• International journal of advanced smart convergence
• /
• v.9 no.1
• /
• pp.90-97
• /
• 2020

Oncolytic viruses are characterized by their ability to selectively kill cancer cells, and thus they have potential for application as novel anticancer agents. Despite an increase in the number of studies on methodologies involving oncolytic viruses, bioinformatic studies generating useful data are lacking. We constructed a database for oncolytic virus research (the oncolytic virus database, OVDB) by integrating scattered genetic information on oncolytic viruses and proposed a systematic means of using the biological data in the database. Our database provides data on 14 oncolytic viral strains and other types of viruses for comparative analysis. We constructed the OVDB using the basic local alignment search tool, and therefore can provides genetic information on highly homologous oncolytic viruses. This study contributes to facilitate systematic bioinformatics research, providing valuable data for development of oncolytic virus-based anticancer therapies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.15 no.1
• /
• pp.117-129
• /
• 1997

In recent years, the 1 : 5,000 scale Digital National Basemap(DNB) has been generated under National Geo-graphic Information System(NGIS) Project. The DNB database generated will be the backdrop data for thematic maps, underground facilities maps and so on. The DNB database will be distributed to the government and private sectors in near future so that it should meet the requirements as the basic data. In order to assure the quality of DNB database, the establishment of quality assurance process to database was in great need. In this study, we were mainly concerned with improving the quality of digital national basemap database in geomatric aspect as well as the processing time due to the amount of digital data generated. As a results of this study, the quality assuance process of DNB database is established and automatic quality assurance program is developed. Also, the program developed in this study is contributed to quality assurance of DNB database as well as economic aspects.

• Health Policy and Management
• /
• v.21 no.2
• /
• pp.279-308
• /
• 2011

Background : Demands have increased for a variety of welfare services and customized services for persons with disabilities(PWD). A management System focused on PWD was needed to provide for comprehensive services. The purpose of this study was to design a disability database and an application system in order to provide continuous and comprehensive rehabilitation service for PWD. Methods : We analyzed local and abroad disability-related policies and systems and derived the contents that should be included in the integrated database for PWD through a survey among rehabilitation specialists. Result : The integrated database for PWD was composed of 7 categories including General Characteristics, Health & Medicine, Assistance, Education, Employment, Economics and Daily & Social Life. The applicable system of integrated database for PWD was proposed to help conducting policies in such areas as follows ; 'welfare', 'education and culture', 'economic activity', 'social participation' and 'Health'. Conclusion : The main goal of disability policy and strategy should be established by systematically analyzing disability-related data integrating database of PWD. Accordingly, specific objectives and directions for disability policies should be set and efficiently managed and operated. The integrated database for PWD may be utilized for disability-related policies and service monitering, sustainable and integrated management and community participation and integration based on the rights of the disabled.

• Microbiology and Biotechnology Letters
• /
• v.48 no.2
• /
• pp.138-147
• /
• 2020

Various microorganisms play important roles in food fermentation, food spoilage, and agriculture. In this study, the biotype of 54 yeast and bacterial strains having high potential for utilization in food and agriculture, including Candida spp., Lactobacillus spp., and Acetobacter spp., were characterized by matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS). This characterization using a fast and robust method provides much-needed information on the selected microorganisms and will facilitate effective usage of these strains in various applications. Importantly, the unique protein profile of each microbial species obtained from this study was used to create a database of fingerprints from these species. The database was validated using microbial strains of the same species by comparing the mass spectra with the created database through pattern matching. The created reference database provides crucial information and is useful for further utilization of a large number of valuable microorganisms relevant to food and agriculture.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.635-638
• /
• 2006

Regression of conventional prediction techniques in data mining uses the model which is generated from the training step. This model is applied to new input data without any change. If this model is applied directly to time series, the rate of prediction accuracy will be decreased. This paper proposes an incremental regression for time series prediction like typhoon track prediction. This technique considers the characteristic of time series which may be changed over time. It is composed of two steps. The first step executes a fractional process for applying input data to the regression model. The second step updates the model by using its information as new data. Additionally, the model is maintained by only recent data in a queue. This approach has the following two advantages. It maintains the minimum information of the model by using a matrix, so space complexity is reduced. Moreover, it prevents the increment of error rate by updating the model over time. Accuracy rate of the proposed method is measured by RME(Relative Mean Error) and RMSE(Root Mean Square Error). The results of typhoon track prediction experiment are performed by the proposed technique IMLR(Incremental Multiple Linear Regression) is more efficient than those of MLR(Multiple Linear Regression) and SVR(Support Vector Regression).

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05c
• /
• pp.1595-1598
• /
• 2003

이 논문은 질의와 검색 대상 객체가 모두 이동 객체인 경우, 즉 3 차원 폴리라인(polyline) 형태의 경로를 가지는 객체들 간의 연속(continuous) 최근접 질의 처리에 유용한 기법을 제안한다. 질의경로를 따라 객체를 탐색해가면서 질의에 대한 최근접 정보가 변하는 시점을 찾는 것이 목적인 연속 최근접 질의 처리는 전체 질의 경로에 올바른 최근접 정보 리스트를 제공하지만, 기존의 방법들은 검색 대상 객체가 동적인 경우에 적용되기에는 시간에 따라 움직이는 객체의 위치변화를 처리하지 못하고, 질의 시점과 대상 객체간의 시점을 연관시키기 어렵다는 문제점들을 가지고 있다. 따라서 이 논문에서는 데이터 객체들의 궤적 정보는 STR 트리로 유지하고, 질의 경로 세그먼트와 질의의 시간 인터벌에 포함되는 데이터 객체 세그먼트 모두에 대해 추출시간(sampling time) 선택, 스윕라인(sweep line) 적용, 위치 추정 함수 이용 등의 단계를 처리함으로써, 이 문제를 해결하고 질의 경로 전체에 정확한 최근접 객체 정보 리스트를 제공한다. 제안된 기법은 물류정보시스템, 국방정보시스템, 기상, 교통 등 시공간 이동 객체의 질의를 다루는 시스템에 적용할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05c
• /
• pp.1579-1582
• /
• 2003

점차 네트워크상의 침입 시도가 증가되고 다변화되어 침입탐지에 많은 어려움을 주고 있다. 시스템에 새로운 침입에 대한 탐지능력과 다량의 감사데이터의 효율적인 분석을 위해 데이터마이닝 기법이 적용된다. 침입탐지 방법 중 비정상행위 탐지는 모델링된 정상행위에서 벗어나는 행위들을 공격행위로 간주하는 기법이다. 비정상행위 탐지에서 정상행위 모델링을 하기 위해 연관규칙이나 빈발에피소드가 적용되었다. 그러나 이러한 기법들에서는 시간요소를 배제하거나 패턴들의 발생순서만을 다루기 때문에 정확하고 유용한 정보를 제공할 수 없다. 따라서 이 논문에서는 이 문제를 해결할 수 있는 시간연관규칙과 분류규칙을 이용한 비정상행위 탐지 모델을 제안하였다. 즉, 발생되는 패턴의 주기성과 달력표현을 이용, 유용한 시간지식표현을 갖는 시간연관규칙을 이용해 정상행위 프로파일을 생성하였고 이 프로파일에 의해 비정상행위로 간주되는 규칙들을 발견하고 보다 정확한 비정상행위 판별 여부를 결정하기 위해서 분류기법을 적용하였다.

• Korean Journal of Remote Sensing
• /
• v.22 no.5
• /
• pp.457-462
• /
• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Computers and Concrete
• /
• v.28 no.5
• /
• pp.441-450
• /
• 2021

This study presents the first analysis system and fast-access cloud database for shrinkage and creep of concrete in the world, named "shrinkage and creep database in Taiwan", SCDT. SCDT not only has the most comprehensive experimental data, including NU, JSCE, Europe, and TW databases, but provides a design tool for researchers and engineers. It can further facilitate the development of prediction models for localized concrete. Users can obtain the shrinkage and creep curves based on their selected prediction models in SCDT. Comparisons of the predicted results of selected models and test results in the chosen database can be generated in seconds. One example of the development of basic creep prediction model in Taiwan based on model B4 by using SCDT to reflect concrete characteristics in Taiwan is also presented in this study. Users anywhere in the world can easily access SCDT to browse and upload data, receive predictive results, or develop predictive models.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.04a
• /
• pp.369-371
• /
• 2009

생명체 내에서 기능 수행 시 각종 물질들이나 단백질들끼리 상호결합을 해야 한다. 이런 결합성을 결정짓는 것들이 단백질의 3차원 구조이기 때문에 단백질 구조연구는 중요하다. 이 논문에서는 단백질 구조데이터 및 관련된 구조정보의 통합된 데이터베이스를 구축하고 웹 환경에서 질의된 단백질과 유사성 비교를 진행하여 그 결과 및 연관된 정보를 검색하여 체계적으로 정보를 제공하는 단백질 구조 비교시스템을 제안한다. 제안 시스템을 구축하기 위하여 공개용 단백질 구조데이터 저장소인 Protein Data Bank의 플랫파일에서 필수적인 구조데이터정보만을 추출하여 여기에서 단백질의 하위구조 생성 알고리즘을 적용하여 데이터베이스를 구축한다. 사용자가 인터넷을 통하여 진행한 질의는 하위구조처리 모듈을 통하여 하위구조를 생성하고 구조유사부분에 대해 RMSD값이 계산되고 이와 연관된 구조정보의 검색이 진행 된 후 체계적으로 출력화면에 보여준다. 제안 시스템은 단백질의 전체적인 서열과 구조 정보를 이용하지 않고서, 단백질 기능을 결정하는 핵심영역을 포함하는 표면을 효과적으로 비교함으로써 기존의 구조비교 시스템보다 빠른 검색과 상세한 분석을 지원한다.