• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.429-443
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• 1997

We consider the problem of obtaining several types of simultaneous confidence bands for the survival curve under the additive risk model. The derivation uses the weak convergence of normalized cumulative hazard estimator to a mean zero Gaussian process whose distribution can be easily approxomated through simulation. The bands are illustrated by applying them from two well-known clinicla studies. Finally, simulation studies are carried outo to compare the performance of the proposed bands for the survival function under the additive risk model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.108-122
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• 2014

Massive antenna array is an attractive candidate technique for future broadband wireless communications to acquire high spectrum and energy efficiency. However, such benefits can be realized only when proper channel information is available at the transmitter. Since the amount of the channel information required by the transmitter is large for massive antennas, the feedback is burdensome in practice, especially for frequency division duplex (FDD) systems, and needs normally to be reduced. In this paper a novel channel feedback reduction scheme based on the theory of distributed compressive sensing (DCS) is proposed to apply to massive antenna arrays with spatial correlation, which brings substantially reduced feedback load. Simulation results prove that the novel scheme is better than the channel feedback technique based on traditional compressive sensing (CS) in the aspects of mean square error (MSE), cumulative distributed function (CDF) performance and feedback resources saving.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.1
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• pp.203-217
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• 2021

Purpose: The purpose of this meta-analysis was to examine the high-level evidence of the effects of manual therapy on musculoskeletal diseases. Methods: Domestic databases were searched for studies that conducted clinical trials associated with manual therapy on chronic musculoskeletal diseases. A total of 591 studies published between 2005 and 2018 were identified, with 18 studies satisfying the inclusion data. The studies were classified according to patient, intervention, comparison, and outcome (PICO). The search outcomes were items associated with pain and physical function. The 18 studies included in the study were evaluated by using the R meta-analysis (version 4.0). The quality of 18 randomized control trials was evaluated by using the Cochrane risk of bias (ROB). The effect sizes were computed as the corrected standardized mean difference (SMD). Subgroup and meta-regression analyses were also used. Egger's regression test was carried out in order to analyze the publication bias. Cumulative meta-analysis and sensitivity analysis were also conducted in order to analyze the data error. Results: The following factors showed the large effect size of manual therapy on chronic musculoskeletal diseases: pain (Hedges's g = 2.66; 95% CI = 1.47 ~ 3.85), and physical function (Hedges's g = 2.15; 95% CI: 1.22 ~ 3.08). The subgroup analysis only showed a statistical difference in the type of manual therapy (pain) and outcome (physical function). No statistically significant difference was found in the meta-regression analysis. Publication bias was found in the data, but the results of the trim-and-fill method showed that such bias did not largely affect the obtained data. Furthermore, there were no data errors in the cumulative meta-analysis and sensitivity analysis. Conclusion: This study provides evidence for the effectiveness of manual therapy on chronic musculoskeletal diseases in pain and physical function. Subgroup analysis suggests that only the type of manual therapy for pain and the type of outcome for physical function differed in effect size.

• Asia pacific journal of information systems
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• v.25 no.3
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• pp.563-578
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• 2015

Forecasting daily box-office performance is critical for planning the distribution of marketing resources, and by extension, maximizing profits. For certain movies, the number of viewers increases rapidly at the beginning of their theatrical run, and the increments slow down later. Other movies are not popular in the beginning, but the audience sizes grow rapidly afterward. Thus, the audience attendance of movies grow in different trajectories, which are influenced by various factors including marketing budget, distributors, directors, actors, and word of mouth. In this paper, we propose a method for predicting the daily performance trajectory of running movies based on the hierarchical linear model. More specifically, we focus on the effect of online word of mouth on the shape of the growth curves. We fitted the mean trajectory of the cumulative audience size as a cubic function of time, and allowed the intercept and slope to vary movie-to-movie. Moreover, we fitted the linear slope with a function of online word of mouth predictors to help determine the shape of the trajectories. Finally, we provide performance predictions for individual movies.

• The Journal of Advanced Prosthodontics
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• v.7 no.4
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• pp.329-337
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• 2015

PURPOSE. This retrospective study aims at the evaluation of implant-supported overdentures (IODs) supported by ceramo-galvanic double crowns (CGDCs: zirconia primary crowns + galvano-formed secondary crown). MATERIALS AND METHODS. In a private practice, 14 patients were restored with 18 IODs (mandible: 11, maxilla: 7) retained by CGDCs on 4 - 8 implants and annually evaluated for technical and/or biological failures/complications. RESULTS. One of the 86 inserted implants failed during the healing period (cumulative survival rate (CSR) implants: 98.8%). During the prosthetic functional period (mean: $5.9{\pm}2.2years$), 1 implant demonstrated an abutment fracture (CSR-abutments: 98.2%), and one case of peri-implantitis was detected. All IODs remained in function (CSR-denture: 100%). A total of 15 technical complications required interventions to maintain function (technical complication rate: 0.178 treatments/patients/year). CONCLUSION. Considering the small sample size, the use of CGDCs for the attachment of IODs is possible without an increased risk of technical complications. However, for a final evaluation, results from a larger cohort are required.

• The Korean Journal of Ecology
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• v.24 no.4
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• pp.213-217
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• 2001

The purpose of this study is to investigate the effects of hardwood competitions in stand structure and dynamics by applying prediction models for unthinned loblolly pine (Pinus taeda L.) plantations. A parameter recovery procedure for the Weibull distribution function based on four percentile equations was applied to develop diameter distribution prediction models. Four percentiles of the cumulative diameter distribution prediction equations were predicted as a function of quadratic mean diameter plus competin hardwood trees perhectare varibales. According to the results of this study. it was found that as the amount of competing hardwood trees increased, diameter distributions in terms of stand structure dynamics tended to be more skewed to the right. Therefore, the influence of non-planted hardwood trees interspecific competitoin on planted loblolly pines showed negative effects on the stand structure and dynamics.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.669-684
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• 2012

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

• Journal of Wetlands Research
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• v.18 no.2
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• pp.132-147
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• 2016

In this study the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) sensor onboard the Soil Moisture Ocean Salinity (SMOS) and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission-Water (GCOM-W1) based soil moisture retrievals were revised to obtain better accuracy of soil moisture and higher data acquisition rate over East Asia. These satellite-based soil moisture products are revised against a reference land model data set, called Global Land Data Assimilation System (GLDAS), using Cumulative Distribution Function (CDF) matching and regression approach. Since MIRAS sensor is perturbed by radio frequency interferences (RFI), the worst part of soil moisture retrieval, East Asia, constantly have been undergoing loss of data acquisition rate. To overcome this limitation, the threshold of RFI, DQX, and composite days were suggested to increase data acquisition rate while maintaining appropriate data quality through comparison of land surface model data set. The revised MIRAS and AMSR2 products were compared with in-situ soil moisture and land model data set. The results showed that the revising process increased correlation coefficient values of SMOS and AMSR2 averagely 27% 11% and decreased the root mean square deviation (RMSD) decreased 61% and 57% as compared to in-situ data set. In addition, when the revised products' correlation coefficient values are calculated with model data set, about 80% and 90% of pixels' correlation coefficients of SMOS and AMSR2 increased and all pixels' RMSD decreased. Through our CDF-based revising processes, we propose the way of mutual supplementation of MIRAS and AMSR2 soil moisture retrievals.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.277-286
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• 2012

For credit assessment models, the ROC curves evaluate the classification performance using two univariate cumulative distribution functions of the false positive rate and true positive rate. In this paper, it is extended to two bivariate normal distribution functions of default and non-default borrowers; in addition, the bivariate ROC curves are proposed to represent the joint cumulative distribution functions by making use of the linear function that passes though the mean vectors of two score random variables. We explore the classification performance based on these ROC curves obtained from various bivariate normal distributions, and analyze with the corresponding AUROC. The optimal threshold could be derived from the bivariate ROC curve using many well known classification criteria and it is possible to establish an optimal cut-off criteria of bivariate mixture distribution functions.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.4
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• pp.119-130
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• 2019

Purpose : The purpose of this study was to investigate the meta-analysis on the effects of action observation training on stroke patients' walking. Methods : Domestic databases (DBpia, KISS, NDSL, and RISS) were searched for studies that conducted randomized controlled trials (RCTs) associated with action observation training in adults after stroke. The search outcomes were items associated with the walking function. The 18 studies that were included in the study were analyzed using R meta-analysis. A random-effect model was used for the analysis of the effect size because of the significant heterogeneity among the studies. Sub-group and meta-regression analysis were also used. Egger's regression test was conducted to analyze the publishing bias. Cumulative meta-analysis and sensitivity analysis were also done to analyze a data error. Results : The mean effect size was 2.77. The sub-group analysis showed a statistical difference in the number of training sessions per week. No statistically significant difference was found in the meta-regression analysis. Publishing bias was found in the data, but the results of the trim-and-fill method showed that such bias did not affect the obtained data. Also, the cumulative meta-analysis and sensitivity analysis showed no data errors. Conclusion : The meta-analysis of the studies that conducted randomized clinical trials revealed that action observation training effectively improved walking of the chronic stroke patients.