From Your Preferences to Niche Tourism: A New “To-Do” List in Hong Kong

There are a lot of services and mobile applications that allow simplifying a search, proactively providing information about famous attractions and user feedback; but travelers may have difficulty in choosing based on their real needs. Smart tourism, under the rapid growth of Internet of Things and machine learning techniques is developed for enhancing travellers’ experience and satisfaction. In recent years, it is essential for most tourism industrialists to strengthen their competitive edge and to improve industrial sustainability through the adoption of smart tourism. In this chapter, the proposed model generates travel recommendations and related useful information to end users through an online platform, namely Niche-E-Travel (NET). This distinctive tourism solution aims to collect all the obscure attractions, to align them with visitors’ interests, and to provide them with a new to-do list in Hong Kong. NET collects basic information from end users and uses the proposed travel analytic model with K-modes and K-means clustering methods to finish a clustering process, and provide some potential activity plans to fit the end user’s interests and requirements. Recommendations made for each user are supported by collaborative filtering to compare different users’ personal interests

Why Do Players Stick to a Specific Online Game? The Users and Gratifications Perspective

Driven by the dominant Internet usage and the prospective profits from the game industry, especially from the thriving and robust free-to-play model of online games, there is a need to realize players’ behaviors. Playing online games is experienceoriented but rare studies further explore what reactions of initial (trial) experiences in game playing are and how they will further influence players’ behaviors. Uses and gratification theory can be seen in cases such as online games selection. Players select an online game not only to fit particular interests but also to attempt to show empowerment or other socially conscience motives. This study, therefore, seeks to explore the important antecedents (i.e. gratifications, presence, service mechanisms, and continuance motivation) of stickiness intention on the online game and examine the associated relationships among them. The implications of findings to both researchers and practitioners are also discussed

Long-term Characteristics of Healthcare-associated Infections in a Neonatal Intensive Care Unit

Background/PurposeHealthcare-associated infections in neonatal intensive care units (NICUs) are associated with a significant risk of morbidity and mortality. Knowledge regarding pathogens, primary sources of infection and antibiotic resistance in the NICU is essential for developing management strategies. This study aimed to analyze the long-term characteristics of healthcare-associated infections in a tertiary referral center in southern Taiwan.MethodsInfants < 30 days old, with positive blood, cerebrospinal fluid, urine or tissue fluid cultures during hospitalization in the NICU of National Cheng Kung University Hospital from July 1989 to June 2008 were included in the study.ResultsIn total, 1,417 organisms and episodes were identified during the study period. Gram-positive organisms, Gram-negative organisms and fungi constituted 923 (65.1%), 358 (25.3%) and 136 (9.6%) of the pathogens, respectively. Of the Gram-positive organisms, coagulase-negative staphylococci (51.5%), Staphylococcus aureus (34.8%) and Enterococcus spp. (6.1%) were the major pathogens; and 27% of Staphylococcus aureus isolates were oxacillin-resistant. For the Gram-negative organisms, Klebsiella pneumoniae (22%), Pseudomonas aeruginosa (21.8%), Escherichia coli (16.7%) and Enterobacter cloacae (16.7%) were dominant. Also, Candida albicans accounted for 50% of fungal infections. The most common source of infection was bloodstream infection (59.0%), and 5.6% of these were catheter-related. Skin and soft tissue infections were also frequent (26.3%).ConclusionBloodstream and skin/soft tissue infections caused by commensal species play an important role in healthcare-associated infections in the NICU. New measures should be developed in response to the changing patterns in the NICU