• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.391-399
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• 2017

Various efforts for reducing greenhouse gas emission due to intensified climate change are being made continuously in all industrial fields, including theimplementation of"green logistics" as countermeasures in the logistics industry. Therefore, energy and greenhouse gas management are necessary for logistics warehouses in the logistics industry. In this study, asurvey on the recognition of logistics center managers and the management elements werecarried out to identify the energy management status of logistics centers. This study was carried out to identify the energy management status of warehouses and the perception of energy managers. The total numberof warehouses and the classification by purpose of use were examinedusing public DB to identify the present status of the warehouses preferentially. Based on the result, asurvey for identifying the present status of energy management and the perception of energy managers targeting 300 warehouses was carried out. Warehouse managers have shown considerable interest in energy management but they experiencedifficulty in this area due to a lack of energy management infrastructure and expertise. In the case of an energy audit, most warehouse managers had no experience in energy auditsbecausethe energy audits werenot mandatory for warehouses. The results of this study can be used as basic data to determineenergy management status and energy management elements for developing IT systems for the energy management of logistics warehouses.

• Journal of Families and Better Life
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• v.23 no.1 s.73
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• pp.125-137
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• 2005

Information technology is an important driving force that has changed consumer information environments. In order to adjust in the new environments, consumers need an innovative information system. The purpose of this study was to develop a Consumer Information System (CIS). CIS is a device that supports consumer's decision-making process and elevates consumer information competence. The CIS was constructed by the following steps: (1) organization of developers, (2) systematization of consumer information, (3) data loading, (4) integration of consumer database: data warehouse, (5) data distribution, (6) composition of data mart, (7) use of data access tools: data-mining, OLAP, statistical analysis, Q+R, (8) data visualization: web server.

• Interdisciplinary Bio Central
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• v.3 no.3
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• pp.9.1-9.5
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• 2011

Entity Attribute Value (EAV) is the widely used solution to represent high dimensional and sparse data, but EAV is not search efficient for knowledge extraction. In this paper, we have proposed a search efficient data model: Optimized Entity Attribute Value (OEAV) for physical representation of high dimensional and sparse data as an alternative of widely used EAV. We have implemented both EAV and OEAV models in a data warehousing en-vironment and performed different relational and warehouse queries on both the models. The experimental results show that OEAV is dramatically search efficient and occupy less storage space compared to EAV.

• The Journal of Bigdata
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• v.1 no.1
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• pp.53-60
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• 2016

Data of central government and local government was collected automatically from the public data portal. And we did the multidimensional analysis based on various perspective like file format and present condition of public data. To complete this work, we constructed Data Warehouse based on the other countries' evaluation index case. Finally, the result from service level evaluation by using multidimensional analysis was used to display each area, establishment, fields.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.135-149
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• 2011

In this paper, we propose the high-risk group detection model for patients with high blood pressure using case-based reasoning. The proposed model can be applied for public health maintenance organizations to effectively manage knowledge related to high blood pressure and efficiently allocate limited health care resources. Especially, the focus is on the development of the model that can handle constraints such as managing large volume of data, enabling the automatic learning to adapt to external environmental changes and operating the system on a real-time basis. Using real data collected from local public health centers, the optimal high-risk group detection model was derived incorporating optimal parameter sets. The results of the performance test for the model using test data show that the prediction accuracy of the proposed model is two times better than the natural risk of high blood pressure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1971-1978
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• 2011

In RFID-based cold-storage systems, product locations are recognized as the logical locations of RFID readers which are attached to the entrance of the cold rooms. However, through these methods, product locations can be incorrect in many different situations of a storage. Cold storage rooms have a huge rage in temperature, and the product in the cold-storage spoils easily. Therefore, highly precise product locations is very important for the product quality In this paper, a new approach is suggested to manage the storage location inaccuracy by adding two readers to existing forklift and attaching RFID tags to the ceiling. One reader recognizes ceiling tags to acquire location data, and the other recognizes product tags to acquire product detail data loaded on the forklift. The product can be seamlessly tracked and traced in realtime by monitoring and analyzing data gathered from these readers. Through the proposed location management method, the effectiveness of the product management in cold-storage can be improved consequently.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.143-150
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• 2009

Spatial data warehouses are a system managing manufactured data through ETL step with extracted spatial data from spatial DBMS or various data sources. In load period, duplicated spatial data in the same subject are not useful in extracted spatial data dislike aspatial data and waste the storage space by the feature of spatial data. Also, in case of extracting source data on heterogeneous system, as those have different spatial type and schema, the spatial extract method is required for them. Processing a step matching address about extracted spatial data using a standard Geocoding DB, the exiting methods load formal data set. However, the methods cause the comparison operation of extracted data with Geocoding DB, and according to integrate spatial data by subject it has problems which do not consider duplicated data among heterogeneous spatial DBMS. This paper proposes efficient extracting method to integrate update query extracted from heterogeneous source systems in data warehouse constructer. The method eliminates unnecessary extracting operation cost to choose related update queries like insertion or deletion on queries generated from loading to current point. Also, we eliminate and integrate extracted spatial data using update query in source spatial DBMS. The proposed method can reduce wasting storage space caused by duplicate storage and support rapidly analyzing spatial data by loading integrated data per loading point.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2863-2874
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• 1999

Apartment auction is a system that is used for the citizens to get a house. This paper deals with the implementation of a web-based intelligent decision support system using OLAP technique and data mining technique for auction decision support. The implemented decision support system is working on a real auction database and is mainly composed of OLAP Knowledge Extractor based on data warehouse and Auction Data Miner based on data mining methodology. OLAP Knowledge Extractor extracts required knowledge and visualizes it from auction database. The OLAP technique uses fact, dimension, and hierarchies to provide the result of data analysis by menas of roll-up, drill-down, slicing, dicing, and pivoting. Auction Data Miner predicts a successful bid price by means of applying classification to auction database. The Miner is based on the lazy model-based classification algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm to reflect the characteristics of auction database.

• The Journal of Society for e-Business Studies
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• v.7 no.3
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• pp.93-103
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• 2002

The combination of data warehousing and Internet technology produces a new concept - web warehousing. Due to the availability of web technologies and the need to make prompt decisions with timely information, web warehousing is emerging as a key strategic business weapon. Yet despite the many promising benefits of web warehousing, researchers have also identified several challenges, including scalability and availability. With the rise of the Internet and data centric computing applications, the use of new Storage Area Network (SAN) technology has been spotlighted for the possibility of a new data repository for web warehousing. In this article, the two new concepts of web warehousing and storage area networks are introduced. In particular, a SAN is discussed in detail as an alternative data repository to overcome the current limitations of web warehousing.

• 한국디지털정책학회:학술대회논문집
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• 2003.12a
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• pp.11-24
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• 2003

It is far more expensive for companies to acquire new customers than it is to retain customers. As a result, companies are turning to Customer Relationship Management (CRM) in order to make decisions about managing the relationship and the profitability of those customer relationships. CRM is a strategy that integrates the concepts of Knowledge Management, Data Mining and Data Warehousing in order to support the organization's decision -making process to retain long-term and profitable relationships with its customers. This paper examines the design implications that CRM poses to data warehousing. We then present a robust data warehouse schema to support CRM analyses and decisions. For example, the proposed schema could be used to calculate customer profitability and to identify social networks of influence between customers. The paper also discusses future areas for research pertaining to CRM data warehousing and data mining.