基于XMC4500的汽车CAN网络检测卡设计

CAN总线作为车用网络的主要应用总线技术,通过CAN总线获得汽车运行时的实时数据成为汽车电子系统研发、维修及故障分析的主要手段;在对传统CAN总线检测卡分析及研究的基础上,为了使移动PC更加便捷地分析及记录汽车CAN网络中的数据,使基于串口通讯的系统及应用软件能够方便地继承使用,设计了基于XMC4500单片机的汽车CAN网络检测卡;实现了将汽车CAN网络中的数据通过USB端口虚拟的高速串口传输至上位机、实时备份相关数据到Micro SD卡中的功能;实验数据显示在最高1 000kb/s的传输速率下,能够100%正确接收及存储相关数据,满足对该卡实时性和可靠性的要求。     

基于LMD的PWM整流电路故障特征提取新方法

脉冲宽度调制(PWM)整流电路结构日益复杂,对其可靠运行提出了更高的要求;对局域均值分解(LMD)用于PWM整流电路的故障特征提取进行研究,提出一种基于LMD和加权频带能量法的特征提取新方法;该方法通过逐步抽取调频调幅成分将故障信号在频域上展开,然后基于信号能量的频带分布特点,充分考虑各频带成分与故障的相关性,构造故障特征向量,实现特征提取;最后以PWM整流电路为例进行仿真,相电压380V,仿真时间0.5s,0.1s时注入故障;结果表明,该方法能有效地提取故障信号的特征,并降低特征向量的维数。     

基于USB总线的机载多脉冲激光雷达产品测试系统研制

针对现有的机载激光雷达产品测试系统不能模拟特定信噪比,且系统使用复杂的问题,开发了基于USB总线的机载多脉冲激光雷达产品测试系统;测控软件可以设定信噪比、脉冲幅值、脉冲周期等参数,并根据静态测距和动态测距的实际需要,生成静态和动态模拟数据;另外,测试系统还能够采集外场数据,并在测控计算机上存储和分析;采集和生成的数据经过USB总线发送给基于FPGA+高速D/A转换器架构的数据转换器,再输出给激光雷达产品,保证了数据传输的高速性和灵活性;经过测试表明,信噪比在3~9的情况下,产生回波信号的距离误差控制在1%以内,信号幅值误差控制在0.5%以内;测试系统的各项指标都满足实际需要,为激光雷达产品调试提供了良好的模拟仿真平台。     

End-to-End 2D Convolutional Neural Network Architecture for Lung Nodule Identification and Abnormal Detection in Cloud

The extent of the peril associated with cancer can be perceived from the lack of treatment, ineffective early diagnosis techniques, and most importantly its fatality rate. Globally, cancer is the second leading cause of death and among over a hundred types of cancer; lung cancer is the second most common type of cancer as well as the leading cause of cancer-related deaths. Anyhow, an accurate lung cancer diagnosis in a timely manner can elevate the likelihood of survival by a noticeable margin and medical imaging is a prevalent manner of cancer diagnosis since it is easily accessible to people around the globe. Nonetheless, this is not eminently efficacious considering human inspection of medical images can yield a high false positive rate. Ineffective and inefficient diagnosis is a crucial reason for such a high mortality rate for this malady. However, the conspicuous advancements in deep learning and artificial intelligence have stimulated the development of exceedingly precise diagnosis systems. The development and performance of these systems rely prominently on the data that is used to train these systems. A standard problem witnessed in publicly available medical image datasets is the severe imbalance of data between different classes. This grave imbalance of data can make a deep learning model biased towards the dominant class and unable to generalize. This study aims to present an end-to-end convolutional neural network that can accurately differentiate lung nodules from non-nodules and reduce the false positive rate to a bare minimum. To tackle the problem of data imbalance, we oversampled the data by transforming available images in the minority class. The average false positive rate in the proposed method is a mere 1.5 percent. However, the average false negative rate is 31.76 percent. The proposed neural network has 68.66 percent sensitivity and 98.42 percent specificity.     

Quantum Fuzzy Regression Model for Uncertain Environment

In the era of big data, traditional regression models cannot deal with uncertain big data efficiently and accurately. In order to make up for this deficiency, this paper proposes a quantum fuzzy regression model, which uses fuzzy theory to describe the uncertainty in big data sets and uses quantum computing to exponentially improve the efficiency of data set preprocessing and parameter estimation. In this paper, data envelopment analysis (DEA) is used to calculate the degree of importance of each data point. Meanwhile, Harrow, Hassidim and Lloyd (HHL) algorithm and quantum swap circuits are used to improve the efficiency of high-dimensional data matrix calculation. The application of the quantum fuzzy regression model to small-scale financial data proves that its accuracy is greatly improved compared with the quantum regression model. Moreover, due to the introduction of quantum computing, the speed of dealing with high-dimensional data matrix has an exponential improvement compared with the fuzzy regression model. The quantum fuzzy regression model proposed in this paper combines the advantages of fuzzy theory and quantum computing which can efficiently calculate high-dimensional data matrix and complete parameter estimation using quantum computing while retaining the uncertainty in big data. Thus, it is a new model for efficient and accurate big data processing in uncertain environments.     

Technology landscape and a short patentometric review for antibiofilm technologies

This study presents an overview and a short critical review of patented antibiofilm technologies. Patent information was used to determine scenarios that could be used by decision-makers or business intelligence. The study found that academia, mainly from the USA, has been applying for the most patents since 1997. Based on the S-curve analysis, the maturity of this technology sector is emerging. The technological specialization for the 10 most prominent patent applicants and state-of-the-art antibiofilm patents are presented.The high dispersion of patent applicants, the presence of universities among the most active patent applicants, and the content of the patents analyzed are good indicators to infer that developed technologies are close to the academic level. Moreover, many efforts are necessary to bring these technologies into the market.Polymers-N-based, amino acids and peptides, P and S compounds, chelating agents and organometallic complexes, nanoparticles, or composites are claimed to be active against biofilm formation. Such compounds are presented in this work, and in rare cases, they are described as compositions ready for use as marketable products.     

基于激光点云数据的叶片型面三维重构

在四坐标叶片型面检测基础上,提出基于激光点云数据的叶片型面三维重构方法。激光位移传感器对叶片型面进行多视角扫描采样,快速采集叶片型面海量点云数据。运用由点到线到面的数学建模原理,先基于端点一阶导矢连续法拟合出光顺NURBS曲线,再依据分片能量法构建辅助曲面拟合出光顺NURBS曲面,最后对分片NURBS曲面进行统一描述,构造出精确光滑的叶片型面,实现叶片型面的三维重构。实验结果表明：采用该方法实现对各类叶片复杂型面的三维重构,重构误差均<0.015 mm,能够满足精密零件的测量需求。     

Beyond Market Baskets: Generalizing Association Rules to Dependence Rules

One of the more well-studied problems in data mining is the search for association rules in market basket data. Association rules are intended to identify patterns of the type: A customer purchasing item A often also purchases item B. Motivated partly by the goal of generalizing beyond market basket data and partly by the goal of ironing out some problems in the definition of association rules, we develop the notion of dependence rules that identify statistical dependence in both the presence and absence of items in itemsets. We propose measuring significance of dependence via the chi-squared test for independence from classical statistics. This leads to a measure that is upward-closed in the itemset lattice, enabling us to reduce the mining problem to the search for a border between dependent and independent itemsets in the lattice. We develop pruning strategies based on the closure property and thereby devise an efficient algorithm for discovering dependence rules. We demonstrate our algorithm's effectiveness by testing it on census data, text data (wherein we seek term dependence), and synthetic data.     

Design and Configuration Rationales for Digital Video Storage and Delivery Systems

Recent advances in computing technology have brought multimedia information processing to prominence. The ability to digitize, store, retrieve, process, and transport analog information in digital form has changed the dimensions of information handling. Several architectural and network configurations have been proposed for efficient and reliable digital video delivery systems. However, these proposals succeed only in addressing subsets of the whole problem. In this paper, we discuss the characteristics of video services. These include Cable Television, Pay-Per-View, and Video Repository Centers. We also discuss requirements for Video On Demand services. With respect to these video services, we analyze two important video properties: image quality and response time. We discuss and present configurations of a Digital Video Delivery System (DVDS) from three general system components - servers, clients, and connectivities. Pertinent issues in developing each component are also analyzed. We also present an architecture of a DVDS that can support the various functionalities that exist in the various video services. Lastly, we discuss data allocation strategies which impact performance of interactive video on demand (IVOD). We present preliminary results from a study using a limited form of mirroring to support high performance IVOD.     

带DDE通讯功能的控制仪表

带DDE通讯功能的控制仪表可以在WINDOWS环境下利用商用软件进行各种数据的读取和仪表参数的修改．从而构成具有较高性能价格比的方便易用的集散控制系统．