Obliging Institutions and Industry Evolution: A Comparative Study of the German and UK Wind Energy Industries

This paper firstly examines the relationship between state coordination and wind energy growth by comparing the differences between UK and German institutional configurations and state involvements in the 1990s. While the EU was calling for a unified regulatory framework for its member states, the UK and Germany adopted very different renewable energy policies. The evidence of the early 1990s shows that the British government employed “deregulation” with so limited state involvement that wind energy project developers faced thorny development problems, while the German government tried to require the electricity supply industry to purchase expensive wind power by “regulation” but encountered formidable resistance. Nevertheless, both the British and German administrations later could resolve these problems through new forms of state power. This suggests that, firstly, neither “deregulation” nor “regulation” is an effective means to develop wind power with increasing electricity liberalization and regionalization. Secondly, “obliging” regulations and state powers are vital to the policy outcome by harnessing the state's institutional capacity to smooth out technology innovation and diffusion.     

Three generations of asynchronous microprocessors

We trace the evolution of Caltech asynchronous processors from a simple proof of concept, to a high-performance MIPS-like processor using a different buffer circuit for better performance, to the latest 8051 clone targeting low-energy operation. We describe the control aspects of the evolving circuit styles. We describe these three generations of asynchronous microprocessors (Caltech asynchronous processors, MiniMIPS and Lutonium) and the corresponding circuit families and design methods. The asynchronous circuits we use are called quasidelay-insensitive (QDI) circuits. A QDI circuit involves no assumption about, or knowledge of, delays in operators and wires, except for isochronic forks, which the designer assumes have similar delays on the different branches. QDI circuits are the most conservative asynchronous circuits in terms of delays.     

Developing an Automated Enzyme Immunoassay for High-Throughput Screening of Bovine Serum Antibodies to Neospora Caninum

An enzyme-linked immunosorbent assay (ELISA) for Neospora caninum antibodies was automated with a robotic workstation, the Beckman Coulter Biomek 2000, to screen 200 bovine sera. Comparing these results with manually run ELISA data, a 95.92% agreement (K = 0.9592) between the two assays was obtained. The automated assay was specific and sensitive with excellent positive and negative predictive values. The results were repeatable and reproducible. The automation flexibility was high and the operation complexity was minimal. High-throughput screening (HTS) for bovine antibodies to Neospora caninum was achieved. The assay was developed according to the internationally recognized ISO17025 standard requirements.     

An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem

As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novel learning rule. It is called the integrated SOM (ISOM) since its learning rule integrates the three learning mechanisms in the SOM literature. Within a single learning step, the excited neuron is first dragged toward the input city, then pushed to the convex hull of the TSP, and finally drawn toward the middle point of its two neighboring neurons. A genetic algorithm is successfully specified to determine the elaborate coordination among the three learning mechanisms as well as the suitable parameter setting. The evolved ISOM (eISOM) is examined on three sets of TSP to demonstrate its power and efficiency. The computation complexity of the eISOM is quadratic, which is comparable to other SOM-like neural networks. Moreover, the eISOM can generate more accurate solutions than several typical approaches for TSP including the SOM developed by Budinich, the expanding SOM, the convex elastic net, and the FLEXMAP algorithm. Though its solution accuracy is not yet comparable to some sophisticated heuristics, the eISOM is one of the most accurate neural networks for the TSP.     

From association to classification: inference using weight of evidence

Association and classification are two important tasks in data mining and knowledge discovery. Intensive studies have been carried out in both areas. But, how to apply discovered event associations to classification is still seldom found in current publications. Trying to bridge this gap, this paper extends our previous paper on significant event association discovery to classification. We propose to use weight of evidence to evaluate the evidence of a significant event association in support of, or against, a certain class membership. Traditional weight of evidence in information theory is extended here to measure the event associations of different orders with respect to a certain class. After the discovery of significant event associations inherent in a data set, it is easy and efficient to apply the weight of evidence measure for classifying an observation according to any attribute. With this approach, we achieve flexible prediction.     

Off-line handwritten Chinese character recognition as a compoundBayes decision problem

A handwritten Chinese character off-line recognizer based on contextual vector quantization (CVQ) of every pixel of an unknown character image has been constructed. Each template character is represented by a codebook. When an unknown image is matched against a template character, each pixel of the image is quantized according to the associated codebook by considering not just the feature vector observed at each pixel, but those observed at its neighbors and their quantization as well. Structural information such as stroke counts observed at each pixel are captured to form a cellular feature vector. Supporting a vocabulary of 4616 simplified Chinese characters and alphanumeric and punctuation symbols, the writer-independent recognizer has an average recognition rate of 77.2 percent. Three statistical language models for postprocessing have been studied for their effectiveness in upgrading the recognition rate of the system. Among them, the CVQ-based language model is the most effective one upgrading the recognition rate by 10.4 percent on the average     

求解结构动应力有限元方法的新探讨

利用常规有限元方法，结合数值计算方法对振型函数进行［Ｌ］算子的微分计算，从而可方便迅速的得到了复杂结构动应力响应，通过算例计算表明该方法具有较高的精度，较一般的动态有限元具有通用性强、计算简单等特点     

Object-oriented CAD for Hydraulic Circuits of Pressing Machines

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Compiler Support for Array Distribution on NUMA Shared Memory Multiprocessors

Management of program data to improve data locality and reduce false sharing is critical for scaling performance on NUMA shared memory multiprocessors. We use HPF-like data decomposition directives to partition and place arrays in data-parallel applications on Hector, a shared-memory NUMA multiprocessor. We describe a compiler system for automating the partitioning and placement of arrays. The compiler exploits Hectors shared memory architecture to efficiently implement distributed arrays. Experimental results from a prototype implementation demonstrate the effectiveness of these techniques. They also demonstrate the magnitude of the performance improvement attainable when our compiler-based data management schemes are used instead of operating system data management policies; performance improves by up to a factor of 5.