Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions i...Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.展开更多
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
Cryogenic block streams consist of a stream of rocks superficially resembling a stream deposit but lacking a matrix, usually occurring on a valley or gully floor or on slopes that are less steep than the maximum angle...Cryogenic block streams consist of a stream of rocks superficially resembling a stream deposit but lacking a matrix, usually occurring on a valley or gully floor or on slopes that are less steep than the maximum angle of repose of coarse sediments. They are usually formed on perennially frozen ground, but can also occur as relict landforms. There are three main active kinds forming today, viz., Siberian and Tibetan dynamic rock streams and lag block streams. During their formation, the blocks in the active Siberian and Tibetan dynamic block streams move downslope at up to 1 rn/a. They are forming today on the Tibetan Plateau and in the more arid parts of south-central Siberia, although the processes involved in the movement are different. In the case of the Tibetan type, individual blocks slide downslope over the substrate in winter on an icy coating in areas of minimal winter precipitation. The Siberian type develops in areas of 15-80 cm of winter snow cover and an MAAT (mean annual air temperature) of-4 ~C to -17 ~C. The movement is due to creep of snow and ice and collapse of the blocks downslope during thawing. Lag block streams are formed by meltwater flowing over the surface of sediment consisting primarily of larger blocks with a limited amount of interstitial sediment. The erosion of the matrix is primarily in the spring in areas of higher winter precipitation on 10^-30~ slopes. The blocks remain stationary, but the interstitial sediment is washed out by strong seasonal flows of meltwater or rain to form an alluvial fan. The boulders undergo weathering and become more rounded in the process. Lag block streams can also develop without the presence of permafrost in areas with cold climates or glaciers. Block streams also occur as relict deposits in older deposits under various climatic regimes that are unsuitable for their formation today. An example of relict lag block streams with subangular to subrounded blocks occurs in gullies on the forested mountainsides at Felsen in Germany, and is the original "felsenmeer". Similar examples occur near Vitosha Mountain in Bulgaria. The "stone runs" in the Falkland Islands are examples of the more angular relict lag block streams. In both Tasmania and the Falkland Islands, they mask a more complex history, the underlying soils indicating periods of tropical and temperate soil formation resulting from weathering during and since the Tertiary Period. Block streams have also been reported from beneath cold-based glaciers in Sweden, and below till in Canada, and when ex- humed, can continue to develop.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
The phytic acid contents of eight fractions of wheat flours from different mill streams and those in wheat brans, which were separated by different sieves into various sizes, were determined and analyzed. A rapid meth...The phytic acid contents of eight fractions of wheat flours from different mill streams and those in wheat brans, which were separated by different sieves into various sizes, were determined and analyzed. A rapid method for phytic acid assay by adding thioglycolic acid (mercapto acetic acid) with 2,2-bipyridine was used, with an acidic iron-Ⅲ-solution of known iron content. The amount ofphytate was indicated by the decrease in iron in the supernatant. Significant differences were observed in phytic acid content among different milling streams and different cultivars (P〈0.05). On an average, coarse bran had the highest phytic acid content (53.85 mg g^-1), and the shorts had 28.48 mg g^-1. The B5 break flour had a higher phytic acid content (4.8 mg g^-1) than the B7 (2.75 mg g^-1) and B8 (2.03 mg g^-1) reduction flours. Lower values were found in the B3, B6 and B7 flours (1.07, 0.79, and 0.76 mg g^-1, respectively). The phytic acid contents of bran decreased with smaller bran sizes, ranging from 54 to 5.09 mg g^-1.展开更多
Objective To compare the bacterioplankton communities in streams exposed to pollution of different types. Methods The bacterioplankton communities in three selected heavily polluted streams were investigated by using ...Objective To compare the bacterioplankton communities in streams exposed to pollution of different types. Methods The bacterioplankton communities in three selected heavily polluted streams were investigated by using terminal‐restriction fragment length polymorphism (T‐RFLP) analysis in combination with 16S rRNA gene clone library analysis. Results Both T‐RFLP and 16S rRNA gene clone library revealed a great difference in bacterioplankton community composition in the different streams. Conclusion This work might provide some new insights into bioremediation of heavily polluted streams.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
文摘Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.
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Cryogenic block streams consist of a stream of rocks superficially resembling a stream deposit but lacking a matrix, usually occurring on a valley or gully floor or on slopes that are less steep than the maximum angle of repose of coarse sediments. They are usually formed on perennially frozen ground, but can also occur as relict landforms. There are three main active kinds forming today, viz., Siberian and Tibetan dynamic rock streams and lag block streams. During their formation, the blocks in the active Siberian and Tibetan dynamic block streams move downslope at up to 1 rn/a. They are forming today on the Tibetan Plateau and in the more arid parts of south-central Siberia, although the processes involved in the movement are different. In the case of the Tibetan type, individual blocks slide downslope over the substrate in winter on an icy coating in areas of minimal winter precipitation. The Siberian type develops in areas of 15-80 cm of winter snow cover and an MAAT (mean annual air temperature) of-4 ~C to -17 ~C. The movement is due to creep of snow and ice and collapse of the blocks downslope during thawing. Lag block streams are formed by meltwater flowing over the surface of sediment consisting primarily of larger blocks with a limited amount of interstitial sediment. The erosion of the matrix is primarily in the spring in areas of higher winter precipitation on 10^-30~ slopes. The blocks remain stationary, but the interstitial sediment is washed out by strong seasonal flows of meltwater or rain to form an alluvial fan. The boulders undergo weathering and become more rounded in the process. Lag block streams can also develop without the presence of permafrost in areas with cold climates or glaciers. Block streams also occur as relict deposits in older deposits under various climatic regimes that are unsuitable for their formation today. An example of relict lag block streams with subangular to subrounded blocks occurs in gullies on the forested mountainsides at Felsen in Germany, and is the original "felsenmeer". Similar examples occur near Vitosha Mountain in Bulgaria. The "stone runs" in the Falkland Islands are examples of the more angular relict lag block streams. In both Tasmania and the Falkland Islands, they mask a more complex history, the underlying soils indicating periods of tropical and temperate soil formation resulting from weathering during and since the Tertiary Period. Block streams have also been reported from beneath cold-based glaciers in Sweden, and below till in Canada, and when ex- humed, can continue to develop.
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.
基金support was provided bythe National Basic Research Program of China (973Program, 2009CB118301)the National Natural Sci-ence Foundation of ChinaNational High-Tech R&D Program of China (863 Program, 2006AA10Z1E9)
文摘The phytic acid contents of eight fractions of wheat flours from different mill streams and those in wheat brans, which were separated by different sieves into various sizes, were determined and analyzed. A rapid method for phytic acid assay by adding thioglycolic acid (mercapto acetic acid) with 2,2-bipyridine was used, with an acidic iron-Ⅲ-solution of known iron content. The amount ofphytate was indicated by the decrease in iron in the supernatant. Significant differences were observed in phytic acid content among different milling streams and different cultivars (P〈0.05). On an average, coarse bran had the highest phytic acid content (53.85 mg g^-1), and the shorts had 28.48 mg g^-1. The B5 break flour had a higher phytic acid content (4.8 mg g^-1) than the B7 (2.75 mg g^-1) and B8 (2.03 mg g^-1) reduction flours. Lower values were found in the B3, B6 and B7 flours (1.07, 0.79, and 0.76 mg g^-1, respectively). The phytic acid contents of bran decreased with smaller bran sizes, ranging from 54 to 5.09 mg g^-1.
基金supported by the Research Fund from China Priority Scientific Research Project for Water Pollution Control and Treatment (No. 2008ZX07526‐001‐004)
文摘Objective To compare the bacterioplankton communities in streams exposed to pollution of different types. Methods The bacterioplankton communities in three selected heavily polluted streams were investigated by using terminal‐restriction fragment length polymorphism (T‐RFLP) analysis in combination with 16S rRNA gene clone library analysis. Results Both T‐RFLP and 16S rRNA gene clone library revealed a great difference in bacterioplankton community composition in the different streams. Conclusion This work might provide some new insights into bioremediation of heavily polluted streams.
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.