• Journal of Soil and Groundwater Environment
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• v.15 no.6
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• pp.91-98
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• 2010

The effective thermal conductivity of porous materials is usually determined by porosity, water content, and the conductivity of the matrix. In addition, it is also affected by the internal structure of the materials such as the size, arrangement, and connectivity of the matrix-forming grains. Based on the structural models for multi-phase materials, thermal conductivities of soils and sands measured with varying the water content were analyzed. Thermal conductivities of dry samples were likely to fall in the region between the Maxwell-Eucken model with air as the continuous phase and the matrix as the dispersed phase ($ME_{air}$) and the co-continuous (CC) model. However, water-saturated samples moved down to the region between the $ME_{wat}$ model and the series model. The predictive inconsistency of the structural models for dry and water-saturated samples may be caused by the increase of porosity for water-saturated samples, which leads to decrease of connectivity among the grains of matrix. In cases of variably saturated samples with a uniform grain size, the thermal conductivity showed progressive changes of the structural models from the $ME_{air}$ model to the $ME_{wat}$ model depending on the water content. Especially, an abrupt increase found in 0-20% of the water content, showing transition from the $ME_{air}$ model to the CC model, can be attributed to change of water from the dispersed to continuous phase. On the contrary, the undisturbed soil samples with various sizes of grains showed a gradual increase of conductivity during the transition from the $ME_{air}$ model to the CC model.

• Journal of the Korea Convergence Society
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• v.8 no.6
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• pp.17-27
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• 2017

Recently, as cyber attacks have been activated, many such attacks have come into contact with various media. Research on security engineering and reverse engineering is active, but there is a lack of research that integrates them and applies attack systems through cost effective attack engineering. In this paper, security - enhanced information systems are developed by security engineering and reverse engineering is used to identify vulnerabilities. Using this vulnerability, we compare and analyze lifecycle models that construct or remodel attack system through attack engineering, and specify structure and behavior of each system, and propose more effective modeling. In addition, we extend the existing models and tools to propose graphical attack specification models that specify attack methods and scenarios in terms of models such as functional, static, and dynamic.

• Genomics & Informatics
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• v.15 no.4
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• pp.142-146
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• 2017

More effective production of human insulin is important, because insulin is the main medication that is used to treat multiple types of diabetes and because many people are suffering from diabetes. The current system of insulin production is based on recombinant DNA technology, and the expression vector is composed of a preproinsulin sequence that is a fused form of an artificial leader peptide and the native proinsulin. It has been reported that the sequence of the leader peptide affects the production of insulin. To analyze how the leader peptide affects the maturation of insulin structurally, we adapted several in silico simulations using 13 artificial proinsulin sequences. Three-dimensional structures of models were predicted and compared. Although their sequences had few differences, the predicted structures were somewhat different. The structures were refined by molecular dynamics simulation, and the energy of each model was estimated. Then, protein-protein docking between the models and trypsin was carried out to compare how efficiently the protease could access the cleavage sites of the proinsulin models. The results showed some concordance with experimental results that have been reported; so, we expect our analysis will be used to predict the optimized sequence of artificial proinsulin for more effective production.

• Computers and Concrete
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• v.5 no.4
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• pp.375-388
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• 2008

Crack opening governs many transfer properties that play a pivotal role in durability analyses. Instead of trying to combine continuum and discrete models in computational analyses, it would be attractive to derive from the continuum approach an estimate of crack opening, without considering the explicit description of a discontinuous displacement field in the computational model. This is the prime objective of this contribution. The derivation is based on the comparison between two continuous variables: the distribution if the effective non local strain that controls damage and an analytical distribution of the effective non local variable that derives from a strong discontinuity analysis. Close to complete failure, these distributions should be very close to each other. Their comparison provides two quantities: the displacement jump across the crack [U] and the distance between the two profiles. This distance is an error indicator defining how close the damage distribution is from that corresponding to a crack surrounded by a fracture process zone. It may subsequently serve in continuous/discrete models in order to define the threshold below which the continuum approach is close enough to the discrete one in order to switch descriptions. The estimation of the crack opening is illustrated on a one-dimensional example and the error between the profiles issued from discontinuous and FE analyses is found to be of a few percents close to complete failure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.11
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• pp.961-971
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• 2012

This article is concerned with effective numerical techniques for partial differential equation (PDE)-based image restoration. Numerical realizations of most PDE-based denoising models show a common drawback: loss of fine structures. In order to overcome the drawback, the article introduces a new time-stepping procedure, called the method of nonflat time evolution (MONTE), in which the timestep size is determined based on local image characteristics such as the curvature or the diffusion magnitude. The MONTE provides PDE-based restoration models with an effective mechanism for the equalization of the net diffusion over a wide range of image frequency components. It can be easily applied to diverse evolutionary PDE-based restoration models and their spatial and temporal discretizations. It has been numerically verified that the MONTE results in a significant reduction in numerical dissipation and preserves fine structures such as edges and textures satisfactorily, while it removes the noise with an improved efficiency. Various numerical results are shown to confirm the claim.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• Research in Mathematical Education
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• v.5 no.2
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• pp.107-118
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• 2001

Mathematics subject of the seventh national curriculum in Korea, which has been effective since 2000, strongly encourages the use of calculators and computers to help children gain a better understanding of basic mathematical concepts and develop creative thinking and problem-solving skills without spending too much time and effort on making mechanical computations. Despite the recommendation by the national curriculum, however, only a small segment of elementary school teachers have been using calculators because of the fear that children\\`s dependence on calculators might bring about negative consequences. As a result, little research has been conducted in this area as well. This study has been conducted on the assumption that calculators have the potential for being a useful instructional tool in certain areas of elementary school mathematics education. To investigate the usefulness of calculators, a review was made of the scanty literature in the area. The literature review indicated that calculators are effective when they are used for the following purposes: understanding concepts and properties in numbers and operations, deducing mathematical rules, and solving problems. In view of the available research finding, we will give some concrete learning and teaching models of such uses of calculators. The teaching-learning models are organized around three categories: concept formation, discovery of principles and rules, and problem solving. Such organization is intended to help teachers use the models with ease.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.5
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• pp.25-30
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• 2016

This study investigates the heat transfer due to a change in the shape of a radiator panel inside a computer. As with models of radiator panels, models have the same surface areas. As the gap between heat transfer surfaces in model 1 becomes wider than those in model 2, the heat transfer at model 1 becomes smoother than that of model 2. By comparing the cooling processes between models 1 and 2 with respect to natural convection, a maximum temperature of $47.432^{\circ}C$ at model 1 becomes lower than that of model 2, at $49.821^{\circ}C$. Within the radiator panel, model 1 has been shown to be more effective than model 2. Accordingly, these results can be effectively applied to the shape design of radiator panels to imbue them with smoother and faster heat transfer through the finite element method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.105-115
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• 2016

Ensemble classification involves combining individually trained classifiers to yield more accurate prediction, compared with individual models. Ensemble techniques are very useful for improving the generalization ability of classifiers. The random subspace ensemble technique is a simple but effective method for constructing ensemble classifiers; it involves randomly drawing some of the features from each classifier in the ensemble. The instance selection technique involves selecting critical instances while deleting and removing irrelevant and noisy instances from the original dataset. The instance selection and random subspace methods are both well known in the field of data mining and have proven to be very effective in many applications. However, few studies have focused on integrating the instance selection and random subspace methods. Therefore, this study proposed a new hybrid ensemble model that integrates instance selection and random subspace techniques using genetic algorithms (GAs) to improve the performance of a random subspace ensemble model. GAs are used to select optimal (or near optimal) instances, which are used as input data for the random subspace ensemble model. The proposed model was applied to both Kaggle credit data and corporate credit data, and the results were compared with those of other models to investigate performance in terms of classification accuracy, levels of diversity, and average classification rates of base classifiers in the ensemble. The experimental results demonstrated that the proposed model outperformed other models including the single model, the instance selection model, and the original random subspace ensemble model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.619-624
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• 2000

Design of experiments based on Taguchi's orthogonal array is utilized for exploring the design space and for building response surface models of insulator and isolator database in order to facilitate the effective solution of multi-objective optimization commonly occurred in NVH problems. Response surface models, called engineering database of design space, provide an efficient means to rapidly model the trade-off among many conflicting NVH goals in automotive. In the design of insulator and isolator in automotive interior part, it is important not only to construct effective matrices of NVH but also to build up engineering database of current products. The experimental design especially based on orthogonal array and the nonlinear optimization algorithms are successfully used together to obtain the optimal design of insulator and isolator. The $2^{nd}$ order response surface models of absorption coefficient and insertion loss are constructed by using modified Taguchi's $L_{12}2^13^7$ orthogonal array and successfully used in optimal design of insulator and isolator.