• Title/Summary/Keyword: empirical ratio

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Unified calculation model for the longitudinal fundamental frequency of continuous rigid frame bridge

  • Zhou, Yongjun;Zhao, Yu;Liu, Jiang;Jing, Yuan
    • Structural Engineering and Mechanics
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    • v.77 no.3
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    • pp.343-354
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    • 2021
  • The frequencies formulas of the bridge are of great importance in the design process since these formulas provide insight dynamic characteristics of the structure, which guides the designers to parametric analyses and the layout of the bridge in conceptual or preliminary design. Continuous rigid frame bridge is popular in the mountainous area. Mostly, this type of bridge was simplified either as a girder or cantilever when calculating the frequency, however, studies showed that the different configuration of the bridge made the problem more complex, and there is no unified fundamental calculation pattern for this kind of bridge. In this study, an empirical frequency equation is proposed as a function of pier's height, stiffness of pier and the weight of the structure. A unified fundamental frequency formula is presented based on the energy principle, then the typical continuous rigid frame bridge is investigated by finite element method (FEM) to study the dynamic characteristics of the structure, and then several key parameters are investigated on the effect of structural frequency. These parameters include the number, position and stiffness of the tie beam. Nonlinear regression analyses are conducted with a comprehensive statistical study from plenty of engineering structures. Finally, the proposed frequency equation is validated by field test results. The results show that the fundamental frequency of the continuous rigid frame bridge increases more than 15% when the tie beams are set, and it increases with the stiffness ratio of tie beam to pier. The results also show that the presented unified fundamental frequency has an error of 4.6% compared with the measured results. The investigation can predicate the approximate longitudinal fundamental frequency of continuous ridged frame bridge, which can provide reference for the seismic response and dynamic impact factor design of the pier.

Using Taguchi design of experiments for the optimization of electrospun thermoplastic polyurethane scaffolds

  • Nezadi, Maryam;Keshvari, Hamid;Yousefzadeh, Maryam
    • Advances in nano research
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    • v.10 no.1
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    • pp.59-69
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    • 2021
  • Electrospinning is a cost-effective and versatile method for producing submicron fibers. Although this method is relatively simple, at the theoretical level the interactions between process parameters and their influence on the fiber morphology are not yet fully understood. In this paper, the aim was finding optimal electrospinning parameters in order to obtain the smallest fiber diameter by using Taguchi's methodology. The nanofibers produced by electrospinning a solution of Thermoplastic Polyurethane (TPU) in Dimethylformamide (DMF). Polymer concentration and process parameters were considered as the effective factors. Taguchi's L9 orthogonal design (4 parameters, 3 levels) was applied to the experiential design. Optimal electrospinning conditions were determined using the signal-to-noise (S/N) ratio with Minitab 17 software. The morphology of the nanofibers was studied by a Scanning Electron Microscope (SEM). Thereafter, a tensile tester machine was used to assess mechanical properties of nanofibrous scaffolds. The analysis of DoE experiments showed that TPU concentration was the most significant parameter. An optimum combination to reach smallest diameters was yielded at 12 wt% polymer concentration, 16 kV of the supply voltage, 0.1 ml/h feed rate and 15 cm tip-to-distance. An empirical model was extracted and verified using confirmation test. The average diameter of nanofibers at the optimum conditions was in the range of 242.10 to 257.92 nm at a confidence level 95% which was in close agreement with the predicted value by the Taguchi technique. Also, the mechanical properties increased with decreasing fibers diameter. This study demonstrated Taguchi method was successfully applied to the optimization of electrospinning conditions for TPU nanofibers and the presented scaffold can mimic the structure of Extracellular Matrix (ECM).

The Effect of Firm's Internationalization on Accounting Earnings Persistence (기업의 국제화가 회계이익의 지속성에 미치는 효과 분석)

  • Choi, Yu-Jeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.221-230
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    • 2021
  • In this study, a firm's internationalization level was measured as the ratio of foreign sales to total sales (FSTS) of individual firms. A demonstration was conducted with several control variables that affect the persistence of the firm's profits using the Sloan (1996) model as a proxy for its primary relationship between net profit and the next profit. An empirical analysis of the end-December settlement firms listed on the securities market from 2011 to 2016 was conducted using a fixed-effect model to confirm that the persistence of the firm's internationalization and accounting profits was positive at the 1% significant level, indicating that the persistence of the firm's profits also increased as the level of individual firm's internationalization increased. In addition, the firm size, financial soundness, cash accompanying, growth, and investment ability, consistent with forecasts, represented a statistically significant (+) relationship with globalization. These results suggest that firms can maintain and expand their value stably by securing new overseas markets and promoting growth by implementing internationalization strategies.

AN INVESTIGATION OF THE KOREAN GENERAL INSURANCE INDUSTRY: EVIDENCE OF STRUCTURAL CHANGES AND IMPACT OF MACRO-ECONOMIC FACTORS ON LOSS RATIOS

  • Thompson, Ephraim Kwashie;Kim, So-Yeun
    • East Asian mathematical journal
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    • v.38 no.5
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    • pp.617-641
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    • 2022
  • In this study, we first present a brief overview of the Korean general insurance market. We then explore the characteristics of the loss ratios of the Korean general insurance industry and apply Markov regime-switching methodology to model the loss ratios of these insurance companies by line of business based on changes in economic regimes. This study applies a number of confirmatory tests such as Zivot-Andrews test (2002), the Chow (1960) test and the Bai and Perron (1998) to confirm the presence of structural breaks in the time series of the loss ratios by line of business. Then, we employ Markov regime-switching methodology to model these loss ratios. We find empirical evidence that the loss ratios reported by insurance companies in Korea is characterized by two distinct regimes; a regime with high volatility and a regime with low volatility, except for vehicle insurance. Our analyses suggest that macro-economic conditions have significant explanatory effect on loss ratios but the direction of effect differs based on the line of business and the regime. Unlike previous studies that have applied linear regressions or divided the samples into different periods and then apply linear regressions to model loss ratios, we argue for the application of Markov regime-switching methodology, which are able to automatically distinguish the different regimes that may be associated with the movements of loss ratios based on differing economic conditions and regulatory upheavals. This study provides a more in depth understanding of loss ratios in the general insurance industry and will be of value to insurance practitioners in modelling the loss ratios associated with their businesses to aid in their decision making. The results may also provide a basis for further studies in other markets apart from Korea as well as for shaping policy decisions related to loss ratios.

A Study on Properties of Crude Oil Based Derivative Linked Security (유가 연계 파생결합증권의 특성에 대한 연구)

  • Sohn, Kyoung-Woo;Chung, Ji-Yeong
    • Asia-Pacific Journal of Business
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    • v.11 no.3
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    • pp.243-260
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    • 2020
  • Purpose - This paper aims to investigate the properties of crude oil based derivative security (DLS) focusing on step-down type for comprehensive understanding of its risk. Design/methodology/approach - Kernel estimation is conducted to figure out statistical feature of the process of oil price. We simulate oil price paths based on kernel estimation results and derive probabilities of hitting the barrier and early redemption. Findings - The amount of issuance for crude oil based DLS is relatively low when base prices are below $40 while it is high when base prices are around $60 or $100, which is not consistent with kernel estimation results showing that oil futures prices tend to revert toward $46.14 and the mean-reverting speed is faster as oil price is lower. The analysis based on simulated oil price paths reveals that probability of early redemption is below 50% for DLS with high base prices and the ratio of the probability of early redemption to the probability of hitting barrier is remarkably low compared to the case for DLS with low base prices, as the chance of early redemption is deferred. Research implications or Originality - Empirical results imply that the level of the base price is a crucial factor of the risk for DLS, thus introducing a time-varying knock-in barrier, which is similar to adjust the base price, merits consideration to enhance protection for DLS investors.

Hybrid adaptive neuro fuzzy inference system for optimization mechanical behaviors of nanocomposite reinforced concrete

  • Huang, Yong;Wu, Shengbin
    • Advances in nano research
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    • v.12 no.5
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    • pp.515-527
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    • 2022
  • The application of fibers in concrete obviously enhances the properties of concrete, also the application of natural fibers in concrete is raising due to the availability, low cost and environmentally friendly. Besides, predicting the mechanical properties of concrete in general and shear strength in particular is highly significant in concrete mixture with fiber nanocomposite reinforced concrete (FRC) in construction projects. Despite numerous studies in shear strength, determining this strength still needs more investigations. In this research, Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to determine the strength of reinforced concrete with fiber. 180 empirical data were gathered from reliable literature to develop the methods. Models were developed, validated and their statistical results were compared through the root mean squared error (RMSE), determination coefficient (R2), mean absolute error (MAE) and Pearson correlation coefficient (r). Comparing the RMSE of PSO (0.8859) and ANFIS (0.6047) have emphasized the significant role of structural parameters on the shear strength of concrete, also effective depth, web width, and a clear depth rate are essential parameters in modeling the shear capacity of FRC. Considering the accuracy of our models in determining the shear strength of FRC, the outcomes have shown that the R2 values of PSO (0.7487) was better than ANFIS (2.4048). Thus, in this research, PSO has demonstrated better performance than ANFIS in predicting the shear strength of FRC in case of accuracy and the least error ratio. Thus, PSO could be applied as a proper tool to maximum accuracy predict the shear strength of FRC.

Integral Design and Structural Analysis for Safety Assessment of Domestic Specialized Agrivoltaic Smart Farm System (한국형 영농형 태양광 스마트팜 시스템의 종합설계 및 구조해석을 통한 안전성 검토)

  • Lee, Sang-ik;Kim, Dong-su;Kim, Taejin;Jeong, Young-joon;Lee, Jong-hyuk;Son, Younghwan;Choi, Won
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.4
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    • pp.21-30
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    • 2022
  • Renewable energy systems aim to achieve carbon neutrality and replace fossil fuels. Photovoltaic technologies are the most widely used renewable energy. However, they require a large operating area, thereby decreasing available farmland. Accordingly, agrivoltaic systems (AVSs)-innovative smart farm technologies that utilize solar energy for crop growth and electricity production-are attracting attention. Although several empirical studies on these systems have been conducted, comprehensive research on their design is lacking, and no standard model suitable for South Korea has been developed. Therefore, this study created an integral design of AVS reflecting domestic crop cultivation conditions and conducted a structural analysis for safety assessment. The shading ratio, planting distance, and agricultural machinery work of the system were determined. In addition, national construction standards were applied to evaluate their structural safety using a finite element analysis. Through this, the safety of this system was ensured, and structural considerations were put forward. It is expected that the AVS model will allow for a stable utilization of renewable energy and smart farm technologies in rural areas.

Application of deep convolutional neural network for short-term precipitation forecasting using weather radar-based images

  • Le, Xuan-Hien;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.136-136
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    • 2021
  • In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

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Anisotropic Elastic Shear Moduli of Sands Measured by Multi-directional Bender Element Tests in Stress Probe Experiments (사질토의 전단 하중 재하 시 다축 벤더엘리먼트 시험으로 구한 이방적 전단탄성계수)

  • Ko, Young Joo;Jung, Young Hoon;Lee, Choong Hyun;Chung, Choong Ki
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3C
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    • pp.159-166
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    • 2008
  • The stress-strain behavior of soils can usually be regarded as non-linear, while it is also known that the soil exhibits the linear-elastic behavior at pre-failure state (very small strain range, $<10^{-3}%$). This study aims to analyze the variation of anisotropic elastic shear moduli of granular soils in various stress conditions. The stress probe experiments with the triaxial testing device equipped with local strain gages and multi-directional bender elements were conducted. When the stress ratio exceeds the range between -0.5 and 1.5, the elastic shear stiffness in the axial direction deviates from the empirical correlation with current stresses, which indicates that the yielding of soils alters the internal pathway through which the elastic shear wave propagates. The experimental results show that the variation of elastic shear moduli in the horizontal direction closely relates to the volume change of soils.

What Factors Contribute to the Entry of Foreign Investors to Chinese Commercial Banks? (외국인투자자의 중국상업은행 투자결정요인에 관한 연구)

  • Kang, Shin-Ae;Sul, Woksik
    • International Area Studies Review
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    • v.15 no.1
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    • pp.367-389
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    • 2011
  • This paper examines what factors contribute to the entry of foreign investors to Chinese commercial banks from 1996 to 2008. Empirical results show that using survival analysis, size, liquidity ratio and non-interest incomes are important to foreign investors. This indicates that as Chinese banking system opened, foreign investors invest in bigger but financially weak banks. For Joint-Stock commercial banks, foreign investors invest in banks whose asset qualities and non-interest incomes are low. But for City commercial banks, foreign investors invest in banks that are big but have low liquidity ratios. This results indicate that because City commercial banks operate in only one city, foreign investors require minimum bank size to operate in that city.