智能涡街流量变送器

介绍采用MSP430微功耗微处理构成的智能补偿电路及软件。该电路接受涡街流量变送器输出的脉冲fi，根据频率fi一线性度E曲线，软件采用多点线性内查补偿运算出与流量成正比的频率fic，为确保频率fic的转换精度，微处理器的定时器接受双时钟源，输出占空比为50％PWM方波，从而提高变送器的线性度及准确度。     

To analyze binary data from mixed-level orthogonal arrays

Orthogonal arrays of mixed levels have been found useful in setting up highly fractional factorial experiments. When the responses from such experiments are binary, logistic regression analysis is used to analyze such data. Usually, the maximum likelihood estimates of parameters under the logistic regression model need to be found by an iterative procedure in order to test the importance of factors. In this article, a simple approximate procedure is proposed and compared to the maximum likelihood method with an example.     

Identification of Kalman-Bucy filters from noisy measurement arrays

The paper presents a method for jointly identifying all the parameters of the transition, input-covariance and measurement-noise eovarianee matrices from noisy measurements if no a priori parameter knowledge is available. The method is first derived for single-input—single-output processes and is further extended to single-input-multi-output processes and finally to multi-input-multi-output processes. The convergence of the resulting parameter estimates is discussed and computation results are given for the singlo-input—single-output ease, for the single-input-multi-output case (two outputs) ami for the multi-input—multi-output ease (two inputs and two outputs) to demonstrate the readability of the method.     

跟踪型数字滤波方法在涡街信号处理中的应用

涡街流量计广泛应用于流量测量领域。由于测量现场工况复杂,涡街流量信号常会掺杂着各种噪声干扰。尤其低流速时,涡街信号微弱,常被噪声淹没,如何提取真实的涡街信号是涡街信号处理的难点。提出一种新的算法来滤除噪声并提取涡街信号。该算法是基于涡街信号特征来设计的一种特殊滤波器,它能够实现涡街信号幅1／f2值衰减并且动态跟踪真实涡街信号频率。实验结果表明该算法能够自动识别涡街信号,滤除噪声。该算法严格控制了计算量,信号处理精度高,适合于工业现场应用。     

Synthesizing systolic arrays with control signals from recurrence equations

We present a technique for synthesizing systolic arrays which have non-uniform data flow governed by control signals. The starting point for the synthesis is anAffine Recurrence Equation—a generalization of the simple recurrences encountered in mathematics. A large class of programs, including most (single and multiple) nested-loop programs can be described by such recurrences. In this paper we extend our earlier work (Rajopadhye and Fujimoto 1986) in two principal directions. Firstly, we characterize a class of transformations calleddata pipelining and show that they yield recurrences that havelinear conditional expressions governing the computation. Secondly, we discuss the synthesis of systolic arrays that have non-uniform data flow governed by control signals. We show how to derive the control signals in such arrays by applying similar pipelining transformations to theselinear conditional expressions. The approach is illustrated by deriving the Guibas-Kung-Thompson architecture for computing the cost of optimal string parenthesization.Supported by a University of Utah Graduate Research Fellowship, and NSF grant No. MIP-8802454     

Unified selection from lists,arrays, and objects

The first language computer science students learn, more often than not, is a common production language such as C++ or Java. A minority of curricula, however, begin with a language, such as Scheme, assumed to be a better framework for teaching about computation. SWAY is an experimental teaching language, as expressive as Scheme, but provides an easier transition to production languages. It is a functional language at its core, but adds assignment and a simple object system. One of the goals of SWAY is to incorporate C-style syntax, but to vary from that syntax when pedagogical or ease of programming needs arise. One such area that SWAY differs from languages with C-like expressions is in the selection of items from homogeneous and heterogeneous aggregates. Much like the overloading of the plus operator to add integers as well as reals, a single operator is used for selection in SWAY, regardless of the aggregate structure. It is shown that taking such an approach naturally eases the burden of moving from arrays to objects to lists, in any order, both in teaching and programming.     

Optimal simulation of tree arrays by linear arrays

We show that an n-node complete binary tree can be embedded into an n-node linear array such that the maximum edge length is n/log n, and the distribution of the tree nodes is regular in the sense that if each node in the tree array is a finite-state machine and each edge is a communication channel, then the message exchanges (i.e., communication) among the tree nodes can be easily simulated by the linear array which has also finite-state machines for its nodes. The embedding is optimal with respect to the maximum edge length. The motivation for this is the proof of the following result: every cellular (or (log n)-depth iterative) tree array running in T(n) time can be simulated by a linear cellular (or iterative) array in nT(n)/log n time.     

Unimodular arrays

This paper explores relationships between optimal erasure-burst-correcting convolutional codes, arrays of integers within which all submatrices whose upper left corner lies on a certain boundary have determinant one, and enumerations of certain parts within such arrays.     

流系统的降载技术

流数据连续查询及优化研究已成为当前国际数据库研究领域的一个热点。数据流的到达速率经常是不可预测的且具有很高的突发性,数据流速这种不规则的变化会引起系统负载急剧的波动。当输入速率超过系统处理能力时,系统会发生过载并且导致系统性能的恶化,降载技术是解决此问题最有效的途径之一。对降载技术中系统负载估计、降载器的最佳的放置位置、降载量的大小、降载器合并等关键问题进行了讨论。     

涡街流量计及其应用

介绍了涡街流量计的工作原理、分类、特点 ,以及选型和应用中所需注意的事项。     

Visualization of magnetically confined plasmas

With the rapid developments in experimental and theoretical fusion energy research towards more geometric details, visualization plays an increasingly important role. In this paper we will give an overview of how visualization can be used to compare and contrast some different configurations for future fusion reactors. Specifically we will focus on the stellarator and tokamak concepts. In order to gain understanding of the underlying fundamental differences and similarities these two competing concepts are compared and contrasted by visualizing some key attributes. Received: 21 April 1998 / Accepted: 22 December 1998     

涡街流量计的研究

涡街流量计是目前发展势头十分良好的流量计,在管道流量测量中得到广泛应用,并已跻身通用流量计之列.但涡街流量计尚属发展中流量计,其理论基础和实践经验较薄弱,在使用中,还会出现一些预想不到的问题.为解决这些问题,国内外科研工作者进行了大量的研究工作,并取得了一定进展.从涡街流量计中旋涡分离、涡街发生体形状、涡街信号检测方法及涡街信号分析和处理几方面对国内外研究现状进行了综述,指出研究中存在的难点及今后的研究方向,并提出一种利用涡街原理的新质量流量测量方法.     

多变量涡街变送器的研究

在生产过程自动控制领域中,用1台仪表同时进行温度、压力、流量等参数测量的多变量变送器是非常重要的,介绍了多变量变送器的工作原理、结构,讨论了二线制变送器的设计难点。     

消除涡街流量计的使用障碍

文章阐述了涡街流量计在石油化工装置工程设计和使用过程中出现的问题，并着重就进口涡街流量计与管道内径匹配问题及涡街流量计在蒸汽流量测量中的温压补偿问题提供了简单的分析方法和计算公式。     

A quick tour on suffix arrays and compressed suffix arrays

Suffix arrays are a key data structure for solving a run of problems on texts and sequences, from data compression and information retrieval to biological sequence analysis and pattern discovery. In their simplest version, they can just be seen as a permutation of the elements in {1,2,…,n}, encoding the sorted sequence of suffixes from a given text of length n, under the lexicographic order. Yet, they are on a par with ubiquitous and sophisticated suffix trees. Over the years, many interesting combinatorial properties have been devised for this special class of permutations: for instance, they can implicitly encode extra information, and they are a well characterized subset of the n! permutations. This paper gives a short tutorial on suffix arrays and their compressed version to explore and review some of their algorithmic features, discussing the space issues related to their usage in text indexing, combinatorial pattern matching, and data compression.     

输电线脱冰过程中耐张串金具的受力仿真分析

针对脱冰过程中导线张力对输电线连接金具的破坏作用,运用ABAQUS软件分别建立特高压输电线路的导线模型和耐张串连接金具的整体模型.然后基于改变密度法模拟均匀覆冰的六分裂导线和覆冰脱落过程,研究不同步脱冰时各子导线的动态张力和导线束扭转角的变化规律,结果表明未脱冰子导线的动态最大张力大于导线覆冰静态张力,导线动张力与导线...     

General-purpose systolic arrays

The extension of systolic array architecture from fixed- or special-purpose architectures to general-purpose, SIMD (single-instruction stream, multiple-data stream), MIMD (multiple-instruction stream, multiple-data stream) architectures, and hybrid architectures that combine both commercial and FPGA (field-programmable gate array) technologies is chronicled. The authors present a taxonomy for systolic organizations, discuss each architecture's methods of exploiting concurrencies, and compare performance attributes of each. The authors also describe a number of implementation issues that determine a systolic array's performance efficiency, such as algorithms and mapping, system integration through memory subsystems, cell granularity, and extensibility to a wide variety of topologies     

CPU load shedding for binary stream joins

We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept ofselective processing for load shedding. We allow stream tuples to be stored in the windows and shed excessive CPU load by performing the join operations, not on the entire set of tuples within the windows, but on a dynamically changing subset of tuples that are learned to be highly beneficial. We support such dynamic selective processing through three forms of runtimeadaptations: adaptation to input stream rates, adaptation to time correlation between the streams and adaptation to join directions. Our load shedding approach enables us to integrateutility-based load shedding withtime correlation-based load shedding. Indexes are used to further speed up the execution of stream joins. Experiments are conducted to evaluate our adaptive load shedding in terms of output rate and utility. The results show that our selective processing approach to load shedding is very effective and significantly outperforms the approach that drops tuples from the input streams. Bugra Gedik received the B.S. degree in C.S. from the Bilkent University, Ankara, Turkey, and the Ph.D. degree in C.S. from the College of Computing at the Georgia Institute of Technology, Atlanta, GA, USA. He is with the IBM Thomas J. Watson Research Center, currently a member of the Software Tools and Techniques Group. Dr. Gedik's research interests lie in data intensive distributed computing systems, spanning data-centric peer-to-peer overlay networks, mobile and sensor-based distributed data management systems, and distributed data stream processing systems. His research focus is on developing system-level architectures and techniques to address scalability problems in distributed continual query systems and applications. He is the recipient of the ICDCS 2003 best paper award. He has served in the program committees of several international conferences, such as ICDE, MDM, and CollaborateCom. Kun-Lung Wu received the B.S. degree in E.E. from the National Taiwan University, Taipei, Taiwan, the M.S. and Ph.D. degrees in C.S. both from the University of Illinois at Urbana-Champaign. He is with the IBM Thomas J. Watson Research Center, currently a member of the Software Tools and Techniques Group. His recent research interests include data streams, continual queries, mobile computing, Internet technologies and applications, database systems and distributed computing. He has published extensively and holds many patents in these areas. Dr. Wu is a Senior Member of the IEEE Computer Society and a member of the ACM. He is the Program Co-Chair for the IEEE Joint Conference on e-Commerce Technology (CEC 2007) and Enterprise Computing, e-Commerce and e-Services (EEE 2007). He was an Associate Editor for the IEEE Trans. on Knowledge and Data Engineering, 2000–2004. He was the general chair for the 3rd International Workshop on E-Commerce and Web-Based Information Systems (WECWIS 2001). He has served as an organizing and program committee member on various conferences. He has received various IBM awards, including IBM Corporate Environmental Affair Excellence Award, Research Division Award, and several Invention Achievement Awards. He received a best paper award from IEEE EEE 2004. He is an IBM Master Inventor. Philip S. Yu received the B.S. Degree in E.E. from National Taiwan University, the M.S. and Ph.D. degrees in E.E. from Stanford University, and the M.B.A. degree from New York University. He is with the IBM Thomas J. Watson Research Center and currently manager of the Software Tools and Techniques group. His research interests include data mining, Internet applications and technologies, database systems, multimedia systems, parallel and distributed processing, and performance modeling. Dr. Yu has published more than 430 papers in refereed journals and conferences. He holds or has applied for more than 250 US patents. Dr. Yu is a Fellow of the ACM and a Fellow of the IEEE. He is associate editors of ACM Transactions on the Internet Technology and ACM Transactions on Knowledge Discovery in Data. He is a member of the IEEE Data Engineering steering committee and is also on the steering committee of IEEE Conference on Data Mining. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001–2004), an editor, advisory board member and also a guest co-editor of the special issue on mining of databases. He had also served as an associate editor of Knowledge and Information Systems. In addition to serving as program committee member on various conferences, he will be serving as the general chair of 2006 ACM Conference on Information and Knowledge Management and the program chair of the 2006 joint conferences of the 8th IEEE Conference on E-Commerce Technology (CEC' 06) and the 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE' 06). He was the program chair or co-chairs of the 11th IEEE Intl. Conference on Data Engineering, the 6th Pacific Area Conference on Knowledge Discovery and Data Mining, the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, the 2nd IEEE Intl. Workshop on Research Issues on Data Engineering: Transaction and Query Processing, the PAKDD Workshop on Knowledge Discovery from Advanced Databases, and the 2nd IEEE Intl. Workshop on Advanced Issues of E-Commerce and Web-based Information Systems. He served as the general chair of the 14th IEEE Intl. Conference on Data Engineering and the general co-chair of the 2nd IEEE Intl. Conference on Data Mining. He has received several IBM honors including 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, 2 Research Division Awards and the 84th plateau of Invention Achievement Awards. He received an Outstanding Contributions Award from IEEE Intl. Conference on Data Mining in 2003 and also an IEEE Region 1 Award for “promoting and perpetuating numerous new electrical engineering concepts” in 1999. Dr. Yu is an IBM Master Inventor. Ling Liu is an associate professor at the College of Computing at Georgia Tech. There, she directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining research issues and technical challenges in building large scale distributed computing systems that can grow without limits. Dr. Liu and the DiSL research group have been working on various aspects of distributed data intensive systems, ranging from decentralized overlay networks, exemplified by peer to peer computing, data grid computing, to mobile computing systems and location based services, sensor network computing, and enterprise computing systems. She has published over 150 international journal and conference articles. Her research group has produced a number of software systems that are either open sources or directly accessible online, among which the most popular ones are WebCQ and XWRAPElite. Dr. Liu is currently on the editorial board of several international journals, including IEEE Transactions on Knowledge and Data Engineering, International Journal of Very large Database systems (VLDBJ), International Journal of Web Services Research, and has chaired a number of conferences as a PC chair, a vice PC chair, or a general chair, including IEEE International Conference on Data Engineering (ICDE 2004, ICDE 2006, ICDE 2007), IEEE International Conference on Distributed Computing (ICDCS 2006), IEEE International Conference on Web Services (ICWS 2004). She is a recipient of IBM Faculty Award (2003, 2006). Dr. Liu's current research is partly sponsored by grants from NSF CISE CSR, ITR, CyberTrust, a grant from AFOSR, an IBM SUR grant, and an IBM faculty award.     

Vortex Sheet Intensity Computation in Incompressible Flow Simulation Around an Airfoil by Using Vortex Methods

A numerical scheme is developed to simulate a flow around airfoils by using vortex methods. For this scheme, a numerical algorithm is constructed and exact analytical expressions are obtained for the coefficients of a system of linear algebraic equations. For some test problems, it is shown that the developed scheme allows us to solve a wider class of problems and provides much more accurate results in comparison with the known approaches.     

Wafer-scale transducer arrays

The production of wafer-scale transducer arrays using laser interconnection techniques and micromatching technology is discussed. The design of a wafer-scale thermal dynamic scene simulator that was implemented using the laser-linking redundancy technique is presented to illustrate typical design requirements. The simulator uses small arrays of thermal pixels and control circuitry in 3 μm CMOS technology