• Proceedings of the Korea Database Society Conference
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• 1998.09a
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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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• v.1 no.1
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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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• v.42 no.1
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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.

• Journal of The Korean Astronomical Society
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• v.38 no.3
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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..

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.43-55
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• 1996

The objective of this research is to design a digital map database structure supporting video images which is one of the fundamental elements of hypermap. In order to reach the research objective, the work includes the identification of the relationships between two dimensional digital map database and video elements. The proposed database model has functions for interactive browsing between video image frames and specific points on two dimensional digital map, fer connecting the map elements and features on video images. After that, the images and the database are transformed to the pilot system fer testing the map database structure. The pilot project results indicate that the map database structure can integrate functionally two dimensional digital map and video images.

• Spatial Information Research
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• v.15 no.3
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• pp.323-333
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• 2007

Recently, the South and North Korea have collaborated in the economic cooperation. Success for the cooperation of the South and North Korea has supported the basic and fundamental GIS data building for geographic information (GI) and the land-use of the North Korea. This North Korea GIS project is also vital to facilitate rebuilding and reconnecting socio-economic infrastructures such as reconnecting road and railway networks between the South and North Korea. Thus, this paper emphasizes on the fundamental issues of GIS data building in North Korea area and suggests GI and data establishment methods of the North Korea regions which has not been achieved in GIS research activities in Korea. As the basic GI and data in the North Korea, topographical maps, satellite imageries, and thematic maps were collected and used for surveying of territorial areas of the North Korea. The database of those dataset were built by scanning, image processing, and classifying land-use types. In addition, this paper exacted vector data from the database and included the vector data into the database as other basic GI dataset that enable to analyze quantitative and qualitative territorial land use and development in the North Korea.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.446-449
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• 2002

To establish integrated Database, this paper (1) grasped key success factors of integrated data environment, (2) selected linking information through investigating information-oriented projects and database necessary to perform construction project in public section, (3) divided selected information into project-based information and general information, and then (4) presented plan of sharing knowledge through using the linking method of knowledge database and meta-database.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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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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• v.63 no.2
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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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• v.9 no.5
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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.