多用途放射性废物焚烧系统工程验证试验

对建立的多用途放射性废物焚烧系统，进行了工程验证试验。试验主要包括固体废物（包括树脂）和废油焚烧及烟气净化时系统的性能测定、非放示踪试验、72h连续运行考验等。经过共计500多小时的试验，验证了工艺流程、主要设备结构、仪表测控及系统安全等设计的可行性和可靠性；系统运行平稳，设备及仪表工作正常。本系统可一炉多用，其处理能力、减容系数、焚烧灰中残炭率以及系统总去污系数等指标，均达到了设计要求。     

时间Petri网与CAGA算法相结合的并行测试研究

在并行测试的研究中对于任务的测试次序一直是个研究重点及难题。用时间Petri网建立关于并行测试系统的模型,并首次用元胞遗传算法(CAGA)对模型中的变迁序列进行搜索,快速得到最好的测试序列。通过仿真结果表明,该算法展示了很好的收敛效果,并且与已有的研究成果相比更具优势。     

塔架式抽油机的远程控制系统

针对传统的抽油机远程控制系统存在的弊端,提出了新型的控制层结构,设计了三层架构的远程控制系统;设计即时通信系统应用于远程控制系统中,详细地分析其服务器、电脑客户端和移动客户端的构架,实现管理层和控制层之间的信息交互;设计了基于WiFi的网络通信模块与上位机进行通信,介绍远程控制终端的核心控制模块,实现对电机的控制。经过测试,系统具有即时性、高可靠性以及快速性,确保对抽油机的有效控制,具有一定的工业价值和推广价值。     

一种改进的ViBe目标检测算法

现有ViBe目标检测算法存在误检率高,得到的结果噪声较大的问题。为此本文提出了一种将判定阈值自适应规则与优化结果反馈机制相结合的改进算法。该算法首先使用样本自身统计值作为阈值进行目标检测;接着对检测结果进行去噪、形态学处理等优化处理;最后将优化后的检测结果反馈给背景模型更新过程使检测更精确。与传统的ViBe算法相比,本文算法可更精确的提取出运动目标,误判率低,过检率较原始算法降低10%-20%。实验结果证明了该算法的有效性。     

基于TMS320C6678的多核程序加载研究与实现

针对多核D SP系统程序加载复杂的问题,基于T MS320C6678对多核程序加载进行了研究与设计。从一级引导程序出发,设计并优化了多核程序内容存储格式。设计了简洁的二级引导程序,以修正一级引导程序只识别主核程序入口地址,而从核入口地址缺失的现象。为了快速生成特定格式的多核程序内容,设计了多个工具用于添加S PI启动参数表、DDR3启动表、从核程序入口地址以及完成程序内容格式的转换。实现了S PI Flash多核程序加载以及基于I2C主模式的Nand Flash多核程序加载。     

一种基于FPGA的实时NPR系统

在进行非真实感渲染(NPR)处理时需要大量的计算,这对高帧率、高分辨率的视频做实时的NPR渲染是一个难题。根据FPGA以并行运算为主的特点,对传统的NPR算法做了改进和简化,最终设计了一种基于FPGA的实时NPR系统。实验结果表明,该系统对高帧率、高分辨率的视频做实时NPR处理具有运算速度快、系统稳定等特点,同时还具有体积小、便于携带等优点。     

High quality voice conversion using prosodic and high-resolution spectral features

Voice conversion methods have advanced rapidly over the last decade. Studies have shown that speaker characteristics are captured by spectral feature as well as various prosodic features. Most existing conversion methods focus on the spectral feature as it directly represents the timbre characteristics, while some conversion methods have focused only on the prosodic feature represented by the fundamental frequency. In this paper, a comprehensive framework using deep neural networks to convert both timbre and prosodic features is proposed. The timbre feature is represented by a high-resolution spectral feature. The prosodic features include F0, intensity and duration. It is well known that DNN is useful as a tool to model high-dimensional features. In this work, we show that DNN initialized by our proposed autoencoder pretraining yields good quality DNN conversion models. This pretraining is tailor-made for voice conversion and leverages on autoencoder to capture the generic spectral shape of source speech. Additionally, our framework uses segmental DNN models to capture the evolution of the prosodic features over time. To reconstruct the converted speech, the spectral feature produced by the DNN model is combined with the three prosodic features produced by the DNN segmental models. Our experimental results show that the application of both prosodic and high-resolution spectral features leads to quality converted speech as measured by objective evaluation and subjective listening tests.     

图谱法脑部MRI图像自动分割技术发展及应用

脑部MRI图像自动分割是计算机技术运用于医学上的一个典 型工作,脑部图像分割技术对于人类研究脑部疾病具有重要意义。虽然有一些非常广泛应用 的图像分割方法,如阈值法、区域增长法、聚类法等,但在脑部MRI图像分割中,这些方法 都 没有图谱法具有更为实际的医学研究与临床价值。本文回顾了脑部图像配准、分割的发展历 程,介绍了图谱分割算法的发展及基本原理,以及当前比较前沿的多图谱分割系统的组成和 应用。最后本文对图谱法脑部自动分割在实际临床医学中的应用前景作了总结和展望。     

Modeling sediment resuspension and transport induced by storm wind in Apalachicola Bay, USA

Sediment is an important environmental factor for aquatic ecosystem and oyster productivities of Apalachicola Bay located in Florida, USA. Based on the data analysis in this study, surface wind speed is highly correlated to the turbidity of water column, which results from sediment resuspension and transport in the Apalachicola Bay. In this paper, an application of a 3D sediment transport model to predict the wind-induced sediment transport in Apalachicola Bay is described. The sediment model is coupled with a 3D hydrodynamic module in the Environmental Fluid Dynamics Code (EFDC) model that provides information on estuarine circulation and salinity transport under normal temperature conditions. The hydrodynamic model was calibrated with field observations of water levels and salinity. The sediment transport model solves the transport equation with sources and sinks terms to describe sediment deposition and resuspension. The coupled hydrodynamic and sediment transport models were used to investigate wind-induced total suspended sediments (TSS) resuspension and transport in the bay. For the period June 1–July 30, 2005 two storm events with strong winds gave model results of TSS concentrations that compared well with the field observations. Model simulations reasonably reproduce the sudden increase of sediment concentrations during the storm events. Maximum sediment concentrations in the bay during the two storm events were 10 times or more than those in the pre-storm conditions. Spatial sediment transport from model simulations indicate active sediment resuspension and transport near areas of highly productive oyster beds. The model predictions of TSS and salinity can be used as inputs to an oyster dynamic model (Wang, H., Huang, W., Harwell, M., Edmiston, L., Johnson, E., Hsieh, P., Milla, K., Christensen, J., Stewart, J., Liu, X., 2008. Modeling eastern oyster population dynamics in response to changing environment in Apalachicola Bay, Florida. Journal of Ecological Modeling 211, 77–89) to support the ecological study of oyster growth and mortality in the aquatic ecosystem of Apalachicola Bay.     

虚拟惯量控制响应延时对控制效果的影响分析

电力电子接口电源通过虚拟惯量控制模拟同步机惯量响应,但控制过程存在响应延时。全面分析了延时对虚拟惯量控制效果的影响,发现延时并非越小越好。虚拟惯量控制可以降低频率变化率和最大频差两个指标。响应延时增大,扰动后短时间内平均频率变化率变大,但是,最大频差先下降后上升,并在某个延时取值处获得最优值。而且延时增大时调频功率峰值和能量峰值均降低,控制成本更小。虚拟惯量控制的目标不同时,对延时的要求不同。分析结论有助于更加全面地认识虚拟惯量控制的效果并指导实际应用。