太湖流域某净水厂嗅味物质变化特征研究

为了探讨净水厂中嗅味物质的浓度变化规律与各级处理单元之间的关系,以期为净水厂更加高效地去除水中的嗅味物质提供依据,采用固相微萃取—气质联用技术对太湖流域某净水厂中的2-甲基异莰醇(2-methylisobornel,2-MIB)、土臭素(Geosmin,GSM)、β-紫罗兰酮(β-Ionone,p-Ion)和β环柠檬醛(pCyclocitrial,p-Cyc)4种特征嗅味物质进行检测,并分析比较了净水厂各级处理单元对嗅味物质的去除效果.结果表明:β-Cyc的平均浓度最高,为5.83 μg/L,其次为β-Ion,平均浓度达到41.36 ng/L,2-MIB和GSM的平均浓度相对较低,分别为4.02 ng/L、l.13 ng/L;净水厂处理工艺对2-MIB、β-Cyc、β-Ion和GSM的去除率分别为99.93％、93.73％、64.09％和0;净水厂的处理工艺对嗅味物质具有一定的去除效果,嗅味物质浓度沿着水处理工艺流程呈下降趋势,嗅味物质的去除主要发生在深度处理阶段.     

基于XCT扫描图像的混凝土二维细观受压断裂模拟

为了研究混凝土细观层次断裂力学特性,对混凝土试件进行原位XCT扫描,基于扫描图像提出了具有真实内部结构特征的混凝土二维细观模型,并预先在水泥砂浆和骨料-水泥砂浆界面插入零厚度粘结裂缝单元用以模拟潜在的裂缝。通过对该模型进行混凝土单轴受压数值仿真模拟,讨论其裂缝的发展过程以及不同细观结构和相应参数对混凝土断裂损伤行为的影响。结果表明：数值模拟得到的混凝土二维模型抗压强度与试验测得的强度相接近;混凝土的抗压强度受到水泥砂浆和骨料-砂浆界面裂缝单元的绝对数值影响,其中水泥砂浆裂缝单元强度对材料强度起控制作用;骨料-砂浆界面裂缝单元强度与水泥砂浆裂缝单元强度的比率对裂缝衍生发展有显著影响。     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.     

Parallel source separation system for heart and lung sounds

The Journal of Supercomputing - In this paper, we propose a parallel source separation system designed to extract heart and lung sounds from single-channel mixtures. The proposed system is based on...     

From text to graph: a general transition-based AMR parsing using neural network

Neural Computing and Applications - Semantic understanding is an essential research issue for many applications, such as social network analysis, collective intelligence and content computing,...     

Trajectory tracking control for underactuated unmanned surface vehicle subject to uncertain dynamics and input saturation

Neural Computing and Applications - In this paper, one concerns with the problem of trajectory tracking control for an underactuated unmanned surface vehicle subject to uncertain dynamics and input...     

基于正切图像处理(TIP)模型的自适应图像增强算法

针对图像增强算法复杂度高、对噪声敏感等问题,在分析对数图像处理模型的基础上,提出了一种基于正切图像处理模型的自适应图像增强算法,该算法具有实现容易、运算速度快等特点,对噪声具有一定的抑制作用,可以增强和保留图像细节信息。既可以增强灰度图像,又可以增强彩色图像,实验和理论分析说明了该算法的优越性。     

Customer knowledge discovery from online reviews

The explosive growth of Chinese electronic market has made it possible for companies to better understand consumers?? opinion towards their products in a timely fashion through their online reviews. This study proposes a framework for extracting knowledge from online reviews through text mining and econometric analysis. Specifically, we extract product features, detect topics, and identify determinants of customer satisfaction. An experiment on the online reviews from a Chinese leading B2C (Business-to-Customer) website demonstrated the feasibility of the proposed method. We also present some findings about the characteristics of Chinese reviewers.     

The analysis of global input-to-state stability for piecewise affine systems with time-delay

In this paper, global input-to-state stability (ISS) for discrete-time piecewise affine systems with time-delay are considered. Piecewise quadratic ISS-Lyapunov functions are adopted. Both Lyapunov-Razumikhin and Lyapunov-Krasovskii methods are used. The theorems of Lyapunov-Razumikhin type and Lyapunov-Krasovskii type for piecewise affine systems with time-delay are shown, respectively.     

Hysteresis Compensation and Adaptive Controller Design for a Piezoceramic Actuator System in Atomic Force Microscopy

This paper presents an indirect adaptive controller combined with hysteresis compensation to achieve high accuracy positioning control of piezoceramic actuators and illustrates the results with an atomic force microscope (AFM) application. A dynamic model of a piezoceramic actuator system in AFM is derived and analyzed. A feedforward controller based on the Preisach model is proposed to compensate for the nonlinear hysteresis effects. Then an indirect adaptive controller is designed to achieve desired tracking performance as well as deal with the uncompensated nonlinearity from hysteresis and the system parameter variation due to creep. Experimental results indicate that the proposed controller can significantly improve the positioning control accuracy of the piezoceramic actuator as well as achieve high image quality of the AFM system. The maximum scanning error was reduced from 2µm to 0.3µm in comparison with a proportional‐integral‐derivative (PID) controller. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society