During the two cruises in March and July of 2011, the tidal cycling of turbulent properties and the T/S profiles at the same location in seasonally stratified East China Sea （ECS） were measured synchronously by a bo...During the two cruises in March and July of 2011, the tidal cycling of turbulent properties and the T/S profiles at the same location in seasonally stratified East China Sea （ECS） were measured synchronously by a bottom-mounted fast sampling ADCP （acoustic Doppler current profiler） and a RBR CTD （RBR-620） profiler. While focusing on the tide-induced and stratification＇s impact on mixing, the Reynolds stress and the turbulent kinetic energy （TKE） production rate were calculated using the ‘variance method＇. In spring, the features of mixing mainly induced by tides were clear when the water column was well-mixed. Velocity shear and turbulent parameters intensified towards the seabed due to the bottom friction. The components of the velocity shear and the Reynolds stress displayed a dominant semi-diurnal variation related to velocity changes caused by the flood and ebb of M2 tide. Stratification occurred in summer, and the water column showed a strongly stratified pycnocline with a characteristic squared buoy- ancy frequency of N2~ （1-6）x 10 3 S-2 The components of the velocity shear and the Reynolds stress penetrated upwards very fast from the bottom boundary layer to the whole water column in spring, while in summer they only penetrated to the bottom of the pycnocline with a relatively slow propagation speed. In summer, the TKE production within the pycnocline was comparable with and sometimes larger than that in the well-mixed bottom layer under the pycnocline. Considering the associated high velocity shear, it is speculated that the mixing in the pycnocline is a result of the local velocity shear.展开更多
As the Smart city trend especially artificial intelligence,data science,and the internet of things has attracted lots of attention,many researchers have created various smart applications for improving people’s life ...As the Smart city trend especially artificial intelligence,data science,and the internet of things has attracted lots of attention,many researchers have created various smart applications for improving people’s life quality.As it is very essential to automatically collect and exploit information in the era of industry 4.0,a variety of models have been proposed for storage problem solving and efficient data mining.In this paper,we present our proposed system,Trendy Keyword Extraction System(TKES),which is designed for extracting trendy keywords from text streams.The system also supports storing,analyzing,and visualizing documents coming from text streams.The system first automatically collects daily articles,then it ranks the importance of keywords by calculating keywords’frequency of existence in order to find trendy keywords by using the Burst Detection Algorithm which is proposed in this paper based on the idea of Kleinberg.This method is used for detecting bursts.A burst is defined as a period of time when a keyword is continuously and unusually popular over the text stream and the identification of bursts is known as burst detection procedure.The results from user requests could be displayed visually.Furthermore,we create a method in order to find a trendy keyword set which is defined as a set of keywords that belong to the same burst.This work also describes the datasets used for our experiments,processing speed tests of our two proposed algorithms.展开更多
Breaking wave induced nearsurface turbulence has important consequences for many physical and biochemical processes including water column and nutrients mixing, heat and gases exchange across air-sea interface. The en...Breaking wave induced nearsurface turbulence has important consequences for many physical and biochemical processes including water column and nutrients mixing, heat and gases exchange across air-sea interface. The energy loss from wave breaking and the bubble plume penetration depth are estimated. As a consequence, the vertical distribution of the turbulent kinetic energy （TKE）, the TKE dissipation rate and the eddy viscosity induced by wave breaking are also provided. It is indicated that model results are found to be consistent with the observational evidence that most TKE generated by wave breaking is lost within a depth of a few meters near the sea surface. High turbulence level with intensities of eddy viscosity induced by breaking is nearly four orders larger than vw1（ = κu ＊wz）, the value predicted for the wall layer scaling close to the surface, where u ＊w is the friction velocity in water, κ with 0. 4 is the yon Kármán constant, and z is the water depth, and the strength of the eddy viscosity depends both on wind speed and sea state, and decays rapidly through the depth. This leads to the conclusion that the breaking wave induced vertical mixing is mainly limited to the near surface layer, well above the classical values expected from the similarity theory. Deeper down, however, the effects of wave breaking on the vertical mixing become less important.展开更多
基金supported by the National Basic Research Program of China (973 Program,2010CB428904)the National Science Foundation of China (No.41276016)+1 种基金the Program for New Century Excellent Talents in University (NCET-11-0475)the National Key Technology R&D Program of China (2011BAC03B02)
文摘During the two cruises in March and July of 2011, the tidal cycling of turbulent properties and the T/S profiles at the same location in seasonally stratified East China Sea （ECS） were measured synchronously by a bottom-mounted fast sampling ADCP （acoustic Doppler current profiler） and a RBR CTD （RBR-620） profiler. While focusing on the tide-induced and stratification＇s impact on mixing, the Reynolds stress and the turbulent kinetic energy （TKE） production rate were calculated using the ‘variance method＇. In spring, the features of mixing mainly induced by tides were clear when the water column was well-mixed. Velocity shear and turbulent parameters intensified towards the seabed due to the bottom friction. The components of the velocity shear and the Reynolds stress displayed a dominant semi-diurnal variation related to velocity changes caused by the flood and ebb of M2 tide. Stratification occurred in summer, and the water column showed a strongly stratified pycnocline with a characteristic squared buoy- ancy frequency of N2~ （1-6）x 10 3 S-2 The components of the velocity shear and the Reynolds stress penetrated upwards very fast from the bottom boundary layer to the whole water column in spring, while in summer they only penetrated to the bottom of the pycnocline with a relatively slow propagation speed. In summer, the TKE production within the pycnocline was comparable with and sometimes larger than that in the well-mixed bottom layer under the pycnocline. Considering the associated high velocity shear, it is speculated that the mixing in the pycnocline is a result of the local velocity shear.
基金The work of Tham Vo is supported by Lac Hong University,and funded by Thu Dau Mot University(No.DT.20-031)The work of Phuc Do is funded by Vietnam National University,Ho Chi Minh City(No.DS2020-26-01).
文摘As the Smart city trend especially artificial intelligence,data science,and the internet of things has attracted lots of attention,many researchers have created various smart applications for improving people’s life quality.As it is very essential to automatically collect and exploit information in the era of industry 4.0,a variety of models have been proposed for storage problem solving and efficient data mining.In this paper,we present our proposed system,Trendy Keyword Extraction System(TKES),which is designed for extracting trendy keywords from text streams.The system also supports storing,analyzing,and visualizing documents coming from text streams.The system first automatically collects daily articles,then it ranks the importance of keywords by calculating keywords’frequency of existence in order to find trendy keywords by using the Burst Detection Algorithm which is proposed in this paper based on the idea of Kleinberg.This method is used for detecting bursts.A burst is defined as a period of time when a keyword is continuously and unusually popular over the text stream and the identification of bursts is known as burst detection procedure.The results from user requests could be displayed visually.Furthermore,we create a method in order to find a trendy keyword set which is defined as a set of keywords that belong to the same burst.This work also describes the datasets used for our experiments,processing speed tests of our two proposed algorithms.
基金This research was supported by the National Natural Science Foundation of China under contract Nos 40576021 and 40531005.
文摘Breaking wave induced nearsurface turbulence has important consequences for many physical and biochemical processes including water column and nutrients mixing, heat and gases exchange across air-sea interface. The energy loss from wave breaking and the bubble plume penetration depth are estimated. As a consequence, the vertical distribution of the turbulent kinetic energy （TKE）, the TKE dissipation rate and the eddy viscosity induced by wave breaking are also provided. It is indicated that model results are found to be consistent with the observational evidence that most TKE generated by wave breaking is lost within a depth of a few meters near the sea surface. High turbulence level with intensities of eddy viscosity induced by breaking is nearly four orders larger than vw1（ = κu ＊wz）, the value predicted for the wall layer scaling close to the surface, where u ＊w is the friction velocity in water, κ with 0. 4 is the yon Kármán constant, and z is the water depth, and the strength of the eddy viscosity depends both on wind speed and sea state, and decays rapidly through the depth. This leads to the conclusion that the breaking wave induced vertical mixing is mainly limited to the near surface layer, well above the classical values expected from the similarity theory. Deeper down, however, the effects of wave breaking on the vertical mixing become less important.
