• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.387-399
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• 2009

Mobile wireless networks continue to be plagued by theft of identify and intrusion. Both problems can be addressed in two different ways, either by misuse detection or anomaly-based detection. In this paper, we propose a dissimilarity-based anomaly detection method which can effectively identify abnormal behavior such as mobility patterns of mobile wireless networks. In the proposed algorithm, a normal profile is constructed from normal mobility patterns of mobile nodes in mobile wireless networks. From the constructed normal profile, a dissimilarity is computed by a weighted dissimilarity measure. If the value of the weighted dissimilarity measure is greater than the dissimilarity threshold that is a system parameter, an alert message is occurred. The performance of the proposed method is evaluated through a simulation. From the result of the simulation, we know that the proposed method is superior to the performance of other anomaly detection methods using dissimilarity measures.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.95-100
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• 1995

In this study, we have evaluated the effect of amplitude and frequency perturbation of EGG signal for single vowels associated with laryngeal pathology. The normal EGG signal was properly characterized by an autoregressive model which has an optimal order of ninth using the parametric method. This can be analyzed by determining the transfer function. Perturbations in the fundamental pitch and in the peak amplitude of EGG signal measured with a four-electrode system using the modulation/demodulation techniques were investigated for the purpose of developing a decision criteria for the laryngeal function analysis. The abnormal EGG signal has nonperiodic and unstable characteristics. It can be discriminated by the calculation of opening and closing time of glottis using the EGG signal. In case of normal and abnormal subjects, m$\pm$0.5*sd was discriminating line for frequency perturbation and m$\pm$2*sd for normal amplitude perturbations, respectively. Also, The normal and abnormal cases of the subjects can be discriminated effectively using the pattern of attractor derived with Hilbert transform of EGG signal.

• Journal of Wetlands Research
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• v.22 no.4
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• pp.275-285
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• 2020

In this study, after estimating VCI (Vegation Condition Index), TCI (Thermal Condition Index) and VHI (Vegetation Health Index) from the NDVI (Normalized Differentiation Vegetation Index) and LST (Land Surface Temperature) remotely sensed at major sites in Korea during the 2001-1919 period, the correlation between these indices and various drought indices is analyzed for the purpose of assessing the effects of ecological drought. The relative impact of VCI and TCI on vegetation health was found to vary by region. The effects of drought on vegetation in Korea's forest areas could be more clearly identified in TCI than in VCI. It is suggested that the revised VHI, reflecting the relative influence of VCI and TCI, can better explain the effects of drought on vegetation.

• Journal of the Korean Geosynthetics Society
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• v.12 no.4
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• pp.1-10
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• 2013

Recently, the closed landfills are usually converted into parks or playground by the check the stability of landfill because they settle unevenly making them unsuitable for structures. When the closed landfill reuse, environmental and structural stability is important. To increase the bearing capacity and reduce the probable settlement of a foundation on waste disposal ground, a layer of geosynthetics(Geocell) is placed on the waste disposal ground. In this paper, the analysis of long-term settlement parameter correlation was performed, also the evaluation of bearing capacity reinforcement effect was conducted by field test. The settlement measured in the field, and input the same ground index when an integer to identify each model were compared by calculating the settlement. In addition, by adjusting the parameters of each model to identify the most similar to the value of field measurement parameters were calculated. Based on the analysis results, when the using the Park's model C(intermediate) = 0.0678, the expected settlement is similar to the field measurement results. Also, the bearing capacity of geocell reinforced ground is 1.193~1.554 times higher than that of unreinforced ground.

• Korean Security Journal
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• no.38
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• pp.109-136
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• 2014

Korea domestic casino industry has been experienced an explosive growth marking the highest quantity and quality with rapid growth of domestic economy since the 1960s. However there are really lack of study about presenting guideline for establishing risk management planning reflected characteristics of casino industry. Therefore, we analyzed previous studies about concept of the risk and criteria and drew dimension of safety supervision reflecting characteristics of casino industry. we, also, identified detailed safety management factors as well as classified three dimensions of environment, human and facility on the dimension of safety supervision. This study was designed to examine effect relationship between risk management factors and performance of security management organization focused on The mediation effect of atmosphere of organization We used two different tools for data analysis: SPSS 18.0 for the descriptive statistics and PLS 3.0 to validate the integrity of the research model and proposed hypotheses that is main effects from risk management factors to security management organization and mediation effects of atmosphere of organization. The data analysis confirmed the importance of risk management factors to enhanced performance of security management organization. The mediation effect of atmosphere of organization, also, supported relationship between risk management factors and performance of security management organization. It provided theoretical and practical implication for building risk management strategy well suited casino company and conducting security management.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.65-76
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• 2014

The basic purpose of this study is to examine the relationship among entrepreneurial intention, university supports for startup, and startup activities of university students. For the study, we identified the influence factors of students' startup intention based on reviewing preceding studies and examined how these factors affect their intention of new venture startup. In addition, this study attempted to examine how these factors that can have a significant impact on entrepreneurial intention affect startup activities and analyzed how entrepreneurial intention would mediate the relationship between these influence factors and startup activities. A total of 769 students who chosen by random were surveyed and all questionnaires were sent by mail to the universities that entrepreneurship education and entrepreneurial programs were selected as the forerunners from the government. As a result, this study revealed that student's psychological traits such as entrepreneurial self-efficacy and risk-taking have significant effect on the intention of startup. And student's exposure to the role models and various entrepreneurial experiences such as entrepreneurship education and entrepreneurial student's club in the university has significantly positive influence on the intention of startup. This study also found that the effects of these explanatory variables of this research on startup activities have been partially mediated by entrepreneurial intention. The entrepreneurial intention was also proven to have a significant effect on startup activities. Finally, the extent to which university supports activities for students' startup moderated the relationship between entrepreneurial intention and university students' startup activities. We believe that these results of this study contribute to the understanding of the entrepreneurship process both theoretical and practical perspectives.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.93-102
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• 2005

This paper proposes an approach to verify signature using autonomous self-organized Neural Network Model , fused with fuzzy membership equation of fuzzy c-means algorithm, based on the features of the signature. To overcome limitations of the functional approach and Parametric approach among the conventional on-line signature recognition approaches, this Paper presents novel autonomous signature classification approach based on clustering features. Thirty-six globa1 features and twelve local features were defined, so that a signature verifying system with FE-SONN that learns them was implemented. It was experimented for total 713 signatures that are composed of 155 original signatures and 180 forged signatures yet 378 original signatures written by oneself. The success rate of this test is more than 97.67$\%$ But, a few forged signatures that could not be detected by human eyes could not be done by the system either.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.700-708
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• 2015

A software birthmark is the set of characteristics of a program which can be used to identify the program. Many researchers have studied on detecting theft of java programs using some birthmarks. In case of Android apps, code obfuscation techniques are used to protect the apps against reverse-engineering and tampering. However, attackers can also use the obfuscation techniques in order to conceal a stolen program. A birthmark (feature) of an app can be alterable by code obfuscations. Therefore, it is necessary to detect Android app theft based on the birthmark which is resilient to code obfuscation. In this paper, we propose an effective Android app birthmark and app theft detection through the proposed birthmark. By analyzing some obfuscation tools, we have first selected parameter and the return types of methods as an adequate birthmark. Then, we have measured similarity of target apps using the birthmarks extracted from the apps, where some target apps are not obfuscated and the others obfuscated. The measurement results show that our proposed birthmark is effective for detecting Android app theft even though the apps are obfuscated.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.97-106
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• 2022

In this study, H&E staining is necessary to distinguish cells. However, dyeing directly requires a lot of money and time. The purpose is to convert the phase image of unstained cells to the amplitude image of stained cells. Image data taken with FPM was created with Phase image and Amplitude image using Matlab's parameters. Through normalization, a visually identifiable image was obtained. Through normalization, a visually distinguishable image was obtained. Using the GAN algorithm, a Fake Amplitude image similar to the Real Amplitude image was created based on the Phase image, and cells were distinguished by objectification using MASK R-CNN with the Fake Amplitude image As a result of the study, D loss max is 3.3e-1, min is 6.8e-2, G loss max is 6.9e-2, min is 2.9e-2, A loss max is 5.8e-1, min is 1.2e-1, Mask R-CNN max is 1.9e0, and min is 3.2e-1.