• Structural Engineering and Mechanics
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• v.4 no.6
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• pp.601-612
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• 1996

To simulate the large-scale failure evolution with current computational facilities, a simple approach, that catches the essential feature of failure mechanisms, must be available so that the routine use of failure analysis is feasible. Based on the previous research results, a simple analysis procedure is described in this paper for failure simulation. In this procedure, the evolution of localization is represented by a moving surface of discontinuity, and the transition between continuous and discontinuous failure modes are described via the moving jump forms of conservation laws. As a result, local plasticity and damage models, that are formulated based on thermodynamic restrictions, are still valid without invoking higher order terms, and simple integration schemes can be designed for the rate forms of constitutive models. To resolve localized large deformations and subsequent cracking, an efficient structural solution scheme is given for Static and dynamic problems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.3 no.2
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• pp.1-12
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• 1997

One of the main uses for ship simulators is in the field of port design, and an increasing number of simulators, of varying degrees of fidelity, are being used for this purpose. An essential feature of all such simulators is their visual scene, which must be of sufficent fidelity to convey the key visual cues adequately. This paper examines the ability of a number of experienced mariners to perceive speeds and distances correctly using Computer Generated Imagery visual scenes of different fidelity, compared with their performance at sea. From the results, it was found that the microcomputer based simulator might be considered, as far as its visual scene representation is concerned, to be as valid as the full mission ship simulator for the port design task.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.120-122
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• 2004

Wearable input device that can make free-space typewriting possible is introduced. We named this device as $SCURRY^{TM}$. To measure the angular velocity of hand and the acceleration rates at the ends of fingers, we buried MEMS inertial sensors in this keyboard. We processed sensor signals to get the information on hand movement and finger-click motion. With this signal processing, apparent finger movements were depicted over the virtual keyboard shown on output device of a target computing system. In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger clicking of $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click part, and cross-talk avoidance part. The experiments were conducted to verify the effectiveness and efficiency of the proposed algorithms.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.587-598
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• 2022

To increase building change recognition accuracy, we present a deep learning-based building change detection using remote sensing images. In the proposed approach, by merging pixel-level and object-level information of multitemporal remote sensing images, we create the difference image (DI), and the frequency-domain significance technique is used to generate the DI saliency map. The fuzzy C-means clustering technique pre-classifies the coarse change detection map by defining the DI saliency map threshold. We then extract the neighborhood features of the unchanged pixels and the changed (buildings) from pixel-level and object-level feature images, which are then used as valid deep neural network (DNN) training samples. The trained DNNs are then utilized to identify changes in DI. The suggested strategy was evaluated and compared to current detection methods using two datasets. The results suggest that our proposed technique can detect more building change information and improve change detection accuracy.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.904-911
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• 2003

In this paper, we propose an effective method for the distinction between machine-printed and handwritten Korean address images. It is important to know whether an input image is handwritten or machine-printed, because methods for handwritten image are quite different from those of machine-printed image in such applications as address reading, form processing, FAX routing, and so on. Our method consists of three blocks: valid connected components grouping, feature extraction, and classification. Features related to width and position of groups of valid connected components are used for the classification based on a neural network. The experiment done with live Korean address images has demonstrated the superiority of the proposed method. The correct classification rate for 3,147 testing images was about 98.85%.

• Fashion & Textile Research Journal
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• v.11 no.5
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• pp.808-817
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• 2009

The purpose of this study was to verify potential differences in group- specific external feature concerns and beauty care behaviors of Korean women in their 20's~40's depending on their narcissistic propensity. This study is to take psychological approaches to narcissistic propensity of our contemporary society, so that it can get better understanding about consumers and provide marketing data on beauty-related industry. To meet the above goals, total 400 sheets of questionnaire were distributed to subjects from March 30 to April 8, 2009. Out of 376 sheets of questionnaire collected, total 355 valid questionnaires except incomplete 21 ones were used for final data analysis. For data analysis, this study used SPSS 12.0 as statistic program to perform factor analysis, reliability test (Cronbac's ${\alpha}$ coefficient), cluster analysis, t-test, analysis of variance (ANOVA), Duncan's multiple range test and multiple regression analysis. As a result, this study could come to the following findings: First, according to cluster analysis depending upon different factors such as self-directed narcissism, others-conscious narcissism and others-sensitive narcissism, it was found that our women in 20's to 40's could fall into 4 groups, i.e. complex narcissism group, mixed narcissism group, others-sensitive narcissism group and dispirited narcissism group. Second, according to analysis on potential differences in external feature concerns among four groups depending on their narcissistic propensity, it was found that there were significant differences in all relevant factors among groups. Third, according to analysis on differences in beauty care behaviors among four groups depending upon their narcissistic propensity, it was found that there were significant differences in all relevant factors among groups. Fourth, according to analysis on potential factors of external feature concerns that may influence beauty care behaviors of complex narcissism group, it was found that those factors had significant effects on fashion-orientedness, cosmetic surgery and personality pursuit of this group. And it was also found that there were significant differences in fashion-orientedness, cosmetic surgery, makeup and hair styling of mixed narcissism group, others-sensitive narcissism group and dispirited narcissism group respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.12-18
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• 2012

Stereo correspondence is the central problem of stereo vision. In this paper, we propose a stereo matching scheme based on a genetic algorithm using a multi-resolution method and AD-Census. The proposed approach considers the matching environment as an optimization problem and finds the disparity by using a genetic algorithm And adaptive chronosome structure using edge pixels and crossover mechanism are employed in this technique. A cost function is composes of certain constraints whice are commonly used in stereo matching. AD-Census measure is applied to reduce disparity error. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement using local feature vector. We valid our method not only reduces the search time for correspondence compared with conventional GA-based method but also ensures the validity of matching.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1334-1339
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• 2018

Viola & Jones's face detection algorithm is a typical face detection algorithm and shows excellent face detection performance. However, the Viola & Jones's algorithm in images including many faces generates undetected faces and wrong detected faces, such as false faces and duplicate detected faces, due to face diversity. This paper proposes an improved face detection algorithm using a face verification algorithm that eliminates the false detected faces generated from the Viola & Jones's algorithm. The proposed face verification algorithm verifies whether the detected face is valid by evaluating its size, its skin color in the designated area, its edges generated from eyes and mouth, and its duplicate detection. In the face verification experiment of 658 face images detected by the Viola & Jones's algorithm, the proposed face verification algorithm shows that all the face images created in the real person are verified.

• Convergence Security Journal
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• v.22 no.3
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• pp.101-110
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• 2022

As the cases of using artificial intelligence in various fields increase, attempts to solve various issues through artificial intelligence in the intrusion detection field are also increasing. However, the black box basis, which cannot explain or trace the reasons for the predicted results through machine learning, presents difficulties for security professionals who must use it. To solve this problem, research on explainable AI(XAI), which helps interpret and understand decisions in machine learning, is increasing in various fields. Therefore, in this paper, we propose an explanatory AI to enhance the reliability of machine learning-based intrusion detection prediction results. First, the intrusion detection model is implemented through XGBoost, and the description of the model is implemented using SHAP. And it provides reliability for security experts to make decisions by comparing and analyzing the existing feature importance and the results using SHAP. For this experiment, PKDD2007 dataset was used, and the association between existing feature importance and SHAP Value was analyzed, and it was verified that SHAP-based explainable AI was valid to give security experts the reliability of the prediction results of intrusion detection models.

• Journal of Korean Medical classics
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• v.29 no.1
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• pp.125-137
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• 2016

Objectives : Introduction to Medicine(醫學入門, Yixuerumen) is one of the basic clinical texts in Korean medical history. This study is designed to prove clinical value of Introduction to Medicine for practitioners in their early stage of clinical practice. Methods : Introduction to Medicine is closely reviewed in various aspects in order to examine broad outlines of specificity as well as its distinctive constructional feature. Results : Since Introduction to Medicine showed peculiar intention of developing practitioner's clinical ability, it has been a preferential choice for Korean medicine practitioners to enhance their qualification at the early stage of one's career in Korean history. It is still valid for modern practitioners because composite medical texts are needed in order to systematize one's fragmental knowledge acquired from institutional education. Conclusions : Introduction to Medicine shows a large potential as a clinical textbook in the course of maximizing one's clinical ability with its aid. Through understanding multilateral aspects of clinical guidelines and directions engraved in Introduction to Medicine, learners will be able to derive full capacity from the text.