• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1866-1883
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• 2019

As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

• Asia-Pacific Journal of Business
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• v.11 no.3
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• pp.137-151
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• 2020

Purpose - The purpose of this study is to investigate whether financial analysts' cash flow forecasts mitigate the accrual anomaly. In addition, we examine whether the more accurate analysts' cash flow forecasts are the greater the decline of the accrual anomaly. Design/methodology/approach - Data used in the empirical tests are extracted through KIS-VALUE and FN-GUIDE, and the sample consists of firms listed on Korea Stock Exchange for 7 years from 2005 to 2011. We test the hypotheses using multiple regression analysis and we also estimate the regressions with the decile ranks of the explanatory variables to minimize the influence of outliers. Findings - We have failed to capture evidence that the provision of financial analysts' cash flow forecasts itself reduces the accrual anomaly. However, we find the accrual anomaly to be less severe when financial analysts provide more accurate cash flow forecasts. The findings are consistent in the regression models with the decile ranks as well as in the robustness tests that controlled the accruals quality. Research implications or Originality - This study contributes to the expansion of related studies in the Korea by providing empirical evidence partially that the financial analysts' cash flow forecasts mitigate the accrual anomaly.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.1-13
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• 2022

This paper empirically explores the predicting ability of the newly proposed smooth transition (ST) time-varying combining forecast methods. The proposed method allows the "weight" of combining forecasts to change gradually over time through its unique feature of transition variables. Stock market returns from 7 countries were applied to Ad Hoc models, the well-known Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, and the Smooth Transition Exponential Smoothing (STES) models. Of the individual models, GJRGARCH and STES-E&AE emerged as the best models and thereby were chosen for constructing the combined forecast models where a total of nine ST combining methods were developed. The robustness of the ST combining forecasts is also validated by the Diebold-Mariano (DM) test. The post-sample forecasting performance shows that ST combining forecast methods outperformed all the individual models and fixed weight combining models. This study contributes in two ways: 1) the ST combining methods statistically outperformed all the individual forecast methods and the existing traditional combining methods using simple averaging and Bates & Granger method. 2) trading volume as a transition variable in ST methods was superior to other individual models as well as the ST models with single sign or size of past shocks as transition variables.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.953-965
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• 2021

This study aims to analyze the benefits of corporate social responsibility (CSR) performance on corporate risk in controversial and non-controversial industries. The hypothesis of this study is based on the conflicting effects of industry type on CSR and firm risk. The research sample consisted of 927 companies listed on the Indonesia Stock Exchange from 2016 to 2019. The main method for data processing was the ordinary least square method and subgroup analysis as a robustness test. The findings suggest that the performance of CSR can reduce corporate risk. However, the impact was only significant for non-controversial firms and weakened for controversial industries. These results support risk management and signaling theory. Firm risk in this study reflects the company's total risk, further research can categorize it into systematic and idiosyncratic risk. Besides, the number of samples of controversial industry research is not as much as non-controversial; further research can use paired samples. Regulators can use the results to create a new policy regarding CSR implementation. This study contributes to the existing literature by showing that the ability of social responsibility to reduce corporate risk only works in non-controversial industries. This result may be due to the controversial industry receiving negative stigma from its stakeholders.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1371-1383
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• 2021

The study aims to investigate the organizational commitment and loyalty among millennial generation employees in Integrated Islamic Schools. The study gathered information and data from three different Islamic education institutions in Central Java, Indonesia. A total of 261 responses gathered using an online questionnaire distributed among millennial generation employees on each institution. The result then analyzed using confirmatory factor analysis with the help of SPSS and SEM AMOS. From the analysis, it is found that employee trust and satisfaction strongly impacted employee organizational commitment, and employee organizational commitment strongly impacted employee loyalty, both attitudinal and behavioral. Test for model robustness was also conducted accordingly within suggestions from the previous research, resulted in quite different findings especially in continuance commitment variable. This study pointed out the importance of trust and satisfaction to maintain the millennials employee, and the importance of millennial understanding especially in the education sector. This study provides the reference for future organizational commitment and loyalty study among the millennial generation especially in a growing nation like Indonesia and pointed out the importance of the generational study on organizational behavior topics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.10 no.4
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• pp.13-19
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• 2000

With the rapid development of the information communication technology, more and more distribution multimedia data and electronic publishing in the web, has created a need for the copyright protection with authentication of digital information. In this paper, we propose a multi-watermarking adding and adaptive spectral watermark algorithm well adaptive frequency domain of each hierarchical using orthogonal forward wavelet transform(FWT. Numerical test results, created watermarking image robustness not only image transform such as low-pass filtering, bluring, sharpen filtering, wavelet compression but also brightness, contrast gamma correction, histogram equalization, cropping.

• Smart Structures and Systems
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• v.29 no.3
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• pp.457-473
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• 2022

A high-frequency vibration control method is proposed in this paper for Pumped Storage Power Plants (PSPPs) using Eddy Current Tuned Mass Damper (EC-TMD), based on which a new type of EC-TMD device is designed. The eddy current damper parameters are optimized by numerical simulation. On this basis, physical simulation model tests are conducted to compare and study the effect of structural performance with and without damping, different control strategies, and different arrangement positions of TMD. The test results show that EC-TMD can effectively reduce the control effect under high-frequency vibration of the plant structure, and after the additional damping device forms EC-TMD, the energy dissipation is further realized due to the intervention of eddy current damping, and the control effect is subsequently improved. The Multi-Tuned Mass Damper (MTMD) control strategy broadens the tuning band to improve the robustness of the system, and the vibration advantage is more obvious. Also, some suggestions are made for the placement of the dampers to promote their application.

• Korea Trade Review
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• v.46 no.6
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• pp.211-224
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• 2021

Based on the perspective of international trade and cross-border e-commerce development, this paper explores the impact of cross-border e-commerce on international trade. This paper first describes the current situation of China's cross-border e-commerce and proposes a theoretical model of the influence of China's cross-border e-commerce on its international trade based on the research and summary of a large number of relevant documents. This paper establishes an extended gravity model based on the proposed theoretical model. Relevant data of 13 trading partner countries were used as sample data, and OLS regression analysis and heterogeneity analysis were conducted on gravity model by using Eviews 11.0. Then, in order to study the influence of each variable on import and export trade volume, import and export trade volume were respectively taken as explained variables and further studied by OLS regression analysis. To test the robustness of the model, the empirical analysis results show that cross-border e-commerce does promote the volume of China's international trade.

• Asia-Pacific Journal of Business
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• v.14 no.3
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• pp.221-240
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• 2023

Purpose - This paper investigates how business cycle impacts on corporate credit spreads since global financial crisis. Furthermore, it tests how the impact changes by the phase of the cycle. Design/methodology/approach - This study collected dataset from Barclays Global Aggregate Bond Index through the Bloomberg. It conducted multi-regression analysis by projecting business cycle using Hodrick-Prescott filtering and various cyclical variables, while ran dynamic analysis of 5-variable Vector Error Correction Model to confirm the robustness of the test. Findings - First, it proves to be statistically significant that corporate credit spreads have moved countercyclicaly since the crisis. Second, It indicates that the corporate credit spread's countercyclicality to the macroeconomic changes works symmetrically by the phase of the cycle. Third, the VECM supports that business cycle's impact on the spreads maintains more sustainably than other explanatory variable does in the model. Research implications or Originality - It becomes more appealing to accurately measure the real economic impact on corporate credit spreads as the interaction between credit and business cycle deepens. The economic impact on the spreads works symmetrically by boom and bust, which implies that the market stress could impact as another negative driver during the bust. Finally, the business cycle's sustainable impact on the spreads supports the fact that the economic recovery is the key driver for the resilience of credit cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3364-3382
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• 2023

Remote sensing image segmentation plays an important role in realizing intelligent city construction. The current mainstream segmentation networks effectively improve the segmentation effect of remote sensing images by deeply mining the rich texture and semantic features of images. But there are still some problems such as rough results of small target region segmentation and poor edge contour segmentation. To overcome these three challenges, we propose an improved semantic segmentation model, referred to as MRU-Net, which adopts the U-Net architecture as its backbone. Firstly, the convolutional layer is replaced by BasicBlock structure in U-Net network to extract features, then the activation function is replaced to reduce the computational load of model in the network. Secondly, a hybrid multi-scale recognition module is added in the encoder to improve the accuracy of image segmentation of small targets and edge parts. Finally, test on Massachusetts Buildings Dataset and WHU Dataset the experimental results show that compared with the original network the ACC, mIoU and F1 value are improved, and the imposed network shows good robustness and portability in different datasets.