• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.189-199
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• 2021

This study attempts to examine the relationship between corporate social responsibility (CSR) disclosure and earnings management practices in the context of Saudi Arabia after mandatory IFRS adoption. It is carried out on an unbalanced panel of 277 observations over the period 2017-2019. For this purpose, CSR disclosure is measured by Bloomberg ESG scores, while the residuals from the modified Jones model are considered for earnings management. As control variables, we have retained the firm performance, market-to-book ratio, firm size, financial leverage, board independence, ownership concentration, managerial ownership, and lagged discretionary accruals. Using the system GMM estimator in the dynamic panel, the results show a positive association between CSR disclosure and earnings management practices, thus supporting the perspective of agency theory. Managers engage in socially responsible activities beforehand to conceal their wrongdoing and convince stakeholders that the organization is transparent. They probably use ethical codes as a tool to achieve their own goals rather than the firm's goals. Our contribution is the use of recent data (2017-2019) taking into account the mandatory adoption of IFRS in Saudi Arabia. Additionally, to our knowledge, this study is the first to address CSR disclosure and earnings management practices using GMM system estimates.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.417-430
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• 2023

As the key part in the reinforced concrete column-steel beam (RCS) frame, the beam-column joints are usually subjected the axial force, shear force and bending moment under seismic actions. With the aim to study the seismic behavior of RCS joints with and without RC slab, the quasi-static cyclic tests results, including hysteretic curves, slab crack development, failure mode, strain distributions, etc. were discussed in detail. It is shown that the composite action between steel beam and RC slab can significantly enhance the initial stiffness and loading capacity, but lead to a changing of the failure mode from beam flexural failure to the joint shear failure. Based on the analysis of shear failure mechanism, the calculation formula accounting for the influence of RC slab was proposed to estimate shear strength of RCS joint. In addition, the finite element model (FEM) was developed by ABAQUS and a series of parametric analysis model with RC slab was conducted to investigate the influence of the face plates thickness, slab reinforcement diameter, beam web strength and inner concrete strength on the shear strength of joints. Finally, the proposed formula in this paper is verified by the experiment and FEM parametric analysis results.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.657-668
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• 2023

It's important to note that air compressors in the industrial sector are major energy consumers, accounting for a significant portion of total energy costs in manufacturing plants, ranging from 12% to 40%. To address this issue, researchers have compared forecasting models that can predict the power consumption of air compressors. The forecasting models were designed to incorporate variables such as flow rate, pressure, temperature, humidity, and dew point, utilizing statistical methods, machine learning, and deep learning techniques. The model performance was compared using measures such as RMSE, MAE and SMAPE. Out of the 21 models tested, the Elastic Net, a statistical method, proved to be the most effective in power comsumption forecasting.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.685-686
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• 2015

The world is currently undergoing an intense urbanization process. The percentage of urban dwellers has never been so high. In 2010, and for the first time, urban population surpassed the rural one, accounting for 51% of global population, and this trend will continue in the forthcoming years. This increment in concentration of population and supporting assets in cities, make their performance a critical issue for world population. Recent events such as Fukushima tsunami and the hurricane Katrina have shown how fragile built environments are and the unpredictability of occurrence and magnitude of the hazards. Such an expansion of the world's urban population, together with an increase in severity and number of hazards and catastrophes, has put under the spotlight the necessity to build cities not only sustainable, but resilient. Decision makers should acknowledge failure as an option, and the importance of developing city resilience. This paper will provide an initial review on urban resilience, definitions and assessment approaches as a first step for decision makers to account for resilience in their decision making process.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.63-73
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• 2024

NeQuick G is the ionosphere model utilized by Galileo single-frequency users to estimate the ionospheric delay on each user-satellite link. The model is characterized by the effective ionization level (Az) index, determined by a modified dip latitude (MODIP) and broadcast coefficients derived from daily global space weather observations. However, globally fitted Az coefficients may not accurately represent ionosphere within local area. This study introduces a method for regional ionospheric modeling that searches for locally optimized Az coefficients. This approach involves fitting TEC output from NeQuick G to TEC data collected from GNSS stations around Korea under various ionospheric conditions including different seasons and both low and high solar activity phases. The optimized Az coefficients enable calculation of the Az index at any position within a region of interest, accounting for the spatial variability of the Az index in a polynomial function of MODIP. The results reveal reduced TEC estimation errors, particularly during high solar activity, with a maximum reduction in the RMS error by 85.95%. This indicates that the proposed method for NeQuick G can effectively model various ionospheric conditions in local areas, offering potential applications in GNSS performance analyses for local areas by generating various ionospheric scenarios.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1445-1453
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• 2023

In 2022, the domestic production performance of functional cosmetics in South Korea reached 4.6 trillion won, accounting for 33.85% of the total cosmetics production. The number of functional cosmetics reviewed increased by about 7.5% from the previous year, totaling 974 items. Especially with the increasing importance of the skin barrier function due to skin sensitivity caused by various environmental pollutants, domestic cosmetic companies are showing interest in the development of new ingredients and products related to this area. This study aims to analyze academic research trends related to in vitro experiments for the development of cosmetics improving the skin barrier, to provide practical information for the cosmetic industry. The findings are as follows: Academic research mainly focused on the efficacy of natural ingredients in improving the skin barrier, but there is a significant lack of quantitative accumulation of research. For the development of skin barrier-improving cosmetic ingredients, efficacy evaluation indicators were set, including hyaluronic acid production, expression of filaggrin gene, loricrin, formation of cornified envelope (CE), and expression of ceramide synthesis enzyme genes. Moreover, effective cosmetic ingredients for improving the skin barrier included lemongrass and perilla leaf extracts, flavonoids, Lactococcus lactis subsp. lactis, Exosomelike Nanovesicles derived from apple callus, Eleutherococcus sessiliflorus, Acanthopanax sessiliflorus, Eleutherococcus gracilistylus, Acer okamotoanum extracts, Aloe vera adventitious root extract, ethanol extract of Aruncus dioicus, and organic solvent fraction of Dracocephalum argunense.

• Earthquakes and Structures
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• v.27 no.4
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• pp.303-315
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• 2024

This study proposes a comprehensive methodology for estimating accumulative damage of bridge structures under multiple seismic excitations, in the framework of site-specific probabilistic hazard analysis. Specifically, a typical earthquake-prone region in China is chosen to perform probabilistic seismic hazard analysis (PSHA) to find the mean annual rate (MAR) of ground motion intensity at a specific level, based on which, a mass of ground motion observations is selected to construct random earthquake sequences with various number of shocks. Then, nonlinear time history analysis is implemented on the finite element (FE) model of a RC girder bridge at the site of interest, to investigate structural responses under different earthquake sequences, and to develop predictive model for cumulative damage computation, in which, a scalar seismic intensity measure (IM) is adopted and its performance in damage prediction is discussed by an experimental column. Furthermore, a mathematic model is established to calculate occurrence probability of earthquakes with various number of shocks, based on PSHA and homogenous Poisson random process, and a modified cumulative damage indicator is proposed, accounting for probabilistic occurrence of various earthquake scenarios. At end, the applicability of the proposed methodology to main shock and aftershock scenarios is validated, and characteristics of damage accumulation under different multiple earthquake scenarios are discussed.

• Management & Information Systems Review
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• v.38 no.3
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• pp.113-125
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• 2019

This study empirically analyzes the effect of SNS informativeness, playfulness and reliability on purchase intention and the effect of consumer's purchase intention on business performance through structural equation model, In doing so, this study aims to suggest ways to enhance consumers' purchase intention and consequently increase the business performance through various SNS marketing strategies that can efficiently manage consumers. The questionnaires were distributed to adult men and women who are in their 20s through 60s, actively use SNS, and primarily reside in Daegu and Gyeongbukdo. The 400 copies of questionnaire were distributed from September 15 to October 1, 2018, of which 364 (91%) were used for the empirical analysis, except for 36 of the questionnaires that were unfaithful or unresponsive. Basic statistical analysis including frequency analysis was performed using SPSS 22.0 and AMOS 24.0, reliability and validity analysis were also performed, and finally hypotheses were tested by performing confirmatory factor analysis and path analysis of structural equation model. All of the SNS informativeness, playfulness and reliability were shown to have positive effects on the purchase intention. In addition, the effect of purchase intention on business performance was found to be significant. Companies should come up with a strategic SNS marketing plan to encourage consumers to enhance the willingness to purchase their products and services through SNS, and to make actual purchases, thereby improving business performance.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.357-371
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• 2007

For the time-to-failure data with competing risks, cumulative incidence functions (CIFs) are commonly estimated using nonparametric methods. If the cases of events due to the cause of primary interest are infrequent relative to other cause of failure, nonparametric methods may result in rather imprecise estimates for CIF. In such cases, Bryant et al. (2004) suggested to model the cause-specific hazard of primary interest parametrically, while accounting for the other modes of failure using nonparametric estimator. We represented the semiparametric cumulative incidence estimator and extended to the model of Weibull and log-normal distribution. We also conducted simulations to access the performance of the semiparametric cumulative incidence estimators and to investigate the impact of model misspecification in log-normal cause-specific hazard model.

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.365-377
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• 2008

Large artificial dam reservoirs and associated downstream ecosystems are under increased pressure from long-term negative impacts of turbid flood runoff. Despite various emerging issues of reservoir turbidity flow, turbidity modeling studies have been rare due to lack of experimental data that can support scientific interpretation. Modeling suspended sediment (SS) dynamics, and therefore turbidity ($C_T$), requires provision of constitutive relationships ($SS-C_T$) and accounting for deposition of different SS size fractions/types distribution in order to display this complicated dynamic behavior. This study explored the performance of a coupled two-dimensional (2D) hydrodynamic and particle dynamics model that simulates the fate and transport of a turbid density flow in a negatively buoyant density flow regime. Multiple groups of suspended sediment (SS), classified by the particle size and their site-specific $SS-C_T$ relationships, were used for the conversion between field measurements ($C_T$) and model state variables (SS). The 2D model showed, in overall, good performance in reproducing the reservoir thermal structure, flood propagation dynamics and the magnitude and distribution of turbidity in the stratified reservoir. Some significant errors were noticed in the transitional zone due to the inherent lateral averaging assumption of the 2D hydrodynamic model, and in the lacustrine zone possibly due to long-term decay of particulate organic matters induced during flood runoffs.