针对现有试卷质量评价理论依据不充分、分析指标标准不一,科学性差的特点,结合CTT(classical test theory)真分数不变性、误差安全性及IRT(item response theory)参数不变性、线性等值等优点,提出了一个基于CTT和IRT的试卷质量评价系统的建设思路,并完成系统实现。以某大学五门课程试卷及考生成绩为例,进行了试卷分析和试题分析,分析结果显示,IRT得到的学生能力更贴近实际情况,正确反映了学生能力在该考试中的位置,通过分析结果说明考试排名与学生的客观能力的符合程度,并给出该次考试试卷的改进建议。
Soil temperature is a key factor for best planting dates decision-making in the large scale farming areas of northeast China because of high latitudes and frigid environment.Continuous data were collected from a wireless sensor network(WSN)-based monitoring system to exactly analyze and understand soil temperature of the whole farmland.Using the classical statistics and geo-statistics methods,real-time monitoring data were analyzed with three aspects,i.e.temporal variation,spatial variation and spatio-temporal variation.Temporal variation analysis of each sensor node showed a sinusoidal curve of daily soil temperature and gave the long-term trend of daily average soil temperature in a certain period.Spatial variation analysis provided the spatial distribution map of daily average soil temperature within a study region for a certain day.Spatio-temporal variation analysis quantified the variation process of the spatial distribution over time by the monitored classes distribution indicator(MCDI)proposed.Experimental results showed that the above variations analysis of the real-time data provide an effective approach to determine whole-farmland soil temperature.
为了有效管理农机资源,实时监控农机作业状态和工况数据,及时对农机故障进行预警,提高作业效率,采用.NET提供的应用程序开发接口服务(WCF)生成Web Service客户端,并在此基础上通过ArcGIS Server Java框架进行二次开发,设计并实现了基于ArcGIS Server的农机远程监管服务系统。该系统的主要功能包括农机信息管理、合作社内部信息管理、农机实时监控、农机历史轨迹查询、农机工况数据实时监测与即时报警。
