美汉草（Meehania fargesii Levl）生物量分配分析

调查阔叶红松林林下早春开花植物美汉草(Meehania fargesii Levl)各个器官生物量分配变化情况.结果表明:在整个生长季节中,美汉草各器官生物量总体上呈现先增加后减少的趋势,5月初~7月初,根生长速率先快后慢,茎叶生长速率先慢后快,7月中旬以后各器官生物量逐渐减少;美汉草有性生殖的生殖分配占总生物量的比例较小(4%~6%);根冠比在5~6月不断上升,6~7月迅速下降,7月以后保持稳定;根和茎叶生物量分别与总生物量呈显著的线性正相关关系.分析显示:为了适应阔叶红松林林下的光照变化,在林分郁闭前,能量主要分配给地下部分;林分郁闭后,茎叶生长占主导.美汉草主要以营养繁殖为主,第2年的地下根状茎来自第1年地上茎的繁殖方式及生物量分配策略,可能是美汉草成为林下优势草本的重要原因.     

Exact inference for two exponential populations with competing risks data

In a reliability comparative test, the joint censoring model is usually adopted to evaluate the performances of units with the same facility. However, most researchers ignore the pos- sibility that there is more than one factor for the failure when a test unit fails. To solve this problem, we consider a joint Type-II hybrid censoring model for the analysis of exponential competing failure data. Based on the maximum likelihood theory, we compute the maximum likelihood estimators （MLEs） of parameters and then obtain the condition ensuring MLEs existence for every unknown parameter. Then we derive the conditional exact distributions and corresponding moment properties for parameters by the moment generating function （MGF）. A Monte-Carlo simulation is conducted to compare the performances of different ways. And finally, we conduct a numerical example to illustrate the proposed method.     

考虑壅塞特性的电子膨胀阀流量特性模型

分析了电子膨胀阀内部制冷剂的壅塞流动特性，应用均相流和冷冻流模型描述电子膨胀阀的流量特性，用亚稳态特性系数建立膨胀阀质量流量计算模型，并采用某型号电子膨胀阀的实验数据与所建模型的计算值进行对比.结果表明，该模型的计算值与实测值的偏差在-8.59%~7.56%以内.     

非线性的双目数码成像定位模型

2008年高教杯全国大学生数学建模竞赛题有A,B两题,A题是一个双目数码成像定位问题。解决这一问题,有较大的难度,需要很巧妙的数学技巧。文章用透视对应链的观点建立了双目定位的非线性模型,该模型参数实际含义清楚明了,表达式直观准确,数据计算简单流畅,具有很强的创新性。     

种群多样度的改进

对几种常见多样度的提法做了比较,提出了种群多样度的另一种定义,在很大程度上改善了以往多样度定义的缺陷,为种群多样性的判断提供了有力的依据.     

粒度组成对KR搅拌头用浇注料性能的影响

以Andreassen颗粒紧密堆积理论为基础,研究KR搅拌头外衬莫来石浇注料临界粒度和粒度组成对其密度、强度和热震稳定性的影响.结果表明,随着临界粒度的增大,浇注料干燥和烧结后冷态密度与强度均明显提高;临界粒度一定时,粒度组成对浇注料冷态密度、强度以及热震稳定性的影响基本一致,但临界粒度不同的浇注料试样达到最佳性能所对应的粒度组成并不完全相同;与冷态性能相比,浇注料热震稳定性受临界粒度的影响较小.     

An Efficient Multidimensional Fusion Algorithm for IoT Data Based on Partitioning

The Internet of Things (IoT) implies a worldwide network of interconnected objects uniquely addressable, via standard communication protocols. The prevalence of IoT is bound to generate large amounts of multisource, heterogeneous, dynamic, and sparse data. However, IoT offers inconsequential practical benefits without the ability to integrate, fuse, and glean useful information from such massive amounts of data. Accordingly, preparing us for the imminent invasion of things, a tool called data fusion can be used to manipulate and manage such data in order to improve process efficiency and provide advanced intelligence. In order to determine an acceptable quality of intelligence, diverse and voluminous data have to be combined and fused. Therefore, it is imperative to improve the computational efficiency for fusing and mining multidimensional data. In this paper, we propose an efficient multidimensional fusion algorithm for IoT data based on partitioning. The basic concept involves the partitioning of dimensions (attributes), i.e., a big data set with higher dimensions can be transformed into certain number of relatively smaller data subsets that can be easily processed. Then, based on the partitioning of dimensions, the discernible matrixes of all data subsets in rough set theory are computed to obtain their core attribute sets. Furthermore, a global core attribute set can be determined. Finally, the attribute reduction and rule extraction methods are used to obtain the fusion results. By means of proving a few theorems and simulation, the correctness and effectiveness of this algorithm is illustrated.     

Simultaneous mineralization of CO2 and recovery of soluble potassium using earth-abundant potassium feldspar

CO2 capture and storage(CCS) is an important strategy in combatting anthropogenic climate change.However,commercial application of the CCS technique is currently hampered by its high energy expenditure and costs.To overcome this issue,CO2 capture and utilization(CCU) is a promising CO2 disposal method.We,for the first time,developed a promising method to mineralize CO2 using earth-abundant potassium feldspar in order to effectively reduce CO2 emissions.Our experiments demonstrate that,after adding calcium chloride hexahydrate as an additive,the K-feldspar can be transformed to Ca-silicates at 800 C,which can easily mineralize CO2 to form stable calcium carbonate and recover soluble potassium.The conversion of this process reached 84.7%.With further study,the pretreatment temperature can be reduced to 250 C using hydrothermal method by adding the solution of triethanolamine(TEA).The highest conversion can be reached 40.1%.The process of simultaneous mineralization of CO2 and recovery of soluble potassium can be easily implemented in practice and may provide an economically feasible way to tackle global anthropogenic climate change.     

库普河大桥T梁预制的质量控制和外观缺陷处理探讨

文章针对库普河大桥预制T梁的质量控制、外观缺陷处理，分析过程并提出处理方法和预防措施，以期达到使T梁的质量得到保证。     

沥青稳定碎石ATB-30柔性基层配合比设计

ATB-30沥青稳定碎石柔性基层的配合比设计及其结构特点、油石比的确定，详细介绍了原材料的选择，得出合理的配合比指导施工。