The growth habit of the basic magnesium oxysulfate whisker was investigated based on the theoreticalmodelof anion coordination polyhedron growth units.It is found that typicalbasic magnesium oxysulfate whisker growth ...The growth habit of the basic magnesium oxysulfate whisker was investigated based on the theoreticalmodelof anion coordination polyhedron growth units.It is found that typicalbasic magnesium oxysulfate whisker growth is consistent with anion tetrahedralcoordination incorporation rules.The growth units of basic magnesium oxysulfate whiskers are [Mg-（OH）_4]^（2-） and HSO_4^-.[Mg-（OH）_4]^（2-） is the favorable growth unit and whisker growth is in the direction of the [Mg-（OH）_4]^（2-） combination.A plurality of [Mg-（OH）_4]^（2-） s combine and become a larger dimensionalgrowth unit in a one-dimensionaldirection.Then HSO_4^- and larger dimensionalgrowth units connect as basic magnesium sulfate whiskers,according to the structuralcharacteristics of the basic magnesium sulfate whisker,which can guide the synthesis of magnesium hydroxide whisker.展开更多
Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency a...Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency and some of its phonological, morphological, and orthographic features challenge the development and initiatives in the area of ASR. By considering these challenges, this study is the first endeavor, which analyzed the characteristics of the language, prepared speech corpus, and developed different ASR systems. A small 3-hour read speech corpus was prepared and transcribed. Different basic and rounded phone unit-based speech recognizers were explored using multilingual deep neural network (DNN) modeling methods. The experimental results demonstrated that all the basic phone and rounded phone unit-based multilingual models outperformed the corresponding unilingual models with the relative performance improvements of 5.47% to 19.87% and 5.74% to 16.77%, respectively. The rounded phone unit-based multilingual models outperformed the equivalent basic phone unit-based models with relative performance improvements of 0.95% to 4.98%. Overall, we discovered that multilingual DNN modeling methods are profoundly effective to develop Chaha speech recognizers. Both the basic and rounded phone acoustic units are convenient to build Chaha ASR system. However, the rounded phone unit-based models are superior in performance and faster in recognition speed over the corresponding basic phone unit-based models. Hence, the rounded phone units are the most suitable acoustic units to develop Chaha ASR systems.展开更多
针对目前尚未深入研究多视点视频编码(Multi-view Video Coding,MVC)码率控制的问题,提出了一种基于相关性分析的多视点视频编码码率控制算法。该算法的核心是先根据视差预测和运动预测的结构关系,将所有图像分成6种类型的编码帧,并改...针对目前尚未深入研究多视点视频编码(Multi-view Video Coding,MVC)码率控制的问题,提出了一种基于相关性分析的多视点视频编码码率控制算法。该算法的核心是先根据视差预测和运动预测的结构关系,将所有图像分成6种类型的编码帧,并改进二项式率失真模型,然后根据多视点视频相关性分析在各个视点之间进行合理的码率分配,将码率控制分成4层结构进行多视点视频编码的码率控制。其中,帧层码率控制考虑分层B帧等因素分配码率,基本单元层码率控制根据宏块的内容复杂度采用不同的量化参数。实验结果表明该码率控制算法实际码率与目标码率平均误差能控制0.6%。展开更多
基金Funded by the National Natural Science Foundation of China(No.51272207)
文摘The growth habit of the basic magnesium oxysulfate whisker was investigated based on the theoreticalmodelof anion coordination polyhedron growth units.It is found that typicalbasic magnesium oxysulfate whisker growth is consistent with anion tetrahedralcoordination incorporation rules.The growth units of basic magnesium oxysulfate whiskers are [Mg-（OH）_4]^（2-） and HSO_4^-.[Mg-（OH）_4]^（2-） is the favorable growth unit and whisker growth is in the direction of the [Mg-（OH）_4]^（2-） combination.A plurality of [Mg-（OH）_4]^（2-） s combine and become a larger dimensionalgrowth unit in a one-dimensionaldirection.Then HSO_4^- and larger dimensionalgrowth units connect as basic magnesium sulfate whiskers,according to the structuralcharacteristics of the basic magnesium sulfate whisker,which can guide the synthesis of magnesium hydroxide whisker.
文摘Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency and some of its phonological, morphological, and orthographic features challenge the development and initiatives in the area of ASR. By considering these challenges, this study is the first endeavor, which analyzed the characteristics of the language, prepared speech corpus, and developed different ASR systems. A small 3-hour read speech corpus was prepared and transcribed. Different basic and rounded phone unit-based speech recognizers were explored using multilingual deep neural network (DNN) modeling methods. The experimental results demonstrated that all the basic phone and rounded phone unit-based multilingual models outperformed the corresponding unilingual models with the relative performance improvements of 5.47% to 19.87% and 5.74% to 16.77%, respectively. The rounded phone unit-based multilingual models outperformed the equivalent basic phone unit-based models with relative performance improvements of 0.95% to 4.98%. Overall, we discovered that multilingual DNN modeling methods are profoundly effective to develop Chaha speech recognizers. Both the basic and rounded phone acoustic units are convenient to build Chaha ASR system. However, the rounded phone unit-based models are superior in performance and faster in recognition speed over the corresponding basic phone unit-based models. Hence, the rounded phone units are the most suitable acoustic units to develop Chaha ASR systems.
文摘针对目前尚未深入研究多视点视频编码(Multi-view Video Coding,MVC)码率控制的问题,提出了一种基于相关性分析的多视点视频编码码率控制算法。该算法的核心是先根据视差预测和运动预测的结构关系,将所有图像分成6种类型的编码帧,并改进二项式率失真模型,然后根据多视点视频相关性分析在各个视点之间进行合理的码率分配,将码率控制分成4层结构进行多视点视频编码的码率控制。其中,帧层码率控制考虑分层B帧等因素分配码率,基本单元层码率控制根据宏块的内容复杂度采用不同的量化参数。实验结果表明该码率控制算法实际码率与目标码率平均误差能控制0.6%。
