• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.470-476
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• 2005

Ultra light metal structures have been studied for several years because of their superior specific stiffness, strength and potential of multi functions. Many studies have been focused on how to manufacture ultra light metal structures and optimize them. In this study, we introduced a new idea to make sandwich panels having octet truss cores. Wires bent in a shape of triangular wave were assembled to construct an Octet truss core and it was bonded with two face sheets to be a sandwich panel. The bending & compressive strength and stiffness were estimated through elementary mechanics for the sandwich specimens with two kinds of face sheets and the results were compared with the ones measured by experiments. Some aspects of assembling and mechanical behavior were discussed compared with Kagome core fabricated from wire, which had been introduced in the authors' previous work.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.167-179
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• 2001

This paper discusses an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, we suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multi-dimensional index using a feature vector as indexing attributes. For query precessing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verily the superiority of our method, we perform extensive experiments. The results reseal that our method achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.47.1-47.1
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• 2016

The determination of three dimensional parameters (e.g., radial speed, angular width, source location) of Coronal Mass Ejections (CMEs) is very important for space weather forecast. To estimate these parameters, several cone models based on a flat cone or a shallow ice-cream cone with spherical front have been suggested. In this study, we investigate which cone model is proper for halo CME morphology using 26 CMEs which are identified as halo CMEs by one spacecraft (SOHO or STEREO-A or B) and as limb CMEs by the other ones. From geometrical parameters of these CMEs such as their front curvature, we find that near full ice-cream cone CMEs are dominant over shallow ice-cream cone CMEs. Thus we develop a new full ice-cream cone model by assuming that a full ice-cream cone consists of many flat cones with different heights and angular widths. This model is carried out by the following steps: (1) construct a cone for given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, (4) minimize the difference between the estimated projection speeds with the observed ones. We apply this model to 12 SOHO halo CMEs and compare the results with those from other stereoscopic methods (a geometrical triangulation method and a Graduated Cylindrical Shell model) based on multi-spacecraft data.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.556-564
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• 2021

Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.531-539
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• 2019

This paper proposes the training features for malware family analysis and analyzes the multi-classification performance of ensemble models. We construct training data by extracting API and DLL information from malware executables and use Random Forest and XGBoost algorithms which are based on decision tree. API, API-DLL, and DLL-CM features for malware detection and family classification are proposed by analyzing frequently used API and DLL information from malware and converting high-dimensional features to low-dimensional features. The proposed feature selection method provides the advantages of data dimension reduction and fast learning. In performance comparison, the malware detection rate is 93.0% for Random Forest, the accuracy of malware family dataset is 92.0% for XGBoost, and the false positive rate of malware family dataset including benign is about 3.5% for Random Forest and XGBoost.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.11
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• pp.1073-1079
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• 2009

The proper orthogonal decomposition (POD) method can identify principal modes that optimally capture the energy content from large multi-dimensional data set. In this study unsteady pressure fields on the rotor blade surface of a helicopter in forward flight are expressed by a reduced order model based on the POD method. Special modes containing high energy are analyzed to investigate the aerodynamic characteristics in more efficient way. The CFD simulation of flowfields around helicopter rotor blade in hovering motion is also conducted to validate its prediction with experimental result. In the process 7 modes containing energy ratio 99% from 240 snapshots information are identified and utilized to construct a reduced order model.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.53-63
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• 1999

For the close range digital photogrammetry, multi-step procedures should be embodied in an integrated system. However, it is hard to construct an Integrated system through conventional procedural processing. Using Object Oriented Programming(OOP), photogrammetric processings can be classified with corresponding subjects and it is easy to construct an integrated system lot digital photogrammetry as well as to add the newly developed classes. In this study, the equation of 3-dimensional mathematic model is developed to make an immediate calibration of the CCD camera, the focus distance of which varies according to the distance of the object. Classes for the input and output of images are also generated to carry out the close range digital photogrammetric procedures by OOP. Image matching, coordinate transformation, dirct linear transformation and bundle adjustment are performed by producing classes corresponding to each part of data processing. The bundle adjustment, which adds the principle coordinate and focal length term to the non-photogrammetric CCD camera, is found to increase usability of the CCD camera and the accuracy of object positioning. In conclusion, classes and their hierarchies in the digital photogrammetry are designed to manage multi-step procedures using OOP and close range digital photogrammetric process is implemented using CCD camera in an integrated System.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.414-421
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• 2024

In this paper, we design and verify a system that can detect piping leakage noise in an environment with significant reverberation and reflection using a multi-channel acoustic sensor module as a technology to prevent major plant accidents caused by leakage. Four-channel microphones arranged in a tetrahedron are designed as a single sensor module to measure three-dimensional sound intensity vectors. In an environment with large effects of reverberation and reflection, the measurement error of each sensor module increases on average, so after placing multiple sensor modules in the field, measurement results showing locations with large errors due to effects such as reflection are excluded. Using the intersection between three-dimensional vectors obtained from several pairs of sensor modules, the coordinates where the sound source is located are estimated, and outliers (e.g., positions estimated to be outside the site, positions estimated to be far from the average position) are detected and excluded among the points. For achieving aforementioned goal, an excluding algorithm by deciding the outliers among the estimated positions was proposed. By visualizing the estimated location coordinates of the leakage sound on the site drawing within 1 second, we construct and verify a system that can detect the location of the leakage sound in real time and enable immediate response. This study is expected to contribute to improving accident response capabilities and ensuring safety in large plants.

• Journal of Distribution Research
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• v.13 no.3
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• pp.101-125
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• 2008

This research suggests an ideal role between franchisee and franchisee for survival and development of the Korean franchise business by identifying causal relationships between entrepreneurship of franchisees and their business performance. Besides, when considering multi-dimensional features of a franchise system, this study aims to show that the market orientation of the franchisee and the relationship commitment between franchisee and franchisee will play an important mediating role to achieve a better business performance. Thus specific causal relationships among sub-dimensional constructs of entrepreneurship and market orientations were investigated. They are innovativeness, risk-taking propensity, pro-activeness, information creation, intelligence generation, intelligence dissemination, response design, response implementation. The results demonstrate that pro-activeness of franchisee plays a crucial role for franchisee's business performance. It was noted that franchisor's market orientation and innovativeness is also important for high market orientation of franchisor. The higher the market orientation of franchisor was, the higher relationship commitment of franchisee was formed. By identifying the mediation effect of relationship commitment and market orientation of franchisor, this paper showed that relationship commitment positively affect the improvement of franchisee's business performance. Above all, it should be noted that this research empirically identified the relationship between franchisee's entrepreneurship and business performance that most of the previous researchers have ignored. Furthermore, the analysis was conducted at sub-dimensional construct level. It is expected that empirical results from this study will be able to provide a meaningful framework and theoretical basis for future research on franchise, entrepreneurship and market orientation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.713-722
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• 2009

Gravity measurement can determine the earth gravitational field, also is the fundamental to the research of earth gravitational field, geodesy and geodynamic, vertical movement of the crust, geoid surface, sea level and climate etc. Recently, National Geographic Information Institute (NGII) introduced FG-5 absolute gravity meter in order to lay a foundation for establishment of Absolute Gravity Network, and furthermore NGII plan to construct about 1,200 multi dimensional and function Unified Control Points(UCP) in nationwide. It will play an important role in development of high accuracy geoid model in South Korea. This paper explains the fundamental theory and method of relative gravity measurement, surveys the relative gravity of 21 stations using latest Scintrex CG-5 relative gravimeter. In addition, it calculates gravity values, compare and analysis gravity survey results using datum-free adjustment and weighted constraint adjustment. The results indicate show that datum-free and weighted constraint adjustment methods are available to determine high accuracy gravity achievement, datum-free method is more advantage than weighted constraint adjustment.