• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.1025-1032
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• 2003

Percentiles are convenient measures of the entire range of values of simulation outputs. However, unlike means and standard deviations, the observations have to be stored since calculation of percentiles requires several passes through the data. Thus, percentile (PE) requires a large amount of computer storage and computation time. The best possible computation time to sort n observations is (O($nlog_{2}n$)), and memory proportional to n is required to store sorted values in order to find a given order statistic. Several approaches for extimating percentiles in RS(regenerative simulation) and non-RS, which can avoid difficulties of PE, have been proposed in [11, 12, 21]. In this paper, we implemented these three approaches known as : leanear PE, batching PE, spectral $P^2$ PE in the context of sequential steady-state simulation. Numerical results of coverage analysis of these PE approachs are present.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.63-84
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• 2023

Purpose - The purpose of this study is to examine the effect of CSR activities on innovation performance and to identify the mediating role of knowledge sharing and innovation behaviors between CSR activities and innovation performance. In addition, the purpose of this study is to verify the role of sequential mediating effect of knowledge sharing and innovation behavior between CSR activities and innovation performance. Design/methodology/approach - This study collected survey data from 293 organizational members working in Chinese companies. The exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability analysis, correlation analysis and process macro were used in order to analyze the data. Findings - First, this study verified that CSR activities had a significant positive effect on knowledge sharing, innovation behavior, and innovation performance. Second, it was found that knowledge sharing had a significant positive effect on innovation behavior and innovation performance. Third, it was verified that innovation behavior had a significant positive effect on innovation performance. Fourth, knowledge sharing and innovation behavior had a sequential mediating effect in the relationship between CSR activities and innovation performance. Research implications or Originality - With the uncertainty of the environment and the intensification of competition among companies, more and more companies begin to pay attention to innovation. Different from existing studies, this study focuses on CSR activities, identifies the role of CSR activities, explores ways to guide innovation performance, and verifies the sequential mediating role of knowledge sharing and innovation behavior. Through this measure, the importance of knowledge sharing and innovative behavior among organizational members is emphasized, solutions to strengthen innovation are explored, and theoretical and practical implications are provided for companies.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.681-691
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• 2010

LiDAR waveform decomposition plays an important role in LiDAR data processing since the resulting decomposed components are assumed to represent reflection surfaces within waveform footprints and the decomposition results ultimately affect the interpretation of LiDAR waveform data. Decomposing the waveform into a mixture of Gaussians involves two related problems; 1) determining the number of Gaussian components in the waveform, and 2) estimating the parameters of each Gaussian component of the mixture. Previous studies estimated the number of components in the mixture before the parameter optimization step, and it tended to suggest a larger number of components than is required due to the inherent noise embedded in the waveform data. In order to tackle these issues, a new LiDAR waveform decomposition algorithm based on the sequential approach has been proposed in this study and applied to the ICESat waveform data. Experimental results indicated that the proposed algorithm utilized a smaller number of components to decompose waveforms, while resulting IMP value is higher than the GLA14 products.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• Archives of design research
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• v.11 no.1
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• pp.109-118
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• 1998

Recently, the importance of user-interface design has been increasing due to the development of electronic and semiconductor technology. Under these surroundings a lot of Approaches that are for the analysis of video sequential data have been developed. The study on the method of analysing various aspects in the use of real product should find the characteristics of users' behavior. Also, the study should include the interaction dffects among these aspects. For these reasons this study proposed an analysis method for the video sequential data of usability test. The study begins with discussing the nature of user-interface through reviewing the various aspects of user-interface. Based on the findings the structure of methods that analyze the characterisics of user's behavior is identified. Thereafter, we developed a computerized tool for analysing video sequential data from usability tests. The tool comprises of four different modules: module for identifying users' profiles, module for video data logging, module for analysing user's characteristics, and module for synthesizing these data for user-interface design. Finally findings are summarized and further research was suggested.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.233-237
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• 2010

The recent advance of sensor networks and ubiquitous techniques allow collecting and analyzing of the data which overcome the limitation imposed by time and space in real-time for making decisions. Also, analysis and prediction of collected data can support useful and necessary information to users. The collected data in sensor networks environment is the stream data which has continuous, unlimited and sequential properties. Because of the continuous, unlimited and large volume properties of stream data, managing stream data is difficult. And the stream data needs dynamic processing method because of the memory constraint and access limitation. Accordingly, we analyze correlation stream data using principal component analysis. And using result of analysis, it helps users for making decisions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.669-678
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• 2009

Real-time image georeferencing technologies are required to generate spatial information promptly from the image sequences acquired by a multi-sensor system. We thus derive a sequential adjustment algorithm based on the combined adjustment model. By adopting the sequential adjustment model, we develop a sequential AT(Aerial Triangulation) algorithm to georeference image sequences in real-time. The proposed algorithm enables to perform AT rapidly with the minimum computation at the current stage by using the results computed at the previous stage whenever a new image is added. Experiments with simulated data were conducted to verify the effectiveness of the proposed algorithm. The results of the experiments show that the georeferencing of each image took very short time and its accuracy was determined within ${\pm}4cm$ on the ground control points comparing to the results of the existing simultaneous AT.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.59-72
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• 1999

A study on workflow system as an automated business processing system is done recently. However, it did not consider various dependencies between parallel tasks. Therefore, this paper proposes modeling and verification of workflows with various parallel dependencies. For this, firstly, we propose four dependencies to specify various parallel dependencies between tasks. They contain sequential starts, parallel starts, sequential commits, and parallel commits. Secondly, we suggest a method to specify various parallel dependencies on workflow graph. Thirdly, we propose a verification method to detect contradictions on workflow specifications.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.294-297
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• 2001

SNS는 MRP의 부품전개 방식을 SN(Sequential Number : 누계)으로 적용하여 개량한 시스템으로, 계획과 실적을 이원화한 진도관리 중심으로 개발되었으며, 정보처리 로직이 간단하여 대기업뿐만 아니라 중소기업에 활용하기에 적합하다. 그러나, 소프트웨어 구현에 있어서 불량품 정보를 반영할 수 있는 로직이 불분명하여 정보의 정확성이 결여되고, 결국에는 소프트웨어에서 제공하는 정보를 활용하지 못하는 단점이 있다. 따라서, 본 논문은 SNS의 생산 및 재고관리의 실적입력 시 불량품 정보를 처리하는 알고리즘을 개발하여 현실적으로 재고와 진도를 파악할 수 있는 누계시스템의 불량품 정보의 처리방법을 제공한다.