• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1998년도 국제 컨퍼런스: 국가경쟁력 향상을 위한 디지틀도서관 구축방안
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• pp.187-198
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• 1998

마케팅의 Fundamental\ulcorner 마케팅 : 제품구매와 관련된 소비자의 행위를 연구 마케팅의 역사 : Mass marketing $\longrightarrow$ Market segmentation $\longrightarrow$ Database marketing 소비자 이해와 관리를 위한 다양한 정보와 지식을 제공한다. DBM, Relationship marketing, Frequency marketing, Loyalty marketing, Program customer management, Direct marketing(중략)

• Journal of Computing Science and Engineering
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• 제1권1호
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• pp.1-30
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• 2007

In this paper we have provided an extensive survey of the databases and other resources related to the current research in bioinformatics and the issues that confront the database researcher in helping the biologists. Initially we give an overview of the concepts and principles that are fundamental in understanding the basis of the data that has been captured in these databases. We briefly trace the evolution of biological advances and point out the importance of capturing data about genes, the fundamental building blocks that encode the characteristics of life and proteins that are the essential ingredients for sustaining life. The study of genes and proteins is becoming extremely important and is being known as genomics and proteomics, respectively. Whereas there are numerous databases related to various subfields of biology, we have maintained a focus on genomic and proteomic databases which are the crucial stepping stones for other fields and are expected to play an important role in the future applications of biology and medicine. A detailed listing of these databases with information about their sizes, formats and current status is presented. Related databases like molecular pathways and interconnection network databases are mentioned, but their full coverage would be beyond the scope of a single paper. We comment on the peculiar nature of the data in biology that presents special problems in organizing and accessing these databases. We also discuss the capabilities needed for database development and information management in the bioinformatics arena with particular attention to ontology development. Two research case studies based on our own research are summarized dealing with the development of a new genome database called Mitomap and the creation of a framework for discovery of relationships among genes from the biomedical literature. The paper concludes with an overview of the applications that will be driven from these databases in medicine and healthcare. A glossary of important terms is provided at the end of the paper.

• Steel and Composite Structures
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• 제42권1호
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• pp.123-137
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• 2022

The fundamental period (FP) is one of the most critical parameters for the seismic design of structures. In the reinforced concrete (RC) infilled frame, the infill walls significantly affect the FP because they change the stiffness and mass of the structure. Although several formulas have been proposed for estimating the FP of the RC infilled frame, they are often associated with high bias and variance. In this study, an efficient soft computing model, namely the group method of data handling (GMDH), is proposed to predict the FP of regular RC infilled frames. For this purpose, 4026 data sets are obtained from the open literature, and the quality of the database is examined and evaluated in detail. Based on the cleaning database, several GMDH models are constructed and the best prediction model, which considers the height of the building, the span length, the opening percentage, and the infill wall stiffness as the input variables for predicting the FP of regular RC infilled frames, is chosen. The performance of the proposed GMDH model is further underscored through comparison of its FP predictions with those of existing design codes and empirical models. The accuracy of the proposed GMDH model is proven to be superior to others. Finally, explicit formulas and a graphical user-friendly interface (GUI) tool are developed to apply the GMDH model for practical use. They can provide a rapid prediction and design for the FP of regular RC infilled frames.

• 천문학회지
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• 제38권3호
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• pp.357-363
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• 2005

A deep stellar analysis is introduced for the poorly studied open cluster NGC 2509. The Near-IR database of the digital Two Micron All Sky Survey (2MASS) has been used to re-estimate and refine the fundamental parameters of the cluster, i.e. age, reddening, distance, and diameter. As well as, luminosity function, mass function, total mass, relaxation time, and mass segregation of NGC 2509 have been estimated here for the first time..

• 대한공간정보학회지
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• 제4권1호
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• pp.43-55
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• 1996

본 연구에서는 하이퍼맵의 주요 하부구조의 하나인 동영상을 GIS에 도입하는 과정에서 필요한 동영상지원 수치지도 데이타베이스의 구조에 대한 연구를 진행하였다. 이 데이타베이스는 도로상의 위치와 연결된 동영상의 출력 및 동영상에 표현된 각종 지형지물과 2차원 수치지도내의 지형지물을 연계가 가능하도록 설계하였다. 연구의 평가를 위해 실험용 GIS시스템을 제작하여 2차원 수치지도의 기능, 동영상과 도로선형의 연계 기능, 동영상 및 수치지도상의 지형지물의 상호연계기능 등을 검토한 결과, 본 연구에서 제안된 수치지도 데이타베이스 구조를 바탕으로 수치지도 도로선형과 지형지물 데이타 및 동영상을 기능적으로 통합하여 활용하는 것이 가능함을 알 수 있었다.

• Spatial Information Research
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• 제15권3호
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• pp.323-333
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• 2007

최근 들어 남북한은 경협을 중심으로 교류가 활발히 추진되고 있다. 도로철도 연결, 공단개발 등과 같은 남북한 협력사업이 실효를 거두기 위해서는 북한지역의 지형지물과 같은 물리적인 지리정보와 토지이용현황 등에 관한 기초자료를 구축해야 한다. 따라서 이러한 요구를 만족시키기 위해 북한지역의 국토이용 현황을 파악할 수 있는 자료의 구축방법에 대한 연구가 필요하다. 본 논문은 이러한 요구를 만족시키고자 북한지역의 국토이용 현황을 파악할 수 있는 데이터베이스를 실험적으로 구축하고, 이를 통하여 절차와 과정을 구체화하였다. 북한지역의 국토이용 현황을 파악하는데 도움이 되는 지형도, 위성영상, 주제도 등 모든 종류의 가용자료를 수집 활용하였다. 이렇게 수집된 데이터는 스캐닝, 위성영상처리, 토지피복분류 등 적합한 처리과정을 통해 데이터베이스로 구축하였다. 또한 기존 자료를 DB화 하는데 그치지 않고 구축한 데이터베이스를 이용하여 벡터형태의 지리정보를 추출하여 데이터베이스에 추가하여 정성적, 정량적인 북한지역 국토이용현황조사가 가능하도록 하였다.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2002년도 학술대회지
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• pp.446-449
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• 2002

건설사업을 수행하기 위해서는 건설사업과 직접 또는 간접적으로 연관된 다양한 정보들이 요구된다. 본 연구는 건설CALS 통합데이터베이스를 구축하기 위하여 핵심 성공 요인을 도출하고 공공부문의 정보화 사업과 데이터베이스의 조사를 통해 건설사업 수행에 필요한 연계 대상 정보를 선정하였다. 그리고, 선정된 정보를 프로젝트 기반 정보와 일반정보로 구분하여 각각의 정보통합 방안으로 지식관리시스템을 통한 연계와 메타데이터를 통한 중계연계 방식을 제안하고 포탈환경의 건설CALS 통합데이터베이스 구축 방안을 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1557-1569
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• 2017

In recent times, the Internet of Things (IoT) has rapidly emerged as one of the most influential information and communication technologies (ICT). The various constituents of the IoT together offer novel technological opportunities by facilitating the so-called "hyper-connected world." The fundamental tasks that need to be performed to provide such a function involve the transceiving, storing, and analyzing of digital data. However, it is challenging to handle voluminous data with IoT devices because such devices generally lack sufficient computational capability. In this study, we examine the IoT from the perspective of security and digital forensics. SQLite is a light-weight database management system (DBMS) used in many IoT applications that stores private information. This information can be used in digital forensics as evidence. However, it is difficult to obtain critical evidence from IoT devices because the digital data stored in these devices is frequently deleted or updated. To address this issue, we propose Schema Pattern-based Recovery (SPaRe), an SQLite recovery scheme that leverages the pattern of a database schema. In particular, SPaRe exhaustively explores an SQLite database file and identifies all schematic patterns of a database record. We implemented SPaRe on an iPhone 6 running iOS 7 in order to test its performance. The results confirmed that SPaRe recovers an SQLite record at a high recovery rate.

• Structural Engineering and Mechanics
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• 제63권2호
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• pp.237-249
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• 2017

The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.

• Computers and Concrete
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• 제9권5호
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• pp.375-387
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• 2012

The objective of this investigation was to develop rules for automatic categorization of concrete quality using selected artificial intelligence methods based on machine learning. The range of tested materials included concrete containing a new waste material - solid residue from coal combustion in fluidized bed boilers (CFBC fly ash) used as additive. The rapid chloride permeability test - Nordtest Method BUILD 492 method was used for determining chloride ions penetration in concrete. Performed experimental tests on obtained chloride migration provided data for learning and testing of rules discovered by machine learning techniques. It has been found that machine learning is a tool which can be applied to determine concrete durability. The rules generated by computer programs AQ21 and WEKA using J48 algorithm provided means for adequate categorization of plain concrete and concrete modified with CFBC fly ash as materials of good and acceptable resistance to chloride penetration.