• Proceedings of the Korean Society for Bioinformatics Conference
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• 2002.06a
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• pp.5-23
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• 2002

Motivation: Protein-protein interaction plays a critical role in the biological processes. The identification of interacting proteins by bioinformatical methods can provide new lead In the functional studies of uncharacterized proteins without performing extensive experiments. Results: Protein-protein interactions are predicted by a computational algorithm based on the weighted scoring system for domain interactions between interacting protein pairs. Here we propose potential interaction domain (PID) pairs can be extracted from a data set of experimentally identified interacting protein pairs. where one protein contains a domain and its interacting protein contains the other. Every combinations of PID are summarized in a matrix table termed the PID matrix, and this matrix has proposed to be used for prediction of interactions. The database of interacting proteins (DIP) has used as a source of interacting protein pairs and InterPro, an integrated database of protein families, domains and functional sites, has used for defining domains in interacting pairs. A statistical scoring system. named "PID matrix score" has designed and applied as a measure of interaction probability between domains. Cross-validation has been performed with subsets of DIP data to evaluate the prediction accuracy of PID matrix. The prediction system gives about 50% of sensitivity and 98% of specificity, Based on the PID matrix, we develop a system providing several interaction information-finding services in the Internet. The system, named PreDIN (Prediction-oriented Database of Interaction Network) provides interacting domain finding services and interacting protein finding services. It is demonstrated that mapping of the genome-wide interaction network can be achieved by using the PreDIN system. This system can be also used as a new tool for functional prediction of unknown proteins.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.759-762
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• 2005

Recently, Intelligent Transportation System(ITS) has been applied to satisfy increasing traffic demand every year and to solve many traffic problems. Especially, Advanced Traveller Information System(ATIS) is a transportation system to optimize the trip of each other vehicle. It is important to provide the driver with quick and comfortable path from source to destination. However, it is difficult to provide a shortest path in a road network with dynamic cost. Because the existing research has a static cost. Therefore, in this paper we propose an operator for searching traffic dependent shortest path. The proposed operator finds the shortest path from source to destination using a current time cost and a difference cost of past time cost. Such a method can be applied to the road status with time. Also, we can expect a predicted arrival time as well as the shortest path from source to destination. It can be applied to efficiently application service as ITS and have the advantages of using the road efficiently, reducing the distribution cost, preparing an emergency quickly, reducing the trip time, and reducing an environmental pollution owing to the saving the fuel.

• Proceedings of the KSRS Conference
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• v.2
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• pp.623-626
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• 2006

Group of genes controls the functioning of a cell by complex interactions. These interacting gene groups are called Gene Regulatory Networks (GRNs). Two previous data mining approaches, clustering and classification have been used to analyze gene expression data. While these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rule. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and detect gene expression patterns applying FP-growth algorithm. And then, we construct gene regulatory network from frequent gene patterns using chain rule. Finally, we validated our proposed method by showing that our experimental results are consistent with published results.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.107-115
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• 2022

Recently, big data applications need another database different from the Relation database. NoSQL databases are used to save and handle massive amounts of data. NoSQL databases have many advantages over traditional databases like flexibility, efficiently processing data, scalability, and dynamic schemas. Most of the current applications are based on the web, and the size of data is in increasing. NoSQL databases are expected to be used on a more and large scale in the future. However, NoSQL suffers from many security issues, and one of them is access control. Many recent applications need Fine-Grained Access control (FGAC). The integration of the NoSQL databases with FGAC will increase their usability in various fields. It will offer customized data protection levels and enhance security in NoSQL databases. There are different NoSQL database models, and a document-based database is one type of them. In this research, we choose the CouchDB NoSQL document database and develop an access control mechanism that works at a fain-grained level. The proposed mechanism uses role-based access control of CouchDB and restricts read access to work at the document level. The experiment shows that our mechanism effectively works at the document level in CouchDB with good execution time.

• Digital Contents
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• no.9 s.16
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• pp.122-125
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• 1994

우리는 흔히 정보통신, ISDN, PC통신, NETWORK 등 수많은 단어들을 접한다. 비록 이 용어자체는 익숙하지만 정확한 의미를 모르는 상태에서 사용하는 경우가 많다. 이번호 부터는 이러한 데이터베이스 관련 용어를 정리함으로 독자들에게 보다 나은 정보를 제공하고자 한다.

• Digital Contents
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• no.12 s.19
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• pp.90-95
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• 1994

정보가 있고, 없음이 비즈니스 결과를 크게 좌우하는 시대이다. TMI-SERVICE는 기업 및 산업관련정보를 수집, 가공, 데이터베이스화하여 국내외 업체에 정확하고 신속한 정보를 공급하기 위해 한국무역시장정보(주)가 제공하는 전문 BUSINESS NETWORK이다.

• Digital Contents
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• no.10 s.125
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• pp.30-32
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• 2003

홈네트워크 산업을 활성화하는데 구심체 역할을 할 한국 홈네트워크산업협회(HNA : Home Network industry Association)가 지난달 1일 서울 소공동 롯데호텔에서 창립총회를 열고 본격적인 활동을 시작했다.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.5
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• pp.43-51
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• 2011

Irrigation facilities are spread over demand area in a low density and exposed in the field requiring efficient operation and maintenance. Thus, it could be more efficient to manage an irrigation system when it is with wireless sensor network (WSN) using RFID (Radio Frequency Identification) application. A WSN, a kind of ubiquitous sensor network composed of wireless network, RFID and database management system was developed for agricultural water management in terms of operational status and maintenance requirements. Identification code for RFID tag was designed and an application for RFID reader was developed for field data collection, and a database management system was constructed for managing irrigation facility attributes. The system was installed in I-dong irrigation districts in Gyounggi-province, Korea and the operated results showed the applicability of the WSN for agricultural water management.

• Spatial Information Research
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• v.5 no.1
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• pp.61-75
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• 1997

National Geographic Information System(NGIS) should be designed on the assumption that geographic data collected by each national organization should be integrated into geographic database systemically. To achieve this object, NGIS database would be better connected to National Very High-Speed Communication Network. In the process of research, some problems related to Korean NGIS are found. These are standardization, compatibility, extension, issue of making and opening digital map, and issue related to land information. So, it is required that pilot project apply National Geographic Information System in terms of National Very High-Speed computer network project. This project is to contain two main theme building of physical network and special management of network which is related with NGIS.

• Phonetics and Speech Sciences
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• v.8 no.3
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• pp.31-38
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• 2016

Speech inversion (acoustic-to-articulatory mapping) is not a trivial problem, despite the importance, due to the highly non-linear and non-unique nature. This study aimed to investigate the performance of Deep Neural Network (DNN) compared to that of traditional Artificial Neural Network (ANN) to address the problem. The Wisconsin X-ray Microbeam Database was employed and the acoustic signal and articulatory pellet information were the input and output in the models. Results showed that the performance of ANN deteriorated as the number of hidden layers increased. In contrast, DNN showed lower and more stable RMS even up to 10 deep hidden layers, suggesting that DNN is capable of learning acoustic-articulatory inversion mapping more efficiently than ANN.