• Communications of the Korean Mathematical Society
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• v.38 no.4
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• pp.983-992
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• 2023

Let A be a ring and 𝓙 = {ideals I of A | J(I) = I}. The Krull dimension of A, written dim A, is the sup of the lengths of chains of prime ideals of A; whereas the dimension of the maximal spectrum, denoted by dim _𝓙A, is the sup of the lengths of chains of prime ideals from 𝓙. Then dim _𝓙A ≤ dim A. In this paper, we will study the dimension of the maximal spectrum of some constructions of rings and we will be interested in the transfer of the property J-Noetherian to ring extensions.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.39
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• pp.15.1-15.7
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• 2017

Background: This study constructed a partial-least-square path-modeling (PLS-PM) model and found the pathway by which the postsurgical vertical dimension (VD) affects the extent of the final mandibular setback on the B point at the posttreatment stage for the skeletal class III surgery-first approach (SFA). Methods: This study re-analyzed the data from the retrospective study by Lee et al. on 40 patients with skeletal class III bimaxillary SFA. Variables were obtained from cone beam computed tomography (CBCT)-generated cephalograms. Authors investigated all variables at each time point to build a PLS-PM model to verify the effect of the VD on the final setback of the mandible. Results: From PLS-PM, an increase in $VD_{10}$ was found to decrease the absolute value of the final setback amount of the mandible, which reflects the postsurgical physiological responses to both surgery and orthodontic treatment, which, in turn, can be interpreted as an increase in postoperative mandibular changes. Conclusions: To resolve the issue of collinear cephalometric data, the present study adopted PLS-PM to assess the orthodontic treatment. From PLS-PM, it was able to summarize the effect of increased postsurgery occlusal vertical dimension on the increased changeability of the B point position at the posttreatment stage.

• Journal of the Korean Society of Safety
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• v.22 no.3 s.81
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• pp.81-87
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• 2007

In this study digital human models of ship construction tasks using modeling & simulation were constructed and human models' activities through human activity analysis were evaluated. Human Factors experts analyzed the actual workers' tasks using the same technique used in human activity analysis at the same time. The main objective of this study is to check a possibility of applying digital human modeling technique to ship construction tasks that are mostly non-standardized(not uniformed) whereas most applications of digital human modeling technique have been applied to standardized tasks. We evaluated postures of both real workers and digital humans by RULA. It turned out that the final scores of RULA evaluation on real workers are the same as the RULA scores for digital humans. However, there were differences of RULA detail scores between real workers and digital humans in the several processes related with the wrist twist and deviations. Those differences are considered to be resulted from the error in the on-site measuring worker's body dimension which could be reduced by accurate tools to correct data for body dimension and digital real drawings for facilities. The results showed possibility of application of digital human modeling and ergonomic analysis on informal work operations as well as formal operations in the shipbuilding industry.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.668-671
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• 2010

Comparative study on propellant modeling has been investigated using a non-dimensional method and an one-dimensional method. The propellant location in the chamber can not be described by the non-dimensional method. It is, however, possible for the one-dimensional method to describe. Therefore, the analysis of the interior ballistics according to the propellant arrangements has been performed by the one-dimensional method. The negative differential pressure in the chamber could be predicted and the necessity of the one-dimensional modeling for the analysis of the interior ballistics has been confirmed.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.120-131
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• 1997

This paper prsents a new method that automatically recognizes the dimension lines (consisting of shape lines, tail lines and extension lines) from the mechanical drawings. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then the object lines and interpretation lines are vectorized by using several techniques such as thinning, line-vectorization, and vector-clustering. Finally, after recognizing arrowheads by using pattern matching, we recognize dimension lines from interpretation lines by using arrohead's directional vector and centroid. By using the methods of geometric modeling and mathematical operation, the proposed method readility recognizes the dimension lines from complex drawings. Experimental resuls are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.813-822
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• 2010

We investigate a possible achievement in dimension reduction of time series via partially quantified principal component. Partial quantification technique allows us in modeling to accommodate artificial variable(s) of practical importance which is defined subjectively by the data analyst. Suggested procedures are described and in turn illustrated in detail by analyzing monthly unemployment rates in Korea.

• MALSORI
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• no.67
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• pp.167-180
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• 2008

This paper describes a novel spectral envelope conversion method based on Gaussian mixture model (GMM). The core of this paper is rearranging source feature vectors in input space to the transformed feature vectors in feature space for the better modeling of GMM of source and target features. The quality of statistical modeling is dependent on the distribution and the dimension of data. The proposed method transforms both of the distribution and dimension of data and gives us the chance to model the same data with different configuration. Because the converted feature vectors should be on the input space, only source feature vectors are rearranged in the feature space and target feature vectors remain unchanged for the joint pdf of source and target features using KPCA. The experimental result shows that the proposed method outperforms the conventional GMM-based conversion method in various training environment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.96-100
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• 1996

So far the analysis and modeling of cutting process is studied commonly assumed as being linear stochastic or chaotic without experimental verification. So we verified force signals of cutting process(ball end-milling) is low-dimensional chaos by calculating Lyapunov Exponents. reconstructing attractor using time delay coordinates and calcula-ting it's fractal dimension.

• Journal of the Korean Society of Costume
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• v.38
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• pp.31-49
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• 1998

This study is the primary basic study about the spatial feature of modeling of Fashion Design. Then, this researcher lays significance in establishing the basic system about the character of dress and its ornaments as modeling in spatial-formal, dimension, examining the feature of modeling closely through perception principle and offering the basic principle to plan and organize the modeling space for dress and its ornaments on the basis of it. To generalize the findings is as follows : First, the spatial system of modeling for dress and its ornaments is made with 3 elements such as space, human beings and dress and its ornaments. Second, the form of dress and its ornaments and the spatial organization start from the structural basis which is human body, and the sensible system of body is made through inter-action, but the aesthetic expression is complet-ed by the moment of body. Third, the characteristic principle of model-ing for dress and its ornaments which was suggested in Chapter IV is based on the visuo-per-ceptional modeling experience, and these thinking contents are inputted in cognition course as the invisible in formation in the new space plan and organization and activate the apperception course and aim at the action about aesthetic judgement.