• Journal of Korean Association for Spatial Structures
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• v.2 no.1 s.3
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• pp.75-84
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• 2002

In this study, the 'force density method' for shape finding of cable net structures is presented. This concept is based on the force-length ratios or force densities which are defined for each branch of the net structures. This method renders a simple linear 'analytical form finding' possible. If the free choice of the force densities is restricted by further condition, the linear method is extended to a nonlinear one. The nonlinear one can be applied to the detailed computation of networks. In this paper, the general inverse matrix is introduced to solve the nonlinear equilibrium equation including Jacobian matrix which is rectangular matrix. Several examples for linear and nonlinear analysis applied additional constraints are presented. It is shown that the force density method is suitable for form finding of cable net and the general inverse matrix can be applied to solve the nonlinear equation without Lagrangian factors.

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.1-2
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• 2000

This paper introduces the equivalent frequency response method (EFRM) into runoff analysis. This EFRM originally had been developed to analyze dynamic behavior of nonlinear elements such as threshold and saturation in control engineering. Many runoff models are described by nonlinear ordinary or partial differential equations. This paper presents that these nonlinear differential equations can be converted into semi-linear ones based on EFRM. The word of “a semi-linear equation” means that the coefficients of derived equations depend on average rainfall

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.731-740
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• 1999

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.287-298
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• 2019

The purpose of this study to investigate the impact of rewards on job satisfaction and whether economic trends moderate the relationship of job satisfaction and rewards or not. Furthermore, this study also investigates whether the relationship between job satisfaction and reward is linear or nonlinear and whether the relationship diminishes or improves with predictor inclusion. Data collection was done through online and self-administered questionnaires by adopting cluster sampling technique from higher education institutions of Pakistan. Results based on 2160 responses suggest that economic trends moderate the relationship of job satisfaction and reward while assuming the economic trends as perceived rewards. The logit model was adopted to probabilistic relationship between job satisfaction and reward in moderation with economics trends. The moderations magnify the impact of rewards on job satisfaction. The job satisfaction is more sensitive to extrinsic reward as compared to intrinsic reward. The relationship of job satisfaction and reward is nonlinear for both extrinsic and intrinsic reward suggesting the diminishing relationship of job satisfaction and rewards. This study has pivotal implication for the higher education sector as it helps the sector to align the rewards with economic and trends and can normalize the reward after assessing the nonlinear stricture of relationship.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.71-79
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• 2021

This study investigates the capital structure policy among Indonesian public companies. Previous studies suggest that capital structure policy could follow either static or dynamic behavior. The sample data used in this study was companies in the manufacturing sector, divided into three sub-sectors: the basic and chemical industry, miscellaneous industry, and the consumer goods industry. This study uses panel data from 2010 to 2018, with the Generalized Least Square (GLS) method and compared whether the fixed effect model is better than the common effect model. The results show that the dynamic and non-linear model tests can explain the capital structure determinants than the static and linear models. The dynamic model shows that the capital structure of a certain year is influenced by the capital structure of the previous year. The findings indicate that the company performs some adjustments in its capital structure policy by referring to the previous debt ratio, which implies support to the trade-off theory (TOT). The study also shows that profitability, tangible assets, size, and age explain the variation of capital structure policy. The patterns on the dynamic and non-linear confirm that capital structure runs in a nonlinear pattern, based on the sector, company condition, and the dynamic environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.842-845
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• 2005

A method for the numerical simulation of two-dimensional free-surface flow resulting from the propagation of regular gravity waves over topography with arbitrary bottom shape is presented. The method is based on the numerical solution of the Euler equations subject to the fully nonlinear free-surface boundary conditions and the appropriate bottom, inflow and outflow conditions using a hybrid finite-differences and spectral-method scheme. The formulation includes a boundary-fitted transformation, and is suitable for extension to incorporate large-eddy simulation (LES) and large-wave simulation (LWS) terms for turbulence and breaking wave modeling, respectively. Results are presented for the simulation of the free-surface flow over two different bottom topographies, with constant slope values of 1:10 and 1:20, two different inflow wave lengths and two different inflow wave heights. An absorption outflow zone is utilized and the results indicate minimum wave reflection from the outflow boundary. Over the bottom slope, lengths of waves in the linear regime are modified according to linear theory dispersion, while wave heights remain more or less unchanged. For waves in the nonlinear regime, wave lengths are becoming shorter, while the free surface elevation deviates from its initial sinusoidal shape.

• Korean Journal of Community Nutrition
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• v.23 no.5
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• pp.397-410
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• 2018

Objectives: An association between dietary patterns and mental health in children has been suggested in a series of studies, yet detailed analyses of dietary patterns and their effects on ADHD (attention deficit hyperactivity disorder) are limited. Methods: We included 4569 children who had dietary intake data as part of the CHEER (Children's Health and Environmental Research) study conducted nationwide from 2005 to 2010. We assessed ADHD (Attention Deficit Hyperactivity Disorder) by the DuPaul's ADHD Rating Scales and dietary intake by a semi-quantitative food frequency questionnaire. Using intake data, we constructed five dietary patterns: "Plant foods & fish," "Sweets," "Meat & fish," "Fruits & dairy products," and "Wheat based." Results: The overall proportion of ADHD was 12.3%. Boys (17.8%) showed a higher rate of ADHD than girls (6.5%). The total intake of calories (85 kcal) and plant fat (2g) in the ADHD group was significantly higher than that of the normal group. ADHD was significantly negatively associated with dietary habits such as having breakfast and meal frequency, and positively associated with eating speed, unbalanced diet, overeating, and rice consumption. Regarding dietary patterns, the "Sweets" category was relevant to high ADHD risk (OR 1.59, 95% CI: 1.18, 2.15 for Q5 vs. Q1) in a linear relationship. An inverse, non-linear association was found between "Fruits & dairy products" and ADHD (OR 0.55, 95% CI: 0.39, 0.76 for Q4 vs. Q1). Conclusions: Our study confirms both positive and negative associations between diet and ADHD in elementary school age children. Moreover, linear or nonlinear associations between diet and ADHD draw attention to the possible threshold role of nutrients. Further studies may consider characteristics of diet in more detail to develop better intervention or management in terms of diet and health.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.97-97
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• 2021

Hydrometeorological variables contain highly complex system for temporal revolution and it is quite challenging to illustrate the system with a temporal linear and nonlinear models. In recent years, deep learning algorithms have been developed and a number of studies has focused to model the complex hydrometeorological system with deep learning models. In the current study, we investigated the temporal structure inside deep learning models for the hydrometeorological variables such as streamflow and climate indices. The results present a quite striking such that each hidden unit of the deep learning model presents different dependence structure and when the number of hidden units meet a proper boundary, it reaches the best model performance. This indicates that the deep dependence structure of deep learning models can be used to model selection or investigating whether the constructed model setup present efficient or not.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1083-1093
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• 2021

It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.817-826
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• 2002

Many researchers have been tried to forecast the future as analyzing data characteristics and the forecasting methodology may be divided into two cases of deterministic and stochastic techniques. However, the understanding data characteristics may be very important for model construction and forecasting. In the sense of this view, recently, the deterministic method known as nonlinear dynamics has been studied in many fields. This study uses the geometrical methodology suggested by Poincare for analyzing nonlinear dynamic systems and we apply the methodology to understand the characteristics of known systems and hydrologic data, and determines the possibility of forecasting according to the data characteristics. Say, we try to understand the data characteristics as constructing Poincare map by using Poincare section and could conjecture that the data sets are linear or nonlinear and an appropriate model.