• IE interfaces
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• v.16 no.3
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• pp.344-351
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• 2003

Critical dimension is one of the most important characteristics of up-to-date integrated circuit devices. Hence, critical dimension control in a semiconductor wafer fabrication process is inevitable in order to achieve optimum device yield as well as electrically specified functions. Currently, in complex semiconductor wafer fabrication processes, statistical methodologies such as Shewhart-type control charts become crucial tools for practitioners. Meanwhile, given a critical dimension sampling plan, the analysis of variance technique can be more effective to investigating critical dimension variation, especially for on-chip and on-wafer variation. In this paper, relating to a typical sampling plan, linear statistical models are presented for the analysis of critical dimension variation. A case study is illustrated regarding a semiconductor wafer fabrication process.

• Bulletin of the Korean Mathematical Society
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• v.51 no.2
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• pp.519-530
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• 2014

Let (R,m) be a Noetherian local ring and M a finitely generated R-module. For an integer s > -1, we say that M is Cohen-Macaulay in dimension > s if every system of parameters of M is an M-sequence in dimension > s introduced by Brodmann-Nhan [1]. In this paper, we give some characterizations for Cohen-Macaulay modules in dimension > s in terms of the Noetherian dimension of the local cohomology modules $H^i_m(M)$, the polynomial type of M introduced by Cuong [5] and the multiplicity e($\underline{x}$;M) of M with respect to a system of parameters $\underline{x}$.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.114-125
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• 1997

This paper presents a method that automatically recognizes dimension sets from the mechanical drawings, and that classifies 6 types dimension sets according to functional purpose. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then object lines and interpretation lines are vectorized. And, after recognizing dimension sets(consistings of arrowhead, shape line, tail lines, extension lines, text-string, and feature control frame), we classify recognized dimension sets as horizontal, vertical, angular, diametral, radial, and leader dimension sets. Finally the proposed method converts classified dimension sets into AutoCAD data by using AutoLisp language. By using the methods of geometric modeling, the proposed method readily recognized and classifies dimension sets from complex drawings. Experimetnal results are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.513-521
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• 2018

The goal of sufficient dimension reduction (SDR) is to replace original p-dimensional predictors with a lower-dimensional linearly transformed predictor. The sliced inverse regression (SIR) (Li, Journal of the American Statistical Association, 86, 316-342, 1991) is one of the most popular SDR methods because of its applicability and simple implementation in practice. However, SIR may yield different dimension reduction results for different numbers of slices and despite its popularity, is a clear deficit for SIR. To overcome this, a fused sliced inverse regression was recently proposed. The study shows that the dimension-reduced predictors is robust to the numbers of the slices, but it does not investigate how robust its dimension determination is. This paper suggests a permutation dimension determination for the fused sliced inverse regression that is compared with SIR to investigate the robustness to the numbers of slices in the dimension determination. Numerical studies confirm this and a real data example is presented.

• Journal of the Korean Home Economics Association
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• v.26 no.3
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• pp.1-12
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• 1988

The objectives of the study were two folds. The first objective was to determine the dimensions of the evaluative criteria of various clothing items (underwear, pajamas, jeans, blouse, two-piece, coat). The second objective was to compare the importance of the dimensions according to the clothing items and the socioeconomic status of the subjects. The questionnaires were administered to college female students living in Seoul. Principal component factor analysis with varimax rotation and ANOVA were used for the analysis. The results were as follows; 1) The evaluative criteria dimensions were found to be different according to clothing items. (1) In underwear, pajamas, jeans, evaluative criteria were classified into Aesthetic dimension, economic dimension and Functional dimension. (2) In blouse, two-piece, coat, evaluative criteria were classified into Aesthetic dimension and practical dimension. 2) there were partially significant differences in placing importance on each evaluative criteria dimension between socio-economic groups. (1) In jeans, there was a significant difference in placing importance on Aesthetic dimension between socioeconomic status groups. (2) In blouse and two-piece there was a significant difference in placing importance on Practical dimension between socioeconomic status groups.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.42-48
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• 1997

This paper has apparaised ability of speaker recognition and speech recognition using correlation dimension and Lyapunov dimension. In this method, speech was regarded the cahos that the random signal is appeared in determinisitic raising system. we deduced exact correlation dimension and Lyapunov dimension with searching important orbit from AR model power spectrum when reconstruct strange attractor using Taken's embedding theory. We considered a usefulness of speech recognition and speaker recognition using correlation dimension and Lyapunov dimension that characterized reconstruction attractor. As a result of consideration, which were of use more the speaker recognition than speech recognition, and in case of speaker recognition using Lyapunov dimension were much recognition rate more than speaker recognitions using correlation dimension.

• Journal of Dental Rehabilitation and Applied Science
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• v.18 no.3
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• pp.185-195
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• 2002

Purpose This article describes the historic and clinical aspects of the determination of the vertical dimension of occlusion and the synoptic procedure of the determination of the vertical dimension of occlusion in complete denture. The determining procedure of the susceptible vertical dimension of occlusion is one of the most important steps in construction of complete denture and prosthodontic treatment. It is considered essential for the improvement and the recovery of facial esthetics and stomatognathic functions. Results Several methods have been suggested for measurement of the vertical dimension of occlusion in the construction of complete denture and the prosthodontic rehabilitation. These range from pre-extraction records to the use of physiologic rest position, swallowing, phonetics, esthetics and facial proportion, etc. But, there is no universally accepted or completely accurate method. There seems to be no significant advantages of one technique other than those of cost, time and equipment requirements, and seems to be in controversial in determining the vertical dimension. Conclusion The vertical dimension of occlusion should be determined and reinspected carefully by dentist for a successful prosthesis with several methods. The more investigations are necessary for more objective and scientific techniques in determining the vertical dimension of occlusion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1140-1148
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• 1994

In this paper, we carried out some experiments on the Korean vowel recognition using the fractal dimension of the speech signals. We chose the Minkowski-Bouligand dimension as the fractal dimension, and computed it using the morphological covering method. For our experiments, we used both the fractal dimension and the LPC cepstrum which is conventionally known to be one of the best parameters for speech recognition, and examined the usefulness of the fractal dimension. From the vowel recognition experiments under various consonant contexts, we achieved the vowel recognition error rates of 5.6% and 3.2% for the case with only LPC cepstrum and that with both LPC cepstrum and the fractal dimension, respectively. The results indicate that the incorporation of the fractal dimension with LPC cepstrum gives more than 40% reduction in recognition errors, and indicates that the fractal dimension is a useful feature parameter for speech recognition.

• Journal of Fashion Business
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• v.22 no.1
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• pp.135-147
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• 2018

Since the 20th century, there has been a growing interest in the new concept of fractals, a combination of mathematics and art, and the attempt to study the creative spatial aspects of the concept is being made. The purpose of this research is to examine artistic characteristics of fractal dimension and then analyze the types of fractal dimensions expressed in the fashion. Previous literature on fractals and dimension, and visual data on art and fashion collected over the Internet were used for analysis. Fractal dimension refers to the spatial concept of structural dimension of geometrical self-similarity. An analysis of the types of fractals seen in fashion revealed spatial expansion, the repetition in continual figures, superposition accordant to different sizes, and shades of different shapes. The aesthetic characteristics of fractal dimension appearing in fashions were examined based on analyses of fractal dimension types; the inherent characteristics of self-similarity, superimposition, and atypicality were found. Results obtained from this study are expected to be used as basic materials for the application of the design of fractal dimension into various perspectives of fashion.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.4
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• pp.301-312
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• 2022

In an extensive oral rehabilitation, determining a proper occlusal vertical dimension is a critical step and the starting point for successful treatment. Since changing the occlusal vertical dimension could be time-consuming, financially challenging, and physically demanding for both clinicians and patients, multi-faceted analysis and careful consideration are essential in the diagnosis and further treatment process. The purpose of this narrative review is to discuss the occlusal vertical dimension and its current issues, and to summarize previous methods of evaluating occlusal vertical dimension to propose clinical guidance for determining a viable occlusal vertical dimension for full-mouth rehabilitation.