An Intelligent Interface Integrated Services Environment for Electronic Commerce

This paper proposes an intelligent interface integrated services environment for electronic commerce. It contains four main modules, i.e., dialog manager, EC transaction ontology, information collector, and data analyzer. The dialog manager manages the transaction history of the user to collect the user-specific information. It also provides different helping functions for the user. The EC transaction ontology stores the business type of electronic commerce in the system. It classifies the business process into eight categories, i.e., transaction type, ordering pattern, merchandise type, logistic type, customer category, transport vehicle, delivery type, and service type. It also provides the relations and constraints between different business steps. The information collector instantiates and dispatches different information agents to extract, filter, and synthesize relevant transaction data from different data sources timely. The data analyzer is the main component of the system. It instructs the dialog manager to provide proper helping functions for the different users. It then uses the user model to classify the knowledge and skill level of a user. It also predicts the goal of the user by using case-based reasoning and fuzzy Petri-Net to recommend the user with the best transaction plan and browsing behavior. Finally, it monitors the quality of service that the system provided for the user. This environment not only provides an integrated human-machine interface but also manages the business information thoroughly for the users

An Intelligent Information Management Environment for Mobile Commerce

This work proposes an intelligent information management environment for mobile commerce. The environment contains four modules, namely, interface manager, information repository, information analyzer, and information collector. The interface manager provides an intelligent interface for generating and collecting business information from the mobile device. The information repository contains the user-specific information and the meta-information of information sources. The information analyzer performs the tasks of user behavior analysis, quality of information service measurement, information repository management, cost evaluation, anytime information supporting, and information filtering. Finally, the information collector dispatches different information agents for collecting business information from different information sources

An Adaptive Interface for Customer Transaction Assistant in Electronic Commerce

Personalized service and adaptive interface play important factors in electronic commerce. This work proposes an adaptive interface to for helping the customer transaction in electronic commerce. The adaptive interface collects the consumer behaviors by monitoring the customer operations, excluding unnecessary operations, and recognizing the behavior patterns. The interface uses the Bayesian belief network and the RBF neural networks to achieve the above tasks. The interface then evaluates knowledge and skill proficiency according to the customer behavior patterns. Finally, the interface generates the adaptive interface to the consumers for helping the transaction process

Flow Experience and Challenge-Skill Balance in E-Learning

Flow is an optimal experience resulting in intense engagement in the activity. People achieved flow state when they perceived balance between challenge of the activity and their skill to the activity. The concept of flow can be used to explore students’ learning performance in e-learning environment. The current research aims to empirically explore the influence of challenge-skill balance on the flow experience and the influence of flow experience on learning satisfaction and learning performance in e-learning environment. The current research conducted a quasi-experimental design with questionnaire survey and carried out an electroencephalography (EEG) analysis, a psychophysiological method. The empirical survey results have shown that challenge-skill balance is an antecedent factor affecting learners’ flow experience. Once learners reach flow experience, their learning performance and learning satisfaction would get improved. Besides, the current research also found that flow experience is relative with learners’ attention measured by EEG brainwave signal. Learners’ perception of challenge-skill balance would influence their attention in e- learning activities. The current research is also in the pioneering position that using non-medical purpose EEG device in e-learning research

Gender and Posture are Significant Risk Factors to Musculoskeletal Symptoms during Touchscreen Tablet Computer Use

[Purpose] To investigate the prevalence of neck and shoulder symptoms during the use of tablet computer, and to identify the risk factors associated with these symptoms. [Subjects and Methods] A cross-sectional survey was conducted to study tablet computer usage, posture during use, and neck and shoulder symptoms in 412 participants in a school setting. Significant risk factors for musculoskeletal symptoms during tablet computer use were identified. [Results] Overall prevalence of musculoskeletal symptoms during tablet computer use was 67.9% with greater prevalence of neck symptoms (neck: 84.6%; shoulder/upper extremity: 65.4%). Significant risk factors associated with symptoms during use were: current musculoskeletal symptoms, gender, roles, and postural factors including: sitting without back support, sitting with device in lap, and lying on the side and on the back during tablet computer use. A multivariate analysis further showed that the odds for females to have symptoms were 2.059 times higher than males. [Conclusion] The findings revealed that female gender and other postural factors were significantly associated with musculoskeletal symptoms during the use of tablet computer. Among all postural factors, sitting without back support was identified as the most important risk factor for having musculoskeletal symptom

Epidemiology of digital amputation and replantation in Taiwan: A population-based study

AbstractBackgroundPublications on digital amputation and replantation have been mostly derived from case series in high-volume hand surgery practices, and epidemiological studies are few. This study used a population-based dataset to illustrate the incidence of digital amputation, patient and hospital characteristics, and their relationships with replantation.MethodsA claim for reimbursement dataset (2008) was provided as a research database by the Bureau of National Health Insurance, Taiwan. Patients with ICD-9-CM coded as digital amputation (885 and 886) were included. These were cross-referenced with procedure codes for replantation procedures (84.21 and 84.22). We defined the patients who underwent thumb replantation (84.21) and thumb amputation (84.01) during a single hospitalization as replantation failure. Patient and hospital characteristics were studied with statistical analysis.ResultsIn total, 2358 patients with digital amputation were admitted (1859 male, 499 female), mean age 39.2 ± 15.5 years. The incidence was 10.2/100,000 person–years. The highest incidence was 14.7/100,000 person–years in the age group 45–54 years. Machinery and powered hand tools caused 68.8% of digital amputations. Thumb amputation [odds ratio (OR): 1.35, p = 0.01], private hospital (OR: 1.40, p = 0.01), medical center (OR: 2.38, p < 0.001), regional hospital (OR: 2.41, p < 0.001) and hospitals with an annual volume >20 digital amputations (OR: 4.23, p < 0.001) were associated with higher attempt rates for replantation. Elderly patients (age >65 years) had higher risk of thumb replantation failure (OR: 32.30, p = 0.045), while hospitals with >20 annual replantations had lower risk (OR: 0.11, p = 0.02).ConclusionOur study of the National Health Insurance database characterized the epidemiology of digital amputation patients undergoing replantation and the facilities in Taiwan where these procedures are performed. The hospitals treating more digital amputation patients had higher attempt rates and lower thumb failure rates