• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.49-58
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• 2011

The workloads of facilities and laborers are important for the capacity planning in a factory. They are always referenced whenever a factory develops a new product, increases the production quantity and makes a plan of new investment. There are many measuring methods for estimating the workload effectiveness of facilities and laborers. In this paper, various measuring methods including survey, work sampling, micro-motion study, data gathering from ERP system and simulation, are analyzed for comparing the accuracy of workload. This case study is conducted in a Korean company that produces semiconductor parts like leadframe and packaging substrate.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1461-1470
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• 2016

In side channel analysis, signal processing techniques can be used as preprocessing to enhance the efficiency and performance of analysis by reducing the noise or compressing the dimension. As signal processing techiniques using singular value decomposition can increase the information of main signal and reduce the noise by using the variance and tendency of signal, it is a great help to improve the performance of analysis. Typical techniques of that are PCA(Principal Component Analysis), LDA(Linear Discriminant Analysis) and SSA(Singular Spectrum Analysis). PCA and LDA can compress the dimension with increasing the information of main signal, and SSA reduces the noise by decomposing the signal into main siganl and noise. When applying each one or combination of these techniques, it is necessary to compare the performance. Therefore, it needs to suggest methodology of that. In this paper, we compare the performance of the three technique and propose using Sinal-to-Noise Ratio(SNR) as the methodology. Through the proposed methodology and various experiments, we confirm the performance and efficiency of each technique. This will provide useful information to many researchers in the field of side channel analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.73-88
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• 2006

As a computerized application for controlling enterprise processes, BPM(Business Process Management) has been received such concerns that many solution vendors developed their own process definition and storage methods. The fact causes the needs of process modeling standards for process model exchange and at the same time, requires the appropriate methodology for adopting the global standards. In this paper, we propose a transformation methodology of BPMN-based file into XMI(XML Metadata Interchange)-based neutral file format. We devised translation templates for 21 workflow patterns, and compared the results with BPEL4WS(Business Process Execution Language for Web Services) translation. As a result, our XMI transformation model enables more complete translation of process model in comparison with existing model, and thus can be practically utilized to the BPM vendors adopting BPMN standards.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.281-292
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• 2014

As the importance of algorithm trading is getting stronger, researches for artificial intelligence (AI) based trading strategy is also being more important. However, there are not enough studies about using more than two AI methodologies in one trading system. The main aim of this study is development of algorithm trading strategy based on the rough set theory that is one of rule-based AI methodologies. Especially, this study used genetic algorithm for optimizing profit of rough set based strategy rule. The most important contribution of this study is proposing efficient convergence of two different AI methodology in algorithm trading system. Target of purposed trading system is KOPSI200 futures market. In empirical study, we prove that purposed trading system earns significant profit from 2009 to 2012. Moreover, our system is evaluated higher shape ratio than buy-and-hold strategy.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.3-13
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• 2009

Knowledge management (KM) has been considered to be an effective means of learning from past projects to effect continuous performance improvement in the construction industry. Despite the growing importance of KM in the construction industry, the usage and effectiveness of IT tools for implementing KM are limited to some extent. Case studies of current KM practices in Korean construction sectors revealed that the chief causes of this problem are the top-down approach of the current practices. To address this challenging issue, this research proposes bottom-up approach, which motivates knowledge creation by shifting the ownership of contents, and facilitates effective reuse of knowledge by providing rich contextual information.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.11-20
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• 2010

In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.28-38
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• 2019

The smart card data stores the transit usage records of individual passengers. By using this, it is possible to analyze the traffic demand by station and time. However, since the purpose of the trip is not recorded in the smart card data, the demand for each purpose such as commuting, school, and leisure is estimated based on the survey data. Since survey data includes only some samples, it is difficult to predict public transport demand for each purpose close to the complete enumeration survey. In this study, we estimates the purposes of trip for individual passengers using the smart card data corresponding to the complete enumeration survey of public transportation. We estimated trip purposes such as commute, school(university) considering frequency of O-D, duration, and departure time of a passenger. Based on this, the passengers are classified as workers and university students. In order to verify our methodology, we compared the estimation results of our study with the patterns of the survey data.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.42-51
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• 2019

The train operation institution establishes a transportation plan based on the forecast of transport demand and the ability of train vehicles to transport, and establishes a train operation plan accordingly. The train operation plan adjusts the intervals between trains, creates a timetable (train diagram) for trains, and establishes a plan for the operation of train vehicles used for train operation. The train operation institution shall establish a crew schedule to determine and place the crew members of the trains arranged in the diagram in order to enhance the efficiency of the operation management of the trains. In this study, the authors apply the neighborhood search method that satisfies the constraints at the phase of generating the crew diagram. This suggests a methodology for efficient management of crew schedule plan. The crew diagram generated in this study compared with the existing crew diagram in accordance with the actual operating train timetable, and verified the effectiveness of the suggested method.