优序法在管理成果评价中的应用

在对管理成果进行评价时 ,首先要建立指标体系 ,而在这些指标当中有的可以定量描述 ,有的只能定性来描述 ,所以在评价时应当将定性和定量指标进行综合考虑。优序法就是通过对多目标决策问题进行两两相对比较 ,最后给出全部方案的优序排序。此方法应用简单 ,既能处理定量问题 ,又能处理定性问题。在建立管理成果指标体系的基础上 ,利用优序法 ,给出了管理成果评价方法。     

基于模糊规则的病虫害预防研究

基于Takagi-Sugeno模糊逻辑系统,运用遗传算法提取模糊规划,构建系统的模糊模型,并用于病虫害的预测工作。图2,表1,参6。     

A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase

Grain weight is one of the most important components of grain yield and is controlled by quantitative trait loci (QTLs) derived from natural variations in crops. However, the molecular roles of QTLs in the regulation of grain weight have not been fully elucidated. Here, we report the cloning and characterization of GW2, a new QTL that controls rice grain width and weight. Our data show that GW2 encodes a previously unknown RING-type protein with E3 ubiquitin ligase activity, which is known to function in the degradation by the ubiquitin-proteasome pathway. Loss of GW2 function increased cell numbers, resulting in a larger (wider) spikelet hull, and it accelerated the grain milk filling rate, resulting in enhanced grain width, weight and yield. Our results suggest that GW2 negatively regulates cell division by targeting its substrate(s) to proteasomes for regulated proteolysis. The functional characterization of GW2 provides insight into the mechanism of seed development and is a potential tool for improving grain yield in crops.     

An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting

For forecasting nonstationary and nonlinear energy prices time series, a novel adaptive multiscale ensemble learning paradigm incorporating ensemble empirical mode decomposition (EEMD), particle swarm optimization (PSO) and least square support vector machines (LSSVM) with kernel function prototype is developed. Firstly, the extrema symmetry expansion EEMD, which can effectively restrain the mode mixing and end effects, is used to decompose the energy price into simple modes. Secondly, by using the fine‐to‐coarse reconstruction algorithm, the high‐frequency, low‐frequency and trend components are identified. Furthermore, autoregressive integrated moving average is applicable to predicting the high‐frequency components. LSSVM is suitable for forecasting the low‐frequency and trend components. At the same time, a universal kernel function prototype is introduced for making up the drawbacks of single kernel function, which can adaptively select the optimal kernel function type and model parameters according to the specific data using the PSO algorithm. Finally, the prediction results of all the components are aggregated into the forecasting values of energy price time series. The empirical results show that, compared with the popular prediction methods, the proposed method can significantly improve the prediction accuracy of energy prices, with high accuracy both in the level and directional predictions. Copyright © 2016 John Wiley & Sons, Ltd.     

VR外设驱动的虚拟人姿态优化仿真方法

为解决常用的VR外设为穿戴于操作者身上的位置跟踪器,会给操作者带来额外不便的问题,提出一种基于视觉传感器组合的虚拟人驱动方案,实现简便无标记虚拟人运动实时驱动。引入参数化人体模型SMPL(skinned multi-person linear),通过最小化多个误差项组成的目标函数,改进算法提高虚拟人驱动精度,并计算得到符合真人形态与姿态的拟合人体模型数据,实现操作姿态人机工程学评价。实验结果表明：所提出的虚拟人数据驱动方法具有有效性。     

Hardy-Littlewood极大函数双权范数积分不等式的研究

对于Rn中形如∫J[f*(x)]pU(x)dx≤C∫J|f(x)|pU(x)dx的一类Hardy-Littlewood极大函数f*(x)的积分不等式进行了双权方向的研究,证明了它与权函数Ap条件之间的关系,并进一步推广到了任意测度空间.     

基于J2ME移动通讯设备软件的研究与开发

本文深入介绍了J2ME体系结构,分析了移动设备应用程序的结构和开发过程,讨论了将J2ME/M IDP应用程序和J2EE服务集成的方法,并预测了移动商务的前景.     

无可信中心的(t,k)门限RSA数字签名体制

提出了一种新的不需要可信中心的门限数字签名方案.在k个成员组成的群组中,只有t个或t个以上成员才能够代表群组签名,而少于t个成员则不能代表群组签名.方案基于Boneh等学者的分布式RSA密钥产生协议和Shamir秘密共享方案而构建.签名过程分为四个阶段:系统初始化、生成个体签名、生成群签名以及签名验证.在系统的初始化阶段不需要可信中心的参与,并且个体签名的生成、群签名的生成和验证都可以方便地实现.通过对方案的安全性分析显示,个体签名和群签名都是不可伪造的,并且在整个签名过程中都没有系统秘密信息的泄漏.     

多点损伤梁的波传播与振动功率流特性

基于结构噪声的观点研究了在集中力作用下多点损伤梁的波传播与振动功率流特性．采用局部转动弹簧来模拟梁中的损伤,利用断裂力学的有关理论得到局部弹簧的转动刚度。分析得到了两点损伤梁的弯曲波运动及振动功率流的输入和传播．讨论了振动功率流与损伤位置及其深度的关系,结果表明多点损伤梁中的振动功率流与各损伤点的位置以及其特征尺寸是相关联的．