医院计算机网络需适应现代医学的发展

随着时代的不断进步,计算机网络技术在远程医学、多所医院通过网络相互进行交流和医疗技术上的相互探讨研究上发挥着重要作用。因此,医院对计算机网络技术的要求越来越高。本文重点阐述计算机网络技术如何适应现代医学领域的广泛发展。     

INTELLIGENT SELF-DEVELOPING AND SELF-ADAPTIVE ELECTRIC LOAD FORECASTER BASED ON TYPE-2 FUZZY BAYESIAN YING-YANG LEARNING ALGORITHM

In new advocated “smart grid” development, an electric load forecaster should possess high-level intelligence in order to handle higher uncertainty, indefiniteness, and variability on electric load demand. The intelligence is referred to as self-learning, self-adaptability, and the highest capability of handling various uncertainties, which the forecaster should possess. In this study, a novel methodology, self-developing and self-adaptive fuzzy neural networks using type-2 fuzzy Bayesian Ying-Yang learning algorithm (SDSA-FNN-T2BYYL) is proposed. Its novelty is that (1) the Bayesian Ying-Yang learning algorithm (BYYL) is used to construct a compact system structure automatically. (2) Further, a novel T2 fuzzy BYYL is presented, which integrates type-2 (T2) fuzzy theory and BYYL in order to achieve two objectives simultaneously: compact system structure and better handling of data uncertainty. (3) Because a training dataset cannot include all possible operation conditions, the system should be able to restructure continuously for good generalization. Consequently, a T2 fuzzy BYY split-and-merge algorithm is proposed. The proposed method is validated using a real operational dataset collected from a Macao electric utility. Simulation and test results reveal that SDSA-FNN-T2BYYL has superior accuracy for load forecasting over other existing relevant techniques.     

Neural network based mobile phone localization using Bluetooth connectivity

Location information is useful for mobile phones. There exists a dilemma between the relatively high price of GPS devices and the dependence of location information acquisition on GPS for most phones in current stage. To tackle this problem, in this paper, we investigate the position inference of phones without GPS according to Bluetooth connectivity and positions of beacon phones. With the position of GPS-equipped phones as beacons and with the Bluetooth connections between neighbor phones as constraints, we formulate the problem as an optimization problem defined on the Bluetooth network. The solution to this optimization problem is not unique. Heuristic information is employed to improve the performance of the result in the feasible set. Recurrent neural networks are developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. The hardware implementation of the proposed neural network is also explored in this paper. Simulations and comparisons with different application backgrounds are considered. The results demonstrate the effectiveness of the proposed method.     

Decentralized control of collaborative redundant manipulators with partial command coverage via locally connected recurrent neural networks

This paper studies the decentralized control of multiple redundant manipulators for the cooperative task execution problem. Different from existing work with assumptions that all manipulators are accessible to the command signal, we propose in this paper a novel strategy capable of solving the problem even though there exists some manipulators unable to access the command signal directly. The cooperative task execution problem can be formulated as a constrained quadratic programming problem. We start analysis by re-designing the control law proposed in (Li et al. Neurocomputing, 2012), which solves the optimization problem recursively. By replacing the command signal with estimations with neighbor information, the control law becomes to work in the partial command coverage situation. However, the stability and optimality of the new system are not necessarily the same as the original system. We then prove in theory that the system indeed also globally stabilizes to the optimal solution of the constrained quadratic optimization problem. Simulations demonstrate the effectiveness of the proposed method.     

软件安全性残留风险分级评估的实例分析

评估软件安全性常用的方法有风险评估和基于可靠性模型的评估。基于上述二种方法提出了残留风险分级评估方法。该方法用失效强度和失效严重度来刻画软件的风险,较好地解决了由于测试数据按失效严重度分类后数据少而难以应用可靠性模型的问题,并用实例说明了新方法的可行性。     

用于演化硬件的动态变异率进化策略

为解决(1+λ)进化策略运行时搜索范围优化与优良基因积累之间的矛盾,分析了个体在不同变异率下变异操作后适应度变化情况,提出了一种根据当前最佳个体适应度及种群历史信息动态调整变异率的方法,构造了一个变异率调整函数。在MAT-LAB软件平台上进行了外部进化实验,结果表明,相对于传统的固定变异率方法,该方法不仅减少了所需的演化代数,而且在一定程度上提高了算法的稳定性。     

基于机器视觉复杂形状工件的非接触测量方法

介绍一种利用机器视觉技术完成复杂形状工件断面尺寸检测的非接触测量方法,该方法利用数字图像处理算法对高分辨率CCD器件采集的工件断面图像进行处理,可实现多品种工件的多参数自动测量。通过系统结构和工作过程分析了影响测量精度的因素。     

基于模糊粗糙集模型的注塑模浇注系统方案智能化设计研究

选择影响注塑件质量的注塑模浇注系统方案为研究对象,提出了浇注系统方案智能化设计策略。考虑到浇注系统方案设计中存在的模糊性和不确定性等因素,对经典的粗糙集理论进行了扩展。将等价关系扩展为模糊相似关系,提出一种模糊粗糙集模型归纳学习算法,并利用此模型建立了具有规则数目少、规则简捷等优点的浇注系统方案设计模糊知识库,并开发了一个浇注系统方案智能化设计原型系统。设计实例初步表明该研究工作和开发的设计原型系统能提高浇注系统设计效率。     

日立Z-5000型原子吸收分光光度计常见故障分析及排除

文章介绍了日立Z-5000型原子吸收分光光度计火焰系统和石墨炉系统在日常分析中出现的故障现象和解决方法。     

椭球面屋盖与圆锥面玻璃幕墙的风压分布特征

结合杭州大剧院主体结构风压分布的风洞试验研究 ,详细介绍了风洞试验及数据处理方法 ,讨论了在不同风向角下椭球面屋盖和圆锥面玻璃幕墙的风压分布 ,并与荷载规范中类似结构的风压分布进行了比较。为了便于整体结构设计 ,根据结构的实际情况对椭球面和圆锥面进行分块并给出相应的分块风压数据 ,根据各风向角下的风压分布特征给出了整体结构抗风设计的最不利风向角。