John Black Day Hospital

The degrees of association among haze and impact factors determine the correct judgment and grasp the decision-making path of haze governance. This paper uses the gray correlation method of system theory comparative analyze relevance factors of haze in Beijing-Tianjin-Hebei region. Higher absolute correlation degree of industrial structure and haze in Beijing province, and highest association of population and haze in Tianjin area and Hebei province; The relative degree of grey incidence between haze and population is highest in Beijing, the relative degree of financial development and haze in Tianjin area is highest, Hebei province urbanization rate is the highest; the comprehensive degree industry structure associated with haze is the highest in Beijing, Tianjin and Hebei province urbanization rate is the highest comprehensive correlation with haze. It can be seen that the economic development stage and economic development situation is different, Haze problems in Tianjin and Hebei have similar places so Beijing-Tianjin-Hebei regions need to take a coordinated haze governance policy. Finally, the paper discusses the haze governance strategies and suggestions for the future green development of Beijing-Tianjin-Hebei region on the basis of the results of this study aiming at the coordinated development of green transformation and coordination in Beijing-Tianjin-Hebei region, and promotes the innovation of urban agglomeration development theory and planning practice.

This paper investigates the challenges in developing a semantic-based Dementia Care Decision Support System based on the non-intrusive monitoring of the patient's behaviour. Semantic-based approaches are well suited for modelling context-aware scenarios similar to Dementia care systems, where the patient's dynamic behaviour observations (occupants movement, equipment use) need to be analysed against the semantic knowledge about the patient's condition (illness history, medical advice, known symptoms) in an integrated knowledgebase. However, our research findings establish that the ability of semantic technologies to reason upon the complex interrelated events emanating from the behaviour monitoring sensors to infer knowledge assisting medical advice represents a major challenge. We attempt to address this problem by introducing a new approach that relies on propositional calculus modelling to segregate complex events that are amenable for semantic reasoning from events that require pre-processing outside the semantic engine before they can be reasoned upon. The event pre-processing activity also controls the timing of triggering the reasoning process in order to further improve the efficiency of the inference process. Using regression analysis, we evaluate the response-time as the number of monitored patients increases and conclude that the incurred overhead on the response time of the prototype decision support systems remains tolerable.