• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.224-227
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• 2003

The Intrsuion Detecion Systems(IDS) are required the accuracy, the adaptability, and the expansion in the information society to be changed quickly. Also, it is required the more structured, and intelligent IDS to protect the resource which is important and maintains a secret in the complicated network environment. The research has the purpose to build the model for the intelligent IDS, which creates the intrusion patterns. The intrusion pattern has extracted from the vast amount of data. To manage the large size of data accurately and efficiently, the link analysis and sequence analysis among the data mining techniqes are used to build the model creating the intrusion patterns. The model is consist of "Time based Traffic Model", "Host based Traffic Model", and "Content Model", which is produced the different intrusion patterns with each model. The model can be created the stable patterns efficiently. That is, we can build the intrusion detection model based on the intelligent systems. The rules prodeuced by the model become the rule to be represented the intrusion data, and classify the normal and abnormal users. The data to be used are KDD audit data.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.221-222
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• 2021

Conventionally, in material management at a construction site, the type, size, and quantity of materials are identified by the eyes of the worker. Labor-intensive material management by manpower is slow, requires a lot of manpower, is prone to errors, and has limitations in that computerization of information on the identified types and quantities is additionally required. Therefore, a method that can quickly and accurately determine the type, size, and quantity of materials with a minimum number of workers is required to reduce labor costs at the construction site and improve work efficiency. In this study, we developed an automated convolution neural network(CNN) and computer vision technology-based rebar size and quantity estimation system that can quickly and accurately determine the type, size, and quantity of materials through images.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.75-81
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• 2011

This paper presents a novel method for image classification based on a hybrid genetic algorithm (GA) and support vector machine (SVM) approach which can significantly improve the classification performance for content-based image retrieval (CBIR). Though SVM has been widely applied to CBIR, it has some problems such as the kernel parameters setting and feature subset selection of SVM which impact the classification accuracy in the learning process. This study aims at simultaneously optimizing the parameters of SVM and feature subset without degrading the classification accuracy of SVM using GA for CBIR. Using the hybrid GA and SVM model, we can classify more images in the database effectively. Experiments were carried out on a large-size database of images and experiment results show that the classification accuracy of conventional SVM may be improved significantly by using the proposed model. We also found that the proposed model outperformed all the other models such as neural network and typical SVM models.

• Korean Management Science Review
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• v.10 no.1
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• pp.81-105
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• 1993

The objective of the paper is to develop models for determining the aggregate budget size in long-range R&D planning of KT(Korea Telecom.) and for allocating it by strategically adopted technologies for KT's TOP(Telecommunication-Oriented Paradise) Strategy. In the model of R&D budget size determination, the linear regression analysis is applied. In allocating the R&D expenditure, criteria weighting and technological importance ranking are determined by means of the Analytic Hierarchy Process(AHP) as a decision aid, along with hierarchical representation and pairwse comparisons. R&D budget analysis provides to basic data for the mid-and long-range R&D planning. The model then needs to be adjusted as the TOP project plan becomes specific. Resource allocation model for R&D based on AHP can be used to identify the importance of the technologies for TOP according to short-, mid-, and long-term perspectives without further modification. It is expected that the R&D budget analysis model works as the basis for planning R&D investment strategies and that the resource allocation model for R&D contributes to the effective use of the limited resource.

• Geomechanics and Engineering
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• v.13 no.6
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• pp.947-961
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• 2017

An innovative spiral variable-section capillary model is established for piping critical hydraulic gradient of cohesion-less soils causing water/mud inrush in tunnels. The relationship between the actual winding seepage channel and grain-size distribution, porosity, and permeability is established in the model. Soils are classified into coarse particles and fine particles according to the grain-size distribution. The piping critical hydraulic gradient is obtained by analyzing starting modes of fine particles and solving corresponding moment equilibrium equations. Gravities, drag forces, uplift forces and frictions are analyzed in moment equilibrium equations. The influence of drag force and uplift force on incipient motion is generally expounded based on the mechanical analysis. Two cases are studied with the innovative capillary model. The critical hydraulic gradient of each kind of sandy gravels with a bimodal grain-size-distribution is obtained in case one, and results have a good agreement with previous experimental observations. The relationships between the content of fine particles and the critical hydraulic gradient of seepage failure are analyzed in case two, and the changing tendency of the critical hydraulic gradient is accordant with results of experiments.

• Journal of Korean Society of Water and Wastewater
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• v.13 no.3
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• pp.42-55
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• 1999

A mathematical model for biological nutrient removal in a sequencing batch reactor process, which is based on the IAWQ Activated Sludge Model No. 2 with a few modifications, has been developed. Twenty water quality components and twenty three kinetic equations are incorporated in the model. The model is structured in the matrix form based on the law of mass conservation using stoichiometry and kinetic equations. Stoichiometric coefficients and kinetic parameters included in the model equations are chosen from the literature. A multistep predictor-corrector algorithm of variable step-size is adopted for solving the vector nonlinear ordinary differential equations. The simulation for experimental results is conducted to evaluate the validity of the model and to calibrate coefficients and parameters. The simulation using the model well represents the experimental results from laboratory. The mathematical model developed in this study may be utilized for the design and operation of a sequencing batch reactor process under the steady and unsteady-state at various environmental conditions.

• Geomechanics and Engineering
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• v.28 no.2
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• pp.135-143
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• 2022

Soils are natural granular materials whose mechanical properties differ according to the size and composition of the particles, so soils exhibit an obvious scale effect. Traditional soil mechanics is based on continuum mechanics, which can not reflect the impact of particle size on soil mechanics. On that basis, a matrix-reinforcing-particle cell model is established in which the reinforcing particles are larger-diameter sand particles and the matrix comprises smaller-diameter bentonite particles. Since these two types of particles deform differently under shear stress, a new shear-strength theory under direct shear that considers the stress concentration and bypass phenomena of the matrix is established. In order to verify the rationality of this theory, a series of direct shear tests with different reinforcing particle diameter and volume fraction ratio are carried out. Theoretical analysis and experimental results showed that the interaction among particles of differing size and composition is the basic reason for the size effect of soils. Furthermore, the stress concentration and bypass phenomena of the matrix enhance the shear strength of a soil, and the volume ratio of reinforcing particles has an obvious impact on the shear strength. In addition, the newly proposed shear-strength theory agrees well with experimental values.

• The Journal of the Acoustical Society of Korea
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• v.13 no.3
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• pp.63-70
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• 1994

In this Paper, we propose a new codeword tying algorithm based on a tree structured classfier. The proposed algorithm which can be viewed as a kind of soft decision using statistical properties between codewords and states has an advantage of fast construction, and guarantees a unique optimal solution. Also, it can easily be applied to any speech recognition system based on discrete hidden Markov model (HMM). Experimental results on speaker-independent isolated word recognition show error reduction of $6\%$ for the codebook of size 256 and $9\%$ for 512 size and also HMM parameter reduction of about $20\%$.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1009-1012
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• 1999

An analytical performance model that can predict the performance of a superscalar processor employing multiple branch prediction is introduced. The model is based on the conditional independence probability and the basic block size of instructions, with the degree of multiple branch prediction, the fetch rate, and the window size of a superscalar architecture. Trace driven simulation is performed for the subset of SPEC integer benchmarks, and the measured IPCs are compared with the results derived from the model. As the result, our analytic model could predict the performance of the superscalar processor using multiple branch prediction within 6.6 percent on the average.

• Computers and Concrete
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• v.11 no.5
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• pp.365-382
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• 2013

Although shear reinforcement in beams typically consists of steel bars bent in the form of stirrups or hoops, the addition of deformed steel fibres to the concrete has been shown to enhance shear resistance and ductility in reinforced concrete beams. This paper presents a model that can be used to predict the shear strength of fibrous concrete rectangular members without stirrups. The model is an extension of the plasticity-based crack sliding model originally developed for plain concrete beams. The crack sliding model has been improved in order to take into account several aspects: the arch effect for deep beams, the post-cracking tensile strength of steel fibre reinforced concrete and its ability to control sliding along shear cracks, and the mitigation of the shear size effect due to presence of fibres. The results obtained by the model have been validated by a large set of experimental tests taken from literature, compared with several models proposed in literature, and numerical analyses are carried out showing the influence of fibres on the beam failure mode.