• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.182-188
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• 2013

In this paper, we propose a complex-valued support vector machine (SVM) classifier which process the complex valued signal measured by pulse doppler radar (PDR) to identify moving targets from the background. SVM is widely applied in the field of pattern recognition, but features which used to classify are almost real valued data. Proposed complex-valued SVM can classify the moving target using real valued data, imaginary valued data, and cross-information data. To design complex-valued SVM, we consider slack variables of real and complex axis, and use the KKT (Karush-Kuhn-Tucker) conditions for complex data. Also we apply radial basis function (RBF) as a kernel function which use a distance of complex values. To evaluate the performance of the complex-valued SVM, complex valued data from PDR were classified using real-valued SVM and complex-valued SVM. The proposed complex-valued SVM classification was improved compared to real-valued SVM for dog and human, respectively 8%, 10%, have been improved.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1477-1484
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• 2015

With the growth of financial industry with smartphone, interest on user authentication using smartphone has been arisen in these days. There are various type of biometric user authentication techniques, but gait recognition using accelerometer sensor in smartphone does not seem to develop remarkably. This paper suggests the method of user authentication using accelerometer sensor embedded in smartphone. Specifically, calibrate the sensor data from smartphone with 3D-transformation, extract features from transformed data and do principle component analysis, and learn model with using gaussian mixture model. Next, authenticate user data with confidence interval of GMM model. As result, proposed method is capable of user authentication with accelerometer sensor on smartphone as a high degree of accuracy(about 96%) even in the situation that environment control and limitation are minimum on the research.

• Journal of Korean Elementary Science Education
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• v.26 no.4
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• pp.372-384
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• 2007

The purposes of this study was to analyze qualitatively changes in students' experience and perceptions in relation to studying science using portfolios and any resultant effects on the portfolio itself. Five fourth-grade elementary students from one small city participated in this study. Data was collected through interviews as well as through student portfolios containing the science content matter of two units over two weeks. Observational diaries recorded by a teacher were also used to test the reliability of data collection. All interviews with students were transcribed to develop a suitable network to categorize students' responses. Students' portfolios were analyzed in order to reveal their essential characteristics in combination with their teacher's observational diaries. The results were as follows. First, student perceptions of their portfolios were categorized into three different levels; superficial, extended, and moderate perceptions. The changes in perception could also be divided into three levels; consistent-superficial, unstable, and a progressive-extended pattern. Second, the experience of students with their portfolio were investigated in terms of the following; successfully completing the elements of the portfolio, development of evidence, interaction with peers, teachers, and parents, and the standards of evaluation used for the portfolios. Third, the perceptions and experience of working on the portfolio by students had a number of direct effects on the way in which students actually created and developed their portfolios. Finally, students with positive attitudes towards their portfolios actively participated in the portfolio experience and finally understood what it meant completely. However, students with negative attitudes regarding portfolio based work, did not leave the experience with any heightened awareness of the utility or indeed, purpose of portfolio based work.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.113-118
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• 1996

Principal component analysis(PCA) is an essential technique for data compression and feature extraction, and has been widely used in statistical data analysis, communication theory, pattern recognition, and image processing. Oja(1992) found that a linear neuron with constrained Hebbian learning rule can extract the principal component by using stochastic gradient ascent method. In practice real data often contain some outliers. These outliers will significantly deteriorate the performances of the PCA algorithms. In order to make PCA robust, Xu & Yuille(1995) applied statistical physics to the problem of robust principal component analysis(RPCA). Devlin et.al(1981) obtained principal components by using techniques such as M-estimation. The propose of this paper is to investigate from the statistical point of view how Xu & Yuille's(1995) RPCA works under the same simulation condition as in Devlin et.al(1981).

• Proceedings of the Korean System Dynamics Society
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• 2002.02a
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• pp.19-40
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• 2002

The intent of this study is to develop system dynamics model for assessment of organizational and human factors in nuclear power plant which can contribute to secure the nuclear safety. Previous studies are classified into two major approaches. One is engineering approach such as ergonomics and probability safety assessment(PSA). The other is social science approach such like sociology, organization theory and psychology. Both have contributed to find organization and human factors and to present guideline to lessen human error in NPP. But, since these methodologies assume that relationship among factors is independent they don't explain the interactions among factors or variables in NPP. To overcome these limits, we have developed system dynamics model which can show cause and effect among factors and quantify organizational and human factors. The model we developed is composed of 16 functions of job process in nuclear power, and shows interactions among various factors which affects employees' productivity and job quality. Handling variables such like degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plant in the organization side. Through simulation, user can get insight to improve safety in plants and to find managerial tools in the organization and human side. Analyzing pattern of variables, users can get knowledge of their organization structure, and understand stands of other departments or employees. Ultimately they can build learning organization to secure optimal safety in nuclear power plant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2B
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• pp.131-140
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• 2011

As the number of Internet users and applications is increasing, the importance of application traffic classification is growing more and more for efficient network management. While a number of methods for traffic classification have been introduced, such as signature-based and machine learning-based methods, Skype application, which uses encrypted communication on its own P2P network, is known as one of the most difficult traffic to identify. In this paper we propose a novel method to identify Skype application traffic on the fly. The main idea is to setup a list of Skype host information {IP, port} by examining the packets generated in the Skype login process and utilizes the list to identify other Skype traffic. By implementing the identification system and deploying it on our campus network, we proved the performance and feasibility of the proposed method.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.301-314
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• 2008

The existing event recognition is accomplished with the limited systematic foundation, and thus much longer learning time is needed for emergency scenario interpretation due to large scale of probability data. In this paper, we propose a method for nile-based event recognition of an independent object(human) which extract a feature vectors from the object and analyze the behavior pattern of each object and interpretation of emergency scenarios using a probability and object's events. The event rule of an independent object is composed of the Primary-event, Move-event, Interaction-event, and 'FALL DOWN' event and is defined through feature vectors of the object and the segmented motion orientated vector (SMOV) in which the dynamic Bayesian network is applied. The emergency scenario is analyzed using current state of an event and its post probability. In this paper, we define diversified events compared to that of pre-existing method and thus make it easy to expand by increasing independence of each events. Accordingly, semantics information, which is impossible to be gained through an.

• Journal of the Korean School Mathematics Society
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• v.15 no.3
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• pp.467-486
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• 2012

By identifying the state of adjustment regarding mathematical education for adolescents who escaped from North Korea and analyzing the relevant factors from multiple perspectives, this study is aimed at finding improvement methods for their math education adoptability. To fulfill such objective, this paper-reviewed the existing literature and research, conducted participatory observation, collected and analyzed survey research on math education adoptability for 43 students who are currently attending an alternative school for North Korean defectors. The results of this research are as follows: There is a serious pattern of maladjustment concerning math education of adolescents who defected from North Korea. The lack of basic skills in mathematical principles due to the gap in their studies results in poor academic performance, particularly in the advanced stages of learning. In the process of defection, environmental challenges, such as the loss of basic study skills which naturally results from the gap in their studies and differences in the educational curriculum between North and South Korea, are posing difficulties for these students.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.636-644
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• 2016

The actress of the movie is an operating system called Samantha. She only has a voice in the movie. Theodore, the main actor writes letters for his clients. He got married Katherin after dating for years but they failed to maintain their relationship. It was hard for them to grow with distance. On the contrary, the learning OS doesn't have any fixed pattern and any limits, so it becomes the ideal partner for him. Since she was accessed by him, Samantha has expanded her ability rhizomatically. She could have sex with human and philosophical debates with a departed philosopher. While they have relationship, Theodore experiences the expansion of his conscience. Love cannot be confined in a small box. After realizing how to love people around him, he sends a love letter to Katherine with all his heart. The meaning of co-existing with A.I. and human is to have a chance to introspect our inner side of mind more deeply.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.177-184
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• 2017

Understanding trends and drivers of technology diffusion is imperative to forecast new technology adoption and understand the process of technological innovation. Our research utilizes a quantitative trend analysis considering both technological and economic indicators for trends and drivers of technology diffusion for 32nm, 22nm, and 14nm logic semiconductor technology. In terms of technological performance, the technology diffusion curve showed an S-curve pattern during the stages of maturity and decline, and the diffusion curve showed evidence supporting the learning curve. The diffusion curve showed the life cycle duration of 2 years, and the rate of technological performance and obsolescence are observed quantitatively between generations. Architectural innovation is affected by technological drivers more significantly than economic drivers. This research has implications as empirical research on the trends and drivers of technology diffusion in the high-tech semiconductor industry, and is meaningful in forecasting new technology adoption or build technology strategy.