Optimal lot sizing with maintenance actions and imperfect production processes

Porteus (1986) explored an economic order quantity model with imperfect production processes that the approximate lot size is derived. Basically, he dealt with the lot size problem is rather meaningful. However, for mathematical simplicity, he adopted a truncated Taylor series expansion to present the approximate expected total cost function that results in overvalue of expected total cost. In this paper, we extend Porteus (1986) to present the optimal lot size model for defective items with a constant probability when the system is out-of-control and taking the maintenance cost into account. We show that there exists a unique optimal lot size such that the expected total cost is minimised. In addition, the bounds of optimal lot size are provided to develop the solution procedure. Finally, numerical examples are given to illustrate the theoretical results and compare optimal solutions obtained by using our approach and Porteus's approach. Numerical results show that our approach is better.     

Extraction of small biotopes and ecotones from multi-temporal RapidEye data and a high-resolution normalized digital surface model

The conservation of habitats and habitat complexes in diverse landscapes is increasingly recognized as a crucial factor in sustaining biodiversity and ecosystems. For the successful management of landscapes, habitat monitoring is necessary, but often small biotopes, e.g. scattered trees, copses, tree rows, hedges, and the transition zones between ecosystems, are ignored. This is important as such small biotopes are recognized as keystone elements in landscape structure for habitat networks. Furthermore, the transition zones between different habitats, often called ecotones, are dynamic and play several functional roles in landscape ecology. This article presents an approach for the extraction of small biotopes and ecotones combining object-based and pixel-based image analysis. Both high-resolution digital elevation data from airborne laser scanning and multi-temporal RapidEye remote-sensing data were used to automatically detect landscape elements and landscape patterns. First, multi-temporal RapidEye images were used to classify the main land-use classes using object-based image analysis. In the second step, a high-resolution digital surface model was integrated with the main classes, and small biotopes and ecotones were delineated by means of pixel-based image analysis. Classification accuracy for main land-use classes is above 92%, and a visual assessment using aerial image and onsite investigation show that the identification results for small biotopes well match reality. The results show the effectiveness of the classification strategy developed and the potential for incorporating the detailed surface mapping in heterogeneous vegetated areas.     

Estimation of air temperature from MODIS data in east China

Air temperature, T _a, with high spatial and temporal resolution is desired for global change, agricultural disaster, land surface studies, and modelling applications. A statistical algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) data is developed for daytime T _a retrievals over east China at a resolution of 0.05° × 0.05°. The approach first applies a statistical regression of the first guess, i.e. the preliminary estimate, of T _a to MODIS 11 μm and 12 μm brightness temperature (T _11μm and T _12μm) and site data (longitude, latitude and altitude) for east China. Then the first guess of T _a is further corrected with a series of bias equations for different latitude zones in east China. Further quantitative validation with measured T _a using 335 synoptic weather stations for the whole of 2006 indicates that the algorithm performs well with overall statistics of R = 0.96, RMSE = 3.23°C, and bias = ?0.09°C. 75% of the estimated T _a is within 3°C of the actual T _a and 92% of the estimated T _a is within 5°C of the actual T _a. This bias correction algorithm can be applied to other geostationary and sun-synchronous satellite instruments for T _a retrieval.     

粗糙集理论在试卷分析中的应用

传统的试卷分析方法是采用数理统计的方法,但得到的分析指标通常不能很好地体现试题的冗余和重要程度.运用粗糙集理论,给出了一种试卷分析的新方法,较之传统的试卷分析方法,可以得到试题的冗余信息和重要度信息,反映试卷结构的合理性,使试卷分析更加合理,规范,客观.     

基于RapidIO的宽带实时频谱分析

研究了宽带实时频谱分析技术的实现方法,详述了硬件实现的两项关键技术:采用RapidIO互连技术解决了高速数据传输和大容量的数据缓存;采用并行流水线结构的实时信号处理器实现了有限硬件资源及处理能力下的实时高精度频谱分析。经测试,系统能够实现分析带宽80 MHz、捕获数据容量为512 MB的高精度实时频谱分析,主要性能指标接近国外最新仪器的水平,并已在部分型号的雷达和通信设备中得到了应用。     

单片机测控技术在平板导热系数仪研制中的应用

就单片机测控技术应用于平板导热系数仪的研制提出了应用方法，介绍了串行A／D转换器TLC2543与单片机的硬件连接，热电偶信号的冷端补偿方法以及高精度运算放大器ICL7650的应用，对数字PID算法提出了新的应用方式。     

3-RSS同轴驱动布局并联机构的打磨机器人设计与运动分析

针对目前串联型打磨机器人在打磨球面时存在刚度不足的问题,提出一种3-RSS同轴驱动布局并联机构工具型打磨机器人.同轴驱动布局是将驱动布置在同一轴线,主体由基柱和3组可以绕基柱旋转的机械臂构成,每个机械臂外接支链杆簇,3组支链杆簇与末端打磨头相连.通过构型分析、结构设计,建立同轴驱动布局打磨机器人模型,并对模型进行运动学...     

基于动态贝叶斯网络的手势识别

研究了动态手势的识别技术,实现人机交互。采用HSV空间的肤色模型实现手势定位,光流场算法进行手势追踪,具有较好的快速性、准确性和鲁棒性。提出应用链码描述手势运动矢量,双手相对位置标量以及双手与脸的相对位置标量,将多条链码作为动态手势的特征进行提取。建立了一个动态手势识别的动态贝叶斯网络模型,将一部分手势链码作为训练样本,通过对DBNs的推理学习实现手势识别。实验构建动态手势识别系统,可应用于多媒体、智能电器或幻灯片控制之中。     

基于WiFi的井下无线智能终端的设计

WiFi技术以其组网方便、易于扩展等优势,越来越受到广泛关注,有着广阔的应用前景。本文设计了基于ARM9的WiFi智能终端,利用WiFi无线局域网技术实现了语音通信、数据采集和远程监控等功能,可用于矿井语音、视频通信和环境的实时监测。