A formal characterization of epsilon serializability

Epsilon serializability (ESR) is a generalization of classic serializability (SR). In this paper, we provide a precise characterization of ESR when queries that may view inconsistent data run concurrently with consistent update transactions. Our first goal is to understand the behavior of queries in the presence of conflicts and to show how ESR in fact is a generalization of SR. So, using the ACTA framework, we formally express the intertransaction conflicts that are recognized by ESR and through that define ESR, analogous to the manner in which conflict-based serializability is defined. Secondly, expressions are derived for the amount of inconsistency (in a data item) viewed by a query and its effects on the results of a query. These inconsistencies arise from concurrent updates allowed by ESR. Thirdly, in order to maintain the inconsistencies within bounds associated with each query, the expressions are used to determine the preconditions that operations have to satisfy. The results of a query, and the errors in it, depend on what a query does with the (possibly inconsistent) data viewed by it. One of the important byproducts of this work is the identification of different types of queries which lend themselves to an analysis of the effects of data inconsistency on the results of the query     

基于知识挖掘和案例推理的电渣重熔过程智能优化设定控制

依据电渣重熔生产工艺特点、操作经验和历史数据库,提出了基于案例推理的电渣重熔生产过程智能 优化设定控制方法．采用粗糙集理论从积累的大量电渣重熔过程历史控制数据中获取知识,将典型工况总结成案例 的形式以构造案例库,并对案例推理过程中的案例检索、案例修正及存储方法进行详细描述．该智能控制策略应用 于某电渣重熔生产过程,稳定了电渣重熔过程工艺指标,取得了较好的应用效果．     

Divergence control algorithms for epsilon serializability

The paper presents divergence control methods for epsilon serializability (ESR) in centralized databases. ESR alleviates the strictness of serializability (SR) in transaction processing by allowing for limited inconsistency. The bounded inconsistency is automatically maintained by divergence control (DC) methods in a way similar to SR is maintained by concurrency control (CC) mechanisms. However, DC for ESR allows more concurrency than CC for SR. The authors first demonstrate the feasibility of ESR by showing the design of three representative DC methods: two-phase locking, timestamp ordering and optimistic approaches. DC methods are designed by systematically enhancing CC algorithms in two stages: extension and relaxation. In the extension stage, a CC algorithm is analyzed to locate the places where it identifies non-SR conflicts of database operations. In the relaxation stage, the non-SR conflicts are relaxed to allow for controlled inconsistency. They then demonstrate the applicability Of ESR by presenting the design of DC methods using other most known inconsistency specifications, such as absolute value, age and total number of nonserializably read data items. In addition, they present a performance study using an optimistic divergence control algorithm as an example to show that a substantial improvement in concurrency can be achieved in ESR by allowing for a small amount of inconsistency     

电渣重熔炉计算机控制系统设计与实现

电渣重熔炉是电渣重熔过程的典型设备。我国在90年代引进的康萨克电渣炉的控制系统存在一定的不足之处。文章通过分析其控制系统原理及潜在的问题,提出了新的控制系统方案,并成功应用于邢台机械轧辊集团铸钢分厂的电渣炉技改项目上。通过现场6个月的实际运行,控制效果良好,部分参数甚至优于原控制系统,从而说明新的控制方案是可行而有效的。     

Constructing models for predicting extract subclass refactoring opportunities using object-oriented quality metrics

ContextRefactoring is a maintenance task that refers to the process of restructuring software source code to enhance its quality without affecting its external behavior. Inspecting and analyzing the source code of the system under consideration to identify the classes in need of extract subclass refactoring (ESR) is a time consuming and costly process.ObjectiveThis paper explores the abilities of several quality metrics considered individually and in combination to predict the classes in need of ESR.MethodFor a given a class, this paper empirically investigates, using univariate logistic regression analysis, the abilities of 25 existing size, cohesion, and coupling metrics to predict whether the class is in need of restructuring by extracting a subclass from it. In addition, models of combined metrics based on multivariate logistic regression analysis were constructed and validated to predict the classes in need of ESR, and the best model is justifiably recommended. We explored the statistical relations between the values of the selected metrics and the decisions of the developers of six open source Java systems with respect to whether the classes require ESR.ResultsThe results indicate that there was a strong statistical relation between some of the quality metrics and the decision of whether ESR activity was required. From a statistical point of view, the recommended model of metrics has practical thresholds that lead to an outstanding classification of the classes into those that require ESR and those that do not.ConclusionThe proposed model can be applied to automatically predict the classes in need of ESR and present them as suggestions to developers working to enhance the system during the maintenance phase. In addition, the model is capable of ranking the classes of the system under consideration according to their degree of need of ESR.     

变频器直流侧电解电容ESR的在线测量与预测

为了估计变频器直流侧电解电容器的剩余寿命,需要测量其等效串联电阻ESR值。提出一种实时测量与预测ESR值的方法,首先将在线采集到的直流侧电压和电流信号传送到上位机的Matlab软件;然后在Simulink环境下分别采用时域法、频域法得到电容器ESR计算值,经数据融合处理后作为ESR实际值;最后进一步利用Matlab中最小二乘支持向量机LSSVM工具箱,对ESR未来值进行预测。预测结果与实际值比较,误差小且预测时间充足,验证了该方法的正确性与有效性。     

基于改进混合蛙跳算法的电渣重熔过程多变量PID 控制器设计

根据电渣重熔过程的工艺特点和数学模型,提出了基于改进混合蛙跳算法（ISFLA）的多变量参数自整定PID控制策略.提出一种新的蛙跳规则,用以增强SFLA的局部搜索能力.该规则主要通过模拟青蛙的感知和运动的不确定性来动态随机地调整青蛙的局部搜索空间和步长,以防止SFLA算法过早收敛,提高算法的搜索效率.仿真结果和工业应用实验均表明了所提出控制方法的可行性和有效性.     

Subsumption resolution: an efficient and effective technique for semi-naive Bayesian learning

Semi-naive Bayesian techniques seek to improve the accuracy of naive Bayes (NB) by relaxing the attribute independence assumption. We present a new type of semi-naive Bayesian operation, Subsumption Resolution (SR), which efficiently identifies occurrences of the specialization-generalization relationship and eliminates generalizations at classification time. We extend SR to Near-Subsumption Resolution (NSR) to delete near–generalizations in addition to generalizations. We develop two versions of SR: one that performs SR during training, called eager SR (ESR), and another that performs SR during testing, called lazy SR (LSR). We investigate the effect of ESR, LSR, NSR and conventional attribute elimination (BSE) on NB and Averaged One-Dependence Estimators (AODE), a powerful alternative to NB. BSE imposes very high training time overheads on NB and AODE accompanied by varying decreases in classification time overheads. ESR, LSR and NSR impose high training time and test time overheads on NB. However, LSR imposes no extra training time overheads and only modest test time overheads on AODE, while ESR and NSR impose modest training and test time overheads on AODE. Our extensive experimental comparison on sixty UCI data sets shows that applying BSE, LSR or NSR to NB significantly improves both zero-one loss and RMSE, while applying BSE, ESR or NSR to AODE significantly improves zero-one loss and RMSE and applying LSR to AODE significantly improves zero-one loss. The Friedman test and Nemenyi test show that AODE with ESR or NSR have a significant zero-one loss and RMSE advantage over Logistic Regression and a zero-one loss advantage over Weka’s LibSVM implementation with a grid parameter search on categorical data. AODE with LSR has a zero-one loss advantage over Logistic Regression and comparable zero-one loss with LibSVM. Finally, we examine the circumstances under which the elimination of near-generalizations proves beneficial.     

基于组件的路由器操作维护系统的研究

路由器操作维护（OAM）系统负责对路由器进行操作和管理,它是由路由器正常运行的保证,是路由器中的重要模块。随着路由器技术的发展,对路由器软件动态升级的要求正越来越受到人们的重视。本文对扩展服务路由器操作管理进行了深入的研究,首先介绍了扩展服务路由器操作管理的设计要求和研究现状,然后介绍了清华大学研制的扩展服务器路由器原型系统的软硬件体系结构和其对操作维护系统的功能要求,高度并实现了基于分布式实时操作系统VxWorks,可实时动态加载扩展服务组件的操作维护管理系统。最后指出了进一步研究方向。     

A microfluidic erythrocyte sedimentation rate analyzer using rouleaux formation kinetics

Red blood cell aggregation is an intrinsic property of red blood cells that form reversible stacked structures, also called rouleaux, under low shear rates. Erythrocyte sedimentation rate (ESR), commonly performed in clinics, is an indirect inflammation screener and a prognostic test for diseases. We have recently developed a microfluidic system for rapid measurement of ESR from 40 µl whole blood employing the aggregation dynamics. In this work, we propose the use of an aggregation inducer, dextran polyglucose, for the preparation of multiple blood samples with differing aggregation dynamics. Using these samples, we characterized the performance of the system with three aggregation indices and under varying experimental conditions. Additionally, using the same underlying principle, we improved the system for ESR measurement using both venipuncture and fingerprick whole blood samples depending on the user needs. The results demonstrate that the system performs equally well with both samples, which validates the compatibility of the system for both laboratory and point-of-care applications where venous and capillary blood are the primary samples, respectively. The detailed characterization presented in this study legitimates the feasibility of the system for ultrafast and facile measurement of ESR in clinics and diverse off-laboratory settings.     

Extended Spectral Regression for efficient scene recognition

This paper proposes a novel method based on Spectral Regression (SR) for efficient scene recognition. First, a new SR approach, called Extended Spectral Regression (ESR), is proposed to perform manifold learning on a huge number of data samples. Then, an efficient Bag-of-Words (BOW) based method is developed which employs ESR to encapsulate local visual features with their semantic, spatial, scale, and orientation information for scene recognition. In many applications, such as image classification and multimedia analysis, there are a huge number of low-level feature samples in a training set. It prohibits direct application of SR to perform manifold learning on such dataset. In ESR, we first group the samples into tiny clusters, and then devise an approach to reduce the size of the similarity matrix for graph learning. In this way, the subspace learning on graph Laplacian for a vast dataset is computationally feasible on a personal computer. In the ESR-based scene recognition, we first propose an enhanced low-level feature representation which combines the scale, orientation, spatial position, and local appearance of a local feature. Then, ESR is applied to embed enhanced low-level image features. The ESR-based feature embedding not only generates a low dimension feature representation but also integrates various aspects of low-level features into the compact representation. The bag-of-words is then generated from the embedded features for image classification. The comparative experiments on open benchmark datasets for scene recognition demonstrate that the proposed method outperforms baseline approaches. It is suitable for real-time applications on mobile platforms, e.g. tablets and smart phones.     

工业过程的一类时变模型的建立与控制方法研究

电渣重熔过程是典型的时变系统。电渣重熔炉冶炼质量高的原因在于过程熔速控制均匀。本文通过现场运行数据采集与仿真分析，详细解析了电渣重熔炉过程中诸多参数之间的相互关系，提出并实现了电渣重熔炉的时变系统模型，并成功的应用于邢台机械轧辊集团铸钢分厂美国康萨克15吨电渣炉技改项目上。通过现场6个月的实际运行，控制效果良好，部分参数甚至优于原控制系统。     

计算机控制的SEESR实验系统的研制

SEESR(Simultaneous Electrochemical ESR)是研究电极过程中的自由基中间体行为的理想和方便的手段。在以前研制的ESR仪数据系统的基础上,我们应用IBM-PC/XT微机与JES-FE1XG型(JEOL产)ESR谱仪及HDV-7型恒电位仪研制了一套由计算机控制的SEESR实验装置。该系统可以完成包括循环伏安法、电流阶跃、电位阶跃及电位反转等多种电化学方法的SEESR实验。系统还具有包括数据平滑、曲线拟合等功能的多种数据处理软件,使用方便。我们应用模型化合物对该系统进行了实际测量,所得结果与文献报道一致。     

电渣重熔过程中两相区的识别

本文利用热传导方程中参数识别方法,将电渣重熔过程中两相区的识别问题化为最优控 制问题来解决.根据脉冲变分原理,给出了识别参数的梯度公式及计算方法,最后的仿真结 果说明了该方法的可行性.     

人脸特征点定位的自适应窗回归方法

针对显式形状回归（ESR）对于一些面部遮挡、面部表情过大样本定位精度低的问题，提出一种自适应窗回归方法。首先，应用先验信息为每张图片生成精确的人脸框，用人脸框的中心点对人脸进行特征映射，并进行相似变换得到多个初始形状；其次，提出一种自适应窗口调整策略，基于先前回归的均方误差自适应地调整特征窗口大小；最后，基于互信息（MI）的特征选择策略，提出新的相关性计算方法，在候选像素集中选出最相关的特征。在三个公开数据集LFPW、HELEN、COFW上，相较于ESR算法，所提方法的定位精度分别提升7.52%、5.72%和5.89%。实验结果表明，自适应窗回归方法可以有效提高人脸特征点定位精度。     

Robust emotional speech classification in the presence of babble noise

Emotional speech recognition (ESR) is a new field of research in the realm of human-computer interactions. Most of the studies in this field are performed in clean environments. Nevertheless, in the real world conditions, there are different noise and disturbance parameters such as car noise, background music, buzz and etc., which can decrease the performance of such recognizing systems. One of the most common noises which can be heard in different places is the babble noise. Because of the similarity of this kind of noise to the desired speech sounds, babble or cross-talk, is highly challenging for different speech-related systems. In this paper, in order to find the most appropriate features for ESR in the presence of babble noise with different signal to noise ratios, 286 features are extracted from speech utterances of two emotional speech datasets in German and Persian. Then the best features are selected among them using different filter and wrapper methods. Finally, different classifiers like Bayes, KNN, GMM, ANN and SVM are used for the selected features in two ways, namely multi-class and binary classifications.     

获取张北地震同震形变场的差分干涉测量技术

基于合成孔径雷达差分干涉测量的基本原理,利用地震前后的ＥＲＳ－１／２的三景数据,获取了１９９８年１月１０日张北地震（Ｍｓ＝６．２级）的同震干涉纹图。这种差分干涉纹图能表现地震断层和形变场的同震形变特征,而且该方法无需任何的辅助信息,适用于大范围的地震监测与研究,研究表明,通过合成孔径雷达差分干涉测量技术能够获取高精的强震同震位移场数据,这是传统的地面观测方法所无法做到的。     

ESR—A large knowledge-based system project of european power generation industry

The paper presents an integrated knowledge-based system aimed at providing technical support to engineers performing assessment and management of remaining life of the high-temperature pressurized components, mainly piping, in power plants. The system (ESR) is being developed at MPA Stuttgart (Germany) with support and under sponsorship of seven European electric utility companies. The initial requirements imposed by the utilities have been met by integrating various sources of knowledge, information, and data, as well as various information technology tools and techniques. The expert system modules use both production rules and object-oriented programming (decision/analysis support) and rely strongly on other integrated software: hypermedia (documentation base and explanation facility), numerics (engineering calculi), and data bases (material, standard geometries, etc.).     

完美前向安全的基于身份认证密钥协商方案

现有的基于身份的一轮认证密钥协商方案没能实现强的完美前向性.采用强不可伪造的签名算法对临时公钥进行签名,提出一种改进的基于身份认证密钥协商方案.首先,对Boneh和Boyen提出的强不可伪造的短签名方案进行改造,提出一种强不可伪造的基于身份签名方案;然后,将新签名方案与Ni等人提出的eCK安全的基于身份一轮认证密钥协商方案相结合,提出新的密钥协商方案.进一步,为了实现新方案的可证明安全性,在对比分析eCK-PFS模型和eCK模型的基础上,融合现有安全模型,定义了基于身份认证密钥协商方案分析的强安全模型ID-eCK-PFS.在ID-eCK-PFS模型下,通过安全性规约,证明了新提出的基于身份认证密钥协商方案实现了强安全性,包括抗密钥泄露伪装、抗临时秘密泄露和完美前向安全性等.