• Journal of Information Processing Systems
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• v.11 no.2
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• pp.280-294
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• 2015

This paper presents the infectious watermarking model (IWM) for the protection of video contents that are based on biological virus modeling by the infectious route and procedure. Our infectious watermarking is designed as a new paradigm protection for video contents, regarding the hidden watermark for video protection as an infectious virus, video content as host, and codec as contagion medium. We used pathogen, mutant, and contagion as the infectious watermark and defined the techniques of infectious watermark generation and authentication, kernel-based infectious watermarking, and content-based infectious watermarking. We experimented with our watermarking model by using existing watermarking methods as kernel-based infectious watermarking and content-based infectious watermarking medium, and verified the practical applications of our model based on these experiments.

• Computers and Concrete
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• v.12 no.2
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• pp.229-241
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• 2013

The objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.

• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.558-566
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• 2005

We propose a feature-based multi-resolution representation of B-rep solid models using history-based Boolean operations based on the merge-and-select algorithm. Because union and subtraction are commutative in the history-based Boolean operations, the integrity of the models at various levels of detail (LOD) is guaranteed for the reordered features regardless of whether the features are subtractive or additive. The multi-resolution solid representation proposed in this paper includes a non-manifold topological merged-set model of all feature primitives as well as a feature-modeling tree reordered consistently with a given LOD criterion. As a result, a B-rep solid model for a given LOD can be provided quickly, because the boundary of the model is evaluated without any geometric calculation and extracted from the merged set by selecting the entities contributing to the LOD model shape.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.8 no.1
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• pp.11-30
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• 2004

Access Control is one of essential branches to provide system's security. Depending on what standards we apply, in general, there are Role-based access control, History-based access control. The first is based on subject's role, The later is based on subject's history. In fact, RBAC has been implemented, we are using it by purchasing some orders through the internet. But, HBAC is so complex that there will occur some errors on the system. This is more and more when HBAC is used with other access controls. So HBAC's formalization and model which are general enough to encompass a range of policies in using more than one access control model within a given system are important. To simplify these, we design the mathematical model called non-access structure. This Non-access structure contains to historical access list. If it is given subjects and objects, we look into subject grouping and object relation, and then we design Non-access structure. Then we can determine the permission based on history without conflict.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.129-142
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• 2014

We propose a variational segmentation model based on statistical information of intensities in an image. The model consists of both a local region-based energy and a global region-based energy in order to handle misclassification which happens in a typical statistical variational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small difference between two Gaussian distributions. Based on statistical information restricted to the local ambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of the proposed variational model.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.101-111
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• 1999

The Web-based simulation was introduced for conducting simulation experiments in the Internet and the Web. Due to the use of the Java language, the Web-based simulation can have such characteristics as reusability, portability, and the capability of execution on the Web. Most of existing Web-based simulation tools have focused mainly on the development of the runtime simulation libraries and mechanisms on the Web. Thus, the model development work in such Web-based simulation tools still requires hand-written coding of model developers. This paper presents a visual model development environment for the Web-based simulation. The proposed environment provides a framework for model development and animation. To show the effectiveness of the proposed environment, we perform simulation experiments for transaction routing algorithms in a distributed transaction processing system.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.368-372
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• 2016

In this paper, the physics-based analytical model of transition metal dichalcogenide (TMD)-based double-gate (DG) tunneling field-effect transistors (TFETs) is proposed. The proposed model is derived by using the two-dimensional (2-D) Landauer formula and the Wentzel-Kramers-Brillouin (WKB) approximation. For improving the accuracy, nonlinear and continuous lateral energy band profile is applied to the model. 2-D density of states (DOS) and two-band effective Hamiltonian for TMD materials are also used in order to consider the 2-D nature of TMD-based TFETs. The model is validated by using the tight-binding non-equilibrium Green's function (NEGF)-based quantum transport simulation in the case of monolayer molybdenum disulfide ($MoS_2$)-based TFETs.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.49-57
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• 2018

The main objective of this paper is come up with methodology approach for FPGA-based system in verification and validation lifecycle regarding software reliability using system engineering approach. The steps of both reverse engineering and re-engineering are carried out to implement an FPGA-based of safety critical system in Nuclear Power Plant. The reverse engineering methodology is applied to elicit the requirements of the system as well as gain understanding of the current life cycle and V&V activities of FPGA based-system. The re-engineering method is carried out to get a new methodology approach of software reliability, particularly Software Reliability Growth Model. For measure the software reliability of a given FPGA-based system, the following steps are executed as; requirements definition and measurement, evaluation of candidate reliability model, and the validation of the selected system. As conclusion, a new methodology approach for software reliability measurement using software reliability growth model is developed.

• Computers and Concrete
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• v.8 no.2
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• pp.177-192
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• 2011

This research paper aims at computer based modeling of carbonation induced corrosion under extreme conditions and its experimental verification by incorporating enhanced electrochemical and mass balance equations based on thermo-hygro physics with strong coupling of mass transport and equilibrium in micro-pore structure of carbonated concrete for which the previous research data is limited. In this paper the carbonation induced electrochemical corrosion model is developed and coupled with carbon dioxide transport computational model by the use of a concrete durability computer based model DuCOM developed by our research group at concrete laboratory in the University of Tokyo and its reliability is checked in the light of experiment results of carbonation induced corrosion mass loss obtained in this research. The comparison of model analysis and experiment results shows a fair agreement. The carbonation induced corrosion model computation reasonably predicts the quantitative behavior of corrosion rate for normal air dry relative humidity conditions. The computational model developed also shows fair qualitative corrosion rate simulation and analysis for various pH levels and coupled environmental actions of chloride and carbonation. Detailed verification of the model for the quantitative carbonation induced corrosion rate computation under varying relative conditions, different pH levels and combined effects of carbonation and chloride attack remain as scope for future research.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.