• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.64.3-64.3
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• 2017

For the detection of transient sources in optical wide field surveys like KMTNet Supernova Project, difference imaging technique is commonly used. As this method produces a fair amount of false positives, it is also common to utilize machine learning algorithms to screen likely true positives. While deep learning methods such as a convolutional neural network has been successfully applied recently, its application can be limited if the size of the training sample is small. I will discuss a variation of more conventional method that adopts the wavelet transform for feature engineering and its performance.

• Journal of the military operations research society of Korea
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• v.3 no.1
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• pp.123-136
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• 1977

This thesis presents a modification and extension to the Burgess and Killebrew heuristic resource leveling procedure for project networks. In contrast to previous algorithms appearing in the literature, the objective function of this algorithm. is the minimization of the sum of the squared errors in each time period (deviations around the mean usage) of all resources over the duration of the project. This objective function continues the search for an improved schedule beyond that of previous algorithms with their associated objective functions. One important feature is that the algorithm tends to reduce the number of periods that a resource is idle during its duration on the project.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.653-655
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• 2005

More than 70 percent of terrestrial territory of Korea is mountainous areas where degradation becomes serious year by year due to illegal tombs, expanding golf courses and stone mine development. We elaborate the potential usage of high resolution image for the monitoring of the phenomena. We made the classification of tombs and the statistical radiometric characteristics of graves were identified from this project. The graves could be classified to 4 groups from the field survey. As compared with grouping data after clustering and discriminant analysis, the two results coincided with each other. Object-oriented classification algorithm for feature extraction was theoretically researched in this project. And we did a pilot project, which was performed with mixed methods. That is, the conventional methods such as unsupervised and supervised classification were mixed up with the new method for feature extraction, object-oriented classification method. This methodology showed about $60\%$ classification accuracy for extracting tombs from satellite imagery. The extraction of tombs' geographical coordinates and graves themselves from satellite image was performed in this project. The stone mines and golf courses are extracted by NDVI and GVI. The accuracy of classification was around 89 percent. The location accuracy showed extraction of tombs from one-meter resolution image is cheaper and quicker way than GPS method. Finally we interviewed local government officers and made analyses on the current situation of mountainous area management and potential usage of KOMPSAT-II images. Based on the requirement analysis, we developed software, which is to management and monitoring system for mountainous area for local government.

• Journal of KIBIM
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• v.5 no.3
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• pp.11-18
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• 2015

Integrated Project Delivery (IPD) is a new trend in the building industry and a key feature of IPD is the use of BIM to support project collaboration. Therefore, engineers should learn the use of BIM and IPD in the construction industry. In this study, the authors draw necessary components for developing an IPD course curriculum through analyzing a project case and current courses provided by universities in Korea. The authors make several suggestions for effective IPD education in universities.

• Korean Architects
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• s.518
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• pp.82-83
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• 2012

• International conference on construction engineering and project management
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• 2007.03a
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• pp.635-641
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• 2007

The construction starts its business by receiving the order from client and owner. The client presents requirements and related information so that the desired result can come out while the designer and the builder express and implement the building according to set objectives and goals of project based on information on project environment and presented requirements. Because the construction project makes decisions on such objectives at its early stage and previous stage becomes the situation for decision making of next stage as the computation to implement decisions get performed. Accordingly, this study has mentioned necessity of requirement analysis and systematization of construction project, analyzed the work of construction's early stage and resented a plan for objective of construction project requirement definition model in which requirements engineering has been applied and using it while making decisions on designing.

• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.63-71
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• 2021

This paper looks into how to enhance construction project management, focusing on the change order, which is often considered one of the major causes for construction delays, disputes, and claims in the middle east construction. First, this paper categorizes the major causes of change orders. It suggests a detailed classification standard for affecting factors resulting from change orders based on a case study result of an on-going construction project in the Middle East. In particular, this paper presents a method to apply a machine learning-based feature selection to quantify the importance of change order triggers and affecting factors. As a result, the case study identifies six major change order triggers and eight affecting factors. Also, a meaningful relationship between change order triggers and affecting factors by each category is presented. This paper will contribute to setting a clear guideline for change order management for the international plant construction field while helping prevent construction delays and cost run-ups by reducing the time required for change order resolution between project owners and contractors.

• Journal of International Society for Simulation Surgery
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• v.2 no.2
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• pp.64-66
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• 2015

Purpose : In this paper we proposed cascade feature filter and projection method for rapid human face recognition for the large-scale high-dimensional face database. Materials and Methods : The relevant features are selected from the large feature set using Fast Correlation-Based Filter method. After feature selection, project them into discriminant using Principal Component Analysis or Linear Discriminant Analysis. Their cascade method reduces the time-complexity without significant degradation of the performance. Results : In our experiments, the ORL database and the extended Yale face database b were used for evaluation. On the ORL database, the processing time was approximately 30-times faster than typical approach with recognition rate 94.22% and on the extended Yale face database b, the processing time was approximately 300-times faster than typical approach with recognition rate 98.74 %. Conclusion : The recognition rate and time-complexity of the proposed method is suitable for real-time face recognition system on the large-scale high-dimensional face database.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.594-596
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• 2022

Over the last decades, deep neural networks have demonstrated significant success in various tasks. To address the special vision task, choosing a hot network as backbone to extract feature is a common way in both research and industry project. However, the choice of backbone usually requires the expert experience and affects the performance of the classification task. In this work, we propose a novel idea to support backbone decision-making by exploring the feature attribution and weights distribution of hidden layers from various backbones. We first analyze the visualization of feature maps on different size object and different depth layers to observe learning ability. Then, we compared the variance of weights and feature in last three layers. Based on analysis of the feature and wights, we summarize the traits and commonalities of existing networks.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.65-72
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• 2018

In this paper, we have studied how to reuse common data link software by applying software product line engineering. Existing common data link software performed different stages of design, implementation, and testing without sharing the accumulated knowledge of different developers. In this situation, developers agreed that sharing the assets of each project and reusing the previously developed software would save human and time costs. Even with the initial difficulties, the common Data Link is a continually proposed project in the defense industry, so we decided to build a product line. The common data link software can be divided into two domains. Among them, the initial feature model for the GUI software was constructed, and the following procedure was studied. Through this, we propose a plan to build a product line for core assets and reuse them in newly developed projects.