• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.325-330
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• 2005

We are generally interested in the analysis, detection and prediction of structural motifs in proteins, in order to infer compatibility of amino acid sequence to structure in proteins of known three-dimensional structure available in the Protein Data Bank. In this context, we are analyzing some of the well-characterized structural motifs in proteins. We have analyzed simple structural motifs, such as, ${\beta}$-turns and ${\gamma}$-turns by evaluating the statistically significant type-dependent amino acid positional preferences in enlarged representative protein datasets and revised the amino acid preferences. In doing so, we identified a number of ‘unexpected’ isolated ${\beta}$-turns with a proline amino acid residue at the (i+2) position. We extended our study to the identification of multiple turns, continuous turns and to peptides that correspond to the combinations of individual ${\beta}$ and ${\gamma}$-turns in proteins and examined the hydrogen-bond interactions likely to stabilize these peptides. This led us to develop a database of structural motifs in proteins (DSMP) that would primarily allow us to make queries based on the various fields in the database for some well-characterized structural motifs, such as, helices, ${\beta}$-strands, turns, ${\beta}$-hairpins, ${\beta}$-${\alpha}$-${\beta}$, ${\psi}$-loops, ${\beta}$-sheets, disulphide bridges. We have recently implemented this information for all entries in the current PDB in a relational database called ODSMP using Oracle9i that is easy to update and maintain and added few additional structural motifs. We have also developed another relational database corresponding to amino acid sequences and their associated secondary structure for representative proteins in the PDB called PSSARD. This database allows flexible queries to be made on the compatibility of amino acid sequences in the PDB to ‘user-defined’ super-secondary structure conformation and vice-versa. Currently, we have extended this database to include nearly 23,000 protein crystal structures available in the PDB. Further, we have analyzed the ‘structural plasticity’ associated with the ${\beta}$-propeller structural motif We have developed a method to automatically detect ${\beta}$-propellers from the PDB codes. We evaluated the accuracy and consistency of predicting ${\beta}$ and ${\gamma}$-turns in proteins using the residue-coupled model. I will discuss results of our work and describe databases and software applications that have been developed.

• Journal of Distribution Science
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• v.14 no.8
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• pp.113-121
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• 2016

Purpose - This paper aims to examine the impact of buyer-supplier cooperation on suppliers' trust on buyers and the moderating role of buyers' governance mechanism between the sharing activities and trust. Research design, data, and methodology - An integrated research model is designed to materialize the research hypotheses. First, the impact of buyer-supplier cooperation is empirically analyzed by looking into how the sharing activities, in the field of information, resource, and knowledge, of buyer with supplier will affect the trust of supplier on buyer. Second, the moderating effect of contract-based governance mechanism of buyer is empirically analyzed. Third, the influence of trust on innovation performance of suppler is empirically analyzed. Results - Our findings provide supporting evidence for some of our hypotheses. First, all of the sharing activities are significantly influential, but in different degree, to trust of supplier. Second, contract-based governance mechanism of buyer have a moderating effect on the relationship between sharing activities and trust, positively in resource-sharing activities, negatively in information-sharing activities, not significant in knowledge-sharing activities. Third, supplier's trust on buyer positively affects supplier's own innovation performance. Conclusions - The strategies applied in supply chain management have become important as the competition among firms has shifted from competition between individual firms to competition between supply chains. A customer's sharing activities with its supplier may contribute to an increase in innovation performance. The supplier's information-sharing activity with its customer could affect its information-sharing activities with its main supplier. Cooperative activity with a partner in the supply chain is cultivated and amassed into relationship knowledge, and this study shows that the cooperative relational knowledge related to information-sharing activities enables firms to participate in sharing activities with their main suppliers. Increasing evidence shows that sharing various activities between buyer and supplier improves trust and performance outcomes, and enables firms to maintain competitive advantage. From the perspective of knowledge theory, external knowledge is becoming more important in firms' innovation activities, because innovative knowledge is acquired primarily through interaction with another organization. In addition, relationship learning could be an important tool in absorbing the supplier's core technology, information, expertise, and core competencies, increasing relational value.

• 한국체육학회지인문사회과학편
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• v.54 no.2
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• pp.299-312
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• 2015

The purpose of this study was to find the effects of user experience on flow and satisfaction of electronic hogu system in the taekwondo game. The subjects were players who had experience using electronic hogu system in the taekwondo game for 2014 year 7month~10month. 652 samples out of 750 samples through convenient sampling method were adopted as a final data. We confirmed the goodness of fit test of the model, utilizing SPSS WIN Ver 18.0, and AMOS 7.0, and after which we tested each hypothesis. The results were as follows; First, sentient, emotional, cognitive, behavioral, relational experience of user experience did not have a significant influence on cognition flow. Second, sentient, emotional, relational experience of user experience did not have a significant influence on behavioral flow. Third, cognitive, behavioral experience of user experience had a significant influence on behavioral flow. Fourth, cognition, behavioral flow had a significant influence on satisfaction. Fifth, factor between native and foreigner taekwondo players had significantly different. This paper is a meaningful to figure out user satisfaction of electronic hogu system in taekwondo games and maximize athletic performance.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.61-75
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• 2009

Generally, the development of the database application includes the requirement analysis phase of creating ERD (Entity Relationship Diagram) and process models, coding, and testing. From the above phases, the analysis phase is not most formalized. It is usually hard task because (1) customers don't know the details of the desired system; (2) developers can't with ease understand the business logic of the customers; (3) the outcomes of the analysis, which are ERD and process models, are not easy to understand to the customers. This paper propose that the executional forms, which are better to understand the systems, should be presented to the customers instead of the ERD. These forms should accept the data input so that customers can review the various aspects of the outcome models. The developers should be able to instantly implement the business logic and also should be able to visually demonstrate the logic in order to get the details of it. For this goal, the customer supplied business logic should be able to be implemented by the references between forms, actions, constraints from the perspective of the data flow. The customers try to execute the forms implementing the business logic and review their supplied logic find new necessary business logic of their own. Iterating these processes for the requirement analysis would result in the success of the analysis which is sufficiently detailed without conflicts.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.326-332
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• 2012

In this paper, error analyses on the calculation of offshore wind speed have been conducted using HeMOSU-1 data to develop offshore wind energy in Yeonggwang sea of Korea and onshore observed wind data in Buan, Gochang and Yeonggwang for 2011. Offshore wind speed data at 98.69 m height above M.S.L is estimated using relational expression induced by linear regression analysis between onshore and offshore wind data. In addition, estimated offshore wind speed data is set at 87.65 m above M.S.L using power law wind profile model with power law exponent(0.115) and its results are compared with the observed data. As a result, the spatial adjustment error are 1.6~2.2 m/s and the altitude adjustment error is approximately 0.1 m/s. This study shows that the altitude adjustment error is about 5% of the spatial adjustment error. Thus, long term observed data are needed when offshore wind speed was estimated by onshore wind speed data. because the conversion of onshore wind data lead to large error.

• Culinary science and hospitality research
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• v.22 no.7
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• pp.187-202
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• 2016

The purpose of this study was to better understand the influence of psychological contract breach in deluxe hotel culinary staff memeberss on job satisfaction and turnover intention. Based on a total of 280 samples obtained for empirical research, this study reviewed the reliability and fitness of the research model and verified a total of 4 hypotheses using the AMOS program. The hypothesized relationships in the model were simultaneously tested by using a structural equation model(SEM). The proposed model provided an adequate fit to the data, ${\chi}^2=334.152$ (p<.001), df=162, CMIN/DF=2.063, GFI=.893, AGFI=.861, NFI=.919, CFI=.956, RMSEA=.062. The model's fit, as indicated by these indexes, was deemed satisfactory, thus providing a good basis for testing the hypothesized paths. The SEM showed that relational contract breach (${\beta}=-.236$) had a negative significant influence on job satisfaction. In addition, job satisfaction (${\beta}=-.236$) had a negative significant influence on turnover intention. The moderating effects on career the formulated model was verified. Limitations and future research directions are also discussed.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1996.06a
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• pp.79-109
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• 1996

In order to transform the underground utility data into the 3-D spatial objects, this thesis defined the type of the 3-D spatial objects and the storage structure of objects, and developed the spatial data transformation system that transforms the 2-D underground utility data into the pre-defined 3-D spatial objects through the Booch Method, an object-oriented development method. For this sake, the relational data model of ARC/INFO and the storage structure are analyzed, as well as the pre-requisites, required for the 3-D visualization of the underground utilities. Also, the 2-D underground utility data, saved in ARC/INFO, were transformed into the ASCII files through the internal pre-processing procedure, then used as the input data of the transformation system. In addition, to develop the transformation system, the object-oriented development methods are studied first and, then, applied to the system analysis and the design procedure with the Booch Method as a development method. Finally, the results of analysis and design procesure are implemented through AML, a ARC/INFO macro language, and C++, an object-oriented programing language. As a result of this study, the 3-D spatial objects that can visualize the 2-D utilities in 3-D, are acquired, and the adaptation of object-oriented development method to the system development procedure enabled an effective development prodedure.

• Spatial Information Research
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• v.19 no.6
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• pp.19-28
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• 2011

Recently, the interests of marine mineral resources has been increasing from the depletion of land resources around the world and many countries are involving in marine exploration work. South Korea is also currently performing exploration work to estimate the marine mineral resources around the Korean Peninsula. However, massive amounts of marine exploration data accumulated from the long-term exploration work have not been systematically managed. The data have been managed by the file based system instead of commercial database. The aim of this study is to construct GIS-based Marine Mineral Resource Information System using a spatial database for the core sediments of the marine exploration data. For constructing such DB system, GIS-based data items were classified, and a database was designed using relational database model. The database was constructed using commercial DBMS(Database Management System), Oracle. Also, necessary functions of the system were defined for the effective use of database based on users' requirement analysis. The GIS-based Marine Mineral Resource Information System has enabled to support the systematic management of the marine exploration data. Furthermore, it is expected that this spatial database will be useful in estimating the reserves of the mineral resources and provide valuable information for economic evaluation. In the future, the application of advanced techniques of spatial analysis and 3-dimensional display function will be required.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.