以微博相关视频为研究对象,对选取样本进行内容分析,探究有可能影响公众健康态度和疫苗健康决策的社交媒体内容如何呈现人乳头瘤病毒(human papillomavirus,HPV)疫苗相关议题,并利用扩展的平行过程模式(expended parallel process model...以微博相关视频为研究对象,对选取样本进行内容分析,探究有可能影响公众健康态度和疫苗健康决策的社交媒体内容如何呈现人乳头瘤病毒(human papillomavirus,HPV)疫苗相关议题,并利用扩展的平行过程模式(expended parallel process model,EPPM)对其内容中的“威胁”和“效能”信息分析得出,兼具大众传播功能和人际传播影响力的微博中,不同来源的HPV疫苗视频对HPV健康风险及疫苗改善措施的信息呈现上存在差异,对于HPV疫苗的接种信息呈现不足,有可能影响用户的健康效能,对公众的健康促进需要更加全面、准确、平衡的HPV疫苗信息呈现。展开更多
Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy co...Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy consumption analytically and systematically for other two representative barrier algorithms:tournament barrier and central counter barrier.Furthermore,energy optimization methods of these two barrier algorithms were implemented on parallel computing platform.The experimental results validate the effectiveness of the energy optimization methods.67.12% and 70.95% energy savings are obtained respectively for tournament barrier and central counter barrier on platforms with 2048 processes with 1.55%?8.80% performance loss.Furthermore,LogP-based energy-saving analytical model for these two barrier algorithms is highly accurate as the predicted energy savings are within 9.67% of the results obtained by simulation.展开更多
文摘以微博相关视频为研究对象,对选取样本进行内容分析,探究有可能影响公众健康态度和疫苗健康决策的社交媒体内容如何呈现人乳头瘤病毒(human papillomavirus,HPV)疫苗相关议题,并利用扩展的平行过程模式(expended parallel process model,EPPM)对其内容中的“威胁”和“效能”信息分析得出,兼具大众传播功能和人际传播影响力的微博中,不同来源的HPV疫苗视频对HPV健康风险及疫苗改善措施的信息呈现上存在差异,对于HPV疫苗的接种信息呈现不足,有可能影响用户的健康效能,对公众的健康促进需要更加全面、准确、平衡的HPV疫苗信息呈现。
基金Projects(60903044,61170049) supported by National Natural Science Foundation of China
文摘Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy consumption analytically and systematically for other two representative barrier algorithms:tournament barrier and central counter barrier.Furthermore,energy optimization methods of these two barrier algorithms were implemented on parallel computing platform.The experimental results validate the effectiveness of the energy optimization methods.67.12% and 70.95% energy savings are obtained respectively for tournament barrier and central counter barrier on platforms with 2048 processes with 1.55%?8.80% performance loss.Furthermore,LogP-based energy-saving analytical model for these two barrier algorithms is highly accurate as the predicted energy savings are within 9.67% of the results obtained by simulation.
