Most of forest birds have the characteristics for habitat selection. The purpose of this study is to clarify the vegetation structure in breeding area of Siberian rubythroat (Luscinia calliope). In Daecheongbong peak,...Most of forest birds have the characteristics for habitat selection. The purpose of this study is to clarify the vegetation structure in breeding area of Siberian rubythroat (Luscinia calliope). In Daecheongbong peak, Mt. Seoraksan national park, South Korea from May to August, 2001, breeding population of Siberian rubythroat and the dominant species in breeding area of Siberian rubythroat (Luscinia calliope) were surveyed by line transect method along the ridge in the Daecheongbong peak area. Number of individuals and location of song posts were observed and recorded. According to the survey results, the study area was classified into high, middle and low density areas. Those birds selected the forest area of dominant species for Ermans birch and dwarf Siberian pine as habitat and preferred the shrubs area with the lower height and higher coverage.展开更多
Multi-component signals contain multiple signal parts expressed in the same physical modality. One way to identify individual components is if they are produced by different physical mechanisms. Here, I studied the me...Multi-component signals contain multiple signal parts expressed in the same physical modality. One way to identify individual components is if they are produced by different physical mechanisms. Here, I studied the mechanisms generating acoustic signals in the courtship displays of the Calliope hummingbird Stellula calliope. Display dives consisted of three synchronized sound elements, a high-frequency tone （hfl）, a low frequency tone （lft）, and atonal sound pulses （asp）, which were then followed by a frequency-modulated fall. Manipulating any of the rectrices （tail-feathers） of wild males impaired production of the lft and asp but not the hfl or fall, which are apparently vocal. I tested the sound production capabilities of the rectrices in a wind tunnel. Single rectrices could generate the lft but not the asp, whereas multiple rectrices tested together produced sounds sitlfilar to the asp when they fluttered and collided with their neighbors percussively, representing a previously unknown mechanism of sound production. During the shuttle display, a trill is generated by the wings during pulses in which the wingbeat frequency is elevated to 95 Hz, 40% higher than the typical hovering wingbeat frequency. The Calliope hummingbird courtship displays include sounds produced by three independent mechanisms, and thus include a minimum of three acoustic signal components. These acoustic mechanisms have different constraints and thus potentially contain different messages. Producing multiple acoustic signals via multiple mechanisms may be a way to escape the constraints present in any single mechanism .展开更多
Background Data-driven event analysis has gradually become the backbone of modern competitive sports analysis. Competitive sports data analysis tasks increasingly use computer vision and machine-learning models for in...Background Data-driven event analysis has gradually become the backbone of modern competitive sports analysis. Competitive sports data analysis tasks increasingly use computer vision and machine-learning models for intelligent data analysis. Existing sports visualization systems focus on the player–team data visualization, which is not intuitive enough for team season win–loss data and game time-series data visualization and neglects the prediction of all-star players. Methods This study used an interactive visualization system designed with parallel aggregated ordered hypergraph dynamic hypergraphs, Calliope visualization data story technology,and i Storyline narrative visualization technology to visualize the regular statistics and game time data of players and teams. NPIPVis includes dynamic hypergraphs of a team’s wins and losses and game plot narrative visualization components. In addition, an integrated learning-based all-star player prediction model, SRR-voting, which starts from the existing minority and majority samples, was proposed using the synthetic minority oversampling technique and Random Under Sampler methods to generate and eliminate samples of a certain size to balance the number of allstar and average players in the datasets. Next, a random forest algorithm was introduced to extract and construct the features of players and combined with the voting integrated model to predict the all-star players, using GridSearch CV, to optimize the hyperparameters of each model in integrated learning and then combined with five-fold cross-validation to improve the generalization ability of the model. Finally, the SHapley Additive ex Planations(SHAP) model was introduced to enhance the interpretability of the model. Results The experimental results of comparing the SRR-voting model with six common models show that the accuracy, F1-score, and recall metrics are significantly improved, which verifies the effectiveness and practicality of the SRR-voting model. Conclusions This study combines data visualization and machine learning to design a National Basketball Association data visualization system to help the general audience visualize game data and predict all-star players;this can also be extended to other sports events or related fields.展开更多
基金This paper was supported by Korea Science and Engineering Foundation (KOSEF No. 2000-2-51300-002-3).
文摘Most of forest birds have the characteristics for habitat selection. The purpose of this study is to clarify the vegetation structure in breeding area of Siberian rubythroat (Luscinia calliope). In Daecheongbong peak, Mt. Seoraksan national park, South Korea from May to August, 2001, breeding population of Siberian rubythroat and the dominant species in breeding area of Siberian rubythroat (Luscinia calliope) were surveyed by line transect method along the ridge in the Daecheongbong peak area. Number of individuals and location of song posts were observed and recorded. According to the survey results, the study area was classified into high, middle and low density areas. Those birds selected the forest area of dominant species for Ermans birch and dwarf Siberian pine as habitat and preferred the shrubs area with the lower height and higher coverage.
基金Acknowledgments I thank S. Weinstein, A. Varma, and T. Feo for assistance in the field L. Benedict and T. Libby for use of equipment, J. Brown for accommodations, and G. Weston-Murphy for assistance with the wind tunnel. Walter Nussbaumer kindly allowed use of a photo. The manuscript was improved by comments from T. Feo and two anonymous reviewers. The research was supported by the MVZ and National Science Foundation IOS-090353 to R. Prum.
文摘Multi-component signals contain multiple signal parts expressed in the same physical modality. One way to identify individual components is if they are produced by different physical mechanisms. Here, I studied the mechanisms generating acoustic signals in the courtship displays of the Calliope hummingbird Stellula calliope. Display dives consisted of three synchronized sound elements, a high-frequency tone （hfl）, a low frequency tone （lft）, and atonal sound pulses （asp）, which were then followed by a frequency-modulated fall. Manipulating any of the rectrices （tail-feathers） of wild males impaired production of the lft and asp but not the hfl or fall, which are apparently vocal. I tested the sound production capabilities of the rectrices in a wind tunnel. Single rectrices could generate the lft but not the asp, whereas multiple rectrices tested together produced sounds sitlfilar to the asp when they fluttered and collided with their neighbors percussively, representing a previously unknown mechanism of sound production. During the shuttle display, a trill is generated by the wings during pulses in which the wingbeat frequency is elevated to 95 Hz, 40% higher than the typical hovering wingbeat frequency. The Calliope hummingbird courtship displays include sounds produced by three independent mechanisms, and thus include a minimum of three acoustic signal components. These acoustic mechanisms have different constraints and thus potentially contain different messages. Producing multiple acoustic signals via multiple mechanisms may be a way to escape the constraints present in any single mechanism .
基金Supported by the National Natural Science Foundation of China(61862018)the Subject of the Training Plan for Thousands of Young and Middle-aged Backbone Teachers in Guangxi Colleges and Universities(2020QGRW017)。
文摘Background Data-driven event analysis has gradually become the backbone of modern competitive sports analysis. Competitive sports data analysis tasks increasingly use computer vision and machine-learning models for intelligent data analysis. Existing sports visualization systems focus on the player–team data visualization, which is not intuitive enough for team season win–loss data and game time-series data visualization and neglects the prediction of all-star players. Methods This study used an interactive visualization system designed with parallel aggregated ordered hypergraph dynamic hypergraphs, Calliope visualization data story technology,and i Storyline narrative visualization technology to visualize the regular statistics and game time data of players and teams. NPIPVis includes dynamic hypergraphs of a team’s wins and losses and game plot narrative visualization components. In addition, an integrated learning-based all-star player prediction model, SRR-voting, which starts from the existing minority and majority samples, was proposed using the synthetic minority oversampling technique and Random Under Sampler methods to generate and eliminate samples of a certain size to balance the number of allstar and average players in the datasets. Next, a random forest algorithm was introduced to extract and construct the features of players and combined with the voting integrated model to predict the all-star players, using GridSearch CV, to optimize the hyperparameters of each model in integrated learning and then combined with five-fold cross-validation to improve the generalization ability of the model. Finally, the SHapley Additive ex Planations(SHAP) model was introduced to enhance the interpretability of the model. Results The experimental results of comparing the SRR-voting model with six common models show that the accuracy, F1-score, and recall metrics are significantly improved, which verifies the effectiveness and practicality of the SRR-voting model. Conclusions This study combines data visualization and machine learning to design a National Basketball Association data visualization system to help the general audience visualize game data and predict all-star players;this can also be extended to other sports events or related fields.
