可持续发展的外语学习能力探析

综合哲学、教育学、心理学和二语习得等不同角度对学习能力的理解,对可持续发展的外语学习能力内涵进行阐释。外语学习能力系统既包括智力因素,也包括非智力因素。外语学习能力应由基本学习能力、拓展学习能力和调节学习能力三大要素构成,三大要素中又包含一系列子要素,其中语言学习的迁移能力、自主学习能力和持久动机是外语学习能力可持续发展的重要指标。     

不同钙质原料对干式振动料性能的影响

采用新型环保复合结合剂和引入无水化钙质材料(石灰石、白云石、消石灰等)作为CaO源原料,研究开发环保型抗水化镁钙质干式料.结果表明, 钙质原料的种类、粒度和数量对干式料性能影响很大.加入部分石灰石颗粒,采用环保型结合剂可制得具有较好物理性能的干式料,其中粒度为3～1mm和1～0mm的石灰石加入量分别为5%和30%时,试样获得了较好的综合性能,是一种理想的CaO源材料.     

DC—DC转换器中电感的选择研究

在DC-DC转换器中,开关电源以其能量转换的高效率而得以广泛应用.基于电感的开关电源其转换功率大而广泛应用于中高功率应用中. 电感的正确选择对于DC-DC转换器是非常重要的,需要对电感的性能以及期望的电路性能进行深刻理解.本文给出了在基于电感的开关电源应用中,电感选择的重要规范,根据本文给出的选择方法,能够很好地满足工程应用中开关电源的设计要求.     

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.     

浅述外围护结构的建筑节能技术

外围护结构在建筑节能中起着重要作用,对外围护结构进行合理的设计选择,能极大地降低建筑能耗.文章针对外围护结构,从墙体、屋面、门窗3方面提出了一些提高外围护结构热保温性能的措施,从而改善建筑节能,以供借鉴.     

基于神经网络技术自动筛选Monastrol抑制剂的算法研究

带自动荧光显微镜的HCS（high content screening）系统是一种新兴的显微摄影、筛选和处理系统.HCS系统在摄影过程中会产生大量数据,人工筛选和识别费时费力.本文为了进行Monastrol抑制剂的筛选,基于前馈式神经网络技术研究了一种对HCS系统摄影的大量细胞同时进行特征提取和细胞显型识别的自动算法.在得到各个通道分离的图像后,对不同通道图像进行并行预处理,并采用神经网络和逻辑运算相结合的算法进行处理.我们将该方法运用于Monastrol抑制剂的筛选中,并将结果与人工识别结果进行分析比较.相比较前人提出的multi-phenotypic mitotic analysis（MMA）算法自动识别的正确率得以提高,可更好评估抗癌药剂效用.     

大学生耐力性素质练习的价值及对策研究

文章针对当前学生耐力素质的现状,运用文献资料调研法,旨在阐明耐力素质的重要性,并就如何科学合理地运用方法手段,提高学生的耐力素质,以促进学生身体素质的全面发展.     

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.     

基于神经网络数据融合的目标跟踪简化算法

分析了基于神经网络数据融合的目标跟踪算法 ,指出了传统的融合算法计算量大 ,神经网络目标向量不易选取等缺点 ,并提出了一种简化的算法。应用理论分析和蒙特卡洛仿真方法 ,对标准卡尔曼滤波算法和简化的滤波算法进行了比较 ,并给出了均方根误差的统计值。该简化算法原理简单 ,数据处理量小 ,速度快 ,误差小 ,特别适用于多传感器的处理 ,将融合结果反馈给单传感器 ,可提高各单传感器的跟踪精度     

关于半拟齐次函数芽正规型的证明

运用半拟齐次函数芽f=f0+f′的性质:f~0f+∑ckek(~表示右等价)给出了一类解析函数芽jxnf的正规型的简单证明方法。