• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.87-94
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• 2015

Recently, management based on statistical data has become a big issue and the importance of the statistics has been emphasized for the management innovation in the defense area. However, the Military Management based on the statistics is hard to expect because of the shortage of the statistics in the military. There are many military information systems having great many data created in real time. Since the infrastructure for gathering data form the many systems and making statistics by using gathered data is not equipped, the usage of the statistics is poor in the military. The Analytical Defense Statistics System is designed to improve effectively the defense management in this study. The new system having the sub-systems of Data Management, Analysis and Service can gather the operational data from interlocked other Defense Operational Systems and produce Defense Statistics by using the gathered data beside providing statistics services. Additionally, the special function for the user oriented statistics production is added to make new statistics by handling many statistics and data. The Data Warehouse is considered to manage the data and Online Analytical Processing tool is used to enhance the efficiency of the data handling. The main functions of the R, which is a well-known analysis program, are considered for the statistical analysis. The Quality Management Technique is applied to find the fault from the data of the regular and irregular type. The new Statistics System will be the essence of the new technology like as Data Warehouse, Business Intelligence, Data Standardization and Statistics Analysis and will be helpful to improve the efficiency of the Military Management.

• The Journal of Fisheries Business Administration
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• v.31 no.2
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• pp.119-132
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• 2000

One of most important wort to build Fisheries Policy Information Systems(FPIS) is related to connect the data warehouse between fisheries departments, This paper presents the developing strategies to build the FPIS. First, developing the FPIS needs to compensate the laws and regulations with assistance of fisheries departments. Second, FPIS developer needs to cooperate the related fisheries departments deeply, Third, developing the data warehouse will be contribute to improve criterion and statistics of fisheries data. Forth, For experts of systems use the FPIS, they are needed to educate for appling the systems in the fisheries environments.

• Korean Journal of Occupational Health Nursing
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• v.26 no.3
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• pp.133-141
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• 2017

Purpose: The purpose of this study was to identify the relationship between work-related characteristics and job stressors and the factors influencing musculoskeletal symptoms of the warehouse employees. Methods: The research was a cross-sectional, descriptive study. Data were collected from 319 warehouse employees who agreed to participate in the study by using self-report questionnaires. Data were analyzed using descriptive statistics, $x^2-test$, and logistic regression analysis (SPSS 18.0). Results: The overall prevalence of musculoskeletal symptoms was 37.6%. The logistic regression analysis revealed a posture that renders fatigue or pain, repetitive work, and a higher total score of job stressors as the risk factors for musculoskeletal symptoms in many body parts. Conclusion: Employers should plan to educate employees who work in warehouses about the correct working posture to prevent musculoskeletal diseases, stop repetitive work, and manage job stressors.

• Korea Trade Review
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• v.46 no.4
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• pp.149-166
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• 2021

This paper aims to reduce the frequency of dangerous goods storage accidents in China. Advocating the managers of warehousing and logistics enterprises to pay attention to the operation process of dangerous goods warehousing business. Improving the safe storage and management capabilities of dangerous goods warehouses. This article first collects official data on dangerous goods storage accidents in China and conducts a general statistical analysis of the accidents. Based on the results of accident statistics and related literature research on dangerous goods storage management, establish a dangerous goods storage safety management factor system, use the analytic hierarchy process, establish a factor importance questionnaire and implement data collection. Through statistics, this paper finds that the storage accidents of dangerous goods in China in the past ten years mainly occurred in the inbound phase of dangerous goods and the storage phase of dangerous goods warehouses. Through the results of the analytic hierarchy process, it is found that the professionalism of the dangerous goods storage practitioners, the compliance of the practitioners with safety regulations, and the awareness of operational safety are the most important.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.25-37
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• 2009

This Study constructs a dashboard system to synthetically and systematically monitor national R&D information based on data warehouse. Managing the national R&D statistics and trend is important since it provides data for policies and decision making for national R&D. Many agencies related to national R&D information collect the basic R&D statistic data which provides the basis of logical decision making and R&D policies. The data has not well been used. The data has not been consistently collected nor managed. The raw data has not been organized nor processed to meet various demands. The needs has been arisen for a consistent national R&D monitoring system to increase the relevance, accessibility and efficiency of data for various users. This study selects 25 key indicators based on the user requirements and designs data warehouse for supporting the indicators using star schema. The dashboard system is developed in this study provides the infrastructure of monitoring national R&D information and analytic environment of supporting statistical analysis and time-series data analysis.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.75-91
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• 2005

This study designs an integrated data architecture to systematically manage the agricultural statistics database. Managing the agricultural statistics is important since it provides data for policies and decision making for agribusinesses. Ministry of Agriculture and the National Statistical Office collect the basic agricultural statistic data which provides the basis of logical decision making and agricultural policies. However, the agricultural statistic data has not well been used. The data has not been consistently collected nor managed. The raw data has not been organized nor processed to meet various demands. The needs has been arisen for a consistent agricultural statistics system to increase the relevance, accessibility, and efficiency of data for various users. There are massive amount of data accumulated over a long time period. Introducing the new system and reorganizing the data will bear large risks. A systematic method is required to reduce the risks in planing, building, and maintaining the database without hindering administration. This study provides a design of the agricultural statistics system architecture based on the user requirement analysis (URA) and similar systems abroad. We have also build a prototype to check the implementability of the system design.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.407-416
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• 2003

As the usage of database systems dramatically increases and the amount of data pouring into them is massive, the performance administration techniques for using database systems effectively are getting more important. Especially in data warehouses, the performance management is much more significant mainly because of large volume of data and complex queries. The objectives and characteristics of data warehouses are different from those of other operational systems so adequate techniques for performance monitoring and tuning are needed. In this paper we extend functionalities of the DBMax, a performance administration tool for Oracle database systems, to apply it to data warehouse systems. First we analyze requirements based on summary management and ETL functions they are supported for data warehouse performance improvement in Oracle 9i. Then, we design architecture for extending DBMax functionalities and implement it. In specifics, we support SQL tuning by providing details of schema objects for summary management and ETL processes and statistics information. Also we provide new function that advises useful materialized views on workload extracted from DBMax log files and analyze usage of existing materialized views.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.94-106
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• 2014

Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance.

• International Journal of Reliability and Applications
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• v.3 no.4
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• pp.155-164
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• 2002

This paper focuses on how modem data mining can be integrated with real-time relational databases and commercial data warehouses to improve reliability in real-time. An important Issue for many manufacturers is the development of relational databases that link key product attributes with real-time process parameters. Helpful data for key product attributes in manufacturing may be derived from destructive reliability testing. Destructive samples are taken at periodic time intervals during manufacturing, which might create a long time-gap between key product attributes and real-time process data. A case study is briefly summarized for the medium density fiberboard (MDF) industry. MDF is a wood composite that is used extensively by the home building and furniture manufacturing industries around the world. The cost of unacceptable MDF was as large as 5% to 10% of total manufacturing costs. Prevention can result In millions of US dollars saved by using better Information systems.

• The Journal of Fisheries Business Administration
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• v.31 no.1
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• pp.55-71
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• 2000

Being Changed the international fisheries situation to begin the WTO, it is important to increase the international competition power in fisheries environment to related our country. One of most important work is to build the Fisheries Information Systems(FIS), FIS should give to increase the efficiency of fisheries policies, to share the fisheries informations, and to increase the competitive power of international fisheries environment. On the conclusion, this paper has four expect effects to build the FIS. First, fisheries information will be supplied the clean fisheries policies based on FIS. Second, The Data Warehouse of FIS will be contributed to improve the criterion and statistics of fisheries data. Third, Fisheries Administration will increase the service between fisheries institutes using the FIS. Finally, fisheries administration will use the fisheries data efficiently as integrating the fisheries data into information systems.