics, and presents discovery methods of similar web service operations using these ontologies. The key ingredient is techniques that cluster parameters in the collection of web services into semantically meaningful concepts, and capture the hierarchical relationships between the words contained in the tag. We implement an operation retrieval system for web services. This system finds out a ranked set of similar operations using a novel similarity measurement method, and selects the most optimal operation which satisfies user's requirements. It can be directly used for the web services composition.

The Modeling of a Systematic Collection Development and Retrieval to Foreign Government Information Resources on the Internet (외국정부정보에 대한 정보원개발과 검색모형 연구 - 메타사이트와 메타DB개발에 대하여 -)

  • Ahn, In-Ja
    • Journal of the Korean Society for Library and Information Science
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    • v.34 no.2
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    • pp.211-232
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    • 2000
  • The acquisition of foreign government documents by exchange or gift is problematic in the electronic government era because the pattern of distributing system is changed. The alternatives for the collection development are developing the meta-site and establishing the subject gateways for the foreign government information as the resource discovery tools. The anchor and link functions of the AltaVista are used to evaluate a meta-site. The Scout Project Isaac is suggested as the model of interoperating resource discovery services for the geographically distributed metadata databases.

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CFD Analysis on a Tall Building Augmented Wind Turbine (풍력발전기가 설치된 고층빌딩에 대한 전산유체역학적 고찰)

  • Jeon, Wan-Ho;Yoon, Seong-Wook;Kim, Wook;Cho, Jang-Hyung
    • Journal of Environmental Science International
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    • v.18 no.8
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    • pp.919-926
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    • 2009
  • Renewable energy or green energy is a hot issue in theses days. Since wind resource can be endlessly supplied by nature, researchers and common people are interested in study how to use that resource at home or company. Especially, many architects have tried to integrate wind power generator for a part of building. So in this paper, three buildings installed wind power turbine are targed to CFD analysis and these buildings are Bahrain trade center, Discovery tower, and Pearl river tower. Bahrain trade center is the first building installed real wind turbine, Discovery tower is constructing at Texas, and Pearl river tower is designed and proved by china researchers. These buildings have very different type of wind power turbine and each turbine has different conditions f3r best power generation. Therefor this paper will focus on characteristic shape of buildings, wind power turbine type, and expected purpose of construction. Moreover, CFD analysis will show wind flow pattern and wind speed while wind is passing through wind turbine of three tall buildings. CFD analysis for three buildings make comparison the wind flow patterns with experimental result.

Detection of API(Anomaly Process Instance) Based on Distance for Process Mining (프로세스 마이닝을 위한 거리 기반의 API(Anomaly Process Instance) 탐지법)

  • Jeon, Daeuk;Bae, Hyerim
    • Journal of Korean Institute of Industrial Engineers
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    • v.41 no.6
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    • pp.540-550
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    • 2015
  • There have been many attempts to find knowledge from data using conventional statistics, data mining, artificial intelligence, machine learning and pattern recognition. In those research areas, knowledge is approached in two ways. Firstly, researchers discover knowledge represented in general features for universal recognition, and secondly, they discover exceptional and distinctive features. In process mining, an instance is sequential information bounded by case ID, known as process instance. Here, an exceptional process instance can cause a problem in the analysis and discovery algorithm. Hence, in this paper we develop a method to detect the knowledge of exceptional and distinctive features when performing process mining. We propose a method for anomaly detection named Distance-based Anomaly Process Instance Detection (DAPID) which utilizes distance between process instances. DAPID contributes to a discovery of distinctive characteristic of process instance. For verifying the suggested methodology, we discovered characteristics of exceptional situations from log data. Additionally, we experiment on real data from a domestic port terminal to demonstrate our proposed methodology.

Study on Dynamic Source Routing Protocol for Mobile Ad Hoc Networks (이동 Ad Hoc 망에 대한 동적 소스 라우팅 프로토콜에 관한 연구)

  • 하재승
    • Journal of the Korea Computer Industry Society
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    • v.2 no.9
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    • pp.1219-1224
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    • 2001
  • There can exist unidirectional links due to asymmetric property of mobile terminals or current wireless environments on practical mobile ad hoc networks. However, at present, the existing mobile ad hoc routing protocols are implemented to support only bidirectional links. Thus, in this paper, we extend the existing dynamic source routing protocol in order to implement a new routing protocol, which is fit to mobile ad hoc networks containing unidirectional links. For performance evaluation, we use combinations of mobility scenario files and connection pattern files from Carnegimelon Univ. We consider received data rate and average route discovery time as evaluation items, which are compared and evaluated for three suggested route discovery methods.

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CFD Analysis on a Tall Building Augmented Wind Turbine (풍력발전기가 설치된 고층빌딜에 대한 전산유체역학적 고찰)

  • Jeon, Wan-Ho;Yoon, Seong-Wook;Kim, Wook;Cho, Jang-Hyung
    • 한국신재생에너지학회:학술대회논문집
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    • 2009.11a
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    • pp.418-421
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    • 2009
  • Renewable energy or green energy is a hot issue in theses days. Since wind resource can be endlessly supplied by nature, researchers and common people are interested in study how to use that resource at home or company. Especially, many architects have tried to integrate wind power generator for a part of building. So in this paper, three buildings installed wind power turbine are targed to CFD analysis and these buildings are Bahrain trade center, Discovery tower, and Pearl river tower. Bahrain trade center is the first builidng installed real wind turbine, Discovery tower is constructing at Texas, and Pearl river tower is designed and proved by china researchers. These buildings have very different type of wind power turbine and each turbine has different conditions for best power generation. Therefor this paper will focus on characteristic shape of buildings, wind power turbine type, and expected purpose of construction. Moreover, CFD analysis will show wind flow pattern and wind speed while wind is passing through wind turbine of three tall buildings. CFD analysis for three buildings make comparison the wind flow patterns with experimental result.

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Accurate and Efficient Log Template Discovery Technique

  • Tak, Byungchul
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.10
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    • pp.11-21
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    • 2018
  • In this paper we propose a novel log template discovery algorithm which achieves high quality of discovered log templates through iterative log filtering technique. Log templates are the static string pattern of logs that are used to produce actual logs by inserting variable values during runtime. Identifying individual logs into their template category correctly enables us to conduct automated analysis using state-of-the-art machine learning techniques. Our technique looks at the group of logs column-wise and filters the logs that have the value of the highest proportion. We repeat this process per each column until we are left with highly homogeneous set of logs that most likely belong to the same log template category. Then, we determine which column is the static part and which is the variable part by vertically comparing all the logs in the group. This process repeats until we have discovered all the templates from given logs. Also, during this process we discover the custom patterns such as ID formats that are unique to the application. This information helps us quickly identify such strings in the logs as variable parts thereby further increasing the accuracy of the discovered log templates. Existing solutions suffer from log templates being too general or too specific because of the inability to detect custom patterns. Through extensive evaluations we have learned that our proposed method achieves 2 to 20 times better accuracy.

In silico discovery and evaluation of phytochemicals binding mechanism against human catechol-O-methyltransferase as a putative bioenhancer of L-DOPA therapy in Parkinson disease

  • Rath, Surya Narayan;Jena, Lingaraja;Bhuyan, Rajabrata;Mahanandia, Nimai Charan;Patri, Manorama
    • Genomics & Informatics
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    • v.19 no.1
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    • pp.7.1-7.13
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    • 2021
  • Levodopa (L-DOPA) therapy is normally practised to treat motor pattern associated with Parkinson disease (PD). Additionally, several inhibitory drugs such as Entacapone and Opicapone are also cosupplemented to protect peripheral inactivation of exogenous L-DOPA (~80%) that occurs due to metabolic activity of the enzyme catechol-O-methyltransferase (COMT). Although, both Entacapone and Opicapone have U.S. Food and Drug Administration approval but regular use of these drugs is associated with high risk of side effects. Thus, authors have focused on in silico discovery of phytochemicals and evaluation of their effectiveness against human soluble COMT using virtual screening, molecular docking, drug-like property prediction, generation of pharmacophoric property, and molecular dynamics simulation. Overall, study proposed, nine phytochemicals (withaphysalin D, withaphysalin N, withaferin A, withacnistin, withaphysalin C, withaphysalin O, withanolide B, withasomnine, and withaphysalin F) of plant Withania somnifera have strong binding efficiency against human COMT in comparison to both of the drugs i.e., Opicapone and Entacapone, thus may be used as putative bioenhancer in L-DOPA therapy. The present study needs further experimental validation to be used as an adjuvant in PD treatment.

Streaming Decision Tree for Continuity Data with Changed Pattern (패턴의 변화를 가지는 연속성 데이터를 위한 스트리밍 의사결정나무)

  • Yoon, Tae-Bok;Sim, Hak-Joon;Lee, Jee-Hyong;Choi, Young-Mee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.1
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    • pp.94-100
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    • 2010
  • Data Mining is mainly used for pattern extracting and information discovery from collected data. However previous methods is difficult to reflect changing patterns with time. In this paper, we introduce Streaming Decision Tree(SDT) analyzing data with continuity, large scale, and changed patterns. SDT defines continuity data as blocks and extracts rules using a Decision Tree's learning method. The extracted rules are combined considering time of occurrence, frequency, and contradiction. In experiment, we applied time series data and confirmed resonable result.

Personalized Media Control Method using Probabilistic Fuzzy Rule-based Learning (확률적 퍼지 룰 기반 학습에 의한 개인화된 미디어 제어 방법)

  • Lee, Hyong-Euk;Kim, Yong-Hwi;Lee, Tae-Youb;Park, Kwang-Hyun;Kim, Yong-Soo;Cho, Joon-Myun;Bien, Z. Zenn
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.244-251
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    • 2007
  • Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.