Stock trading investment is an important method for investors in financial market. Most researches focus on the precise price prediction; however, how to determine the trading points are more practical than getting the price predicted. This paper proposes a novel approach using Colored Petri Net to discover the relationships between various technical indicators, and exposing the trading rules of trading signals hidden in historical data. Experiment results show that we can obtain a considerable return on investment by using our proposed trading signals detection methodology.

MOTIVATION: Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this article, classification by using associative Petri net (APN) for personalized ECG-arrhythmia-pattern identification is proposed for the first time in literature. RESULTS: A rule-based classification model and reasoning algorithm of APN are created for ECG arrhythmias classification. The performance evaluation using MIT-BIH arrhythmia database shows that our approach compares well with other reported studies.

Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this study, classifier by using associative Petri net for personalized ECG arrhythmias pattern identification is proposed. Association production rules and reasoning algorithm of APN are created for ECG arrhythmias detection. The performance of our approach compares well with previously reported results and could be a part of monitoring system for the detection of ECG arrhythmias.

Even though the ubiquity of technology can make many aspects of life more convenient, it may simultaneously raise some concerns about the privacy issues related to personal information. This research focused on the individual's behavior toward self-disclosure online and his or her cognition on personal privacy that was affected by not only the personal psychological factors but also the individual's computer knowledge and associated skills. To study how technological and psychological factors can simultaneously affect one's privacy concern and restrain behavior on disclosure, this study applied both perceived privacy and privacy concern to assess such factors as personal subjective attitude, computer self-efficacy, and perceived behavioral control to investigate the technological influence. A hypothesized model was proposed to describe the relationships among these constructs. After structural equation modeling is utilized to analyze the proposed hypotheses, the research findings showed that, although the perceived behavioral control had a negative effect on self-disclosure online, all the other hypotheses indicated a positive casual effect.

With the increase in the number senior citizens and chronic diseases, the number of elderly patients who need constant assistance has increased. One key point of all critical care for elderly patient is the continuous monitoring of their vital signs. Among these, the ECG signal is used for noninvasive diagnosis of cardiovascular diseases. Also, there is a pressing need to have a proper system in place for patient identification. Errors in patient identification, and hence improper administration of medication can lead to disastrous results. This paper proposes a novel embedded mobile ECG reasoning system that integrates ECG signal reasoning and RF identification together to monitor an elderly patient. As a result, our proposed method has a good accuracy in heart beat recognition, and enables continuous monitoring and identification of the elderly patient when alone. Moreover, in order to examine and validate our proposed system, we propose a managerial research model to test whether it can be implemented in a medical organization. The results prove that the mobility, usability, and performance of our proposed system have impacts on the user's attitude, and there is a significant positive relation between the user's attitude and the intent to use our proposed system.

Compared to the current approach of delivering instructional materials to learners in Web-based learning environments, the service-oriented instructional processes bring benefits in multiple facets. To realize the concept of service-oriented instructional processes, the capability of dynamically searching and binding pedagogical services is inevitable. However, linking remote services results in more latency, which will undermine learning experience and thus needs to be minimized. It is rational to support cache for holding metadata of available instructional resources locally. Besides the cache mechanism, subscription and syndication of pedagogical resourcespsila metadata also will make the implementation of service-oriented instructional processes more practical and efficient. This paper aims to clarify the corresponding design principles and propose the reference architecture for realizing the concept.

RFID technologies represent a common standard for data storage and retrieval that could improve collaboration and data sharing between non-competing organizations. With the advent of RFID (radio frequency identification), organizations have the opportunity to rethink how their organization will be. Unlike companies in the United States and Europe which are mandated by large retailers or government departments, most Taiwan companies are investing in RFID without pressure. The article explores the factor affecting radio frequency identification adoption applications in Taiwan. Its objective is to summarize the ways in which organizations are thinking about their possible uses in a wide variety of companies and industries. An empirical investigation (n=134) found seven factors affecting RFID adoption within Taiwan. They are operation efficiency, manufacturing efficiency and supply chain efficiency, organization context, investment cost, market environment, and technology characteristic. By providing insight into these important factors, this article can help further understanding of their role in the adoption and use of RFID. The theoretical and practical implications of these results are discussed.

Although Bayesian networks (BNs) are increasingly being used to solve real-world risk problems, their use is still constrained by the difficulty of constructing the node probability tables (NPTs). A key challenge is to construct relevant NPTs using the minimal amount of expert elicitation, recognizing that it is rarely cost effective to elicit complete sets of probability values. We describe a simple approach to defining NPTs for a large class of commonly occurring nodes (called ranked nodes). The approach is based on the doubly truncated normal distribution with a central tendency that is invariably a type of weighted function of the parent nodes. In extensive real-world case studies, we have found that this approach is sufficient for generating the NPTs of a very large class of nodes. We describe one such case study for validation purposes. The approach has been fully automated in a commercial tool, called AgenaRisk, and is thus accessible to all types of domain experts. We believe that this work represents a useful contribution to the BN research and technology, since its application makes the difference between being able to build realistic BN models and not.