• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.3
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• pp.340-347
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• 2015

The Commission for Conservation of Antarctic Marine Living Resources (CCAMLR) is utilized to manage krill resources using acoustic data collection and a scientific observer program operating on the fishing boats. However, the acoustic data were contained seriously noise, example of background, spike, and intermittent noise, due to purpose of fish boats. In this study, the noise removal techniques were confirmed the potential of the acoustic data analysis. Acoustic system and frequency used in the survey were commercial echosounder (ES70, SIMRAD) and 200 kHz split beam transducer. Acoustic data were analyzed using Echoview software (Myriax), and general data analysis and new noise removal method was used. Although a variety of noise, most of the noises have been removed using the noise removal processing. We confirmed the possibility of analyzing the acoustic data obtained from fish boats. The results will be useful for analysis of the acoustic data acquired from krill fishing boats.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.319-327
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• 2013

The objective of this research was to develop a relational database management system(RDBMS) to collect, manage and analyze data on agricultural non-point source(NPS) pollution. The system consists of the relational database for agricultural NPS data and data process modules. The data process modules were composed of four sub-modules for data input, management, analysis, and output. The data collected from the watershed of the upper Cheongmi stream and Geunsam-Ri were used in this study. The database was constructed using Apache Derby with meteorological, hydrological, water quality, and soil characteristics. Agricultural NPS-Data Management System(ANPS-DMS) was developed using Oracle Java. The system developed in this study can deal with a variety of agricultural NPS data and is expected to provide an appropriate data management tool for agricultural NPS studies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.3
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• pp.1-9
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• 2016

The current meaning of "Big Data" refers to all the techniques for value eduction and actionable analytics as well management tools. Particularly, with the advances of wireless sensor networks, they yield diverse patterns of digital records. The records are mostly semi-structured and unstructured data which are usually beyond of capabilities of the management tools. Such data are rapidly growing due to their complex data structures. The complex type effectively supports data exchangeability and heterogeneity and that is the main reason their volumes are getting bigger in the sensor networks. However, there are many errors and problems in applications because the managing solutions for the complex data model are rarely presented in current big data environments. To solve such problems and show our differentiation, we aim to provide the solution of actionable analytics and semantic reusability in the sensor web based streaming big data with new data structure, and to empower the competitiveness.

• Journal of Distribution Science
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• v.17 no.12
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• pp.5-12
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• 2019

Purpose - In this paper, we examine the effect of accrual earnings management and real earnings management on the corporate value of retail corporations. Research design, data, and Methodology - The sample cover firms whose settlement is December among retail companies listed on the Korea Stock Exchange's securities market and KOSDAQ market from 2001 to 2016. Of these, the targets were companies with operating profit and equity capital of zero or higher and with sales data. The secondary data was collected through KIS-VALUE data base. The Jones model and the modified Jones model were used for the calculating the accrual-based earnings management and the real earnings management. Result - According to the empirical results, the relationship between accrual earnings management, real earnings management and firm value is positively significant in the retail industry as in manufacturing industry. These results are also significant when controlling the size, profitability, investment, debt ratio, dividend, and growth potential of a company. Conclusions - The characteristics of the distribution business can be identified and the influence of the various kinds of earnings management, which is being researched around the manufacturing industry, can be studied in the distribution industry to give practical implications to investors.

• Agricultural and Biosystems Engineering
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• v.4 no.2
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• pp.50-57
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• 2003

This study was conducted to develop software which provides automatic site-specific field data acquisition, data processing, data mapping and management for precision agriculture. The developed software supports acquisition and processing of both digital and analog data streams. The architecture was object-oriented and each component in the architecture was developed as a separate class. In precision agriculture research, the laborious task of manual ground-truth data collection will be avoided using the developed software. In addition, gathering high-density data eliminates the need for interpolation of values for un-sampled areas. This software shows good potential for expansion and compatibility for variable-rate-application (VRA). The FIM (Field Information Management) computer program provides the user with an easy-to-follow process for field information management for precision agriculture.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Journal of the Korean Solar Energy Society
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• v.27 no.1
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• pp.19-27
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• 2007

The Data quality management system(DQMS) organizes and helps manage and process time sequence data usually collected in monitoring networks and programs. DQMS places particular emphasis on data qualify while maintaining a highly organized and convenient structure for data. It operates with in a flexible and powerful commercial relational data base environment which can readily link to other software platforms from local spreadsheets to network server. The Korea Institute of Energy Research(KIER) has been solar radiation data since May, 1991 for 16 different locations. KIER's new data is expected to be extensively used by designer and researchers of solar systems in lieu of unreliable old ones. Unfortunately, the quality of the data has not always been properly mentioned. The purpose of this study is to systematically identify errors in such data set using DQMS in an effort to rehabilitate error-ridden old data. DET successfully uncovered solar radiation data that had questionable quality.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.224-231
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• 2012

It is necessary to develop flow duration curve (FDC) on each unit watershed in order to analyze flow conditions in the stream for the management of Total Maximum Daily Loads (TMDLs). This study investigated a simple method to develop FDC for the general use of the curve. A simple equation for daily flow estimation was derived from the regression analysis between the 8-day interval flow data of a unit watershed and the daily flow monitoring data of an adjacent upstream region. FDC can be prepared with the calculation of daily flow by the equation for each unit watershed. An annual and a full-period FDC were drawn for each unit watershed in Guem river basin. Standard flow such as low and ordinary flow can be obtained from the annual FDC. Major percentile of flow such as 10, 25, 50, 75 or 90% can be obtained from the full-period FDC. It is considered that this simple method of developing FDC can be utilized more widely for the calculation of standard flow and the assessment of water quality in the process of TMDLs.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.355-378
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• 2015

In recent years, countries such as USA, United Kingdom and Australia have begun to implement national policies in order to systematically manage and share research data produced through publicly funded research. However, Korea as of yet does not have a coordinated research data policy. The lack of infrastructure that supports the sharing and preserving research data results in the poor management and loss of valuable data produced from significant national R&D investments. The need for research data collection, management and sharing goes beyond the outcome assessment of national research: it facilitates the diffusion of research impact and economic development. There is a growing recognition that data sharing is an essential element of research ethics. This research investigates the relevant research data policies and methods of governance at the national level using a case study analysis. United Kingdom was selected as a case study target as it shows a wide variety of policy examples and instruments. In particular, this research focuses on the UK's national legal framework for research data sharing, analyzes the RCUK (Research Councils UK)'s data policies, activities at the seven research councils under RCUK as well as several supporting institutions. Based on the analyses, this research offers a national roadmap for better managing and sharing of research data in Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.433-435
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• 2022

In this paper, we introduce a computing resource standard metadata schema design plan for registering, retrieving, and managing computing resources used for research data analysis and utilization in the Korea Research Data Commons(KRDC). KRDC is a joint utilization system of research data and computing resources to maximize the sharing and utilization of research data. Computing resources refer to all resources in the computing environment, such as analysis infrastructure and analysis software, necessary to analyze and utilize research data used in the entire research process. The standard metadata schema for KRDC computing resource management is designed by considering common attributes for computing resource management and other attributes according to each computing resource feature. The standard metadata schema for computing resource management consists of a computing resource metadata schema and a computing resource provider metadata schema. In addition, the metadata schema of computing resources and providers was designed as a service schema and a system schema group according to their characteristics. The standard metadata schema designed in this paper is used for computing resource registration, retrieval, management, and workflow services for computing resource providers and computing resource users through the KRDC web service, and is designed in a scalable form for various computing resource links.