基于Pro/E的播种机零部件参数化造型

针对旱作节水播种机设计中存在的设计手段落后、设计效率低下等问题，应用基于特征的参数化造型软件Pro/E对旱作节水播种机的零部件进行参数化造型，在对该类播种机开沟器、排种器、地轮等零部件的造型设计中探讨了技术要点，提高了旱作节水播种机修改设计和系列化设计的效率。     

虚拟仪器技术在发动机故障诊断中的应用

为了达到对发动机运行状态进行实时监测和故障诊断的目的,采用PCI-9113A数据采集板实时采集发动机的技术状态参数,以图形化编程语言Lab VIEW实现数据的处理及管理,建立了发动机状态监测及故障诊断系统,实现了发动机振动信号的采集以及数据处理、显示、打印、存储等操作.以该系统为基础,只需添加一些所需要的传感器,同时增加相应的软件模块,就可实现对发动机其它性能参数的监测及故障诊断.     

基于Pro/E的装配体三维设计

介绍了使用Pro/E计算机软件作为计算机设计绘图工具，建立3D实体模型，然后根据零件间的位置关系将所涉及的零件逐个地进行装配；并简单阐述了其工程图的制作及齿轮三维造型的方法。     

日光温室蔬菜智能化管理系统建模

随着精准农业的发展,智能化管理将在现代农业中广泛应用。针对智能化管理在日光温室蔬菜生产中尚鲜见报道的情况,该研究以日光温室蔬菜为研究对象,通过对日光温室环境特征的分析,设计一种基于无线传感器网络技术的低成本温室监测系统,用于监测温度、湿度、二氧化碳浓度等关键环境参数,并建立日光温室蔬菜系统,通过建模,建立不同子模块,实现蔬菜生产的智能化管理。     

数据仓库逻辑建模的初步探讨

针对逻辑建模在数据仓库构建过程中的重要性,介绍了数据仓库创建的基本步骤,并利用实例深入而详细地研究了逻辑模型的设计,分析了几种逻辑模型的特点及其使用场合。     

虚拟现实技术在多媒体课件开发中的应用

目前虚拟现实技术在高校教学多媒体课件开发过程中应用较为广泛,在分析虚拟现实技术及其在课件开发中的应用优势的基础上,针对虚拟现实技术在多媒体课件开发中的具体应用展开了相关论述,以期实现更深层次发展。     

Predicting the potential geographic distribution of Bactrocera bryoniae and Bactrocera neohumeralis(Diptera: Tephritidae) in China using MaxEnt ecological niche modeling

Bactrocera bryoniae and Bactrocera neohumeralis are highly destructive and major biosecurity/quarantine pests of fruit and vegetable in the tropical and subtropical regions in the South Pacific and Australia. Although these pests have not established in China, precautions must be taken due to their highly destructive nature. Thus, we predicted the potential geographic distribution of B. bryoniae and B. neohumeralis across the world and in particular China by ecological niche modeling of the Maximum Entropy(Max Ent) model with the occurrence records of these two species. Bactrocera bryoniae and B. neohumeralis exhibit similar potential geographic distribution ranges across the world and in China, and each species was predicted to be able to distribute to over 20% of the globe. Globally, the potential geographic distribution ranges for these two fruit fly species included southern Asia, the central and the southeast coast of Africa, southern North America, northern and central South America, and Australia. While within China, most of the southern Yangtze River area was found suitable for these species. Notably, southern China was considered to have the highest risk of B. bryoniae and B. neohumeralis invasions. Our study identifies the regions at high risk for potential establishment of B. bryoniae and B. neohumeralis in the world and in particular China, and informs the development of inspection and biosecurity/quarantine measures to prevent and control their invasions.     

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species. In this study, the spatial distribution of five endemic and threatened species belonging to the genus Onosma (including O. asperrima, O. bisotunensis, O. kotschyi, O. platyphylla, and O. straussii) was investigated under present and future climate change scenarios: RCP2.6 (RCP, representative concentration pathway; optimistic scenario) and RCP8.5 (pessimistic scenario) for the years 2050 and 2080 in Iran. Analysis was conducted using the maximum entropy (MaxEnt) model to provide a basis for the protection and conservation of these species. Seven environmental variables including aspect, depth of soil, silt content, slope, annual precipitation, minimum temperature of the coldest month, and annual temperature range were used as main predictors in this study. The model output for the potential habitat suitability of the studied species showed acceptable performance for all species (i.e., the area under the curve (AUC)>0.800). According to the models generated by MaxEnt, the potential current patterns of the species were consistent with the observed areas of distributions. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions. Among all species, O. bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080. Finally, the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes. The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.