• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.180-187
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• 2020

Security threats are increasing with interest due to the mass spread of smart devices, and vulnerabilities in developed applications are being exposed while mobile malicious codes are spreading. The government and companies provide various applications for the public, and for reliability and security of applications, security checks are required during application development. In this paper, among the security threats that can occur in the mobile service environment, we set up the vulnerability analysis items to respond to security threats when developing Android-based applications. Based on the set analysis items, vulnerability analysis was performed by examining three applications of public institutions and private companies currently operating as mobile applications. As a result of application security checks used by three public institutions and companies, authority management and open module stability management were well managed. However, it was confirmed that many security vulnerabilities were found in input value verification, outside transmit data management, and data management. It is believed that it will contribute to improving the safety of mobile applications through the case of vulnerability analysis for Android application security.

• Structural Engineering and Mechanics
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• v.39 no.5
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• pp.703-716
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• 2011

The accurate dynamic analysis of structures is usually performed by a fine finite element discretization with very large number of degrees of freedom. Apart from modal analysis, one can reduce the number of final equations by assuming the deformed shape of the structure as a linear combination of independent Ritz vectors. The efficiency of this method relies heavily on the vectors selected. In this paper, a new set of Ritz vectors is proposed. It is primarily proved that these vectors are linearly independent. Subsequently, various two and three-dimensional examples are analyzed based on the proposed method. In each case, the results are compared with the ones obtained based on usual Ritz and modal analysis methods. It is finally concluded that the proposed method is very effective and efficient method for dynamic analysis of structures in frequency domain.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.12
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• pp.1165-1172
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• 2007

The spacer grid set is a part of a nuclear fuel assembly. The set has a spring and the spring supports the fuel rods safely. Although material nonlinearity is involved in the deformation of the spring, nonlinearity has not been considered in design of the spring. Recently a nonlinear response structural optimization method has been developed using equivalent loads. It is called nonlinear response optimization equivalent loads (NROEL). In NROEL, the external loads are transformed to the equivalent loads (EL) for linear static analysis and linear response optimization is carried out based on the EL in a cyclic manner until the convergence criteria are satisfied. EL is the load set which generates the same response field of linear analysis as that of nonlinear analysis. Shape optimization of the spring is carried out based on EL. The objective function is defined by minimizing the maximum stress in the spring while mass is limited and the support force of the spring is larger than a certain value. The results are verified by nonlinear response analysis. ABAQUS is used for nonlinear response analysis and GENESIS is employed for linear response optimization.

• Economic and Environmental Geology
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• v.50 no.3
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• pp.239-250
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• 2017

Physically based landslide susceptibility analysis has been recognized as an effective analysis method because it can consider the mechanism of landslide occurrence. The physically based analysis used the slope geometry and geotechnical properties of slope materials as input. However, when the physically based approach is adopted in regional scale area, the uncertainties were involved in the analysis procedure due to spatial variation and complex geological conditions, which causes inaccurate analysis results. Therefore, probabilistic method have been used to quantify these uncertainties. However, the uncertainties caused by lack of information are not dealt with the probabilistic analysis. Therefore, fuzzy set theory was adopted in this study because the fuzzy set theory is more effective to deal with uncertainties caused by lack of information. In addition, the vertex method and Monte Carlo simulation are coupled with the fuzzy approach. The proposed approach was used to evaluate the landslide susceptibility for a regional study area. In order to compare the analysis results of the proposed approach, Monte Carlo simulation as the probabilistic analysis and the deterministic analysis are used to analyze the landslide susceptibility for same study area. We found that Fuzzy Monte Carlo simulation showed the better prediction accuracy than the probabilistic analysis and the deterministic analysis.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.06a
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• pp.54-61
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• 2000

A method and results of classification of 4 types metallic wear debris were presented by using their color features. The color image of wear debris was used (or the initial data, and the color properties of the debris were specified by HSI color model. Particle was characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used for the definition of classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.660-667
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• 2006

This paper presents a novel region-based snake method for vessel segmentation. According to geometric shape analysis of the vessel structure with different scale, an efficient statistical estimation of vessel branches is introduced into the energy objective function, which applies not only the vessel intensity information, but also geometric information of line-like structure in the image. The defined energy function is minimized using the gradient descent method and a new region-based speed function is obtained, which is more accurate to the vessel structure and not sensitive to the initial condition. The narrow band algorithm in the level set framework implements the proposed method, the solution of which is steady. The segmentation experiments are shown on several images. Compared with other geometric active contour models, the proposed method is more efficient and robust.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.47-54
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• 2005

One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• Korean Institute of Interior Design Journal
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• no.22
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• pp.16-22
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• 2000

The purpose of this study is to analyze characteristics of set-booth in beauty salon as well as to suggest the basic design data for franchise beauty salon. The method of this research was based on field observation of the franchise beauty salon in Seoul. The results of this research are as follows. 1) In set-booth type analysis, set-mirror wall type and set-mirror partition type are mainly used, but set-mirror table type is not showed in this research. 2) In terms of scale, wall type and partition type are classified as large scale, wall type and partition type are used as meduim scale. In shop front analysis, the result is shown in two things. If it is type, they used partition type and if it is close type, they used wall type. 3) Set-mirror is consisted of mirror and drawer and it is classified by 4 types with combination method. In a result, most of them used separated mirror type because they want to emphasize the separation between set booth and its layout. 4) Lighting method has 4 types; corniced type, bracket type, pendant type and downlight type. Among them, downlight is showed as the most-used.