• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2647-2650
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• 2014

Background: Colorectal cancers(CRC) are the third most common cancer in the western world, with surgery preferred for management of non-metastatic disease and post surgical treatment usually arranged according to the TNM staging system. However, there is still prognostic variation between patients who have the same stage. It is increasingly recognized that variations within disease course and clinical outcome in colorectal cancer patients are influenced by not only oncological characteristics of the tumor itself but also host response factors. Recent studies have shown correlation between the inflammatory response and clinical outcomes in various cancers. The neutrophil/lymphocyte ratio (NLR) has been described as a marker for immune response to various stimuli including cancer. Material-Methods: Two hundred eighty-one CRC patients were included in our retrospective analysis, separated into two groups according to a cut-off value for the NLR. Patient data including age, gender, vertical penetration, anatomic location, and differentiation of the tumor, TNM stage, survival rate, and disease-free survival were analyzed for correlations with the NLR. Results: Using ROC curve analysis, we determined a cut-off value of 2.2 for NLR to be best to discriminate between patient survival in the whole group. In univariate analysis, high pretreatment NLR (p=0.001, 95%CI 1.483-4.846), pathologic nodal stage (p<0.001, 95%CI 1.082-3.289) and advanced pathologic TNM stage (p<0.001, 95%CI 1.462-4.213) were predictive of shorter survival. In multivariate analysis, advanced pathologic TNM stage (p=0.001, 95%CI 1.303-26.542) and high pretreatment NLR (p=0.005, 95%CI 1.713-6.378) remained independently associated with poor survival. Conclusions: High pre-treatment NLR is a significant independent predictor of shorter survival in patients with colorectal cancer. This parameter is a simple, easily accessible laboratory value for identifying patients with poorer prognosis.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.335-343
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• 2019

As the regulations of ship exhaust gas have been strengthened recently, many measures are under consideration to reduce fuel consumption. Among them, research has been performed actively to develop a machine-learning model that predicts fuel consumption by using data collected from ships. However, many studies have not considered the methodology of the main parameter selection for the model or the processing of the collected data sufficiently, and the reckless use of data may cause problems such as multicollinearity between variables. In this study, we propose a method to predict the fuel consumption of the ship by using the principal component analysis to solve these problems. The principal component analysis was performed on the operational data of the 13K TEU container ship and the fuel consumption prediction model was implemented by regression analysis with extracted components. As the R-squared value of the model for the test data was 82.99%, this model would be expected to support the decision-making of operators in the voyage planning and contribute to the monitoring of energy-efficient operation of ships during voyages.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.909-914
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• 2009

A suspension is the most prior apparatus to decide vehicle's running safety and ride comfort, also the suspension stiffness is the most important parameter for the designing of the vehicle. Providing the strong stiffness with the primary suspension in order to improve the running safety with high speed, but it causes a problem with a curve running performance of a railway vehicle. Therefore, many studies deal with the optimal value of suspension stiffness. In this paper, we aim to optimize the suspension system to improve running safety by varying stiffness values of railway vehicle suspension. We have proceeded an analysis by design variables which are position, length, width, stiffness and damping coefficients of primary and secondary suspension to optimize the suspension characteristics. As a result of the optimization, we verified that the derailment coefficients of inside and outside of wheel are decreased in comparison with initial model.

• Journal of Service Research and Studies
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• v.4 no.2
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• pp.11-19
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• 2014

This study simulates cases with 20, 30, 40, 50, 60 and 100 students and 6 values as the parameter of mu. Using the simulation, an analysis was made of how the number of students that couldn't concentrate during class increased over the duration of time. When normalizing the difference in student number when the value of mu is constant, there was a decrease in percentage over time. It also showed a change in percentage when the value of time is fixed while the value of mu changes. Based on the result values, by estimating the mu value with the class atmosphere to predict the outcome and improve the lecture.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1189-1192
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• 2005

Due to their slow degradation properties, hydrophobic organic contaminants in estuarine sediment have been a concern for risks to human health and aquatic organisms. Studies of fate and transport of these contaminants in estuaries are further complicated by the fact that hydrodynamics and sediment transport processes in these regions are complex, involving processes with various temporal and spatial scales. In order to simulate and quantify long-term attenuation of Polycyclic Aromatic Hydrocarbons (PAH) in the Elizabeth River, VA, we develop a modeling approach, which employs the U.S. Environmental Protection Agency's water quality model, WASP, and encompasses key physical and chemical processes that govern long-term fate and transport of PAHs in the river. In this box-model configuration, freshwater inflows mix with ocean saline water and tidally averaged dispersion coefficients are obtained by calibration using measured salinity data. Sediment core field data is used to estimate the net deposition/erosion rate, treating only either the gross resuspension or deposition rate as the calibration parameter. Once calibrated, the model simulates fate and transport PAHs following the loading input to the river in 1967, nearly 4 decades ago. Sediment PAH concentrations are simulated over 1967-2022 and model results for Year 2002 are compared with field data measured at various locations of the river during that year. Sediment concentrations for Year 2012 and 2022 are also projected for various remedial actions. Since all the model parameters are based on empirical field data, model predictions should reflect responses based on the assumptions that have been governing the fate and sediment transport for the past decades.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.1
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• pp.146-159
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• 2011

The continuous increase in the production of metals and their subsequent release into the environment has lead to increased concentration of these elements in agricultural soils. Because microbes are involved in almost every chemical transformations taking place in the soil, considerable attention has been given to assessing their responses to metal contaminants. Short-term and long-term exposures to toxic metals have been shown to reduce microbial diversity, biomass and activities in the soil. Several studies show that microbial parameters like basal respiration, metabolic quotient, and enzymatic activities, including those of oxidoreductases and those involved in the cycle of C, N, P and other elements, exhibit sensitivity to soil metal concentrations. These have been therefore, regarded as good indices for assessing the impact of metal contaminants to the soil. Metal contamination has also been extensively shown to decrease species diversity and cause shifts in microbial community structure. Biochemical and molecular techniques that are currently being employed to detect these changes are continuously challenged by several limiting factors, although showing some degree of sensitivity and efficiency. Variations and inconsistencies in the responses of bioindicators to metal stress in the soil can also be explained by differences in bioavailability of the metal to the microorganisms. This, in turn, is influenced by soil characteristics such as CEC, pH, soil particles and other factors. Therefore, aside from selecting the appropriate techniques to better understand microbial responses to metals, it is also important to understand the prevalent environmental conditions that interplay to bring about observed changes in any given soil parameter.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.6
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• pp.65-71
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• 2008

A one-dimensional site response analysis program (KODSAP) was developed using cyclic soil behavior model by using the modified parallel IWAN model. The model is able to predict the cyclic hardening and degradation of soil through the adjustment of the internal slip stresses of its elements beyond the cyclic threshold, and satisfies Bauschinger's effect and the Masing rule in terms of its own behavior characteristics. The program (KODSAP) used the direct integration method in the time domain. The elasticity of the base rock was considered as a viscous damper boundary condition. The effects of cyclic hardening or degradation of soil on site response analysis were evaluated through parametric studies. Three types of analyses were performed to compare the effect of analysis and cyclic parameter on site response. The first type was equivalent linear analysis, the second was nonlinear analysis, and a third was nonlinear analysis using the cyclic hardening or degradation model.

• Clean Technology
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• v.17 no.2
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• pp.97-102
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• 2011

The adsorption characteristics of amatanth dye by granular activated carbon were experimently investigated in the batch adsorption. Kinetic studies of adsorption of amaranth dye were carried out at 298, 308 and 318 K, using aqueous solutions with 100, 200 and 300 mg/L initial concentration of amatanth. It was established that the adsorption equilibrium of amaranth dye on granular activated carbon was successfully fitted by Langmuir isotherm equation at 298 K. The pseudo first order and pseudo second order models were used to evaluate the kinetic data and the pseudo second order kinetic model was the best with good correlation. Values of the rate constant ($k_2$) have been calculated as 0.1076, 0.0531, and 0.0309 g/mg h at 100, 200 and 300 mg/L initial concentration of amatanth, respectively. Thermodynamic parameter such as activation energy, standard enthalpy, standard entropy and standard free energy were evaluated. The estimated values for standard free energy were -5.08 - -8.10 kJ/mol over activated carbon at 200 mg/L, indicated toward a spontaneous process. The positive value for enthalpy, 38.89 kJ/mol indicates that adsorption interaction of amatanth dye on activated carbon is an endothermic process.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.1-6
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• 1998

The evaluation of reliability is very important in the development process of software. There may be lack of trustfulness on the results that come from the analysis and evaluation of reliability of softwares which do not divide the test phases. At this point, this article studies how to evaluate the reliability dividing the test phases in order to settle the these problems. In doing so, I apply the fault data to be found in Unit Test, Integration Test, Validation Test and System Test to SRGM(Software Reliability Growth Model), Exponential SRGM, Delayed S-shaped SRGM and Inflection S-shaped SRGM. The result is that Inflection S-shaped is best suitable with Unit Test Delayed S-shaped is best suitable with Integration and Validation Test, and Exponential SRGM is best suitable with System test. In this respect, I can show that the results of this study on parameter estimation, difference square summation, number of fault remained is superior to the established methods.