基于C8051F340控制的TD直放站控制方案设计

介绍一种基于C8051F340快速单片机控制的直放站设计;采用GPS同步法,按时隙功率控制,自动增益控制AGC环路,系统的非线性指标良好、抗干扰性强、可靠性高.比以功率检测的同步方法和基于特征窗搜索的同步方法实现简单,应用范围更广,可用于任何无线直放站应用场合,特别适用于干放及无线射频交换场合.     

Design and realization of ad-hoc VoIP with embedded p-SIP server

In this paper we design and implement the pseudo session initiation protocol (p-SIP) server embedded in each mobile node to provide the ad-hoc voice over Internet protocol (VoIP) services. The implemented p-SIP server, being compatible with common VoIP user agents, integrates the standard SIP protocol with SIP presence to handle SIP signaling and discovery mechanism in the ad-hoc VoIP networks. The ad-hoc VoIP signaling and voice traffic performances are analyzed using E-model R rating value for up to six hops in the implemented test-bed. We also conduct the interference experiments to imitate the practical ad-hoc VoIP environment. The analyzed results demonstrate the realization of ad-hoc VoIP services by using p-SIP server.     

Mesh Snapping: Robust Interactive Mesh Cutting Using Fast Geodesic Curvature Flow

This paper considers the problem of interactively finding the cutting contour to extract components from a given mesh. Some existing methods support cuts of arbitrary shape but require careful and tedious input from the user. Others need little user input however they are sensitive to user input and need a postprocessing step to smooth the generated jaggy cutting contours. The popular geometric snake can be used to optimize the cutting contour, but it cannot deal with the topology change. In this paper, we propose a geodesic curvature flow based framework to overcome all these problems. Since in many cases the meaningful cutting contour on a 3D mesh is locally shortest in the sense of some weighted curve length, the geodesic curvature flow is an ideal tool for our problem. It evolves the cutting contour to the nearby local minimum. We should mention that the previous numerical scheme, discretized geodesic curvature flow (dGCF) is too slow and has not been applied to mesh segmentation. With a careful observation to dGCF, we devise here a fast computation scheme called fast geodesic curvature flow (FGCF), which only needs to solve a smaller and easier problem. The initial cutting contour is generated by a variant of random walks algorithm, which is very fast and gives reasonable cutting result with little user input. Experiment results on the benchmark mesh segmentation data set show that our proposed framework is robust to user input and capable of producing good results reflecting geometric features and human shape perception.     

Mesh Decomposition with Cross‐Boundary Brushes

We present a new intuitive UI, which we call cross‐boundary brushes, for interactive mesh decomposition. The user roughly draws one or more strokes across a desired cut and our system automatically returns a best cut running through all the strokes. By the different natures of part components (i.e., semantic parts) and patch components (i.e., flatter surface patches) in general models, we design two corresponding brushes: part‐brush and patch‐brush. These two types of brushes share a common user interface, enabling easy switch between them. The part‐brush executes a cut along an isoline of a harmonic field driven by the user‐specified strokes. We show that the inherent smoothness of the harmonic field together with a carefully designed isoline selection scheme lead to segmentation results that are insensitive to noise, pose, tessellation and variation in user's strokes. Our patch‐brush uses a novel facet‐based surface metric that alleviates sensitivity to noise and fine details common in region‐growing algorithms. Extensive experimental results demonstrate that our cutting tools can produce user‐desired segmentations for a wide variety of models even with single strokes. We also show that our tools outperform the state‐of‐art interactive segmentation tools in terms of ease of use and segmentation quality.     

Hybrid Simulation of Miscible Mixing with Viscous Fingering

By modeling mass transfer phenomena, we simulate solids and liquids dissolving or changing to other substances. We also deal with the very small‐scale phenomena that occur when a fluid spreads out at the interface of another fluid. We model the pressure at the interfaces between fluids with Darcy's Law and represent the viscous fingering phenomenon in which a fluid interface spreads out with a fractal‐like shape. We use hybrid grid‐based simulation and smoothed particle hydrodynamics (SPH) to simulate intermolecular diffusion and attraction using particles at a computable scale. We have produced animations showing fluids mixing and objects dissolving.     

Sentiment-oriented contextual advertising

Web advertising (Online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the world’s most important marketing channels. This paper addresses the mechanism of Content-based advertising (Contextual advertising), which refers to the assignment of relevant ads to a generic web page, e.g., a blog post. As blogs become a platform for expressing personal opinion, they naturally contain various kinds of expressions, including both facts and comments of both a positive and negative nature. Besides, in line with the major tenet of Web 2.0 (i.e., user-centric), we believe that the web-site owners would be willing to be in charge of the ads which are positively related to their contents. Hence, in this paper, we propose the utilization of sentiment detection to improve Web-based contextual advertising. The proposed sentiment-oriented contextual advertising (SOCA) framework aims to combine contextual advertising matching with sentiment analysis to select ads that are related to the positive (and neutral) aspects of a blog and rank them according to their relevance. We experimentally validate our approach using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method can effectively identify those ads that are positively correlated with the given blog pages.     

基于FPGA的新型高速CCD图像数据采集系统

介绍一种基于Actel公司Fusion StartKit FPGA的线阵CCD图像数据采集系统。以FPGA作为图像数据的控制和处理核心,通过采用高速A/D、异步FIFO、UART以及电平转换、放大滤波、二值化电路和光学系统实现对图像数据的信号处理,并运用Visual Studio C++和Microsoft公司的基本类库MFC实现对采集数据的显示、绘图、传输控制等。利用搭建的系统平台实现对物体尺寸的测量,通过对所得的数据进行分析处理,明确测量的精度和可以达到的水平。对该系统在实时监控中的优点进行分析。     

Cascade of genetic algorithm and decision tree for cancer classification on gene expression data

Abstract: Cancer classification, through gene expression data analysis, has produced remarkable results, and has indicated that gene expression assays could significantly aid in the development of efficient cancer diagnosis and classification platforms. However, cancer classification, based on DNA array data, remains a difficult problem. The main challenge is the overwhelming number of genes relative to the number of training samples, which implies that there are a large number of irrelevant genes to be dealt with. Another challenge is from the presence of noise inherent in the data set. It makes accurate classification of data more difficult when the sample size is small. We apply genetic algorithms (GAs) with an initial solution provided by t statistics, called t‐GA, for selecting a group of relevant genes from cancer microarray data. The decision‐tree‐based cancer classifier is built on the basis of these selected genes. The performance of this approach is evaluated by comparing it to other gene selection methods using publicly available gene expression data sets. Experimental results indicate that t‐GA has the best performance among the different gene selection methods. The Z‐score figure also shows that some genes are consistently preferentially chosen by t‐GA in each data set.     

一种基于EZW改进算法的图像压缩方法研究

针对原EZW算法未能很好利用图像小波系数特点及按照频率特性量化小波系数的不足,提出了对图像小波系数进行信噪分离、阈值化处理以及对低、高频图像信息进行分阈值量化的改进算法,并给出了在保证复原图像质量情况下扫描终止的判别条件,以节省压缩时间,在实时传输中能有效地提高图像压缩效率。仿真实验结果表明,改进算法无论在扫描相同次数下的信噪比,还是相近信噪比下的压缩比都获得了较大改善,为小波变换下的图像压缩方法提供了新的思路。     

Improving the authentic learning experience by integrating robots into the mixed-reality environment

The main aim of the modern popular teaching method of authentic learning has been to provide students with everyday-life challenges that develop knowledge and skills through problem solving in different situations. Many emerging information technologies have been used to present authentic environment in pedagogical purpose. However, there are few studies that have been discussed the sense of authenticity and characters in scene and how students interact with the characters involved in the task. We designed a system, RoboStage, with authentic scenes by using mixed-reality technology and robot to investigate the difference in learning with either physical or virtual characters and learning behaviors and performance through the system. Robots were designed to play real interactive characters in the task. The experiment of the study conducted with 36 junior high students. The results indicated that RoboStage significantly improved the sense of authenticity of the task and also positively affected learning motivation. Learning performance was conditionally affected by RoboStage.