Implementation of Mobile Streaming Media Player Based on BREW

Nowadays mobile streaming service through cell phone is becoming the highlight of new value-added mobile services. Based on the present CDMAlx wireless data network and Binary Runtime Environment for Wireless （BREW） platform, adopting compression technologies of H.264 and QCP, a set of streaming media players are designed and implemented, and the principle, structure, key technologies and performance analysis of this system are introduced. This player works well in practice.     

二进制堆排序算法的改进研究

基于对网络服务质量中队列调度算法的介绍和分析,从队列的优先级角度出发,对经典的二进制堆Heap调度排序算法进行了改进,提出了一种新的Heap＋算法,该算法充分利用原算法出队、入队操作数固定的特点,使其在保证硬件实现复杂度低的情况下能够做到出队、入队操作的流水化,从而达到高度的并行性。且具备很高的资源利用率和可扩展性,可用于高速链路上高精度虚拟时间的排序操作。     

Integration of wavelet transform,Local Binary Patterns and moments for content-based image retrieval

The proliferation of large number of images has made it necessary to develop systems for indexing and organizing images for easy access. This has made Content-Based Image Retrieval (CBIR) an important area of research in Computer Vision. This paper proposes a combination of features in multiresolution analysis framework for image retrieval. In this work, the concept of multiresolution analysis has been exploited through the use of wavelet transform. This paper combines Local Binary Pattern (LBP) with Legendre Moments at multiple resolutions of wavelet decomposition of image. First, LBP codes of Discrete Wavelet Transform (DWT) coefficients of images are computed to extract texture feature from image. The Legendre Moments of these LBP codes are then computed to extract shape feature from texture feature for constructing feature vectors. These feature vectors are used to search and retrieve visually similar images from large database. The proposed method has been tested on five benchmark datasets, namely, Corel-1K, Olivia-2688, Corel-5K, Corel-10K, and GHIM-10K, and performance of the proposed method has been measured in terms of precision and recall. The experimental results demonstrate that the proposed method outperforms some of the other state-of-the-art methods in terms of precision and recall.     

COVID-19 discrimination framework for X-ray images by considering radiomics,selective information,feature ranking,and a novel hybrid classifier

In medical imaging procedures for the detection of coronavirus, apart from medical tests, approval of diagnosis has special significance. Imaging procedures are also useful for detecting the damage caused by COVID-19. Chest X-ray imaging is frequently used to diagnose COVID-19 and different pneumonias. This paper presents a task-specific framework to detect coronavirus in X-ray images. Binary classification of three different labels (healthy, bacterial pneumonia, and COVID-19) was performed on two differentiated data sets in which corona is stated as positive. First-order statistics, gray level co-occurrence matrix, gray level run length matrix, and gray level size zone matrix were analyzed to form fifteen sub-data sets and to ascertain the necessary radiomics. Two normalization methods are compared to make the data meaningful. Furthermore, five feature ranking approaches (Bhattacharyya, entropy, Roc, t-test, and Wilcoxon) are mentioned to provide necessary information to a state-of-the-art classifier based on Gauss-map-based chaotic particle swarm optimization and neural networks. The proposed framework was designed according to the analyses about radiomics, normalization approaches, and filter-based feature ranking methods. In experiments, seven metrics were evaluated to objectively determine the results: accuracy, area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, g-mean, precision, and f-measure. The proposed framework showed promising scores on two X-ray-based data sets, especially with the accuracy and area under the ROC curve rates exceeding 99% for the classification of coronavirus vs. others.     

Theory of wire addition and removal in combinational Boolean networks

Let w_t be a wire in a combinational Boolean network. There may exist a wire w_a such that when w_a is added and w_t is removed, the overall circuit functionality is unchanged. Redundancy-addition-and-removal (RAR) is an efficient technique to find such a w_a. The idea is to add a redundant alternative wire w_a to make the target wire w_t redundant. However, as long as the addition of w_a together with the removal of w_t does not change the overall functionality of the circuit, wires that are added and removed do not necessarily need to be redundant. This raises a question about the existence of alternative wires. Why can one wire replace another wire in a combinational Boolean network? In this paper, we analyze theoretically the existence of alternative wires and model it as an error-cancellation problem. The two existing rewiring techniques, the redundancy-addition-and-removal and the global flow optimization, are unified under the proposed generalized model.     

EBPSK载波同步中的相位误差分析

载波同步是通信中的重要环节。该文分析了EBPSK载波同步中的相位误差。首先在包含窄带高斯噪声的条件下,通过建立锁相环线性化模型,推导了EBPSK载波恢复中的输出相位噪声方差;其次在相同的参数条件下,与BPSK的平方环和Costas环输出相位噪声方差进行对比,给出了不同输入信噪比和环路带宽下的仿真结果。研究表明,在EBPSK占空比1:9,相位跳变/4,输入信噪比小于6 dB时,恢复出的载波要比BPSK更加精确。     

自适应阈值及加权局部二值模式的人脸识别

针对局部二值模式(LBP)和中心对称局部二值模式(CS-LBP)方法描述图像纹理特征时,阈值不能自动选取并且图像中不同子块的贡献也没有进行区分的问题,该文提出一种自适应阈值及加权的局部二值模式方法。首先,将图像进行分块,采用设定的自适应阈值提取每个子块的LBP或CS-LBP纹理直方图;然后,将各子图像的信息熵作为直方图的加权依据,对每个子块对应的直方图进行自适应加权,并将所有子块的直方图连接成最终的纹理特征;最后,通过快速计算图像均值加快了算法的计算速度。在人脸数据库上进行的实验证明,利用该文提出的方法提取纹理特征,并结合最近邻分类法可以得到较高的正确识别率。     

一种改进的抗噪和旋转不变纹理图像分类算法

直接在空域计算图像的局部二进制模式(LBP)直方图不能准确描述基元较大的纹理,且不具有抗噪性这一重要的特性。针对这一局限,提出一种将空域和频域结合起来的改进算法。首先在频域对图像进行Curvelet变换,选取能量较大的子带进行图像重构并抽样,最后计算抽样图像的旋转不变LBP算子直方图作为特征向量。这样得到的特征更加紧凑,能更有效地描述图像的细节,同时弥补了传统LBP算法的不足,实现了用相同尺寸的LBP算子描述大基元的纹理,同时具有旋转不变和抗噪性能。仿真结果表明,算法得到的分类率比其他算法有显著提高,并且具有较强的抗噪性。     

基于显著轮廓特征的SAR图像轮廓匹配新方法

在以星载SAR图像作为基准图、机载/弹载SAR图像作为实时图的匹配导航和精确制导研究中,传统基于点特征的匹配方法存在特征点数目过多, 误匹配率较高,容易受噪声及灰度变化影响等问题。该文提出一种基于显著轮廓特征的SAR图像“由粗到精”的匹配新方法。该方法在对SAR图像进行预处理的基础上,采用改进的模糊C均值聚类(FCM)的图像分割方法来提取闭合轮廓特征;采用归一化轮廓中心距离描述符进行双向匹配,获得强鲁棒性的粗匹配轮廓对;在粗匹配轮廓上采用改进的局部二值模式(LBP)算子得到精匹配结果。试验结果表明,该方法在图像旋转、空间变化以及噪声干扰较大的情况下,具有精确性高、鲁棒性强的优势,适宜遥感SAR图像匹配。     

Java语言及其虚拟机技术探讨

随着Internet的迅猛发展，Internet编程语言Java愈来愈成为计算机行业的焦点。本文在简述了Java的主要特点后，重点对Java最关键的技术──虚拟机进行了深入的探讨。