• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.1357-1360
• /
• 2009

In this study, the 0-th order diffraction could be efficiently removed with the obtained data for one hologram using the numerical reconstruction method. This method has a reduced data acquisition and processing time compared with the existing method wherein the data for two or more phase holograms are obtained for regeneration, and efficiently eliminates the 0-th order diffraction.

• The KIPS Transactions:PartD
• /
• v.15D no.2
• /
• pp.163-170
• /
• 2008

Due to the proliferation of the Internet and intranet, a new application domain called stream data processing has emerged. Stream data is real-timely and continuously generated. In this paper, we focus on the processing of stream data whose characteristics vary unpredictably by over time. Particularly, we suggest a method which generates an efficient operator execution order called WT-Heuristics. WT-Heuristics efficiently determines the operator execution order since it considers only two adjacent operators in the operator execution order. Also, our method changes the execution order with respect to the change of data characteristics with minimum overheads.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 1982.10a
• /
• pp.51-55
• /
• 1982

The analysis of Korean language by the first order markov source is carried out. The calculated entropy of the first order Markov source is also included. The results presented here are new data. The data can be useful in designing the keyboard pattern of terminal and the automatic discrimination of monosyllable in Korean language.

• Journal of the Korean Data and Information Science Society
• /
• v.10 no.2
• /
• pp.299-311
• /
• 1999

In this paper the single and product moments of order statistics of the doubly truncated Rayleigh distribution are studied. Some recurrence relations of order statistics are derived. Using order statistics, also characterization of the Rayleigh distribution are derived.

• Journal of Information Technology Applications and Management
• /
• v.10 no.1
• /
• pp.111-125
• /
• 2003

This paper proposes a product data model that can express and enforce integrity constraints on product structure during engineering changes (ECs). The model adopts and extends an active object-oriented database model in order to Integrate IC data and their integrity constraints. Tightly integrated with product structure, It will enable designers to maintain and exchange consistent EC data throughout the product life cycle. In order to properly support operations for ECs, the model provides the data, operations, and Event-Condition-Action rules for nested ECs and simultaneous EC applications to multiple options. in addition, the EC objects proposed In the model integrate the data and Integrity constraints into a unified repository. This repository enables designers to access all EC data and integrity constraints through the product structure and relationships between EC objects. This paper also describes a prototype product data management system based on the proposed model In order to demonstrate its effectiveness.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.45-48
• /
• 2013

In this paper, we proposed an Indexing Structure System (ISS) based on Apache Hadoop in Wireless Sensor Network (WSN). Nowadays sensors data continuously keep growing that need to control. Data constantly update in order to provide the newest information to users. While data keep growing, data retrieving and storing are face some challenges. So by using the ISS, we can maximize processing quality and minimize data retrieving time. In order to design ISS, Indexing Types have to be defined depend on each sensor type. After identifying, each sensor goes through the Indexing Structure Processing (ISP) in order to be indexed. After ISP, indexed data are streaming and storing in Hadoop Distributed File System (HDFS) across a number of separate machines. Indexed data are split and run by MapReduce tasks. Data are sorted and grouped depend on sensor data object categories. Thus, while users send the requests, all the queries will be filter from sensor data object and managing the task by MapReduce processing framework.

• International journal of advanced smart convergence
• /
• v.8 no.3
• /
• pp.46-53
• /
• 2019

When a partitioned structure is derived from a data set using a clustering algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of data. This problem is known as the order bias problem. Many algorithms in machine learning fields try to achieve optimized result from available training and test data. Optimization is determined by an evaluation function which has also a tendency toward a certain goal. It is inevitable to have a tendency in the evaluation function both for efficiency and for consistency in the result. But its preference for a specific goal in the evaluation function may sometimes lead to unfavorable consequences in the final result of the clustering. To overcome this bias problems, the first clustering process proceeds to construct an initial partition. The initial partition is expected to imply the possible range in the number of final clusters. We apply the data centric sorting to the data objects in the clusters of the partition to rearrange them in a new order. The same clustering procedure is reapplied to the newly arranged data set to build a new partition. We have developed an algorithm that reduces bias effect resulting from how data is fed into the algorithm. Experiment results have been presented to show that the algorithm helps minimize the order bias effects. We have also shown that the current evaluation measure used for the clustering algorithm is biased toward favoring a smaller number of clusters and a larger size of clusters as a result.

• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• v.5 no.2
• /
• pp.43-49
• /
• 2024

Ecological monitoring provides indispensable data for biodiversity conservation and sustainable resource management. However, the complexity and variability inherent in ecological monitoring data necessitate robust verification processes to ensure data integrity. This study employed Benford's Law, a statistical principle traditionally used in fields such as finance and health sciences, to evaluate the authenticity of ecological monitoring data related to the abundance of migratory bird species across various locations in South Korea. Benford's Law anticipates a specific logarithmic distribution of leading digits in naturally occurring numerical datasets. Our investigation involved two stages of analysis: a first-order analysis considering the leading digit and a second-order analysis examining the first two digits of bird population counts. While the first-order analysis displayed moderate conformity to Benford's Law that suggested overall data integrity, the second-order analysis revealed more pronounced deviations, indicating potential inconsistencies or inaccuracies in certain subsets of the data. Although our data did not perfectly align with Benford's Law, these deviations underscore the complex nature of ecological research, which is influenced by a multitude of environmental, methodological, and human factors.

• IE interfaces
• /
• v.18 no.2
• /
• pp.148-157
• /
• 2005

The manufacturing industry with Make-to-Order production system is difficult to decide the standard information for the product and the demand is variable to estimate. In this paper, we concerned with the process planning method using data mining in the manufacturing industry with Make-to-Order environment. The subject of our study is the industry transformer plant which is received an diverse order of customer and then produced the product. Currently, process planning method is classified the standard information by hand based on the acquired knowledge through the experience. The standard information stored the various information, such as work sequence, time and so on. This process planning method needs an experts which possesses the field experience for several years. For the product specification which is varied in each order, current process planning method is not efficient due to need many times To solve this problem, we extract the information using data mining process for each processing time, and then construct the knowledge base. We propose a method which is the process planning of the industry transformer product in Make-to-Order environment using the knowledge base.

• Journal of Korea Foundry Society
• /
• v.42 no.1
• /
• pp.35-41
• /
• 2022

In the present paper, the data management of casting processes has been discussed. In order to construct a smart factory in the foundry industry, understanding of the whole casting processes has to be in the first place. Casting process data can be obtained at the kiosk operated by casting engineers and data acquired by sensors in the foundry facility. However, preprocessing of the casting process data must be carried out in order to analyze the casting process by the data. Techniques and some examples for data preprocessing in the foundry was introduced.