中小型海水淡化装置及其能量回收技术的开发和应用

海水淡化是解决沿海地区淡水资源短缺问题的重要途径,目前我国适用于海岛、舰船和钻井平台等工况的中小型海水淡化装置及其能量回收技术还不完善。文章分别介绍手持式、自增压式和撬装式(船用、岛用和风光油储一体化)中小型海水淡化装置系列的技术特点,并按类别分别介绍装置关键技术即能量回收技术的工作原理,提出研发中小型海水淡化装置与能量回收一体机的系列化产品可有效降低能耗、促进技术进步和满足国内需求。     

MATLAB在运用系统建模处理南海气象数据过程中应用

介绍了MATLAB语言特点和系统建模方法的基本理论.根据南海气象数据的实际建模处理过程,给出了建模的详细步骤及其MATLAB实现过程以及MATLABTM的主要实现程序.试验讨论和结果表明利用MATLAB语言可以方便地对南海气象数据用系统建模方法进行建模和处理,MATLAB在运用系统建模法处理南海气象数据方面具有明显的优越性.     

基于噪声随机模型的加权观测融合方法

信息融合技术中,在各局部传感器的有色观测噪声为一阶AR模型的情况下,可以利用观测扩增方法消除有色噪声的影响,得到最优加权观测融合方程,从而实现状态的最优滤波解。对于有色观测噪声为MA或ARMA模型的情况,观测扩增方法不再适用。提出了基于有色观测噪声随机模型级数展开的方法,求解出各局部传感器有色观测噪声的方差,并利用该方差对加权观测融合滤波器进行了构造。通过计算实例证明,该方法不仅适用于观测噪声为AR模型,同时适用于噪声MA或ARMA模型。     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

分组密码的安全性与强化设计

分组密码是数据通讯中最常用的数据加密方式，以DES为例分析现有分组加密算法的安全隐患，并提出了可变密钥加密和变长密文输出两个新思路，可应用于所有现有分组加密算法以提高安全性，并就该方法的安全性、效率、具体应用做出了分析。     

2种亚洲龙鱼的D-Loop序列结构分析

采用PCR技术对2种亚洲龙鱼的mtDNAD_Loop全序列进行扩增和测序,序列结构分析和序列同源性比对结果表明,2种亚洲龙鱼的mtDNAD_Loop在靠近5’端有3个终止相关序列TAS(Ⅰ、Ⅱ、Ⅲ),靠近D_Loop的3’端有4个保守区域CSB1、CSB2、CSB3、CSB-D。在终止相关序列和保守区域之间是连续重复区域。经DNASP4.0软件分析,全序列中检测出多态位点数(S)为26,其中有17个转换,核苷酸多样性(Pi)为0.013,平均核苷酸差异数(K)为17.333。     

冰雹云雷达回波自动识别系统

利用CAPPI资料对立体风暴进行识别，计算并提供出实用的风暴结构参数，采用矩心踊跃法和矩不变量法相结合对单体风暴和混合性风暴回波进行跟踪；最小二第线性外推预报；根据WSD－88D的冰雹算法，在风暴结构基础上本文建立了Windows98操作平台上冰雹识别系统，经单站1年11次强对流天气过程的资料检验，结果表明：雹云识别精度达82％。系统建立了大量人机对话框以方便用户，增加实用性及推广性。     

Sequences in the Hardness Ratio-Peak Energy Plane of Gamma-Ray Bursts

The narrowness of the distribution of the peak energy of the vFv spectrum of gamma-ray bursts (GRBs) and the unification of GRB populations are great puzzles yet to be solved. We investigate the two puzzles based on the global spectral behaviors of different GRB populations, the long GRBs, the short GRBs, and the X-ray flashes (XRFs), in the HR - Ep plane (HR the spectral hardness ratio) with BATSE and HETE-2 observations. It is found that the long GRBs and the XRFs observed by HETE-2 seem to follow the same sequence in the HR-Ep plane, with the XRFs at the low end of this sequence. We fit the sequence by a universal Band function, and find that this sequence is mainly defined by the low energy index α, and is insensitive to the high energy index,β. With fixed β=-5, a best fit is given by α=-1.00 with X^2min/dof=2.2. The long and short GRBs observed by BATSE follow significantly different sequences in the HR-Ep plane, with most of the short GRBs having a larger hardness ratio than the long GRBs at a given Ep. For the long GRBs a best-fit yields α=-0.30 and β=-2.05. For the short GRBs, a best fit gives α=-0.60 with x^2min=1.1 (withβfixed at-2.0 because it is numerically unstable). The α value for the short GRBs is significantly greater than that for the long GRBs. These results indicate that the global spectral behaviors of the long GRB sample and the XRF sample are similar, while that of the short GRBs is different. The short GRBs seem to be a unique subclass of GRBs, and they are not the higher energy extension of the long GRBs.