STUDY ON RESIDUES OF ~（14）C－FENITROTHION IN MODEL RICE－FISH ECOSYSTEM AND FIELD RICE－FISH ECOSYSTEM

ＳＴＵＤＹＯＮＲＥＳＩＤＵＥＳＯＦ~（１４）Ｃ－ＦＥＮＩＴＲＯＴＨＩＯＮＩＮＭＯＤＥＬＲＩＣＥ－ＦＩＳＨＥＣＯＳＹＳＴＥＭＡＮＤＦＩＥＬＤＲＩＣＥ－ＦＩＳＨＥＣＯＳＹＳＴＥＭＺｈａｎｇＺｈｏｎｇｌｉａｎｇ（张仲良）；ＷａｎｇＨｕａｘｉｎ（王化新）；Ｇ?..     

Efficient model reduction in non-linear dynamics using the Karhunen-Loève expansion and dual-weighted-residual methods

 We look at the task of computing the time-evolution of a non-linear system for a long time, in our case under random external influences. Our specific example is the fatigue evaluation of a wind turbine. To facilitate such a computation, we look at a reduction of the computational effort by projecting everything on a low-dimensional basis. In this case we take the Karhunen-Loève basis generated from running the model a little while under the random loading. It is important that the error which is caused by this reduction process can be controlled. We estimate the error by dual or adjoint methods. This in turn allows the process of model reduction to be performed adaptively. Dedicated to the memory of Prof. Mike Crisfield, for his cheerfulness and cooperation as a colleague and friend over many years.     

Modelling and experimental investigation of devolatilizing wood in a fluidized bed combustor

A two-dimensional model is developed for the determination of devolatilization time and char yield of cylindrical wood particles in a bubbling fluidized bed combustor. By using the concept of shape factor, the model is extended to particles of cuboid shape. The model prediction of the devolatilization time agrees with the measured data (present and those reported in the literature) for cylindrical and cuboidal shaped particles within ±20% while the char yield is predicted within ±17%. Influence of some important parameters namely, thermal diffusivity, external heat transfer coefficient and shrinkage, on the devolatilization time and char yield are studied. Thermal diffusivity shows noticeable influence on devolatilization time. The external heat transfer coefficient shows little influence beyond a value of 300 W/(m² K). However particle shrinkage shows negligible effect on the devolatilization time but has a significant influence on the char yield.     

Semi-supervised model adaptation for statistical machine translation

Statistical machine translation systems are usually trained on large amounts of bilingual text (used to learn a translation model), and also large amounts of monolingual text in the target language (used to train a language model). In this article we explore the use of semi-supervised model adaptation methods for the effective use of monolingual data from the source language in order to improve translation quality. We propose several algorithms with this aim, and present the strengths and weaknesses of each one. We present detailed experimental evaluations on the French–English EuroParl data set and on data from the NIST Chinese–English large-data track. We show a significant improvement in translation quality on both tasks.     

虚拟企业模型并行仿真研究

随着各种全新的制造理念,特别是虚拟企业的出现,企业模型的规模不断扩大,使目前存在的大多数企业模型仿真系统的效率大大下降。该文针对此问题,通过深入分析虚拟企业模型结构,并在已有的构件化企业建模体系CEMS及其仿真系统的基础上,结合异步仿真技术和多线程技术提出了一种分层式企业模型仿真体系结构,为虚拟企业模型的快速高效的仿真提供了一种有效的方法。     

涡轮增压柴油机模拟计算等压法的探讨

针对有些模拟计算可以忽略排气压力波的影响，提出了等压法计算的设想，这是一种每一工作循环缸外热力过程只计算一次的简化方法。分析结果表明，这种计算可以满足零维模型必须满足的所有制约方程，能真实地模拟涡轮增压柴油机的实际工作过程，适用于各种增压系统，但仍有待于进一步的研究与改进。根据等压法，建立了一种适用于定压涡轮系统的计算模型--“定压涡轮”模型，用于MPC增压系统的计算，计算结果与试验结果基本吻合，与容积法计算结果趋于一致，从而验证了模型的正确性，同时也表明这种缸外计算法是有效的。     

Step response classification for model-based autotuning via polygonal curve approximation

A model-based autotuning method consists of an identification and a regulator tuning phase. To achieve satisfactory performance and robustness, it is advisable that both phases be tailored a priori to the characteristics of the observed process dynamics. Such characteristics include, but are not limited to, the model structure. For example, overdamped and underdamped models with the same pole-zero structure are parametrised and controlled in different ways. Step response data, that are typically used for the identification phase in the autotuning context, can also be pre-processed to reveal those characteristics. This paper presents a step response classification method suitable for the above purpose. The method is based on a polygonal curve approximation technique for data pre-processing, followed by a neural network classifier. Only normalised I/O data are employed, so that the neural network can be trained off-line with simulated data. Simulation results are reported to show the effectiveness of the proposed classification method in terms of the achievable tuning results.     

Introductory Paper

In today’s competitive market designing of digital systems (hardware as well as software) faces tremendous challenges. In fact, notwithstanding an ever decreasing project budget, time to market and product lifetime, designers are faced with an ever increasing system complexity and customer expected quality. The above situation calls for better and better formal verification techniques at all steps of the design flow. This special issue is devoted to publishing revised versions of contributions first presented at the 12th Advanced Research Working Conference on Correct Hardware Design and Verification Methods (CHARME) held 21–24 October 2003 in L’Aquila, Italy. Authors of well regarded papers from CHARME’03 were invited to submit to this special issue. All papers included here have been suitably extended and have undergone an independent round of reviewing.