• Ocean and Polar Research
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• v.36 no.4
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• pp.487-494
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• 2014

Deep-seabed test miner operated by a self-propelled mining system moving on soft soil is an essential device to secure floating and towing performances. The performances of the tracked vehicle are seriously influenced by noise factors such as the shear strength of the seafloor, bottom current, seafloor slope, speed of tracked vehicle, reaction forces of flexible hose, steering ratio, etc. Due to uncertainties related to noise factors, the design of a deep-sea manganese nodules test miner that satisfies target reliabilities is difficult. Therefore, reliability-based design optimization (RBDO) is required to guarantee system reliability under circumstances where uncertainties related to noise factors prevail. Among noise factors, the bottom current, a bimodal distribution, is censored due to the observation limit of measurement devices. Therefore, estimated distribution of the bottom current is inaccurate without considering these characteristics and the result of RBDO cannot be guaranteed. In this paper, we define censored data as unknown values over the limit of observation. If this data is estimated by using Akaike information criterion (AIC) that cannot consider the characteristics of censored data, the distribution of estimated data cannot guarantee accurate reliability. Therefore, censored AIC that can consider the characteristics of data is used to estimate accurate distribution of the bottom current. Finally, RBDO, under circumstances where uncertainties related to noise factors combined censored data are present, is performed on the mobility of a deep-sea manganese nodules test miner.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3369-3375
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• 2014

Background: C-reactive protein (CRP), considered as a prototypical inflammatory cytokine, has been proposed to be involved in tumor progression through inflammation. Recent studies have indicated CRP as a progostic predictor for urological cancers, but the results remain controversial. Materials and Methods: A systematic search of Medline, Scopus and the Cochrane Library was performed to identify eligible studies published between Jan 1, 2001 and Sep 1, 2013. Outcomes of interest were collected from studies comparing overall survival (OS), cancer-specific survival (CSS) and relapse-free survival (RFS) in patients with elevated CRP levels and those having lower levels. Studies were pooled, and combined hazard ratio (HR) of CRP with its 95% confidence interval (CI) for survival were used for the effect size estimate. Results: A total of 43 studies (7,490 patients) were included in this meta-analysis (25 for RCC, 10 for UC, and 8 for PC). Our pooled results showed that elevated serum CRP level was associated with poor OS (HR: 1.26, 95%CI: 1.22-1.30) and RFS (HR: 1.38 95%CI: 1.29-1.47), respectively. For CSS the pooled HR (HR: 1.33, 95%CI: 1.28-1.39) for higher CRP expression could strongly predict poorer survival in urological cancers. Simultaneously, elevated serum CRP was also significantly associated with poor prognosis in the subgroup analysis. Conclusions: Our pooled results demonstrate that a high serum level of CRP as an inflammation biomarker denotes a poor prognosis of patients with urological cancers. Further large prospective studies should be performed to confirm whether CRP, as a biomarker of inflammation, has a prognostic role in urological cancer progression.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.11-15
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• 2016

Gastrointestinal cancers remain the most prevalent cancers in many developing countries such as Iran. The aim of this study was to estimate incidence, prevalence and mortality, as well as time trends for gastrointestinal cancers in Isfahan province of Iran for the period 2001 to 2010 and to project these estimates to the year 2020. Estimates were driven by applying the MIAMOD method (a backward calculation approach using mortality and relative survival rates). Mortality data were obtained from the Ministry of Health and the relative survival rate for all gastrointestinal cancers combined was derived from the Eurocare 3 study. Results indicated that there were clear upward trends in age adjusted incidence (males 22.9 to 74.2 and females 14.9 to 44.2), prevalence (males 52.6 to 177.7 and females 38.3 to 111.03), and mortality (males 14.6 to 47.2 and females 9.6 to 28.2) rates per 100,000 for the period of 2001 to 2010 and this upward state would persist for the projected period. For the entire period, the male to female ratio increased slightly for all parameters (incidence rate increased from 1.5 to 1.7, prevalence from 1.4 to 1.6, and mortality from 1.5 to 1.7). In males, totals of 2,179 incident cases, 5,097 prevalent cases and 1,398 mortality cases were predicated to occur during the study period. For females the predicted figures were 1,379, 3,190 and 891, respectively. It was concluded that the upward trend of incidence alongside increase in survival rates would induce a high burden on the health care infrastructure in the province of Isfahan in the future.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.33 no.5
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• pp.485-493
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• 2007

Purpose: Heart rate variability(HRV) is the clinical consequence of various influences of the autonomic nervous system(ANS) on heart beat. HRV can estimate the potential physiologic rhythm from the interval between consecutive beats(RR interval or HRV data). It is known as RSA which represents respiration-related HR rhythmic oscillation. Previous studies demonstrated a specific breathing pattern(0.1Hz, 6breaths/min) to improve a physiological body condition related to the stress. In this paper, the level of stress would be evaluated in terms of three phases of the dental treatment, combined with 6breaths/min. Methods: These phases include before, during and after tooth extraction or anesthesia or something.36 patients' stresses were assessed using HRV stress analyzer in each phase in Kangdong Sacred Heart Hospital, and Chuncheon Sacred Heart Hospital, Hallym University Medical Center from Jun. to Sept. of 2007. HRV 5-min data collected were analyzed in time-domain and frequency-domain to evaluate the activity of autonomic nervous system(ANS) which represents the level of stress. Results: All HRV parameters including HF(high frequency), LF(low frequency) and LF/HF ratio showned a significant change affecting the ANS balance. There was a 6.4% difference between R(LF/HF)s on general breathing pattern for balance of Autonomic nervous system, but on controlled breathing pattern, 0.1Hz, was made narrow till 1.4%. The activity of ANS has increased by 1.4% on general breathing pattern, and by 2.9% on controlled breathing pattern, 0.1Hz. Conclusion: After analysis of preoperative stress changes and effect of breathing pattern of 0.1 Hz on the stress in 36 patients who have undergone third molar extraction, following was concluded. In the preoperative stage, the sympathetic change was the greatest?after the?anesthetic injection, and stress was relieved by controlling the breathing pattern to a frequency of 0.1Hz.

• Journal of Korea Water Resources Association
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• v.39 no.11 s.172
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• pp.923-934
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• 2006

In this study, the effects of variability in climate, groundwater withdrawal, and landuse on dry-weather streamflows were investigated by input sensitivity analysis using SWAT (Soil and Water Assessment Tool). Since only dry-period precipitation and daily average solar radiation among climate variables have high correlation coefficients to total flow (TF), sensitivity analyses of those were conducted. Furthermore, an equation was derived from simulation results for 30 years by multiple regression analysis. It may be used to estimate effects of various climatic variations (precipitation during the dry period, precipitation during the previous wet period, solar radiation, and maximum temperature). If daily average maximum temperatures increase, TFs during the dry period will decrease. Sensitivities of groundwater withdrawal and landuse were also conducted. Similarly, groundwater withdrawals strongly affect streamflow during the dry period. However, landuse changes (increasing urbanization) within the forested watershed do not appear to significantly affect TF during the dry period. Finally, a combined equation was derived that describes the relationship between the total runoff during the dry period and the climate, groundwater withdrawal and urban area proportion. The proposed equation will be useful to predict the water availability during the dry period in the future since it is dependent upon changes of temperature, precipitation, solar radiation, urban area ratio, and groundwater withdrawal.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.34 no.5
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• pp.18-38
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• 2002

A previous study on the model coatings based on latex-bound plastic pigment coatings (1) has been extended to latex-bound No. 1 clay, ultra-fine ground calcium carbonate (UFGCC), and clay-carbonate pigment mixture coatings, which are being widely used in the paper industry. The latex binder used was a good film-forming, monodisperse S/B latex or 0.15$\mu\textrm{m}$. No. 1 clay was representative of plate-like pigment particles, whereas UFGCC was of somewhat rounded rhombohedral pigment particlel. Both of them had negatively skewed triangular particle size distributions having the mean particle suet of 0.7${\mu}{\textrm}{m}$ and 0.6$\mu\textrm{m}$, respectively. Their packing volumes were found to be 62.5% and 657%, respectively. while their critical pigment volume concentrations (CPVC's) were determined to be 52.7% and 50.5% ( average of 45% caused by the incompatibility and 55.9% extrapolated) by coating porosity, respectively. Each pigment/latex coating system has shown its unique relationship between coating properties and pigment concentrations, especially above its CPVC. Notably, the clay/latex coating system hat shown higher coating porosity than the UFGCC/latex system at high pigment concentrations above their respective CPVC's. It was also found that their coating porosity and gloss were inter-related to each other above the CPVC's, as predicted by the theory. More interestingly, the blends of these two pigments have shown unique rheological and coating properties which may explain why such pigment blends are widely used in the industry. These findings have suggested that the unique structure of clay coatings and the unique high-shear rheology of ground calcium carbonate coatings can be judiciously combined to achieve superior coatings. Importantly, the low-shear viscosity of the blends was indicative of their unique packing and coating structure, whereas their high-shear rheology was represented by a common mixing rule, i.e., a viscosity-averaging. Transmission and scanning electron and atomic force microscopes were used to probe the state of pigment / latex dispersions, coating surfaces, freeze fractured coating cross-sections, and coating surface topography. These microscopic studies complemented the above observations. In addition, the ratio, R, of CPVC/(Pigment Packing Volume) has been proposed as a measure of the binder efficiency for a given pigment or pigment mixtures or as a measure of binder-pigment interactions. Also, a mathematical model has been proposed to estimate the packing volumes of clay and ground calcium carbonate pigments with their respective particle size distributions. As well known in the particle packing, the narrower the particle size distributions, the lower the packing volumes and the greater the coating porosity, regardless of particle shapes.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.77-83
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• 2009

This paper proposes a new noise-biased compensation of minimum statistics(MS) method using a nonlinear function and a priori speech absence probability(SAP) for speech enhancement in non-stationary noisy environments. The minimum statistics(MS) method is well known technique for noise power estimation in non-stationary noisy environments. It tends to bias the noise estimate below that of true noise level. The proposed method is combined with an adaptive parameter based on a sigmoid function and a priori speech absence probability (SAP) for biased compensation. Specifically. we apply the adaptive parameter according to the a posteriori SNR. In addition, when the a priori SAP equals unity, the adaptive biased compensation factor separately increases ${\delta}_{max}$ each frequency bin, and vice versa. We evaluate the estimation of noise power capability in highly non-stationary and various noise environments, the improvement in the segmental signal-to-noise ratio (SNR), and the Itakura-Saito Distortion Measure (ISDM) integrated into a spectral subtraction (SS). The results shows that our proposed method is superior to the conventional MS approach.

• Geophysics and Geophysical Exploration
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• v.10 no.3
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• pp.183-190
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• 2007

The site effects of seismic stations were evaluated by conducting a simultaneous inversion of the stochastic point-source ground-motion model (STGM model; Boore, 2003) parameters based on the accumulated dataset of horizontal shear-wave Fourier spectra. A model parameter $K_0$ and frequency-dependent site amplification function A(f) were used to express the site effects. Once after a H/V ratio of the Fourier spectra was used as an initial estimate of A(f) for the inversion, the final A(f) which is considered to be the result of combined effect of the crustal amplification and loca lsite effects was calculated by averaging the log residuals at the site from the inversion and adding the mean log residual to the H/V ratio. The seismic stations were classified into five classes according to $logA_{1-10}^{max}$(f), the maximum level of the site amplification function in the range of 1 Hz < f < 10 Hz, i.e., A: $logA_{1-10}^{max}$(f) < 0.2, B: 0.2 $\leq$ $logA_{1-10}^{max}$(f) < 0.4, C: 0.4 $\leq$ $logA_{1-10}^{max}$(f) < 0.6, D: 0.6 $\leq$ $logA_{1-10}^{max}$(f) < 0.8, E: 0.8 $\leq$ $logA_{1-10}^{max}$(f). Implication of the classified result was supported by observing a shift of the dominant frequency of average A(f) for each classified stations as the class changes. Change of site classes after moving seismic stations to a better site condition was successfully described by the result of the station classification. In addition, the observed PGA (Peak Ground Acceleration)-values for two recent moderate earthquakes were well classified according to the proposed station classes.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.