RFID阅读器的驱动及模块设计

当前，大部分有关RFID的文章，都在探讨RFID在提高产品物流速度和信息采集质量方面的作用或研究有关RFID硬件设备，而有关RFID阅读器的驱动及接口技术方面的研究很少。主要介绍了RFID阅读器的驱动模块及模块工作原理，同时介绍阅读器与上层数据管理器之间的接口设计。     

光谱判断田间鲜烟叶成熟度的影响因子研究

利用便携式地物波谱仪Field Spec 3测量烤烟成熟期烟叶的反射光谱,针对采收成熟度M2、M3,分析比较同一时间不同测量位点、及同一位点不同测量时间的反射光谱差异。结果表明:反射光谱的差异在不同测量位点主要体现在350~780 nm可见光波段和780~1300 nm近红外波段,在不同测量时间主要体现在780~1300 nm近红外波段。因此,利用光谱仪判断鲜烟叶成熟度,受测量位点的影响较大,而受测量时间的影响较小,但若测量烟叶生理生化组分、厚度和水分等内在指标,时间及天气状况是必须考虑的重要因素。     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.     

基于机载LiDAR数据的玉米叶面积指数反演

以机载LiDAR离散点云数据为数据源,基于植被冠层孔隙率与叶面积指数的关系,提出一种反演大田玉米叶面积指数的方法。对反演LAI和实测LAI进行对比分析,结果表明:基于Axelsson改进的不规则三角格网加密方法可以将地面点和非地面点分开,结合高分辨率影像能够提取出玉米冠层点云;基于孔隙率反演LAI,尼尔逊参数的选择对结果影响很大,利用扫描天顶角模拟尼尔逊参数,LAI反演结果接近于真实情况。利用机载LiDAR点云数据能精确地反演大田玉米LAI,该研究方法适用于中等高度的农作物,可以扩展到甜菜、甘蔗等其他中等高度农作物。     

对教师个人多媒体教学平台的研究

多媒体教学技术被广泛地应用于教学,有效提高了课堂教学效率和教学质量。但过分或不当使用多媒体技术也会影响和制约着教学效果,限制教师主动性和禁锢教师临场发挥。有必要对这项技术在形式、手段和方法上进行一些反思,重新探讨教学中所需要的多媒体软硬件环境以及平台,研究适合高校教师使用的多媒体辅助教学平台及工具。     

基于STM32电力谐波采样设备的设计

为实现低成本检测电力线谐波,开发基于STM32F103RBT6嵌入式微控制器的电力谐波采样设备,使用CS5463电量采集芯片及以Zigbee传输参数的无线电参数检测器,实现0.4 k V农村低压电网的电参数采集检测及电量计量。介绍设备的总体架构、软硬件设计思路以及实现方案。测试结果表明:设备能够在短时间内进行谐波采样和分析,具有稳定性强、可扩展性强、成本低廉等优点。     

TMS320DM642汇编优化方法在棉种在线筛选系统应用

为了提高基于机器视觉的棉种在线筛选系统的筛选效率,介绍了使用汇编语言优化TMS320DM642程序的几种方法。优化过程中利用了软件流水并实现了"扩展指令的使用""延时间隙的利用""循环展开""并行指令使用"等多种方法。其中"扩展指令的使用"优化了原有的处理算法;"延时间隙的利用"和"循环展开"消除了循环内多余的NOP语句;"并行指令的使用"和软件流水技术提高了DSP8个功能单元的利用率。实验使用图像尺寸为215*640像素的YUV格式图像数据,优化前处理一帧图像用时16.76ms,优化后为1.03ms,优化部分代码执行时间缩短为原来的1/16,充分证明了使用优化方法大大缩短了代码的执行时间,提高了整体系统的实时性,并为后续的复杂算法提供时间保障。     

基于SOFM神经网络的核心种质取样算法

介绍了核心种质和自组织特征映射网络的基本概念，使用自组织特征映射网络的自组织特性对种质性状数据进行了聚类，利用聚类的分组结果，提取核心种质，通过对核心种质的各种参数的检验并与完全随机取样和一般的系统聚类的对比。结果表明，SOFM的取样算法，是一种比较有效快捷的算法，可以在实际中加以应用。     

Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration,crops coefficients,leaf area index and remotely-sensed vegetation indices

The monitoring of crop production and irrigation at a regional scale can be based on the use of ecosystem process models and remote sensing data. The former simulate the time courses of the main biophysical variables which affect crop photosynthesis and water consumption at a fine time step (hourly or daily); the latter allows to provide the spatial distribution of these variables over a region of interest at a time span from 10 days to a month. In this context, this study investigates the feasibility of using the normalised difference vegetation index (NDVI) derived from remote sensing data to provide indirect estimates of: (1) the leaf area index (LAI), which is a key-variable of many crop process models; and (2) crop coefficients, which represent the ratio of actual (AET) to reference (ET₀) evapotranspiration.A first analysis is performed based on a dataset collected at field in an irrigated area of the Haouz plain (region of Marrakesh, Central Morocco) during the 2002–2003 agricultural season. The seasonal courses of NDVI, LAI, AET and ET₀ have been compared, then crop coefficients have been calculated using a method that allows roughly to separate soil evaporation from plant transpiration. This allows to compute the crop basal coefficient (K_cb) restricted to the plant transpiration process. Finally, three relationships have been established. The relationships between LAI and NDVI as well as between LAI and K_cb were found both exponential, with associated errors of 30% and 15%, respectively. Because the NDVI saturates at high LAI values (>4), the use of remotely-sensed data results in poor accuracy of LAI estimates for well-developed canopies. However, this inaccuracy was not found critical for transpiration estimates since AET appears limited to ET₀ for well-developed canopies. As a consequence, the relationship between NDVI and K_cb was found linear and of good accuracy (15%).Based on these relationships, maps of LAI and transpiration requirements have been derived from two Landsat7-ETM+ images acquired at the beginning and the middle of the agricultural season. These maps show the space and time variability in crop development and water requirements over a 3 km × 3 km irrigated area that surrounds the fields of study. They may give an indication on how the water should be distributed over the area of interest in order to improve the efficiency of irrigation. The availability, in the near future, of Earth Observation Systems designed to provide both high spatial resolution (10 m) and frequent revisit (day) would make it feasible to set up such approaches for the operational monitoring of crop phenology and irrigation at a regional scale.     

基于改进PSO算法的电机控制系统PID参数优化

粒子群算法(PSO,Particle Swarm Optimization)作为一种新型的随机优化方法,其算法结构简单,鲁棒性强,在组合优化和自适应控制等领域的非线性优化中有着广泛的应用前景.为此,提出一种改进的PSO优化算法,并将该算法应用于电机控制系统的PID参数优化设计.仿真结果表明,利用改进PSO算法优化的PID参数能有效改善控制系统的性能指标.