基于动量BP神经网络激光陀螺调腔检测方法

为解决激光陀螺人工调腔质量低、效率不高等缺点,提出一种由CCD相机和光电倍增管构成的多传感器信息融合调腔检测方法,该方法同时检测光斑、光阑中心点及陀螺损耗值,并将这些信息送入融合中心,经过融合计算得到陀螺调腔是否合格的综合判断。融合系统采用动量BP神经网络对多源信息进行融合,根据调腔过程中的输入、输出情况,设计包含输入层、隐含层及输出层的3层网络拓扑结构。实验结果表明,此种方法对激光陀螺调腔质量是否合格判断准确率为93.81%,比人工采用单一传感器分步检测准确率提高了6%。     

构建基于过程方法的公安情报产品质量管理体系的研究

基于循环改进的管理学思维,将过程方法应用到公安情报产品质量管理中,构建公安情报产品质量管理体系,以资料汇编、情报策划、产品制定、产品检测、情报应用为控制质量点,构建科学、规范的质量管理体系,解决公安情报部门产品产出过程中的短板,强化管理作用,从流程上优化整体提升产品效能,达到公安情报产品生命周期全覆盖的质量控制目的,为公安情报部门产品质量管理工作提供一种可行性方案。     

基于FPGA的科学级CCD成像系统设计

针对天文、医学等领域科学成像需要,设计了一套基于FPGA的科学级CCD成像系统,并给出了设计中关键技术的解决方法。首先,FPGA提供CCD正常工作所需要的时序信号,驱动CCD输出模拟图像;再将模拟信号预放大、相关双采样、AD转化后输出给FPGA进行处理;最后,将图像信号在FPGA内部进行格式重组、添加图像信息等操作后输出给存储与显示单元。实验结果表明,获取的图像质量较好,不制冷时读出噪声仅6个电子,满足了科学成像的需要。整个系统性能稳定可靠、实时性强,具有较好的通用性。     

VFP中通用查询的实现

数据查询是数据库信息管理系统的重要功能。而通用查询程序具有良好的数据界面，用户可以选取任意输出字段，设置关于任意字段的查询条件；而且在实例值的输入时不必输入定界符，实现数据类型的自动匹配。同时也可以方便地移植到其他的数据库信息管理系统中。     

A 3.3 V, 10 Bits, Clock-Feedthrough Compensated Switched-Current Second Order Sigma-Delta Modulator

This article presents a low-pass sigma-delta modulator for Analogue-to-Digital conversion. The circuit uses a switched-current technique which presents a well known drawback called clock feedthrough. This phenomenon induces an error on the output signal value. In order to cancel the clock feedthrough effect, we use a new method based on a current feedback loop. The circuit is designed in 0.8 μm AMS “Austria Mikro Systems” single poly CMOS process. Measurements of the modulator are performed under A/D converters characterisation system, and show 55 dB dynamic range at 2.048 MHz sampling rate with 8 kHz input frequency bandwidth. These characteristics are suitable for audio applications.     

The Japanese Way of Management

This paper presents a series of frameworks for analyzing and understanding the Japanese way of management which presumably has contributed to the phenomenal growth of the Japanese economy for the past quarter century. The treatment is limited to the context of practice of the so-called rationality-oriented aspects of management, especially to the application of operations research (OR), management science, and possibly also computer technology, to the solution of management decision problems. It encompasses not only the application of other, basic management technologies such as statistical quality control (SQC) and industrial engineering (IE) but also more comprehensive areas of practice such as management information systems (MIS).     

基于多尺度卷积神经网络的自适应熵加权决策融合船舶图像分类方法

针对单一尺度卷积神经网络(CNN)对船舶图像分类的局限性,该文提出一种多尺度CNN自适应熵加权决策融合方法用于船舶图像分类。首先使用多尺度CNN提取不同尺寸的船舶图像的多尺度特征,并训练得到不同子网络的最优模型;接着利用测试集船舶图像在最优模型上测试,得到多尺度CNN的Softmax函数输出的概率值,并计算得到信息熵,进而实现对不同输入船舶图像赋予自适应的融合权重;最后对不同子网络的Softmax函数输出概率值进行自适应熵加权决策融合实现船舶图像的最终分类。在VAIS数据集和自建数据集上分别进行了实验,提出的方法的分类准确率分别达到了95.07%和97.50%,实验结果表明,与单一尺度CNN分类方法以及其他较新方法相比,所提方法具有更优的分类性能。     

System identification using nonstationary signals

The conventional method for identifying the transfer function of an unknown linear system consists of a least squares fit of its input to its output. It is equivalent to identifying the frequency response of the system by calculating the empirical cross-spectrum between the system's input and output, divided by the empirical auto-spectrum of the input process. However, if the additive noise at the system's output is correlated with the input process, e.g., in case of environmental noise that affects both system's input and output, the method may suffer from a severe bias effect. We present a modification of the cross-spectral method that exploits nonstationary features in the data in order to circumvent bias effects caused by correlated stationary noise. The proposed method is particularly attractive to problems of multichannel signal enhancement and noise cancellation, when the desired signal is nonstationary in nature, e.g., speech or image     

An information theoretic approach to the distributed detectionproblem

The distributed detection problem is considered from an information-theoretic point of view. An entropy-based cost function is used for system optimization. This cost function maximizes the amount of information transfer between the input and the output. Distributed detection system topologies with and without a fusion center are considered, and an optimal fusion rule and optimal decision rules are derived     

白绒山羊遗传育种数据库及综合管理平台的设计与实现

为了提高育种质量和繁殖性能，减少育种研究风险和成本，采集陕北白绒山羊资源参考家系的相关育种资料，设计了一种基于Web的育种数据挖掘及管理平台。重点研究了基于遗传算法的育种数据挖掘算法以及决策支持系统、系统数据库的构建、功能模块和物理结构。应用结果表明，该方案可有效地有效解决遗传育种过程中染色体组合无序的地杂交造成优秀基因率降低和种类质量下降等问题。     

Cost impact of telecommunications switch software problems ondivested Bell operating companies

Bellcore has developed a model to support the periodic calculation and reporting of customer costs resulting from poor quality in telecommunications switching system software. This model is designed to provide, as a primary output, total switching system software cost of poor quality, along with a breakdown of this total by major cost component. The primary input to the model is software RQMS data, described in Bellcore's reliability and qualify measurements for telecommunications systems, TR-TSY-000929, and reported by switching system suppliers to the divested Bell operating companies (telcos) on systems operated by these companies. Telco and switching system supplier alike are expected to benefit from the ongoing application of the model, through which accumulated maintenance cost information will be made available to support telco switching system management functions and supplier quality improvement efforts     

An Outage Probability in Cooperative MIMO under (Alamouti,Orthogonal and Quasi Orthogonal STBC) Slow Fading Channel

Slow fading channel is one of the most important channels, which appears widely in a cellular mobile system. It has several problems such as bad effects of fading, which causes an attenuation to the signal. This paper presents a new scheme in cooperative communication system under slow fading channel to enhance and increase the quality of communication systems performance. This new scheme is called a cooperative multiple input–multiple output Antenna. The main idea of this scheme depends on transmitting multi copy of message via two paths. It’s performance has been compared with MIMO technique in term of outage probability. The results show that the negative effects of fading are mitigated and the outage probability and diversity gain are enhanced. Furthermore, the reliability in communication system under slow fading channel is improved.     

A fuzzy approach to deal with uncertainty in image forensics

Image forensics research has mainly focused on the detection of artifacts introduced by a single processing tool, thus resulting in the development of a large number of specialized algorithms looking for one or more specific footprints under precise settings. As one may guess, the performance of such algorithms are not ideal, so the output they provide may be noisy, inaccurate and only partially true. Moreover, in real scenarios a manipulated image is often the result of the application of several tools made available by the image processing software. As a consequence, reliable tamper detection requires that several tools developed to deal with different scenarios are applied. The above observations raise two new problems: (i) deal with the uncertainty introduced by error-prone tools and (ii) devise a sound strategy to merge the information provided by the different tools into a single output. To overcome these problems we propose a decision fusion framework based on the Fuzzy Theory, which permits to cope with the uncertainty and lack of precise information typical of image forensics, by leveraging on the widely known ability of the Fuzzy Theory to deal with inaccurate and incomplete information. We describe a practical implementation of the proposed framework and validate it in a realistic scenario in which five forensic tools exploit JPEG compression artifacts to detect cut&paste tampering within a specified region of an image. The results are encouraging, and provide a significant advantage with respect to those obtained by simply OR-ing the outputs of the single tools.     

On-line learning delivery decision support system for highlyproduct mixed semiconductor foundry

A production learning system (PLS) based on the tool model was constructed as a decision support and real-time information update system to forecast the cycle time. A tool model includes a waiting model and a processing model. Each of the waiting and processing models uses a backpropagation neural network to establish the relationship between the input and output (time) of the model. Hence, cycle time estimation, tool group move and confirm line item performance (CLIP) value can be obtained based on the memory stored in the neural network. The result shows that the forecasting ability of the PLS has an error rate below 8% on average     

Adaptive Input Design for Identification of Output Error Model with Constrained Output

Optimal input design for system identification is an area of intensive modern research. This paper considers the identification of output error (OE) model, for the case of constrained output variance. The constraint plays a very important role in the process industry, in the reduction of degradation of product quality. In this paper, it is shown, in the form of a theorem, that the optimal input signal, with constrained output, is achieved by a minimum variance controller together with a stochastic reference. The key problem is that the optimal input depends on the system parameters to be identified. In order to overcome this problem, a two-stage adaptive procedure is proposed: obtaining an initial model using PRBS as input signal; application of adaptive minimum variance controller together with the stochastic variable reference, in order to generate input signals for system identification. Theoretical results are illustrated by simulations.     

Multichannel Fast QR-Decomposition Algorithms: Weight Extraction Method and Its Applications

Multichannel fast QR decomposition RLS (MC-FQRD-RLS) algorithms are well known for their good numerical properties and low computational complexity. The main limitation is that they lack an explicit weight vector term, limiting themselves to problems seeking an estimate of the output error signal. This paper presents techniques which allow us to use MC-FQRD-RLS algorithms with applications that previously have required explicit knowledge of the adaptive filter weights. We first consider a multichannel system identification setup and present how to obtain, at any time, the filter weights associated with the MC-FQRD-RLS algorithm. Thereafter, we turn to problems where the filter weights are periodically updated using training data, and then used for fixed filtering of a useful data sequence, e.g., burst-trained equalizers. Finally, we consider a particular control structure, indirect learning, where a copy of the coefficient vector is filtering a different input sequence than that of the adaptive filter. Simulations are carried out for Volterra system identification, decision feedback equalization, and adaptive predistortion of high-power amplifiers. The results verify our claims that the proposed techniques achieve the same performance as the inverse QRD-RLS algorithm at a much lower computational cost.     

数据仓库在航空维修信息分析中的应用研究

在空军航空维修管理信息系统的基础上,提出了一个航空维修信息分析系统研究模型,应用此模型可以对航空维修信息进行联机分析处理,并用决策树算法及关联规则算法进行数据挖掘,以实现对航空维修信息的智能分析。     

嵌入式控制系统的VXI总线数据采集软件设计

嵌入式控制系统需要通过电子测量方式进行数据采集,为控制系统提供输入参量模型,采用VXI总线技术进行嵌入式控制系统的32通道控制数据采集和实时数据记录,方便控制系统和客户端现场分析数据.嵌入式控制系统的VXI总线数据采集软件是建立在对控制信息的特征采样和控制参量的信息输入基础上,进行VXI总线数据采集系统总体设计描述和功能指标分析,数据采集通过发射天线、接收天线、发射机、接收机、控制器等构件实现.数据采集系统的软件模块设计包括了通道设置、触发设置、数据端口设置、数据可视化模块设计和数据读取回放等子模块,通过软件优化设计实现VXI总线数据采集.实验分析结果表明,该系统进行数据采集的输入和输出的波形控制的匹配性能较高,稳定性较好,具有较高的数据采集精度.     

A management scheme for improving transportation efficiency and contributing to the enhancement of the social fabric

The continuously increasing need for mobility has brought about not only significant facilities in several aspects of human initiative, but also growing traffic congestions, a phenomenon that leads to unpleasant everyday situations at a short time level, but in the long run also to the degradation of the level of quality of living in large cities and the alienation between people. The management of traffic stands, thus, as a fundamental prerequisite for confronting those issues, enhancing transportation and improving the social fabric. This paper considers the concept of car pooling as a structured approach to this problem, by specifying, developing and validating a mobile-community-driven system for collaborative transportation, namely the “transportation management-car pooling system”. This system is capable of proposing optimal, reliable and secure community matches (taking into consideration personality features, talking interests, driving style, etc.), based on user profile and context information. The paper describes the transportation management-car pooling system, presenting its input parameters, decision making process and outcomes. Finally, indicative simulation results showcase its effectiveness.     

基于信息价值的多属性群决策方法

根据信息的质量和价值这两个重要属性,建立了覆盖信息的时效性、关联性和准确性的价值评价指标体系;然后针对多属性群决策问题的描述和求解特点,构建了基于信息评价的相关数学模型,进而计算决策群体对各备选方案的最终排序结果;最后用炮兵防空实例说明其有效性。该方法将信息价值评价的思想引入到群决策,考虑了决策时所获取信息的延时损失及其与决策任务的关联性。