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Hong W.,Yu Da University | Chen T.-S.,National Taichung Institute of Technology
IEEE Transactions on Information Forensics and Security | Year: 2012

This paper proposes a new data-hiding method based on pixel pair matching (PPM). The basic idea of PPM is to use the values of pixel pair as a reference coordinate, and search a coordinate in the neighborhood set of this pixel pair according to a given message digit. The pixel pair is then replaced by the searched coordinate to conceal the digit. Exploiting modification direction (EMD) and diamond encoding (DE) are two data-hiding methods proposed recently based on PPM. The maximum capacity of EMD is 1.161 bpp and DE extends the payload of EMD by embedding digits in a larger notational system. The proposed method offers lower distortion than DE by providing more compact neighborhood sets and allowing embedded digits in any notational system. Compared with the optimal pixel adjustment process (OPAP) method, the proposed method always has lower distortion for various payloads. Experimental results reveal that the proposed method not only provides better performance than those of OPAP and DE, but also is secure under the detection of some well-known steganalysis techniques. © 2011 IEEE.

To understand the impact of environmental value, ecological lifestyle, customer innovativeness on customer intention to install solar power system (SPS) in their private houses, an empirical model was proposed. Customer innovativeness was treated as a second-order construct with two first-order dimensions, with each of the latter being measured by means of reflective indicators. Using structural equation modeling, data collected from 203 college students and faculties at a University of Taiwan were tested against the model. We found that environmental value has a positive impact on ecological lifestyle and SPS install intention. Although ecological lifestyle associates positively with SPS install intention, the effect disappears when environmental value is included in the model. The effect of customer innovativeness on SPS install intention results from the tendency of customer novelty seeking, while the impact of customer independent judgment-making on SPS install intention is insignificant. The model explained 76% of the total variations within SPS install intention. Managerial implications for promoting of SPS are considered, and suggestions for further research provided. © 2013 Elsevier Ltd.

Yang M.-F.,Yu Da University
Mathematical and Computer Modelling | Year: 2010

Due to today's highly competitive environment, both reducing lead time and the associated inventory cost are critically important issues in supply chain. And, the consideration of time value effect is lacked in most previous researches. However, the effect of inflation is too critical to ignore. Therefore, we develop an integrated inventory model with crashing cost which was determined by the length of lead time is polynomial to recover the real inventory problems. The objective of this research is to minimize present value of the joint expected total cost over infinite time horizon. Then, we provide a solution algorithm to determine the optimal order quantity, the length of lead time and the number of lots which are delivered from the vendor to the buyer in the solution procedure. Numerical example is provided here to illustrate the solution procedure. © 2009 Elsevier Ltd. All rights reserved.

The accessibility of information through the Internet has enables flight attendants to become more informed, as well as developing more control of their own affairs. Employee advocacy is related to the transparency of airlines' employment offers and the airlines' willingness to do what is best for their employees. After reviewing the relevant literature, this study focuses on how employee advocacy is influenced by the way employees are treated by their airlines. We explored strategies that airline administrations apply to employee advocacy, developed a research setting, analyzed the factors involved, and developed a casual model of the antecedents and consequences of employee advocacy. We formulated 5 hypotheses. Data were collected, using a questionnaire survey of flight attendants in Taiwanese airlines. All hypotheses were verified with data from a sample of the respondents, by using a structural equation model. Our results indicated that employee advocacy is positively related to flight attendants' job satisfaction and commitment to the organization. Organizational innovation, supervisor support, and employee empowerment are positively related to employee advocacy. Finally, this study concludes by discussing managerial implications and providing suggestions for future research. © 2014 Elsevier Ltd.

The aim of this study was to analyze food safety control systems (FSCS) in selected hotels in Taiwan in order to identify current issues and future trends in the hotel industry. Fourteen interviews were conducted with personnel in six large international tourist hotels with a FSCS in place. Analysis of the interviews indicated that a hotel's food safety standards and operations depended significantly on the attitudes of the hotel management. Public concern, competitive advantage and the government's food safety policies all had less influence on the implementation and maintenance of a FSCS than the ongoing support of management. Hotel managements hope, therefore, that the government will educate the public on food safety and provide incentives that enable hotels to adopt FSCS strategies while reducing the cost. The study contributes to the development of theory relating to the implementation of food safety strategies, particularly for the hotel industry. © 2012 Elsevier Ltd.

Hong W.,Yu Da University
Optics Communications | Year: 2012

Tai et al. proposed a reversible data embedding method based on histogram shifting and achieved an excellent embedding performance. Their method shifts the absolute difference of two consecutive pixels for data embedment, and employs an embedding level to control the payload. However, the shifting of absolute difference reduces the number of embeddable spaces and results in a reduction in payload. Instead of shifting the absolute differences, this paper proposes an adaptive method to increase the number of embeddable spaces by referencing a dual binary tree. We also adopt a better predictor and employ an error energy estimator to reduce the number of non-embeddable prediction errors. The experimental results reveal that the proposed method significantly improves the image quality and payload of Tai et al.'s works, especially at low embedding level. © 2011 Elsevier B.V. All rights reserved.

The majority of previous studies have used logistic regression analysis(LRA) as an analysis tool to evaluate the impact of service attributes on customer satisfaction and post-purchase behavior. However, LRA assumes that a linear relation exists between the input and output variables, and that variables are normally distributed, which places significant limitations on the analysis. This study uses multilayer perceptrons neural networks(MLPs) to overcome the limitations of LRA. The results show that among the four hotel service attributes, "personnel services" has the greatest impact on customer satisfaction and repurchase or recommending the service to others, whereas "business and travel services" has the lowest impact. MLPs is more accurate than LRA. MLPs achieved an accuracy rate of 93% for predicting customer satisfaction, and 90% for predicting repurchase or recommending the service to others. Although LRA has an accuracy rate of 87% for predicting customer satisfaction, it only scores 23.77% for predicting "unsatisfied customers." MLPs has an accuracy rate of 69.23% for predicting this category. LRA has an accuracy rate of 80% for predicting repurchase or recommending the service to others, but only has 9.52% accuracy in the "no intention to repurchase or recommend the service to others" category. By contrast, MLPs has an accuracy of 71.43% for this category, indicating that MLPs can predict repurchase or recommending the service to others more effectively.

Huang H.-C.,Yu Da University
International Journal of Advancements in Computing Technology | Year: 2012

Recent global economic problems, such as the U.S. financial crisis and Europe's debt crisis, have caused dramatic short-term fluctuations in currency values. Exchange rate fluctuations increase the difficulties encountered by businesses that rely on import and export trade. However, financial markets provide numerous methods for corporations to hedge the risks of exchange rate fluctuations. Nevertheless, a model for predicting exchange rate fluctuations can enable business owners to make more appropriate judgments. This study employs a multilayer perceptions (MLP) neural network with genetic algorithm (GA) to predict the Chinese Yuan (CNY)/ U.S. dollar (USD) exchange rate. The GA is used to determine the optimum hidden nodes for a feed forward neural network, the optimum slope of the activation function, and the optimum learning rates and momentum coefficients. The empirical results show that the ability of the proposed model to predict the CNY/USD exchange rate is excellent. The absolute relative error between the predicted value and the actual value was 0.223%, and the correlation coefficient was 0.998795.

Huang H.-C.,Yu Da University
International Journal of Advancements in Computing Technology | Year: 2012

Success in the service industry requires providing high-quality service and a satisfying consumer experience. However, regardless of the level of quality, preventing service failures is always difficult. When a service failure occurs, it is critical for managers to propose a quick and accurate service recovery plan that can satisfy the consumer. After surveying consumers, the data revealed a 72.99% chance that consumers will return to the place of business if they are satisfied with the service recovery plan. Conversely, there is a 79.64% chance that consumers will not return if they are not satisfied with the service recovery plan. This indicates that managers should manage consumer complaints with extreme care. This paper uses multilayer perceptrons (MLPs) and support vector machines (SVMs) neural networks to predict service recovery. The variables which are input into the MLPs and SVMs artificial neural networks to predict consumer expectations for service recovery are service failure type, easily determined consumer characteristics, the language used in customer complaints, tone of voice, and mood. Both MLPs and SVMs are proved to be efficient and reliable. The SVMs method is more accurate (PPV=95%) than the MLPs method (PPV=87.5%).

Reference table (RT) based embedding method embeds secret digits into pixel pairs under the guidance of a reference table. Most of the existing RT-based methods either require elaborate conversions among different bases, or have limited embedding capacity. In this paper, we use a patched reference table (PRT) as a guide and propose a PRT method to provide a better image quality and extendable embedding capacity. We also exploit the concept of pixel value differencing (PVD) and propose another method PRT-PVD. In the traditional PVD-based methods, the shape of the difference histograms of the stego images is significantly altered and, thus, vulnerable to some steganalyzers. PRT-PVD adopts the PRT method and uses a specially designed embedding sequence to preserve the difference histogram shape. Experimental results reveal that the proposed PRT and PRT-PVD methods not only have better embedding efficiency over the existing methods, but also are robust to detection by modern steganalysis tools. © 2012 Elsevier Inc. All rights reserved.

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