Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to time....Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to time.The growing volume of tweets with sentiment drifts has led to the need for devising an adaptive approach to detect and handle this drift in real time.This work proposes an adap-tive learning algorithm-based framework,Twitter Sentiment Drift Analysis-Bidir-ectional Encoder Representations from Transformers(TSDA-BERT),which introduces a sentiment drift measure to detect drifts and a domain impact score to adaptively retrain the classification model with domain relevant data in real time.The framework also works on static data by converting them to data streams using the Kafka tool.The experiments conducted on real time and simulated tweets of sports,health care andfinancial topics show that the proposed system is able to detect sentiment drifts and maintain the performance of the classification model,with accuracies of 91%,87%and 90%,respectively.Though the results have been provided only for a few topics,as a proof of concept,this framework can be applied to detect sentiment drifts and perform sentiment classification on real time data streams of any topic.展开更多
Clustering high dimensional data is challenging as data dimensionality increases the distance between data points,resulting in sparse regions that degrade clustering performance.Subspace clustering is a common approac...Clustering high dimensional data is challenging as data dimensionality increases the distance between data points,resulting in sparse regions that degrade clustering performance.Subspace clustering is a common approach for processing high-dimensional data by finding relevant features for each cluster in the data space.Subspace clustering methods extend traditional clustering to account for the constraints imposed by data streams.Data streams are not only high-dimensional,but also unbounded and evolving.This necessitates the development of subspace clustering algorithms that can handle high dimensionality and adapt to the unique characteristics of data streams.Although many articles have contributed to the literature review on data stream clustering,there is currently no specific review on subspace clustering algorithms in high-dimensional data streams.Therefore,this article aims to systematically review the existing literature on subspace clustering of data streams in high-dimensional streaming environments.The review follows a systematic methodological approach and includes 18 articles for the final analysis.The analysis focused on two research questions related to the general clustering process and dealing with the unbounded and evolving characteristics of data streams.The main findings relate to six elements:clustering process,cluster search,subspace search,synopsis structure,cluster maintenance,and evaluation measures.Most algorithms use a two-phase clustering approach consisting of an initialization stage,a refinement stage,a cluster maintenance stage,and a final clustering stage.The density-based top-down subspace clustering approach is more widely used than the others because it is able to distinguish true clusters and outliers using projected microclusters.Most algorithms implicitly adapt to the evolving nature of the data stream by using a time fading function that is sensitive to outliers.Future work can focus on the clustering framework,parameter optimization,subspace search techniques,memory-efficient synopsis structures,explicit cluster change detection,and intrinsic performance metrics.This article can serve as a guide for researchers interested in high-dimensional subspace clustering methods for data streams.展开更多
Ephemeral and perennial streams of mountainous catchments in Sabaragamuwa Province of Sri Lanka and Hong Kong of China were studied for two years on vegetation dynamics.Each year,sampling was conducted during a period...Ephemeral and perennial streams of mountainous catchments in Sabaragamuwa Province of Sri Lanka and Hong Kong of China were studied for two years on vegetation dynamics.Each year,sampling was conducted during a period when ephemeral streams had low surface flows.Sampling was realized contiguously using belt transects.The standing crop biomass(hereafter biomass)of herbaceous vegetation in ephemeral channels was comparatively lower than perennials and so was the herb diversity.Herb diversity showed a peak from 1.5 to 4.5 m from the centerline/thalweg of ephemeral and perennial streams.Out of 24 herbs,only three were common for both.A peak herb biomass zone was observed in perennials in the same region where diversity peaked.In ephemerals,herb biomass increased laterally up to^1.5 m,and was constant thereafter.Seedling experiment results tallied with the field diversity observations of both stream types,and suggested that seed dispersion was the main reason for herb colonization.Furthermore,it showed sapling emergence to be significantly higher in perennials than ephemerals.Return period of annual maximum monthly rainfall was a strong indicator of age of trees in ephemeral streams,and elucidated the possibility of hindcasting past flow episodes.Electrical conductivity was significantly high in ephemeral streams among all the water quality parameters.The contents of the water nutrients were approximately the same in both stream types.While recommending further studies on eco-hydrology of ephemerals,we recognize ephemeral streams to be valuable references in climate change studies due to their responsiveness and representativeness in long term hydrological changes.展开更多
In this study conducted in the coastal zone of Cameroon, biological indices and functional feeding groups of benthic macroinvertebrates were used to assess the health status of two urban streams. For a better diagnosi...In this study conducted in the coastal zone of Cameroon, biological indices and functional feeding groups of benthic macroinvertebrates were used to assess the health status of two urban streams. For a better diagnosis, two streams located in coastal forest zone were used as a reference. Benthic macroinvertebrates were sampled monthly over a 3-month period (from May to July 2017) in six urban stations and six forest stations. Measurements of the physicochemical variables were done simultaneously. Physicochemical analysis revealed that urban streams are strongly polluted with high content of decaying organic matters, while forest streams are slightly polluted as indicated by the Principal Component Analysis. Concerning benthic macroinvertebrates, urban streams are poorly diversified with the proliferation of taxa tolerant to water pollution and belonging to the functional feeding groups of collectors-gatherers. Inversely, forest streams are more diversified and dominated by sensitive taxa, most belonging to the functional feeding groups of predators and shredders. These marked differences between biological indices and feeding mode of benthic macroinvertebrates in forest and urban rivers confirm the reliability of benthic macroinvertebrates as good indicators of freshwater ecosystem in the coastal zone of Cameroon.展开更多
The goal of this review paper is to provide a list of methods and devices used to measure sediment accumulation in wadeable streams dominated by cobble and gravel substrate. Quantitative measures of stream sedimentati...The goal of this review paper is to provide a list of methods and devices used to measure sediment accumulation in wadeable streams dominated by cobble and gravel substrate. Quantitative measures of stream sedimentation are useful to monitor and study anthropogenic impacts on stream biota, and stream sedimentation is measurable with multiple sampling methods. Evaluation of sedimentation can be made by measuring the concentration of suspended sediment, or turbidity, and by determining the amount of deposited sediment, or sedimentation on the streambed. Measurements of deposited sediments are more time consuming and labor intensive than measurements of suspended sediments. Traditional techniques for characterizing sediment composition in streams include core sampling, the shovel method, visual estimation along transects, and sediment traps. This paper provides a comprehensive review of methodology, devices that can be used, and techniques for processing and analyzing samples collected to aid researchers in choosing study design and equipment.展开更多
In the present paper it will be shown that, by taking the reference frame moving with the velocity of fluid at the interlace of two steady parallel streams, the laminar boundary layer flow in the two fluids can be dec...In the present paper it will be shown that, by taking the reference frame moving with the velocity of fluid at the interlace of two steady parallel streams, the laminar boundary layer flow in the two fluids can be decoupled into two flows. These are exactly the same as the laminar boundary layer flows along a flat plate. And that, by using the existing exact solution of the laminar boundary layer equation for the boundary layer flow along a flat plate and appropriate boundary conditions. An exact solution of the laminar boundary layer equation for the laminar boundary layer between two parallel streams with different densities,viscocities and velocities is given elegantly.For the cases considered by Lock, the results obtained by the present method are compared with Lock’s numerical calculations in detail.展开更多
文摘Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to time.The growing volume of tweets with sentiment drifts has led to the need for devising an adaptive approach to detect and handle this drift in real time.This work proposes an adap-tive learning algorithm-based framework,Twitter Sentiment Drift Analysis-Bidir-ectional Encoder Representations from Transformers(TSDA-BERT),which introduces a sentiment drift measure to detect drifts and a domain impact score to adaptively retrain the classification model with domain relevant data in real time.The framework also works on static data by converting them to data streams using the Kafka tool.The experiments conducted on real time and simulated tweets of sports,health care andfinancial topics show that the proposed system is able to detect sentiment drifts and maintain the performance of the classification model,with accuracies of 91%,87%and 90%,respectively.Though the results have been provided only for a few topics,as a proof of concept,this framework can be applied to detect sentiment drifts and perform sentiment classification on real time data streams of any topic.
文摘Clustering high dimensional data is challenging as data dimensionality increases the distance between data points,resulting in sparse regions that degrade clustering performance.Subspace clustering is a common approach for processing high-dimensional data by finding relevant features for each cluster in the data space.Subspace clustering methods extend traditional clustering to account for the constraints imposed by data streams.Data streams are not only high-dimensional,but also unbounded and evolving.This necessitates the development of subspace clustering algorithms that can handle high dimensionality and adapt to the unique characteristics of data streams.Although many articles have contributed to the literature review on data stream clustering,there is currently no specific review on subspace clustering algorithms in high-dimensional data streams.Therefore,this article aims to systematically review the existing literature on subspace clustering of data streams in high-dimensional streaming environments.The review follows a systematic methodological approach and includes 18 articles for the final analysis.The analysis focused on two research questions related to the general clustering process and dealing with the unbounded and evolving characteristics of data streams.The main findings relate to six elements:clustering process,cluster search,subspace search,synopsis structure,cluster maintenance,and evaluation measures.Most algorithms use a two-phase clustering approach consisting of an initialization stage,a refinement stage,a cluster maintenance stage,and a final clustering stage.The density-based top-down subspace clustering approach is more widely used than the others because it is able to distinguish true clusters and outliers using projected microclusters.Most algorithms implicitly adapt to the evolving nature of the data stream by using a time fading function that is sensitive to outliers.Future work can focus on the clustering framework,parameter optimization,subspace search techniques,memory-efficient synopsis structures,explicit cluster change detection,and intrinsic performance metrics.This article can serve as a guide for researchers interested in high-dimensional subspace clustering methods for data streams.
基金funded by the Research Grants Council Fund of Hong Kong(Project number:Poly U152161/14E)Environment and Conservation Fund,Hong Kong(Project number:39/2011)。
文摘Ephemeral and perennial streams of mountainous catchments in Sabaragamuwa Province of Sri Lanka and Hong Kong of China were studied for two years on vegetation dynamics.Each year,sampling was conducted during a period when ephemeral streams had low surface flows.Sampling was realized contiguously using belt transects.The standing crop biomass(hereafter biomass)of herbaceous vegetation in ephemeral channels was comparatively lower than perennials and so was the herb diversity.Herb diversity showed a peak from 1.5 to 4.5 m from the centerline/thalweg of ephemeral and perennial streams.Out of 24 herbs,only three were common for both.A peak herb biomass zone was observed in perennials in the same region where diversity peaked.In ephemerals,herb biomass increased laterally up to^1.5 m,and was constant thereafter.Seedling experiment results tallied with the field diversity observations of both stream types,and suggested that seed dispersion was the main reason for herb colonization.Furthermore,it showed sapling emergence to be significantly higher in perennials than ephemerals.Return period of annual maximum monthly rainfall was a strong indicator of age of trees in ephemeral streams,and elucidated the possibility of hindcasting past flow episodes.Electrical conductivity was significantly high in ephemeral streams among all the water quality parameters.The contents of the water nutrients were approximately the same in both stream types.While recommending further studies on eco-hydrology of ephemerals,we recognize ephemeral streams to be valuable references in climate change studies due to their responsiveness and representativeness in long term hydrological changes.
文摘In this study conducted in the coastal zone of Cameroon, biological indices and functional feeding groups of benthic macroinvertebrates were used to assess the health status of two urban streams. For a better diagnosis, two streams located in coastal forest zone were used as a reference. Benthic macroinvertebrates were sampled monthly over a 3-month period (from May to July 2017) in six urban stations and six forest stations. Measurements of the physicochemical variables were done simultaneously. Physicochemical analysis revealed that urban streams are strongly polluted with high content of decaying organic matters, while forest streams are slightly polluted as indicated by the Principal Component Analysis. Concerning benthic macroinvertebrates, urban streams are poorly diversified with the proliferation of taxa tolerant to water pollution and belonging to the functional feeding groups of collectors-gatherers. Inversely, forest streams are more diversified and dominated by sensitive taxa, most belonging to the functional feeding groups of predators and shredders. These marked differences between biological indices and feeding mode of benthic macroinvertebrates in forest and urban rivers confirm the reliability of benthic macroinvertebrates as good indicators of freshwater ecosystem in the coastal zone of Cameroon.
文摘The goal of this review paper is to provide a list of methods and devices used to measure sediment accumulation in wadeable streams dominated by cobble and gravel substrate. Quantitative measures of stream sedimentation are useful to monitor and study anthropogenic impacts on stream biota, and stream sedimentation is measurable with multiple sampling methods. Evaluation of sedimentation can be made by measuring the concentration of suspended sediment, or turbidity, and by determining the amount of deposited sediment, or sedimentation on the streambed. Measurements of deposited sediments are more time consuming and labor intensive than measurements of suspended sediments. Traditional techniques for characterizing sediment composition in streams include core sampling, the shovel method, visual estimation along transects, and sediment traps. This paper provides a comprehensive review of methodology, devices that can be used, and techniques for processing and analyzing samples collected to aid researchers in choosing study design and equipment.
文摘In the present paper it will be shown that, by taking the reference frame moving with the velocity of fluid at the interlace of two steady parallel streams, the laminar boundary layer flow in the two fluids can be decoupled into two flows. These are exactly the same as the laminar boundary layer flows along a flat plate. And that, by using the existing exact solution of the laminar boundary layer equation for the boundary layer flow along a flat plate and appropriate boundary conditions. An exact solution of the laminar boundary layer equation for the laminar boundary layer between two parallel streams with different densities,viscocities and velocities is given elegantly.For the cases considered by Lock, the results obtained by the present method are compared with Lock’s numerical calculations in detail.
