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High quality data and effective data quality assessment are required for accurately evaluating the impact of public health interventions and measuring public health outcomes. Data, data use, and data collection process, as the three dimensions of data quality, all need to be assessed for overall data quality assessment. We reviewed current data quality assessment methods. The relevant study was identified in major databases and well-known institutional websites. We found the dimension of data was most frequently assessed. Completeness, accuracy, and timeliness were the three most-used attributes among a total of 49 attributes of data quality. The major quantitative assessment methods were descriptive surveys and data audits, whereas the common qualitative assessment methods were interview and documentation review. The limitations of the reviewed studies included inattentiveness to data use and data collection process, inconsistency in the definition of attributes of data quality, failure to address data users’ concerns and a lack of systematic procedures in data quality assessment. This review study is limited by the coverage of the databases and the breadth of public health information systems. Further research could develop consistent data quality definitions and attributes. More research efforts should be given to assess the quality of data use and the quality of data collection process.

Recent research has established the potential for virtual characters to establish rapport with humans through simple contingent nonverbal behaviors. We hypothesized that the contingency, not just the frequency of positive feedback is crucial when it comes to creating rapport. The primary goal in this study was evaluative: can an agent generate behavior that engenders feelings of rapport in human speakers and how does this compare to human generated feedback? A secondary goal was to answer the question: Is contingency (as opposed to frequency) of agent feedback crucial when it comes to creating feelings of rapport? Results suggest that contingency matters when it comes to creating rapport and that agent generated behavior was as good as human listeners in creating rapport. A "virtual human listener" condition performed worse than other conditions.

Most of the existing typical ship domains have been comprehensively reviewed and classified. Most of these ship domains are described in a geometrical manner that is difficult to apply to practices and simulations in marine traffic engineering. According to different types of geometrical ship domains, we have proposed mathematical models, based on which a unified analytical framework has been established. It is feasible and practical for the analytical models to be applied to the assessment of navigational safety, collision avoidance and trajectory planning, etc. Finally, some computer simulations and comparative studies of the proposed domain model have been presented and the simulation results show that the uniform analytical framework for ship domains is effective and identical to the original geometrical ones. It should be noted that the analytical domain models could be directly applied in any collision risk, collision avoidance or VTS system while the geometrical ones would be more illustrative but less practical or analytical.

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