• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.4
• /
• pp.395-402
• /
• 2010

According to increasing the value of real estate and various land use by urbanization and industrialization, the importance of land use has enhanced regardless of above or below the surface. Therefore the changes into Digital Cadastre using high-technical surveying methods has tried to find a solution in the purpose of providing accurate land information to End-users in real time. However Korean cadastral system was established for a short time through the Land & Forest project and it has been used for cadastral surveying until now. Land devastation by the Korean war and the indiscreet land use by unplanned land development of industrialization has raised failures to construct correct cadastral records. So it has occurred that it becomes one of social problems due to the current unmatched areas between adjacent parcels. Therefore government has tried to make an effort to solve the problems such as reducing unmatched areas and introducing a Case study for Cadastral resurvey. And also it is necessary to adopt a suitable Korean model for Cadastral resurvey. In this study, the current Korean situation of cadastral surveying was investigated and the optimized models for various patterns of Land surveying was offered.

• Journal of Korean Society for Quality Management
• /
• v.31 no.3
• /
• pp.136-159
• /
• 2003

The purpose of this paper is to propose the effective guidance of Quality Circle(QC) activities. Since 1975, variety of organizations in Korea have widely implemented QC activities for their management systems. The industries have enthusiastically used QC activities and were influenced from them. However, the academics were less interested in this subject, as a result, there were no systematic guidances for QC activities. Thus, in this paper, the effective guidance for QC activities were suggested which were based on the survey from QC proceedings presented in the companies, in the local areas and the national wide contests. As a result, the first main issue is to pick repeated mistakes up during the process period such as unmatched the causes and effects relations in characteristics diagrams, improper selection of important control items in Pareto diagram and so on. Secondly, how to overcome statistics and use them for QC activities. Thirdly, to remind team members about Quality Control 7 tools. Finally, Minitab(Release-13) software has been found that it is not matched with using Korean Standards(KS).

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.196-202
• /
• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.

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