SABUL: A Transport Protocol for Grid Computing

This paper describes SABUL, an application-level data transfer protocol for data-intensive applications over high bandwidth-delay product networks. SABUL is designed for reliability, high performance, fairness and stability. It uses UDP to transfer data and TCP to return control messages. A rate-based congestion control that tunes the inter-packet transmission time helps achieve both efficiency and fairness. In order to remove the fairness bias between flows with different network delays, SABUL adjusts its sending rate at uniform intervals, instead of at intervals determined by round trip time. This protocol has demonstrated its efficiency and fairness in both experimental and practical applications. SABUL has been implemented as an open source C++ library, which has been successfully used in several Grid computing applications.     

Multi-symplectic methods for the coupled 1D nonlinear Schrödinger system

In the paper, the multi-symplectic formulation of the coupled 1D nonlinear Schrödinger system (CNLS) is considered. For the multi-symplectic formulation, a new six point scheme, which is equivalent to the multi-symplectic Preissman integrator, is derived. We also present numerical experiments, which show that the multi-symplectic scheme has excellent long-time numerical behaviour and energy conservation property.     

Classification of heart rate data using artificial neural network and fuzzy equivalence relation

The electrocardiogram is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, etc. may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the signal parameters, extracted and analysed using computers, are highly useful in diagnostics. This paper deals with the classification of certain diseases using artificial neural network (ANN) and fuzzy equivalence relations. The heart rate variability is used as the base signal from which certain parameters are extracted and presented to the ANN for classification. The same data is also used for fuzzy equivalence classifier. The feedforward architecture ANN classifier is seen to be correct in about 85% of the test cases, and the fuzzy classifier yields correct classification in over 90% of the cases.     

Stochastic stabilization of differential systems with general decay rate

Some sufficient conditions concerning stability of solutions of stochastic differential evolution equations with general decay rate are first proved. Then, these results are interpreted as suitable stabilization ones for deterministic and stochastic systems. Also, they permit us to construct appropriate linear stabilizers in some particular situations.     

层叠式Si-PIN伽玛探测器

利用Monte-Carlo方法对新研制的层叠式Si-PIN伽玛探测器的伽玛灵敏度进行了理论计算。结果表明，层叠式Si-PIN伽玛探测器相对于单个的Si-PIN探测器具有更高的灵敏度，而且伽玛灵敏度与每层间的聚四氟乙烯片的厚度有关。实验测量的层叠式探测器和普通单个探测器对1.25MeV的伽玛灵敏度与理论计算值相当。     

电阻器设计研究探讨

阐述了电阻器设计的基本原则，提出根据给定的电阻允差，求出电阻的偏差值，再根据偏差值及材料尺寸偏差，得出材料的加工偏差的方法；此外，电阻器的热耗散可根据本文提供的值进行计算，然后对比一些成熟的产品再作修正，通过多次反复，取得经验，就可以设计出合乎要求的电阻器。     

降低妈湾电厂空预器漏风率的措施

为降低空预器漏风率，从结构设计分折得出空、烟气压差大和密封间隙大是其漏风的主要原因，通过采取高压水冲洗，气脉冲燃气吹灰，双密封改造，空预器重新选型等一系列措施来降低漏风率。     

提高200MW机组高压加热器投入率的研究

通过对武汉钢电股份有限公司2台200MW机组2年来高压加热器运行状况的统计分析，找出影响高加投入率的主要原因，提出相应的技术改造和技术措施，大大提高了高加投入率。     

有限资金约束下独立方案的比选

通过对独立方案在有限资金的约束下,进行方案组合比选的两种方法进行讨论,使两种方法结合在一起形成一种新的比选方法.     

全负压烟囱选型浅析

对全程全负压烟囱造型的理论依据及造型原则作了详细的介绍，并从经济技术角度作了分析，指出了全程全负压烟囱随着火电厂单机容量的增大和环境保护日趋严格的要求，必将在我国大力推广应用。