分块子空间追踪算法

压缩传感理论是一种充分利用信号稀疏性或者可压缩性的全新信号采样理论。该理论表明，通过采集少量的信号测量值就能够实现可稀疏信号的精确重构。本文在研究现有经典重构算法的基础上，提出结合图像分块思想和回溯思想的分块子空间追踪算法（Block Subspace Pursuit, B_SP）用于压缩传感信号的重构。该算法以块结构获取图像，利用回溯过程实现支撑集的自适应筛选，最终实现图像信号的精确重构。实验结果表明，在相同测试条件下，该算法的重构效果无论从主观视觉上还是客观数据上都有不同程度的提高。     

凸齿镇压器作业过程的运动学与动力学分析

[目的]基于理论推导建立凸齿镇压器作业过程中的运动学和动力学模型。[方法]根据运动学中刚体做平面运动的瞬心定理和牵连运动为平动时质点的加速度合成定理,建立凸齿镇压器在不同工作阶段的运动参数模型;根据动力学中的动量定理、动能定理和冲量定理,建立凸齿镇压器工作状态中所需牵引力、凸齿与地面作用瞬间产生的冲击力和冲击能的参数模型。[结果]凸齿镇压器作业过程中所需的牵引力随着凸齿镇压器的自身质量和滚动阻力系数的增加而增大,而凸齿镇压器转动惯量的增加会降低凸齿镇压器所需牵引力;冲击过程中,凸齿镇压器的牵引速度越大、质量和转动惯量越大、冲击时间越短,则冲击力越大;凸齿镇压器冲击土壤时的冲击能随着凸齿的转动惯量、质量和质心竖直向下移动距离的提高而增加,而随土壤的弹性系数与土壤的塑性变形量的增加而减小。[结论]建立了凸齿镇压器在不同工作状态下运动学及动力学模型,分析并揭示了凸齿镇压器结构参数与运动参数间的相互联系,探索了凸齿镇压器冲击土壤的特征规律,为设计和优化其结构参数和运动参数提供了理论依据。     

基于OGSA网格技术的连锁超市进销存系统研究

本研究采用网格计算技术使进销存系统从简单的计算资源集中上升到数据共享层面，并且实现了协作处理和网络节点的高质量的服务，能极大的提高连锁超市间计算资源的效率和利用率，有效破解因计算能力差、数据来源单一或存储资源欠缺而无法解决的问题。     

Production,chemical composition,and fatty acid profile of milk from buffaloes fed with cupuaçu (Theobroma grandiflorum) cake and murumuru (Astrocaryum murumuru) cake in the Eastern Amazon

The objective was to evaluate the effect of concentrate supplementation using by-products of the Amazonian industry on milk production, milk composition, and milk fatty acid profile of dairy buffaloes. Twelve lactating buffaloes (544.5 ± 35.6 kg, 6.4 ± 2.2 years old, 59 ± 6 days in milk) were allotted in a pasture of Mombaça grass and managed under rotational grazing (4 days occupancy/28 days rest). A 3 × 3 Latin square was adopted, and each animal alternately received three supplementary treatments based on corn bran + soybean meal or cupuaçu cake or murumuru cake for 21 days per treatment. Murumuru cake increased the levels of lauric acid and myristic acid in the milk (p < 0.05). Murumuru cake reduced the unsaturated fatty acid contents in the milk compared with animals fed control diet or cupuaçu cake (24.27% vs. 25.24% vs. 25.08%). The n-6/n-3 ratio was 2.6, 1.97, and 2.0 in the control, cupuaçu, and murumuru groups, respectively. Based on this parameter, cakes made from cupuaçu as well as murumuru could be considered to be adequate for inclusion in dairy water buffalo feed. However, the murumuru cake addition requires some caution because its use induces the secretion of higher levels of lauric and myristic fatty acids that are related to human cardiovascular disease.     

Object‐Based Mapping of Karst Rocky Desertification using a Support Vector Machine

Accurate and cost‐effective mapping of karst rocky desertification (KRD) is still a challenge at the regional and national scale. Visual interpretation has been utilised in the majority of studies, while an automated method based on pixel data has been investigated repeatedly. An object‐based method coupling with support vector machine (SVM) was developed and tested using Enhanced Thematic Mapper Plus (ETM+) images from three selected counties (Liujiang, Changshun and Zhenyuan) with different karst landscapes in SW China. The method supports a strategy of defining a mapping unit. It combined ETM+ images and ancillary data including elevation, slope and Normalized Difference Vegetation Index images. A sequence of scale parameters estimation, image segmentation, training data sampling, SVM parameters tuning and object classification was performed to achieve the mapping. A quantitative and semi‐automated approach was used to estimate scale parameters for segmenting an object at an optimal scale. We calculated the sum of area‐weighted standard deviation (WS), rate of change for WS, local variance (LV) and rate of change for LV at each scale level, and the threshold of the aforementioned index that indicated the optimal segment level and merge level. The KRD classification results had overall accuracies of 85·50, 84·00 and 84·86 per cent for Liujiang, Changshun and Zhenyuan, respectively, and kappa coefficients are up to 0·8062, 0·7917 and 0·8083, respectively. This approach mapped six classes of KRD and offered a visually appealing presentation. Moreover, it proposed a conceptual and size‐variable object from the classification standard of KRD. The results demonstrate that the application of our method provides an efficient approach for the mapping of KRD. Copyright © 2012 John Wiley & Sons, Ltd.     

基于高斯自适应拟合的苹果目标分割方法研究

苹果目标的准确识别是苹果机械化采摘需要解决的关键问题之一。为此,基于YUV颜色空间模型,提出了一种结合色差分量与高斯自适应拟合算法的苹果目标分割方法。该方法采用首先将苹果目标由RGB颜色空间转换至YUV颜色空间,并利用色差分量V建立果实与背景分割的高斯分布拟合模型,根据拟合结果自动获取分割阈值,以实现自然场景下苹果目标的准确分割。为了验证文中算法的有效性,利用多幅图像进行了试验并与Otsu自适应阈值分割算法进行了比较。试验结果表明,采用文中算法得到的苹果果实的平均检出率达87.08%,识别率领先Otsu算法9.91%。因此,对于着色度较为均匀的苹果目标,采用高斯自适应拟合方法可以有效提高其识别率。     

食品加工工艺的安全防火措施

随着我国食品加工行业的迅猛发展,食品加工工艺的机械化程度大大提高,用火用电危险品日益增多,容易发生火灾,存在一定的安全隐患,食品加工负责人必须加强火灾防范意识,防止和减少因火灾造成的经济损失和人身安全事故的发生。     

INVITED REVIEW—IMAGE REGISTRATION IN VETERINARY RADIATION ONCOLOGY: INDICATIONS,IMPLICATIONS, AND FUTURE ADVANCES

The field of veterinary radiation therapy (RT) has gained substantial momentum in recent decades with significant advances in conformal treatment planning, image‐guided radiation therapy (IGRT), and intensity‐modulated (IMRT) techniques. At the root of these advancements lie improvements in tumor imaging, image alignment (registration), target volume delineation, and identification of critical structures. Image registration has been widely used to combine information from multimodality images such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) to improve the accuracy of radiation delivery and reliably identify tumor‐bearing areas. Many different techniques have been applied in image registration. This review provides an overview of medical image registration in RT and its applications in veterinary oncology. A summary of the most commonly used approaches in human and veterinary medicine is presented along with their current use in IGRT and adaptive radiation therapy (ART). It is important to realize that registration does not guarantee that target volumes, such as the gross tumor volume (GTV), are correctly identified on the image being registered, as limitations unique to registration algorithms exist. Research involving novel registration frameworks for automatic segmentation of tumor volumes is ongoing and comparative oncology programs offer a unique opportunity to test the efficacy of proposed algorithms.     

基于"3S"技术的甘肃子午岭自然保护区土地利用变化研究

以甘肃省子午岭自然保护区为研究对象,运用"3S"技术,对研究区的地形图、不同时相的TM遥感影像进行数据预处理,并分类提取了研究区2个时段的土地利用信息.对分类信息进行统计分析后并与实地调查数据进行比较,结果表明,近20年来甘肃子午岭自然保护区的森林覆盖面积在稳步提高,乔木林面积明显增加.为甘肃子午岭自然保护区工程的建设提供了基础信息,为林区植物种群生长及分布调查研究提供了宏观数据,并且输出了研究区不同时相土地利用专题图.