Objective:The annual influenza epidemic is a heavy burden on the health care system,and has increasingly become a major public health problem in some areas,such as Hong Kong(China).Therefore,based on a variety of mach...Objective:The annual influenza epidemic is a heavy burden on the health care system,and has increasingly become a major public health problem in some areas,such as Hong Kong(China).Therefore,based on a variety of machine learning methods,and considering the seasonal influenza in Hong Kong,the study aims to establish a Combinatorial Judgment Classifier(CJC)model to classify the epidemic trend and improve the accuracy of influenza epidemic early warning.展开更多
Neighbor discovery is important for docking applications,where mobile nodes communicate with static nodes situated at various rendezvous points.Among the existing neighbor discovery protocols,the probabilistic methods...Neighbor discovery is important for docking applications,where mobile nodes communicate with static nodes situated at various rendezvous points.Among the existing neighbor discovery protocols,the probabilistic methods perform well in average cases but they have aperiodic,unpredictable,and unbounded discovery latency.Yet,deterministic protocols can provide bounded worst-case discovery latency by sacrificing the average-case performance.In this study,we propose a mobility-assisted slot index synchronization(MASS),which is a new synchronization technique that can improve the average-case performance of deterministic neighbor discovery protocols via slot index synchronization without incurring additional energy consumption.Furthermore,we propose an optimized beacon strategy in MASS to mitigate beaconing collisions,which can lead to discovery failures in situations where multiple neighbors are in the vicinity.We evaluate MASS with theoretical analysis and simulations using real traces from a tourist tracking system deployed at the Mogao Grottoes,which is a famous cultural heritage site in China.We show that MASS can reduce the average discovery latency of state-of-the-art deterministic neighbor discovery protocols by up to two orders of magnitude.展开更多
基金This project was supported by grants from the Ministry of Education Humanities and Social Sciences Research Fund Project。
文摘Objective:The annual influenza epidemic is a heavy burden on the health care system,and has increasingly become a major public health problem in some areas,such as Hong Kong(China).Therefore,based on a variety of machine learning methods,and considering the seasonal influenza in Hong Kong,the study aims to establish a Combinatorial Judgment Classifier(CJC)model to classify the epidemic trend and improve the accuracy of influenza epidemic early warning.
基金Project supported by the National High-Tech R&D Program of China(No.2012AA101701)the National Key Technology Support Program of China(Nos.2013BAK01B00 and2014BAK16B00)Grotto Temples Digital Protection of Cultural Relics and Equipment Upgrading of National Cultural Heritage Administration Scientific Research Institutes
文摘Neighbor discovery is important for docking applications,where mobile nodes communicate with static nodes situated at various rendezvous points.Among the existing neighbor discovery protocols,the probabilistic methods perform well in average cases but they have aperiodic,unpredictable,and unbounded discovery latency.Yet,deterministic protocols can provide bounded worst-case discovery latency by sacrificing the average-case performance.In this study,we propose a mobility-assisted slot index synchronization(MASS),which is a new synchronization technique that can improve the average-case performance of deterministic neighbor discovery protocols via slot index synchronization without incurring additional energy consumption.Furthermore,we propose an optimized beacon strategy in MASS to mitigate beaconing collisions,which can lead to discovery failures in situations where multiple neighbors are in the vicinity.We evaluate MASS with theoretical analysis and simulations using real traces from a tourist tracking system deployed at the Mogao Grottoes,which is a famous cultural heritage site in China.We show that MASS can reduce the average discovery latency of state-of-the-art deterministic neighbor discovery protocols by up to two orders of magnitude.
