Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals

Major challenges in the management of the blood supply chain are related to the shortage and wastage of the blood products. Given the perishable characteristics of this product, storing an excessive number of blood units on inventory could result on the wastage of this limited resource. On the other hand, having shortages may result in cancellations of critical health related activities and as a result a potential increase on fatality rates at hospitals.This paper presents integer programming models to minimize the total cost, shortage and wastage levels of blood products at a hospital within a planning horizon. The primary focus is on the red blood cells and the platelet components of the whole blood cells. The stochastic and deterministic models included consider uncertain demand rates, demand for two types of patients, and crossmatch-to-transfusion ratio. Results show wastage rates decreasing from 19.9% to 2.57% on average. In addition, the shortages and total cost are reduced 91.43% and 20.7% respectively for a given capacity increases. Computational results are included and discussed.     

REST在异构移动客户端接入中的应用研究

针对繁多异构的移动客户端接入Web应用系统的问题,提出一个基于REST(Representational State Transfer)的解决方法并给出一个基于MVC(Model-View-Controller)模式的具体的开发框架,通过RESTful Web服务连接移动客户端的View/Controller层与Web系统的Model层。定义了由Web系统的model层定义RESTful Web服务的具体方法和规则。理论分析与实际应用说明了该方法的有效性。     

基于VB的传感器信号数据处理方案设计

基于VB,设计了棉麻纤维纱线晶变改性成套装备传感器信号数据处理方案.方案主要由数据标定、数据滤波、数据补偿、数据应用及储存四部分组成.介绍了传感器相关参数,给出了传感器物理值计算公式.通过数据滤波,降低了数据采集过程中随机干扰对数据造成的随机误差.通过数据补偿,采集值更加接近传感器液晶屏数显值.对处理后数据应用的同时将数据导入到SQL数据库保存.经现场运行,该方案稳定可靠,满足了设计要求.     

MEMS陀螺在航天器控制系统中的应用评述

在分析MEMS陀螺在空间应用优势基础上,对MEMS陀螺的空间适应性进行了分析,提出了其在空间系统中的应用途径,通过国内外应用情况表明:MEMS陀螺能够广泛应用于航天器控制系统,并随着工艺水平的提高,将成为航天器控制系统的最佳选择.     

一种面向浏览式购物行为模式的LBS购书移动应用

为了提升用户体验,目前涌现了一批辅助购物的移动应用。这些应用为用户补充商品的信息,适用于目标明确的购物行为模式。然而,在现实生活中,还普遍存在没有明确购物目标、将购物作为休闲方式的浏览式购物行为模式。现有应用对此模式支持不足。为此,以书店为应用场景,开发了一种基于室内定位技术的浏览式购物辅助移动应用。此应用后端从书店信息系统和互联网中收集包括书籍摆放位置的各类信息,然后利用关键词提取技术,建立基于位置的关键词库;前端则利用室内定位技术,根据购物者位置向其展示附近书籍概览信息,辅助购物者对附近商品快速认知。案例评估表明,此应用可以提升浏览式购物顾客的购物体验。     

基于分度台转位装置的惯性测量单元智能检测

针对惯性测量单元(IMU)批量检测效率低、人工劳动量大的现状,设计开发出一种基于分度台转位装置的IMU智能检测系统。其采用高精度分度台转位装置为IMU提供基准角度位置,利用工控机控制分度台转位装置、程控直流电源和IMU协调有序工作,通过上位机软件智能控制程控直流电源向IMU供电,以及自动发送、采集、分析和处理检测数据,实现对IMU的智能、高效、精确检测。实验结果表明,该系统可同时自动检测4套IMU 的参数指标,并自动计算、显示和保存检测数据,且检测精度、效率和智能化程度高,人工劳动量小,性价比高,此外,软件界面上所有功能均可手动触摸操控,操作十分便捷。     

巧用Vlookup函数完成信息核对--在招生工作中学生信息核对的应用

Excel软件功能强大,操作简便,其提供的函数可用于处理和分析复杂的数据。介绍了Excel中查找函数Vlookup的语法格式及功能,并通过工作中的具体实例来阐述利用Vlookup函数解决核对数据匹配问题,提高了工作效率,节省了大量的人力。     

基于红外热像检测的截齿煤岩截割特性与闪温分析

为实现采煤机截割过程中煤岩界面的精确动态识别,对采煤机截齿截割煤岩过程中的红外热像特性以及瞬态闪温差异进行研究,建立采煤机截齿煤岩截割试验台,分析得到截齿截割煤、岩过程中的温度演化规律及闪温特征.研究结果表明,截齿截割煤、岩过程中在齿尖一侧均产生突兀的点状闪温区,截岩时高温区范围与闪温瞬态峰值明显大于截煤过程,其二者峰值差与采煤机牵引速度及滚筒转速成正比,且煤岩硬度差异越大,截齿温度场峰值差越明显.研究结果为实现煤岩界面动态识别提供了重要的理论及数值依据.     

网络教学环境下士官《计算机应用基础》课程探究式教学改革

探究式教学是当前院校教学改革的热点之一。随着网络信息技术的快速发展,为不断改革和完善士官《计算机应用基础》课程教学的方式方法,提出在《计算机应用基础》课程教学中依托多媒体信息技术和网络资源进行探究式教学改革实践,激发学员学习兴趣,培养自主学习习惯,提高计算机应用能力。     

Which algorithm should I choose: An evolutionary algorithm portfolio approach

Many good evolutionary algorithms have been proposed in the past. However, frequently, the question arises that given a problem, one is at a loss of which algorithm to choose. In this paper, we propose a novel algorithm portfolio approach to address the above problem for single objective optimization. A portfolio of evolutionary algorithms is first formed. Covariance Matrix Adaptation Evolution Strategy (CMA-ES), History driven Evolutionary Algorithm (HdEA), Particle Swarm Optimization (PSO2011) and Self adaptive Differential Evolution (SaDE) are chosen as component algorithms. Each algorithm runs independently with no information exchange. At any point in time, the algorithm with the best predicted performance is run for one generation, after which the performance is predicted again. The best algorithm runs for the next generation, and the process goes on. In this way, algorithms switch automatically as a function of the computational budget. This novel algorithm is named Multiple Evolutionary Algorithm (MultiEA). The predictor we introduced has the nice property of being parameter-less, and algorithms switch automatically as a function of budget. The following contributions are made: (1) experimental results on 24 benchmark functions show that MultiEA outperforms (i) Multialgorithm Genetically Adaptive Method for Single Objective Optimization (AMALGAM-SO); (ii) Population-based Algorithm Portfolio (PAP); (iii) a multiple algorithm approach which chooses an algorithm randomly (RandEA); and (iv) a multiple algorithm approach which divides the computational budget evenly and execute all algorithms in parallel (ExhEA). This shows that it outperforms existing portfolio approaches and the predictor is functioning well. (2) Moreover, a neck to neck comparison of MultiEA with CMA-ES, HdEA, PSO2011, and SaDE is also made. Experimental results show that the performance of MultiEA is very competitive. In particular, MultiEA, being a portfolio algorithm, is sometimes even better than all its individual algorithms, and has more robust performance. (3) Furthermore, a positive synergic effect is discovered, namely, MultiEA can sometimes perform better than the sum of its individual EAs. This gives interesting insights into why an algorithm portfolio is a good approach. (4) It is found that MultiEA scales as well as the best algorithm in the portfolio. This suggests that MultiEA scales up nicely, which is a desirable algorithmic feature. (5) Finally, the performance of MultiEA is investigated on a real world problem. It is found that MultiEA can select the most suitable algorithm for the problem and is much better than choosing algorithms randomly.