• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.485-490
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• 2004

In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.253-263
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• 2018

Internet addiction in adolescents is an important social issue. In this study, sparse partial least-squares regression (SPLS) was applied to internet addiction data in Korean adolescent samples. The internet addiction score and various clinical and psychopathological features were collected and analyzed from self-reported questionnaires. We considered three PLS methods and compared the performance in terms of prediction and sparsity. We found that the SPLS method with the hierarchical likelihood penalty was the best; in addition, two aggression features, AQ and BSAS, are important to discriminate and explain latent features of the SPLS model.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.4
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• pp.444-456
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• 2007

Statement of problem: Implant inclination and cantilever loading increse loads distributed to implants, potentially causing biomechanical complications. Controversy exists regarding the effect of the intentionally distal-inclined implant for the reduction of the cantilever length. Purpose: This study investigated the stress distribution at the bone/implant interface and prostheses with 3D finite element stress analysis by using four different cantilever lengths and implant inclinations in a mandibular implant-supported bar overdenture. Material and methods: Four 3-D finite element models were created in which 4 implants were placed in the interforaminal area and had four different cantilver lengths(10, 6.9, 4 and 1.5mm) and distal implant inclinations$(0^{\circ},\;15^{\circ},\;30^{\circ}\;and\;45^{\circ})$ respectively. Vortical forces of 120N and oblique forces of 45N were applied to the molar area. Stress distribution in the bone around the implant was analysed under different distal implant inclinations. Results: Analysis of the von Mises stresses for the bone/implant interfaces and prostheses revealed that the maximum stresses occurred at the most distal bone/implant interface and the joint of bar and abutment, located on the loaded side and significantly incresed with the implant inclinations, especially over $45^{\circ}$. Conclusion: Within the limitations of this study, it was suggested that too much distal inclination over 45 degrees can put the implant at risk of overload and within the dimension of the constant sum of a anterior-posterior spread and cantilever length, a distal implant inclination compared to cantilever length had the much larger effect on the stress distribution at the bone/implant interface.

• KIEAE Journal
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• v.5 no.2
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• pp.11-18
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• 2005

The Purpose of this study is development and analysis of Effluence Characteristic of the Rainfall in the IRMA Green Roof System(developed in KICT) Plus 50 program is an internal research project at KICT(Korean Institute of Construction Technology) which has it as an object ; to lengthen the building's life 50-year or more and reduce energy conception 50% than present. Green roof system is one of the most important theme in the Plus 50 program. Generally, a Green Roof System has a positive effect on the thermal conductivity in winter, the micro cooling effect on building and city by evaporation in summer, the flood-control effect by runoff-reduction or the treated rainwater-quality of green roof system and so on. However, inspection of the physical effect of green roof system does not consider in Korea. Above all, long-term monitoring and a whole observation of green roof system is needed to probate the effect. So a new experimental method could be tried in this research, which is never attempted in Korea. The measurement by a bucket with a great volume, 1L, gives a new dimension of measuring green roof effect to measure the permanent running flood from a wide roof. This offers a reasonable result on a long-term measuring of a running water. Additionally, the thermal behavior of the IRMA(Insulated Roof Membrane Assembly), known in the western europe as a reasonable solution at green roof system by economical benefits and easy construction, would be experimented.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1095-1106
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• 2016

The quantile regression method proposed by Koenker et al. (1978) focuses on conditional quantiles given by independent variables, and analyzes the relationship between response variable and independent variables at the given quantile. Considering the linear programming used for the estimation of quantile regression coefficients, the model fitting job might be difficult when large data are introduced for analysis. Therefore, dimension reduction (or variable selection) could be a good solution for the quantile regression of large data sets. Regression tree methods are applied to a variable selection for quantile regression in this paper. Real data of Korea Baseball Organization (KBO) players are analyzed following the variable selection approach based on the regression tree. Analysis result shows that a few important variables are selected, which are also meaningful for the given quantiles of salary data of the baseball players.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.11
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• pp.1217-1224
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• 2009

This paper newly proposes a methodology towards computing antenna element weights which are satisfying asymmetric sidelobe levels(SLLs) specified arbitrarily on both sides of the main beam pattern, in the linear phased array antenna pattern synthesis problem. Opposite to the conventional methods in which the element weights are directly optimized from the array factor, this method is based on the optimum perturbations of complex roots inherent to the Schelkunoff's polynomial form which is described for the array factor. From the proposed methodology, the capability of nulling the directions of multiple jammers is also possible by independently perturbing only the complex roots corresponding to each jamming direction, hence allowing an enhancement of the simplicity of the numerical procedure by means of a proper reduction of the dimension of the solution space. The complex weights over the array are then easily computed by substituting the optimally perturbed complex roots to the Schelkunoff's polynomial. Some examples are examined and numerically verified by substituting the extracted weights into the array factor equation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.2
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• pp.86-94
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• 2014

Optical packet switching (OPS) is being considered as one of the switching technologies for a future optical internet. For contention resolution in an optical packet switching (OPS) system, the wavelength dimension is generally used in combination with a fiber delay line (FDL) buffer. In this article, we propose a method to reduce the number of tunable wavelength converters (TWCs) by sharing TWCs for a cost-effective design of an asynchronous OPS system with a shared or an output FDL buffer. Asynchronous and variable-length packets are considered in the OPS system design. To investigate the number of TWCs needed for the OPS system, an algorithm is proposed, which searches for an available TWC and an unused internal wavelength, as well as an outgoing channel. This algorithm is applied to an OPS system with a shared or an output FDL buffer. Also, the number of internal wavelengths (i.e., the conversion range of the TWC) needed for an asynchronous OPS system is presented for cost reduction of the OPS system.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.297-303
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• 2009

In this paper, we propose the biomedical spectral pattern classification techniques by the fusion scheme based on the SpPCA and MLP in extended feature space. A conventional PCA technique for the dimension reduction has the problem that it can't find an optimal transformation matrix if the property of input data is nonlinear. To overcome this drawback, we extract features by the SpPCA technique in extended space which use the local patterns rather than whole patterns. In the classification step, individual classifier based on MLP calculates the similarity of each class for local features. Finally, biomedical spectral patterns is classified by the fusion scheme to effectively combine the individual information. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.21 no.2
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• pp.149-165
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• 1999

The pathomechanism of obstructive sleep apnea(OSA) is not clearly elucidated. The possible mechanisms are pathologic reduction of pharyngeal muscular tonus during sleep, abnormal anatomical stenosis of nasopharyx or a combination of the above two mechanisms. It is very important to find the cause(anatomical location or pathologic dynamic change) of OSA in order to treat it. Cephalometric analysis in patients with obstructive sleep apnea is a good method for evaluating anatomical morphologic change but it cannot give any information about the dynamic changes occurring during sleep. On the contrary, nasopharyngeal endoscopy offer 3 dimensional image and information about the dynamic changes. Accordingly, these two diagnostic tools can be utilize in the diagnosis and treatment planning of OSA Cephalometric analysis of craniofacial skeletal and soft tissue morphology in 53 patients with OSA and 43 controls was performed and cephalometric analysis and nasopharygeal endoscopy were performed in 9 patients with OSA in order to come up with individualized therapy plans. Following results were obtained ; Patients with OSA showed 1. body weight gain 2. clockwise mandibular rotation 3. increased anterior lower facial height 4. inferiorly positioned hyoid bone 5. increased length of soft palate 6. decreased sagittal dimension of nasopharyx 7. increased vertical length of inferior collapsable nasopharyx 8. increased length of tongue Through cephalometric analysis and nasopharygeal endoscopy(mutually cooperative in diagnosis), 9. one can find the possible origin of OSA and make a adequate individualized therapy plan and predict accurate prognosis. Cephalometric analysis and nasopharygeal endoscopy are highly recommended as a diagnostic aid in OSA patients

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.15-24
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• 2008

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.