• 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.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.473-486
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• 2005

The Hippocratic database model recently proposed by Agrawal et at. incorporates privacy protection capabilities into relational databases. The authors have subsequenty proposed the Hippocratic XML daかabase model[4], an extension of the Hippocratic database model for XML databases. In this paper, we propose a new concept that we cail the dynamic predicate(DP) for effective access control in the Hippocratic XML database model. A DP is a novel concept that represents a dynamically constructed rendition that tan be adapted for determining the accessibility of elements during query execution. DPs allow us to effectively integrate authorization checking into the query plan so that unauthorized elements are excluded in the process of query execution. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 219 times over the top-down access control strategy and by up to 499 times over the bottom-up access control strategy. The major contribution of our, paper is enabling effective integration of access control mechanisms with the query plan using the DP under the Hippocratic XML database model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.7-17
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• 2009

The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.159-168
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• 2012

Relation in the new IT environment, such as the SNS, Cloud, Web3.0, has become an important factor. And these relations generate a transaction. However, existing relational database and graph database does not processe graph structure representing the relationships and transactions. This paper, we propose the technique that can be processed concurrently graph structures and transactions in a scalable complex network system. The proposed technique simultaneously save and navigate graph structures and transactions using the Topic Maps data model. Topic Maps is one of ontology language to implement the semantic web(Web 3.0). It has been used as the navigator of the information through the association of the information resources. In this paper, the architecture of the proposed technique was implemented and design using Cassandra - one of column type NoSQL. It is to ensure that can handle up to Big Data-level data using distributed processing. Finally, the experiments showed about the process of storage and query about typical RDBMS Oracle and the proposed technique to the same data source and the same questions. It can show that is expressed by the relationship without the 'join' enough alternative to the role of the RDBMS.

• Journal of Distribution Science
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• v.13 no.4
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• pp.65-76
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• 2015

Purpose - This article aims to present and test a model regarding franchisors' supporting activities that may positively influence franchisees' attitude toward the franchising headquarter and their own business performance. Moreover, the authors examine the moderating effect of competitive intensity between franchisee attitude and business performance. Most previous research focused on behavioral performance measurements such as satisfaction, trust, and commitment. There are few empirical studies that focus on financial performance data because it is difficult to determine a relational mechanism between behavioral and financial performance. Moreover, financial data is confidential and difficult to collect in many cases. However, this study measures financial performance (e.g., sales revenue per square meter) differently than most previous research, which is mostly focused on the behavioral performance measurements. Research design, data, and methodology - To test our hypotheses, we selected 137 franchisee managers who are running chains of one of the foremost bakery franchise brands in South Korea. This study carefully investigated the reliability, content validity, convergent validity, and discriminant validity of the proposed instrument by analyzing the data obtained from the samples. The data was analyzed using the AMOS structural equation modeling program. Results - The results indicated that: non-financial support activities (e.g., information exchange and communication) had a positive impact on the franchisee attitude toward the franchising headquarter. The franchisee attitude in turn had a positive effect on the headquarters' business performance. Furthermore, competitive intensity could enhance the relationship between franchisee attitude toward franchising headquarter and business performance in a local franchise market. However, financial support activities (e.g., rewards and promotional support) and training had no relationship with either franchisee attitude or business performance. Conclusions - This study provides some practical implications to franchisors in terms of franchise operation and store opening strategies. With respect to the franchise operation strategy, franchisors need to focus on non-financial rather than financial support. Most franchisees consider the necessity of financial support activities and not their sufficiency because these activities are specified in their franchise contract. In addition, it is important for franchisees to maintain a positive attitude for the franchise headquarters. The franchisees with a positive attitude for the franchisor can show a high degree of solidarity for various support activities, and it consequently determines franchisees' sales performance. In terms of franchise store opening strategy, this study suggests an additional criterion that can be considered in determining the location of direct and non-direct management stores (e.g., franchisees' stores). In this research, franchise stores located within high level of competitive intensity are shown to have a high relationship between franchisee attitudes of franchisor support activities and business performance compared to the franchisees located within low competitive intensity level. This result shows that opening non-direct franchise stores is more effective than direct stores in higher competitive market situations. Research contribution, implications, and further research directions are discussed at the end of the paper.