• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.23-31
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• 1999

Using Information Systems to process massive data, quickly and exactly, organizations have chances to enhance their performance. The limitations of IS function to support decision-making, however, have been frequently mentioned In this context, in addition to traditional mathematical model that is a kernel DSS, the needs for Data Warehouse which is a system supporting business process analysis are emerging. In this study, for those needs first we introduce issues of implementation methodology for D/W, especially various models relating development process. Then we investigate correlation between these models and key factors for success of R/W.

• 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.

• The Journal of Bigdata
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• v.2 no.2
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• pp.33-46
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• 2017

Service part has the attribute causing a difficulty of the systematic management like a kind of diversity, uncertainty of demand, high request for quick response against general complete product. Especially, order picking is recognized as the most important work in the warehouse of the parts since inbound cycle of the service part long but outbound cycle is relatively short. But, increasing work efficiency in the warehouse has a limitation that cycle, frequency and quantity for the outbound request depend on the inherent features of the part. Through this research, not only are the types of the parts classified with the various and specified data but also the method is presented that it minimizes (that) the whole distances of the order picking and store location about both inbound and outbound by developing the model of the demand prediction. Based on this study, I expect that all of the work efficiency and the space utilization will be improved without a change of the inbound and outbound quantity in the warehouse.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2273-2286
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• 2000

In order to acquire the precise and fast response for an analytical query, proper selection of the views to materialize in data warehouse is very crucial. In traditional view selection algorithms, the whole relations are considered to be selected as materialized views. However, materializing the whole relations rather than a part of relations results in much worse performance in terms of time and space cost. Therefore, we present an improved algorithm for selection of views to materialize using clustering method to overcome the problem resulted from conventional view selection algorithms. In the presented algorithm, ASVMRT(Algorithm for Selection of Views to daterialize using Iteduced Table). we first generate reduced tables in clata warehouse using automatic clustering based on attrihute-values density, then we consider the combination of reduced tables as materialized views instead of the combination of the original hase relations. For the justification of the proposecl algorithm. we show the experimental results in which both time and space cost are approximately 1.8 times better than the conventional algorithms.

• Information Systems Review
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• v.14 no.2
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• pp.47-63
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• 2012

The concept of data warehousing was born in the 1970-80s at the same time when Wal-Mart's growing database gave birth to its need to view records in a more effective way. As the world's largest retail warehouse, Wal-Mart represents the world's largest data warehouse. A large portion of the discussionaround Wal-Mart's database management heretofore has only been process-centric, however, not its data per se. The study largely involves technical concepts around database and takes a deep look at Wal-Mart's chronicle of pre-implementation (preparation), implementation, and post-implementation (evaluation) of the data warehousing project. The highlight underlies how Wal-Mart acted against solving endless problems and was able to gear their data management to business contribution. By revisiting their data warehousing project case from a current point of view, we expect their lessons to be still available and applicable. With the renewed interest in (big) data and business intelligence, Wal-Mart's high respect for data and technology holds a lot more meaning than a couple of decades ago.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.109-121
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• 1992

In this paper, we address a layout design problem for determining a K-class-based dedicated storage layout in an automated storage retrieval system. K-class-based dedicated storage employs K zones in which lots from a class of products are stored randomly. Zones form a partition of storage locations. Our objective function is to minimize the expected single command travel time, which is expressed as a set function of space requirements for zones, average demand rates from classes, and one-way travel times from the pickup/deposit station to locations. We construct a heuristic algorithm based on analytical results and a local search method, the methodology deveolped can be used with easily-available data by warehouse planners to improve the throughput capacity of a conventional warehouse as well as an AS/RS.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.141-142
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• 2022

Recently, fires in logistics warehouses in Korea are continuously increasing. In addition, the need for fire safety in logistics warehouses is emerging. So, it is believed that it is necessary to establish standards for vent facilities under effective smoke control for the evacuation safety of residents in logistics warehouses. Therefore, this paper compares the standards related to combustion facilities in Korea, the United States, and Japan, and applies the design method to logistics warehouses of domestic materials to predict smoke drop time and use it as a basic data for improving domestic smoke facilities standards.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.579-588
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• 2015

The data model for structural experiment information formally organizes the information involved in the structural experiments before the data repository using the data model is implemented. The data model is particularly required for the data repositories for the large-scale structural experiment information and the general information for various types of experiments, such as the NEEShub Project Warehouse developed by NEES. This paper proposes criteria for evaluating the organization and the use of design model for structural experiment information. The term of AVE(attribute value existence) indicates the ratio of attributes who values exist in objects, and then used for defining the Attribute AVE for the use of an attribute, the Class AVE for a class, the Class Level AVE for a class including its lower-level classes, the Project AVE for a project including all classes at class levels, and the Data Model AVE for a data model including projects. These criteria are applied to the projects in the NEES data model, and it is successively possible to numerically describe the evaluation of the use of classes and attributes in the data model.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.353-362
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• 2006

A data warehouse is a data repository that enables users to store large volume of data and to analyze it effectively. In this research, we investigate an algorithm to establish a multidimensional data cube which is a powerful analysis tool for the contents of data warehouses and databases. There exists an inevitable retrieval overhead in a multidimensional data cube due to the sparsity of the cube. In this paper, we propose a dense sub-cube extraction algorithm that identifies dense regions from a large sparse data cube and constructs the sub-cubes based on the dense regions found. It reduces the retrieval overhead remarkably by retrieving those small dense sub-cubes instead of scanning a large sparse cube. The algorithm utilizes the bitmap and histogram based techniques to extract dense sub-cubes from the data cube, and its effectiveness is demonstrated via an experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.181-186
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• 2012

Recently there has been many active researches on searching similar sequences from data generated with the passage of time. Those data are classified as time series data or sequence data and have different semantics from scalar data of traditional databases. In this paper similar sequence search retrieves sequences that have a similar trend of value changes. At first we have transformed the original sequences by applying DFT. The converted data are more suitable for trend analysis and they require less number of attributes for sequence comparisons. In addition we have developed a region-based query and we applied bitmap indexes which could show better performance in data warehouse. We have built bitmap indexes with varying number of attributes and we have found the least cost query plans for efficient similar sequence searches.