In the Fog of Sino-foreign Cooperative Education With the rapid development of Sinoforeig n coop erat ive e ducat ion,t here are various projects have attracted the attention of students and their parents before filin...In the Fog of Sino-foreign Cooperative Education With the rapid development of Sinoforeig n coop erat ive e ducat ion,t here are various projects have attracted the attention of students and their parents before filing the intention for uniersities.How to make right choices to prevent an awkward sitution for the student that not only failed to build a solid academic foundation but spoke poor English?展开更多
Identification of bird species from their sounds has become an important area in biodiversity-related research due to the relative ease of capturing bird sounds in the commonly challenging habitat. Audio features have...Identification of bird species from their sounds has become an important area in biodiversity-related research due to the relative ease of capturing bird sounds in the commonly challenging habitat. Audio features have a massive impact on the classification task since they are the fundamental elements used to differentiate classes. As such, the extraction of informative properties of the data is a crucial stage of any classification-based application. Therefore, it is vital to identify the most significant feature to represent the actual bird sounds. In this paper, we propose a novel feature that can advance classification accuracy with modified features, which are most suitable for classifying birds from its audio sounds. Modified Gammatone frequency cepstral coefficient(GTCC) features have been extracted with their frequency banks adjusted to suit bird sounds. The features are then used to train and test a support vector machine(SVM) classifier. It has been shown that the modified GTCC features are able to give 86% accuracy with twenty Bornean birds. Furthermore, in this paper, we are proposing a novel probability enhanced entropy(PEE) feature, which, when combined with the modified GTCC features, is able to improve accuracy further to 89.5%. These results are significant as the relatively low-resource intensive SVM with the proposed modified GTCC, and the proposed novel PEE feature can be implemented in a real-time system to assist researchers,scientists, conservationists, and even eco-tourists in identifying bird species in the dense forest.展开更多
电力系统中的故障形式复杂多变 ,为了正确地对继保设备进行整定工作 ,正确和快速地计算出短路电流和线路的分支系数显得十分重要。文章介绍了一个将基于 PSS/E(Power system simulator for Engineering)软件包的开发方法应用于分支系数...电力系统中的故障形式复杂多变 ,为了正确地对继保设备进行整定工作 ,正确和快速地计算出短路电流和线路的分支系数显得十分重要。文章介绍了一个将基于 PSS/E(Power system simulator for Engineering)软件包的开发方法应用于分支系数和短路电流的新方式 ,它充分利用了PSS/E的计算引擎 ,可以根据电网结构自动地进行计算并通过比较不同的故障类型产生的数据得到最大。展开更多
Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that th...Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.展开更多
文摘In the Fog of Sino-foreign Cooperative Education With the rapid development of Sinoforeig n coop erat ive e ducat ion,t here are various projects have attracted the attention of students and their parents before filing the intention for uniersities.How to make right choices to prevent an awkward sitution for the student that not only failed to build a solid academic foundation but spoke poor English?
文摘Identification of bird species from their sounds has become an important area in biodiversity-related research due to the relative ease of capturing bird sounds in the commonly challenging habitat. Audio features have a massive impact on the classification task since they are the fundamental elements used to differentiate classes. As such, the extraction of informative properties of the data is a crucial stage of any classification-based application. Therefore, it is vital to identify the most significant feature to represent the actual bird sounds. In this paper, we propose a novel feature that can advance classification accuracy with modified features, which are most suitable for classifying birds from its audio sounds. Modified Gammatone frequency cepstral coefficient(GTCC) features have been extracted with their frequency banks adjusted to suit bird sounds. The features are then used to train and test a support vector machine(SVM) classifier. It has been shown that the modified GTCC features are able to give 86% accuracy with twenty Bornean birds. Furthermore, in this paper, we are proposing a novel probability enhanced entropy(PEE) feature, which, when combined with the modified GTCC features, is able to improve accuracy further to 89.5%. These results are significant as the relatively low-resource intensive SVM with the proposed modified GTCC, and the proposed novel PEE feature can be implemented in a real-time system to assist researchers,scientists, conservationists, and even eco-tourists in identifying bird species in the dense forest.
文摘电力系统中的故障形式复杂多变 ,为了正确地对继保设备进行整定工作 ,正确和快速地计算出短路电流和线路的分支系数显得十分重要。文章介绍了一个将基于 PSS/E(Power system simulator for Engineering)软件包的开发方法应用于分支系数和短路电流的新方式 ,它充分利用了PSS/E的计算引擎 ,可以根据电网结构自动地进行计算并通过比较不同的故障类型产生的数据得到最大。
基金supported by MOST under Grants No.107-2221-E-845-002-MY3 and No.110-2221-E-845-002-。
文摘Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.
