Time filter

Source Type

Wang S.-L.,National Taichung Institute of Technology
Expert Systems with Applications | Year: 2011

Advances in wireless networking, mobile broadband Internet access technology as well as the rapid development of ubiquitous computing means e-learning is no longer limited to certain settings. A ubiquitous learning (u-learning) system must however not only provide the learner with learning resources at any time and any place. However, it must also actively provide the learner with the appropriate learning assistance for their context to help him or her complete their e-learning activity. In the traditional e-learning environment, the lack of immediate learning assistance, the limitations of the screen interface or inconvenient operation means the learner is unable to receive learning resources in a timely manner and incorporate them based on the actual context into the learner's learning activities. The result is impaired learning efficiency. Though developments in technology have overcome the constraints on learning space, an inability to appropriately exploit the technology may make it an obstacle to learning instead. When integrating the relevant information technology to develop a u-learning environment, it is therefore necessary to consider the personalization requirements of the learner to ensure that the technology achieves its intended result. This study therefore sought to apply context aware technology and recommendation algorithms to develop a u-learning system to help lifelong learning learners realize personalized learning goals in a context aware manner and improve the learner's learning effectiveness. © 2011 Elsevier Ltd. All rights reserved.


Chen M.-Y.,National Taichung Institute of Technology
Computers and Mathematics with Applications | Year: 2011

In this paper, we compare some traditional statistical methods for predicting financial distress to some more "unconventional" methods, such as decision tree classification, neural networks, and evolutionary computation techniques, using data collected from 200 Taiwan Stock Exchange Corporation (TSEC) listed companies. Empirical experiments were conducted using a total of 42 ratios including 33 financial, 8 non-financial and 1 combined macroeconomic index, using principle component analysis (PCA) to extract suitable variables. This paper makes four critical contributions: (1) with nearly 80% fewer financial ratios by the PCA method, the prediction performance is still able to provide highly-accurate forecasts of financial bankruptcy; (2) we show that traditional statistical methods are better able to handle large datasets without sacrificing prediction performance, while intelligent techniques achieve better performance with smaller datasets and would be adversely affected by huge datasets; (3) empirical results show that C5.0 and CART provide the best prediction performance for imminent bankruptcies; and (4) Support Vector Machines (SVMs) with evolutionary computation provide a good balance of high-accuracy short- and long-term performance predictions for healthy and distressed firms. Therefore, the experimental results show that the Particle Swarm Optimization (PSO) integrated with SVM (PSOSVM) approach could be considered for predicting potential financial distress. © 2011 Elsevier Ltd. All rights reserved.


Chen M.-Y.,National Taichung Institute of Technology
Information Sciences | Year: 2013

In recent years, newly-developed data mining and machine learning techniques have been applied to various fields to build intelligent information systems. However, few of these approaches offer online support or are able to flexibly adapt to large and complex financial datasets. Therefore, the present research adopts particle swarm optimization (PSO) techniques to obtain appropriate parameter settings for subtractive clustering (SC) and integrates the adaptive-network-based fuzzy inference system (ANFIS) model to construct a model for predicting business failures. Experiments were conducted based on an initial sample of 160 electronics companies listed on the Taiwan Stock Exchange Corporation (TSEC). Experimental results show that the proposed model is superior to other models, providing a lower mean absolute percentage error (MAPE) and root mean squared error (RMSE). The proposed one-order momentum method is able to learn quickly through one-pass training and provides high-accuracy short-term predictions, while the proposed two-order momentum provides high-accuracy long-term predictions from large financial datasets. Therefore, the proposed approach fulfills some important characteristics of the proposed model: the one-order momentum method is suitable for online learning and the two-order momentum method is suitable for incremental learning. Thus, the PS-ANFIS approach could provide better results in predicting potential financial distress. © 2012 Elsevier Inc. All rights reserved.


Chen M.-Y.,National Taichung Institute of Technology
Expert Systems with Applications | Year: 2011

Lately, stock and derivative securities markets continuously and rapidly evolve in the world. As quick market developments, enterprise operating status will be disclosed periodically on financial statement. Unfortunately, if executives of firms intentionally dress financial statements up, it will not be observed any financial distress possibility in the short or long run. Recently, there were occurred many financial crises in the international marketing, such as Enron, Kmart, Global Crossing, WorldCom and Lehman Brothers events. How these financial events affect world's business, especially for the financial service industry or investors has been public's concern. To improve the accuracy of the financial distress prediction model, this paper referred to the operating rules of the Taiwan Stock Exchange Corporation (TSEC) and collected 100 listed companies as the initial samples. Moreover, the empirical experiment with a total of 37 ratios which composed of financial and other non-financial ratios and used principle component analysis (PCA) to extract suitable variables. The decision tree (DT) classification methods (C5.0, CART, and CHAID) and logistic regression (LR) techniques were used to implement the financial distress prediction model. Finally, the experiments acquired a satisfying result, which testifies for the possibility and validity of our proposed methods for the financial distress prediction of listed companies. This paper makes four critical contributions: (1) the more PCA we used, the less accuracy we obtained by the DT classification approach. However, the LR approach has no significant impact with PCA; (2) the closer we get to the actual occurrence of financial distress, the higher the accuracy we obtain in DT classification approach, with an 97.01% correct percentage for 2 seasons prior to the occurrence of financial distress; (3) our empirical results show that PCA increases the error of classifying companies that are in a financial crisis as normal companies; and (4) the DT classification approach obtains better prediction accuracy than the LR approach in short run (less one year). On the contrary, the LR approach gets better prediction accuracy in long run (above one and half year). Therefore, this paper proposes that the artificial intelligent (AI) approach could be a more suitable methodology than traditional statistics for predicting the potential financial distress of a company in short run. © 2011 Elsevier Ltd. All rights reserved.


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.


Hsiao K.-L.,National Taichung Institute of Technology
Online Information Review | Year: 2011

Purpose - In recent years more and more users have begun to use social networking sites (SNSs). Visiting these sites has become a regular habit of many users. However most of the users only use the free services of the sites and are unwilling to pay for services. Therefore, in order to understand what factors affect users' intention to continue to pay for services, this study proposes a research model based on value theory and the academic literature on switching barriers. Design/methodology/approach - An online questionnaire was developed and used to collect research data. The responses of 211 SNS members who pay subscription fees for advanced services were used to test the hypotheses in the research model. Findings - All of the seven study hypotheses were supported. The results indicated that perceived value and service degradation barriers are the main factors which directly influence the intention to pay. Together they account for 37.4 per cent of the variance in intention. Additionally the results demonstrated that sunk costs and lost performance costs both had significant impact on service degradation barriers while enjoyment, social value, and perceived fees were the main determinants of the intention to pay. Practical implications - SNS managers could raise users' perceived value by enhancing the social value and enjoyment of SNSs. In addition they can provide paid members with exclusive member services to increase the barrier. To sum up, in order to increase customers' perceived value, SNS service providers need to understand the real needs of their major customers. These users will be more willing to pay for the services they prefer and feel they need and then recommend that other users use or pay for the services. Originality/value - This study provides a comprehensive framework of the influence of perceived value and service degradation barriers on users' intention to continue to pay for SNSs. The research results could be generalised to other social Web 2.0 services. © 2011 Emerald Group Publishing Limited. All rights reserved.


Chien Y.-H.,National Taichung Institute of Technology
IEEE Transactions on Reliability | Year: 2010

This paper presents the effects of salvage value on the optimal age-replacement policy for non-repairable products sold with a pro rata rebate warranty (PRRW). Cost models from the customer's perspective are developed for both warranted, and non-warranted products. The corresponding optimal replacement ages are derived such that the long-run expected cost rate is minimized. Under the increasing failure rate assumption, the existence and uniqueness of the optimal age for preventive replacement are shown, and the impacts of a PRRW on the optimal age-replacement policy are investigated analytically. Finally, a numerical example is provided for the optimal policy illustration and verification. © 2006 IEEE.


Li C.-Y.,National Taichung Institute of Technology
Expert Systems with Applications | Year: 2012

Increased outsourcing yields less vertically-integrated firms, suppliers have to rely on different buyers and interdisciplinary teams for acquired and utilized knowledge to improve performance. However, knowledge transfer from buyers to suppliers is not always successful. Studies pertaining to the knowledge stickiness between firms in the knowledge transfer process, such as between buyers and suppliers, have been minimal. Furthermore, while knowledge transfer processes are essentially context-specific in terms of who participates and how they participate in the process, it is very important to put knowledge transfer into context. The results provide support for a curvilinear inverted-U shape relationship between knowledge stickiness and manufacturing capability. In addition, the influence of knowledge stickiness on manufacturing capability would be enhanced by the moderating variables of social embeddedness and learning capability. The finding further suggests that supplier manufacturing capabilities impact supplier commitment and supplier performance. © 2011 Elsevier Ltd. All rights reserved.


Chien Y.-H.,National Taichung Institute of Technology
International Journal of Production Economics | Year: 2010

This paper focuses on an age-replacement policy for products under a new warranty strategy, which combines a fully renewable free replacement with a pro-rata warranty policy (called fully renewable FRW/PRW policy). For this combined warranty strategy, whenever a product fails within the warranty period, it is replaced by a new one and a new warranty is issued. Meanwhile, if the failure occurs during the first time interval (i.e., the free-replacement warranty (FRW) interval), replacement is made at no cost to the buyer; however, if the failure occurs during the second time interval (i.e., the pro-rata warranty (PRW) interval), replacement is made at a pro-rata cost to the buyer. Dividing the replacement age into three separate periods: within FRW, during PRW, and post-warranty. Then, given that the replacement age is in a certain interval, the cost model from the user/buyer perspective is developed, and the corresponding local optimal replacement age is derived such that the long run expected cost rate is minimized. Afterward, the global optimal replacement age is determined. Structural properties of these optimal policies are obtained and presented, and special cases of the model are discussed. Finally, a numerical example is given for illustration. © 2009 Elsevier B.V. All rights reserved.


Chien Y.-H.,National Taichung Institute of Technology
International Journal of Production Economics | Year: 2012

This paper presents the effects of a free-repair warranty on a periodic replacement policy with a discrete time process. Considering a repairable product that should be operational at the time over an indefinitely long operation cycle n (n=1, 2,⋯), under the discrete-time periodic replacement policy, a product is preventively replaced at pre-specified operation cycles N, 2N, 3N,⋯ (N=1, 2,⋯). When the product fails, a minimal repair is performed at the time of failure, and the failure rate is not disturbed by each repair. The cost models from the customers perspectives are developed for both warranted and non-warranted products. The corresponding optimal replacement period N is derived such that the long-run expected cost rate is minimized. Under the assumption of the discrete time increasing failure rate, the existence and uniqueness of the optimal replacement period are shown, and the impact of a free-repair warranty on the optimal periodic replacement policies is investigated analytically. The optimal N (*) for a warranted product should be adjusted toward the end of the warranty period. Finally, numerical examples are demonstrated for the optimal policy illustration and verification. The observations from the numerical results provide valuable information for a buyer (user) to adjust the optimal periodic replacement policy if a product is operating in discrete time under a free-repair warranty. © 2011 Elsevier B.V. All Rights Reserved.

Loading National Taichung Institute of Technology collaborators
Loading National Taichung Institute of Technology collaborators