• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.528-533
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• 2010

This research is part of the development of Data Acquisition embedded system that specifically use in ship. The purpose of this data acquisition system mainly is to acquire data from multiple sensors or others related external devices and it will further discuss in this paper. The data collecting, hardware design, software design and the final project outcome of this data acquisition system will be discussed in this paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.317-324
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• 2005

Korean shipyards have accumulated a great amount of data. But they do not have appropriate tools to utilize the data in practical works. Engineering data contains experts' experience and know-how In its own. It is very useful to extract knowledge or information from the accumulated existing data by using datamining technique. This paper treats an evolutionary computation method based on genetic programming (GP), which can be one of the components to realize datamining.

• Journal of Platform Technology
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• v.8 no.2
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• pp.3-9
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• 2020

Big Data is a new concept in the global and local area. This field has gained tremendous momentum in the recent years and has attracted attention of several researchers. Big Data is a data analysis methodology enabled by recent advances in information and communications technology. However, big data analysis requires a huge amount of computing resources making adoption costs of big data technology. Therefore, it is not affordable for many small and medium enterprises. We survey the concepts and characteristics of Big Data along with a number of tools like HADOOP, HPCC for managing Big Data. It also presents an overview of big data like Characteristics of Big data, big data technology, big data management tools etc. We have also highlighted on some challenges and opportunities related to the fields of big data.

• Korean Journal of Computational Design and Engineering
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• v.20 no.2
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• pp.145-158
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• 2015

ISO 15926 is an international standard for the sharing and integration of plant lifecycle information. Plant design data consist of logical configuration, equipment specifications, 2D piping and instrument diagrams (P&IDs), and 3D plant models (shape data). Although 3D computer-aided design (CAD) data is very important data across the plant lifecycle, few studies on the exchange of 3D CAD data using ISO 15926 have been conducted so far. For this, we analyze information requirements regarding plant 3D design in the process industry. Based on the analysis, ISO 15926 templates are defined for the representation of constructive solid geometry (CSG) - based 3D design data. Since system environments for 3D CAD modeling and Semantic Web technologies are different from each other, we present system architecture for processing and visualizing plant 3D design data in the Web Ontology Language (OWL) format. Through the visualization test of ISO 15926-based 3D design data for equipment with a prototype system, feasibility of the proposed method is verified.

• Journal of Power System Engineering
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• v.20 no.4
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• pp.44-51
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• 2016

An investigation on reliability of reanalysis wind data was conducted using the met mast wind data at four coastal regions, Jeju Island. Shinchang, Handong, Udo and Gangjeong sites were chosen for the met mast sites, and ERA-Interim and MERRA reanalysis data at two points on the sea around Jeju Island were analyzed for creating Wind Statistics of WindPRO software. Reliability of reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those from Wind Statistics of WindPRO software. The relative error was calculated for annual average wind speed, wind power density and annual energy production. In addition, Weibull wind speed distribution and monthly energy production were analyzed in detail. As a result, ERA-Interim reanalysis data was more suitable for wind resource assessment than MERRA reanalysis data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.1
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• pp.32-40
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• 2017

Recently, the amount of data to be processed and the complexity thereof have been increasing due to the development of information and communication technology, and industry's interest in such big data is increasing day by day. In the shipbuilding and offshore industry also, there is growing interest in the effective utilization of data, since various and vast amounts of data are being generated in the process of design, production, and operation. In order to effectively utilize big data in the shipbuilding and offshore industry, it is necessary to store and process large amounts of data. In this study, it was considered efficient to apply Hadoop and R, which are mostly used in big data related research. Hadoop is a framework for storing and processing big data. It provides the Hadoop Distributed File System (HDFS) for storing big data, and the MapReduce function for processing. Meanwhile, R provides various data analysis techniques through the language and environment for statistical calculation and graphics. While Hadoop makes it is easy to handle big data, it is difficult to finely process data; and although R has advanced analysis capability, it is difficult to use to process large data. This study proposes a big data platform based on Hadoop for applications in the shipbuilding and offshore industry. The proposed platform includes the existing data of the shipyard, and makes it possible to manage and process the data. To check the applicability of the platform, it is applied to estimate the weights of offshore structure topsides. In this study, we store data of existing FPSOs in Hadoop-based Hortonworks Data Platform (HDP), and perform regression analysis using RHadoop. We evaluate the effectiveness of large data processing by RHadoop by comparing the results of regression analysis and the processing time, with the results of using the conventional weight estimation program.

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.150-156
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• 2003

This paper explored the use of an algorithm for the data mining and method in handling missing data which had generated enhanced association patterns observed using the data illustrated here. The evaluations showed that more association patterns are generated in the second analysis which suggests more meaningful rules than in the first situation. It showed that the model offer more precise and important association rules that is more valuable when applied for business decision making. With the discovery of accurate association rules or business patterns, strategies could be efficiently planned out and implemented to improve marketing schemes. This investigation gives rise to a number of interesting issues that could be explored further like the effect of outliers and missing data for detecting fraud and devious database entries.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.153-154
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• 1998

As the fundamental study to set up the algorithm of the X-ray dosimeter, we obtained the data using the designed X-ray input circuit and the semiconductor sensor. We measured the data of the ten time in the various kVp, mA and sec and then the obtained each data is averaged. After the data obtained under the circumstances of total 600, these data saved the database. We developed the algorithm of the X-ray dosimeter using the saved data. Later the result of this study is so important to design X-ray dosimeter.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.129-132
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• 1997

Laser scanning is widely used due to its fast measuring and high precision, and the segmentation of the scanned data is necessary for the fast and efficient surface modelling. But most segmentation techniques are based on the very regular data and the adaptation of previous techniques to the scanned data does not usually produce good result. A new approach to perform the segmentation on the scanned data is introduced to deal with problems during reverse engineering process. The approach is based on the triangulated data and its result is depending on the some user-defined criteria. The result is illustrated to demonstrate its adaptability to the measured data on free-form surface and the each result by different criteria is compared respectively.