漫射红外技术的智能家居无线局域网设计

分析了红外技术在短距离无线通信中的优势,并将其应用在智能家居局域网中;结合安华高科技公司的HSDL-3020红外收发模块搭建了硬件电路,构成网络的主从节点;介绍了网络组建的过程,包括IrDA协议栈结构、数据编码格式、链路连接、网络管理机制等。本设计实现了对家居设备的统一管理,具有较高的应用价值。     

A new admissibility condition of discrete-time singular systems with time-varying delays

This paper gives a novel delay-dependent admissibility condition of discrete-time singular systems with time-varying delays. For convenience, the time-varying delay is assumed to be the sum of delay lower bound and the integral multiples of a constant delay. Specially, if the constant delay is of unit length, the delay is an interval-like time-varying delay. The proposed admissibility condition is presented and expressed in terms of linear matrix inequality (LMI) by Lyapunov approach. Generally, the uncertainty of time-varying delay would lead to conservatism. In this paper, this critical issue is tackled by accurately estimating the time-varying delay. Consequently, the proposed admissibility condition is less conservative than the existing results, which is demonstrated by a numerical example.     

Data preprocessing using hybrid general regression neural networks and particle swarm optimization for remote terminal units

Data corruption in SCADA systems refers to errors that occur during acquisition, processing, or transmission, introducing unintended changes to the original data. In SCADA-based power systems, the data gathered by remote terminal units (RTUs) is subject to data corruption due to noise interference or lack of calibration. In this study, an effective approach based on the fusion of the general regression neural network (GRNN) and the particle swarm optimization (PSO) technique is employed to deal with errors in RTU data. The proposed hybrid model, denoted as GRNN-PSO, is able to handle noisy data in a fast speed, which makes it feasible for practical applications. Experimental results show the GRNN-PSO model has better performance in removing the unintended changes to the original data compared with existing methods.     

Analysis of gene expression programming for approximation in engineering design

To reduce the computational cost of implementing computer-based simulations and analyses in engineering design, a variety of metamodeling techniques have been developed and used for the construction of metamodels. Metamodels, also called approximation models and surrogate models, can be used to make a replacement of the expensive simulation codes for design and optimization. In this paper, gene expression programming (GEP) algorithm in the evolutionary computing area is investigated as an alternative metamodeling technique to provide the approximation of a design space. The approximation performance of GEP is tested on some low-dimensional mathematical and engineering problems. A comparative study is conducted on GEP and three common metamodeling techniques in engineering design (i.e., response surface methodology (RSM), kriging and radial basis functions (RBF)) for the approximation of the low-dimensional design space. Multiple evaluation criteria are considered in the comparison: accuracy, robustness, transparency and efficiency. Two different sample sizes are adopted: small and large. Comparative results indicate that GEP can achieve the most accurate and robust approximation of a low-dimensional design space for small sample sets. For large sample sets, GEP also presents good prediction accuracy and high robustness. Moreover, the transparency of GEP is the best since it can provide clear function relationships and factor contributions by means of compact expressions. As a novel metamodeling technique, GEP shows great promise for metamodeling applications in a low-dimensional design space, especially when only a few sample points are selected and used for training.     

Study on heat conduction and adsorption/desorption characteristic of MIL-101/few layer graphene composite

Journal of Porous Materials - Aiming at the poor heat conduction performance of porous MIL-101 applied in adsorption cooling process, few layer graphene (FLG) was selected as a promising thermal...     

焊接热源有效利用率的测试计算法

给出实际热输入值是正确求解焊接热弹塑性问题和焊接残余应力与变形问题的前提;因而,准确地确定热源有效利用率η,在焊接力学的发展中是一个急待解决的命题。本文推荐采用的“测试计算法”提供了一个能够准确、简捷地求得η值的新途径。引入被焊材料的熔化潜热系数后,给出了线热源加热焊缝金属至熔化温度(处于液态)时的实际热有效利用率ηt 的表达式。在四种不同类型的薄板材料上进行了钨极氩弧焊试验,测试计算结果与理论值相符合。理论推导与试验结果均证明,形成焊缝所需要的线能量的无量纲数值等于焊缝金属熔化热有效利用率ηt 的倒数。文中给出的焊接规范参数选择原则也适用于符合线热源条件的其它熔焊热源。η值不但与焊接工艺方法、规范参数有关,而且也随被焊材料的热物理特性不同而异。     

挤压变形对Mg95Zn4.3Y0.7合金组织和性能的影响

研究了在250℃、不同挤压比下挤压变形对Mg95 Zn4.3 Y0.7合金组织及性能的影响。结果表明，Mg95 Zn4.3 Y0.7经过挤压变形后，合金中晶界处的共晶相破碎，弥散分布至晶粒内部，并且晶粒显著细化。同时，随着挤压比的增大，晶粒细化程度增加，合金的力学性能单调增加。当挤压比为16时，合金晶粒尺寸为5-8μm，抗拉强度为288.9MPa，显微硬度HV值为117.8。     

长轴表面激光淬火变形与控制

应用激光淬火强化技术控制长轴的淬火变形，分析了激光淬火变形的原因和影响因素。研究结果表明，激光淬火不仅可使长轴振摆变形量控制在很小的范围内，而且可将已变形的长轴校直到很高的精度。     

搜索引擎页面排序算法研究综述*

系统地分析了现有的页面排序算法,指出了它们各自的优势和存在的不足,并指出不同算法在不同领域和场合所具有的优势。建立专业搜索引擎是提高搜索准确性和性能的有效途径。通过网格技术将各种专业搜索引擎集成在一起,形成一个基于网格的搜索引擎,从而更好地满足不同背景不同偏好的用户需求。     

一种结合特征相关的软件质量研究*

首先分析了目前常用的软件质量提高方法及评估标准,结合各种方法的优缺点,提出用户满意度和可靠性是软件成功的两个重要问题.首次提出特征因子的概念,并首次尝试借助神经网络通过特征因子对软件项目进行分析,并得出影响软件工程的影响度.其结论比较符合实际,为提高软件质量提供了一个可参考的方法.