• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.330-343
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• 2007

In this paper, we present a new surface content completion system that can effectively repair both shape and appearance from scanned, incomplete point set inputs. First, geometric holes can be robustly identified from noisy and defective data sets without the need for any normal or orientation information. The geometry and texture information of the holes can then be determined either automatically from the models' context, or manually from users' selection. After identifying the patch that most resembles each hole region, the geometry and texture information can be completed by warping the candidate region and gluing it onto the hole area. The displacement vector field for the exact alignment process is computed by solving a Poisson equation with boundary conditions. Out experiments show that the unified framework, founded upon the techniques of deformable models and PDE modeling, can provide a robust and elegant solution for content completion of defective, complex point surfaces.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.13-23
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• 2006

The present study has investigated the patterns and the causes of safety -accidents on the accident-data in semiconductor Industries through near miss report the cases in the advanced companies. The ratio of incomplete actions to incomplete state was 4 to 6 as the cases of accidents in semiconductor industries in the respect of Human-ware, Hard- ware, Environment-ware and System-ware. The ratio of Human to machine in the attributes of semiconductor accident was 4 to 1. The study also investigated correlation among the system related to production, accident, losses and time. In semiconductor industry, we found that pattern of safety-accident analysis is organized potential, interaction, complexity, medium. Therefore, this study find out that semiconductor model consists of organization, individual, task, machine, environment and system.

• 한국전산유체공학회:학술대회논문집
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• 1995.10a
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• pp.235-240
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• 1995

The paper describes hypersonic rarefied flow of helium and nitrogen over a flat plate by the direct simulation Monte Carlo (DSMC) method. The effect of incomplete accommodation and plate thickness are analyzed and the computational results are compared with wind tunnel test data. Also computational aspects of the method are outlined.

• International Journal of Contents
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• v.9 no.4
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• pp.1-10
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• 2013

The electroencephalogram (EEG) time series is a measure of electrical activity received from multiple electrodes placed on the scalp of a human brain. It provides a direct measurement for characterizing the dynamic aspects of brain activities. These EEG signals are formed from a series of spatial and temporal data with multiple dimensions. Missing data could occur due to fault electrodes. These missing data can cause distortion, repudiation, and further, reduce the effectiveness of analyzing algorithms. Current methodologies for EEG analysis require a complete set of EEG data matrix as input. Therefore, an accurate and reliable imputation approach for missing values is necessary to avoid incomplete data sets for analyses and further improve the usage of performance techniques. This research proposes a new method to automatically recover random consecutive missing data from real world EEG data based on Linear Dynamical System. The proposed method aims to capture the optimal patterns based on two main characteristics in the coevolving EEG time series: namely, (i) dynamics via discovering temporal evolving behaviors, and (ii) correlations by identifying the relationships between multiple brain signals. From these exploits, the proposed method successfully identifies a few hidden variables and discovers their dynamics to impute missing values. The proposed method offers a robust and scalable approach with linear computation time over the size of sequences. A comparative study has been performed to assess the effectiveness of the proposed method against interpolation and missing values via Singular Value Decomposition (MSVD). The experimental simulations demonstrate that the proposed method provides better reconstruction performance up to 49% and 67% improvements over MSVD and interpolation approaches, respectively.

• Journal of Gastric Cancer
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• v.14 no.4
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• pp.259-265
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• 2014

Purpose: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. Materials and Methods: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. Results: The mean patient survival time after diagnosis was $49.1{\pm}4.4$ months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). Conclusions: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.91-97
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• 2021

This paper uses a data extension technique originally designed for the rule refinement problem to handling incomplete data. This technique is characterized in that each event can have a weight indicating importance, and each variable can be expressed as a probability value. Since the key problem in this paper is to find the probability that is closest to the missing value and replace the missing value with the probability, three different algorithms are used to find the probability for the missing value and then store it in this data structure format. And, after learning to classify each information area with the SVM classification algorithm for evaluation of each probability structure, it compares with the original information and measures how much they match each other. The three algorithms for the imputation probability of the missing value use the same data structure, but have different characteristics in the approach method, so it is expected that it can be used for various purposes depending on the application field.

• Journal of Home Health Care Nursing
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• v.25 no.1
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• pp.58-66
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• 2018

Purpose: The purpose of this study was to find out lower urinary tract symptoms, daily life inconvenience, and sleep quality in elderly community woman. Methods: Participants were 140 elderly women. Data collection was conducted from September 1 to October 30, 2017. Data were analyzed using descriptive statistics and t-test with the SPSS program. Results: The rate of urge incontinence was 25.0%, stress incontinence 36.4%, unexplained incontinence 15.7%, and nocturnal incontinence 9.3%. Those participants with urge incontinence presented significantly higher daily life inconvenience scores; urge incontinence, stress incontinence, and unexplained incontinence were significantly associated with lower sleep quality scores. Furthermore, frequent urination, nocturia, and incomplete emptying were significantly higher daily life inconvenience scores; and frequent urination, nocturia, hesitancy, straining, intermittent stream, burning, incomplete emptying, bladder pain, and abnormal strength of stream were significantly related to lower sleep quality scores. Conclusion: It is necessary to develop intervention strategies considering incontinence and urination symptoms to reduce daily life inconvenience caused by lower urinary tract symptoms and improve sleep quality in elderly women.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.932-935
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• 2002

In this paper, we introduce new FTL(Flash Translation Layer) driver algorithm that tolerate the power off errors. FTL driver is the software that provide the block device interface to the upper layer software such as file systems or application programs that using the flash memory as a block device interfaced storage. Usually, the flash memory is used as the storage devices of the mobile system due to its low power consumption and small form factor. In mobile system, the state of the power supplement is not stable, because it using the small sized battery that has limited capacity. So, a sudden power off failure can be occurred when we read or write the data on the flash memory. During the write operation, power off failure may introduce the incomplete write operation. Incomplete write operation denotes the inconsistency of the data in flash memory. To provide the stable storage facility with flash memory in mobile system, FTL should provide the fault tolerance against the power off failure. SSR (Simple Sector Remapper) is a fault tolerant FTL driver that provides block device interface and also provides tolerance against power off errors.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.167-174
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• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.1
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• pp.27-42
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• 2003

The purpose of this study is to evaluate the quality of the Serials Union Catalog(UCAT) of KISTI. In examining both MARC records and bibliographic display records of 172 Japanese serials, AACR2R and KORMARC formats were used as the standard rules. Those records were described in the minimum or incomplete level ; but had repeated errors in various data fields, which included the incorrect choice of main headings, parallel titles and other titles, the improper use of language codes and related data fields, and the provision of incomplete information, etc. To improve the overall quality of bibliographic database, thorough comprehension and application of cataloging rules and MARC formats are strongly required.