• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.171-180
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• 2006

Change is inevitable and is a reality of construction projects. Most construction contracts include change clauses and allowing contractors an equitable adjustment to the contract price and duration caused by change. However, the actions of a contractor can cause a loss of productivity and furthermore can result in disruption of the whole project because of a cumulative or ripple effect. Because of its complicated nature, it becomes a complex issue to determine the cumulative impact (ripple effect) caused by single or multiple change orders. Furthermore, owners and contractors do not always agree on the adjusted contract price for the cumulative impact of the changes. A number of studies have attempted to quantify the impact of change orders on project costs and schedule. Many of these attempted to develop regression models to quantify the loss. However, regression analysis has shortcomings in dealing with many qualitative or noisy input data. This study develops ANN models to classify and quantify the labor productivity losses that are caused by the cumulative impact of change orders. The results show that ANN models give significantly improved performance compared to traditional statistical models.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.117-124
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• 2009

If time series data with seasonal effect exist, various statistical models like winters for successful forecasts could be used. But if the data are not enough to estimate seasonal effect, not much methods are available. This paper proposes the statistical forecasting method based on cumulative data when the data are not enough to estimate seasonal effect. We apply this method to real cosmetic sales data and show its better performance over moving average method.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.555-562
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• 2016

Interval censored data often occur in an observational study where the subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are available. There are several methods to analyze interval censored failure time data (Sun, 2006). However, in the presence of competing risks, few methods have been suggested to estimate covariate effect on interval censored competing risk data. A sub-distribution hazard model is a commonly used regression model because it has one-to-one correspondence with a cumulative incidence function. Alternatively, Klein and Andersen (2005) proposed a pseudo-value approach that directly uses the cumulative incidence function. In this paper, we consider an extension of the pseudo-value approach into the interval censored data to estimate regression coefficients. The pseudo-values generated from the estimated cumulative incidence function then become response variables in a generalized estimating equation. Simulation studies show that the suggested method performs well in several situations and an HIV-AIDS cohort study is analyzed as a real data example.

• Journal of Korean Society of Forest Science
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• v.105 no.2
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• pp.216-222
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• 2016

In relation to the impact of cumulative rainfall on landslides in accordance with the cumulative number of days, for the more than 100 mm rainfall, the 3 days cumulative rainfall experienced 64.9% of the total points, which is 986 points out of the 1520 points. The 5 days cumulative rainfall period experienced 60% of the total landslides, which is 846 points out of 1520 points analyzed. The 3 days or 5 days cumulative rainfall thus had a greater effect on landslides than the other days. In addition, for the 101-200 mm rainfall, more landslides occurred in the 10 days cumulative number of days, for the 201-300 mm, more landslides occurred in the 14 days cumulative number of days, whereas the 18 days cumulative number of days had more landslides for the 301-400 mm rainfall. Thus, it is imperative to take into consideration cumulative rainfall and the cumulative number of days of rainfall in the establishment of forecasting and warning systems for landslides, to minimize the damage caused to life and property by landslides.

• The Journal of the Korean dental association
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• v.55 no.2
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• pp.116-127
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• 2017

Objectives : The aim of this study was to evaluate the cumulative survival rates of the implants placed into grafted sinus and determine the effect of age, gender, smoking, and systemic disease on the implant cumulative survival rates. Materials and Methods : The retrospective study was performed on 51 implants placed in 26 patients by one dentist at the Dental Implant Center, Seoul National University Dental Hospital in the years 2000-2010. The cumulative survival rates were calculated by the Kaplan-Meier method. The differences within the factors were analyzed using log-rank test and the correlations between the factors and implant survival rates were analyzed using Cox proportional hazard model. Results : 1. Among the total of 51 implants placed in 26 patients, 7 implants failed and 44 implants remained stable. The 1-year, 5-year, and 10-year cumulative survival rates were 92%, 88%, and 85%, respectively. 2. Patients in their 50s and in their 70s showed statistically significant difference in the cumulative survival rates (P < 0.05). Gender and the existence of systemic disease did not show significant results. 3. In the implant treatment, smokers showed 7.5 times higher risk of implant failure than non-smokers (P < 0.05). Conclusion: Implants installed in combination with sinus elevation can be considered as a reliable treatment method.

• Journal of the Korean GEO-environmental Society
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• v.17 no.12
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• pp.5-16
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• 2016

This study aims to assess the influence of rainfall patterns on shallow landslides initiation. Doing so, five typical rainfall patterns with the same cumulative amount and intensity components comprising Advanced (A1 and A2), Centralized (C), and Delayed (D1 and D2) were designed based on a historical rainstorm event in Jinbu. Mt area. Those patterns were incorporated as the hydrological conditions into the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS) to assess their influences on groundwater pressure and changes in the stability of the slope. The results revealed that not only the cumulative rainfall thresholds necessary to initiate landslides, but also the rate at which the factor of safety decreases and the time required to reach the critical state, are governed by rainfall patterns. The sooner the peak rainfall intensity, the smaller the cumulative rainfall threshold, and the shorter the time until landslide occurrence. Left-skewed patterns were found to have a greater effect on landslide initiation. Specifically, among five rainfalls, pattern (A1) produced the most critical state. The severity of response was followed by patterns A2, C, D1, and D2. Our conclusion is that rainfall patterns have a significant effect on the cumulative rainfall threshold, the build-up of groundwater pressure, and the occurrence of shallow landslides.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.202-202
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• 2016

Despite the potentially major influence of rainstorm patterns on the prediction of shallow landslides, this relationship has not yet received significant attention. In this study, five typical temporal rainstorm patterns with the same cumulative amount and intensity components comprising Advanced (A1 and A2), Centralized (C), and Delayed (D1 and D2) were designed based on a historical rainstorm event occurred in 2006 in Mt. Jinbu area. The patterns were incorporated as the hydrological conditions into the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS), in order to assess their influences on pore pressure variation and changes in the stability of the covering soil layer in the study area. The results revealed that not only the cumulative rainfall thresholds necessary to initiate landslides, but also the rate at which the factor of safety (FS) decreases and the time required to reach the critical state, are governed by rainstorm pattern. The sooner the peak rainfall intensity occurs, the smaller the cumulative rainfall threshold, and the shorter the time until landslide occurrence. Left-skewed rainfall patterns were found to have a greater effect on landslide initiation. More specifically, among the five different patterns, the Advanced storm pattern (A1) produced the most critical state, as it resulted in the highest pore pressure across the entire area for the shortest duration; the severity of response was then followed by patterns A2, C, D1, and D2. Thus, it can be concluded that rainfall patterns have a significant effect on the cumulative rainfall threshold, the build-up of pore pressure, and the occurrence of shallow landslides, both in space and time.

• Journal of Preventive Medicine and Public Health
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• v.32 no.4
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• pp.427-434
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• 1999

Objectives: This study was conducted to determine, by reviewing the literature, whether treatment of Helicobacter pylori infection in patients with non-ulcer dyspepsia affects symptoms. Methods: We retrieved the literature using MEDLINE search, with nonulcer dyspepsia and Hericobacter pylori and treatment as key words, which were reported from 1984 to 1998, and manual literature search. The criteria for inclusion was as follows; 1) The paper should have confirmed nonulcer dyspepsia as case definition. 2) The paper should have peformed a randomized, blind trial. 3) Confirmation of Helicobacter pylori eradication should be done 4 weeks after treatment. 4) studies with no information on measurement of symptoms after treatment were not accepted. The percentage of patients with symptom improvement after eradication therapy for Helicobacter pylori infection was calculated. Cumulative odds ratio was compared by fixed effect model and random effect model as sensitivity and funnel plot was used to evaluate publication bias. Results: The overall effect size of symptom improvement was calculated by cumulative odds ratio. Cumulative odds ratio of random effect model was 4.16(95% CI: 1.55-11.19). Before integrating each effect sizes into common effect size, the homogeneity test was conducted and random effect model was selected(Cochran's Q=41.08 (d.f=10, p<0.001)). The heterogeneity across studies was evaluated and the different methodological aspects of studies led to differences between study results Conclusions: The results suggest that the eradication of Helicobacter pylori in patients with non-ulcer dyspepsia results more symptom improvement. In studios that shows the opposite results there are methodological aspects explaining the heterogeneity.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.129-137
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• 2008

An active application of concrete track is being expected far the future constructions of Korean railroad. In comparison with the existing ballasted tract, a concrete track is very susceptible for the settlement, since its rehabilitation requires much time and cost. When a concrete track is constructed on fine-grained subgrade soil, excessive cumulative plastic settlements due to repetitive train road may occur. In this case, the settlement of the concrete track may be effectively reduced by installing a small number of small-diameter piles beneath the track. This paper presents the effect of pile installation on the reduction of cumulative plastic settlement of concrete track. A method combining experiential equation and numerical method is proposed. Using an existing experiential equation and the estimated earth pressure distribution, the cumulative plastic strain was calculated. From the results, it is verified that the effects of the pile installation is significant to effectively reduce the cumulative plastic settlement of concrete track. The reduction effects of the cumulative plastic settlement according to the pile number and pile arrangement are presented.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.1-19
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• 2023

Observational data with missing or incomplete data are common in biomedical research. Multiple imputation is an effective approach to handle missing data with the ability to decrease bias while increasing statistical power and efficiency. In recent years propensity score (PS) matching has been increasingly used in observational studies to estimate treatment effect as it can reduce confounding due to measured baseline covariates. In this paper, we describe in detail approaches to competing risk analysis in the setting of incomplete observational data when using PS matching. First, we used multiple imputation to impute several missing variables simultaneously, then conducted propensity-score matching to match statin-exposed patients with those unexposed. Afterwards, we assessed the effect of statin exposure on the risk of heart failure-related hospitalizations or emergency visits by estimating both relative and absolute effects. Collectively, we provided a general methodological framework to assess treatment effect in incomplete observational data. In addition, we presented a practical approach to produce overall cumulative incidence function (CIF) based on estimates from multiple imputed and PS-matched samples.