Adherence clustering: an efficient method for mining market-basket clusters

We explore in this paper the efficient clustering of market-basket data. Different from those of the traditional data, the features of market-basket data are known to be of high dimensionality and sparsity. Without explicitly considering the presence of the taxonomy, most prior efforts on clustering market-basket data can be viewed as dealing with items in the leaf level of the taxonomy tree. Clustering transactions across different levels of the taxonomy is of great importance for marketing strategies as well as for the result representation of the clustering techniques for market-basket data. In view of the features of market-basket data, we devise in this paper a novel measurement, called the category-based adherence, and utilize this measurement to perform the clustering. With this category-based adherence measurement, we develop an efficient clustering algorithm, called algorithm k-todes, for market-basket data with the objective to minimize the category-based adherence. The distance of an item to a given cluster is defined as the number of links between this item and its nearest tode. The category-based adherence of a transaction to a cluster is then defined as the average distance of the items in this transaction to that cluster. A validation model based on information gain is also devised to assess the quality of clustering for market-basket data. As validated by both real and synthetic datasets, it is shown by our experimental results, with the taxonomy information, algorithm k-todes devised in this paper significantly outperforms the prior works in both the execution efficiency and the clustering quality as measured by information gain, indicating the usefulness of category-based adherence in market-basket data clustering.     

Genomic imprinting and carcinogenesis

The solution structure of a synthetic ET(B) selective agonist, ET-1[Cys(Acm)(1,15), Ala3, Leu7, dAsp8, Aib11] has been solved by 1H NMR and molecular modelling studies. Such solution structures of linear modified peptides in aqueous methanol are being used in an ongoing program of research designed to assist in an understanding of the basic structural requirements for the biological activity of vasoconstrictors. The resulting structure of this peptide is characterised by an alpha-helical conformation between residues Leu6-His16 and by N- and C-termini which assume no defined conformation. A knowledge of the solution structures of this and related peptides, which are ET(B) selective agonists, are proving to be important in the understanding of how they interact with the ET(B) receptor.     

从萨沃伊别墅探究勒·柯布西耶的机器美学

文章论述了萨沃伊别墅的机器美学思想,主要结合了勒·柯布西耶在1926年提出的"建筑新五点"来探讨他所主张的机器美学在萨沃伊别墅上是如何得以实现。     

无线ILC系统测控信号延时效应补偿方法

针对通过无线信道进行测控信号传输的远程迭代学习控制( ILC)系统,研究信号传输延时对控制系统性能的影响.分析了测控信号延时情况下ILC系统的收敛性问题,通过引入预控制向量,提出了ILC系统信道延时效应补偿的向量更新方法.数值仿真结果表明了所提方法的有效性.     

带曲率补偿的带隙基准电流源的设计

简单介绍了带隙基准源的基本原理,给出了一款基于Widlar结构的带曲率补偿的带隙基准电压电流源的设计方法,通过采用TSMC₀.5μm工艺库对电路进行仿真,在-40～150℃的温度范围内,其带隙基准的输出具有12ppm/℃的温度系数,电流基准的输出具有42ppm/℃。此外,文中还对曲率补偿电路的工作原理进行了分析,并且通过仿真波形对曲率补偿的工作机制进行了讨论。     

基于SSH的企业员工信息管理系统的设计与实现

以企业员工信息管理系统为例,论述该系统的设计及其实现,研究J2EE、Struts、Hibernate和Spring等主流技术在实际开发中的应用。结果表明,SSH技术架构在构建复杂业务系统中提高了开发效率和系统的可维护性,同时增强了系统的可扩展性。     

Image classification method on class imbalance datasets using multi-scale CNN and two-stage transfer learning

Neural Computing and Applications - Image classification tasks widely exist in many actual scenarios, including medicine, security, manufacture and finance. A major problem that hurts algorithm...     

高灰度级TFT-LCD显示系统的实现

提出了一种以FPGA为核心控制器的高灰度级TFT-LCD显示系统的设计方案。该系统采用幅值-帧速率控制调制-空间混合灰度调制方法,首先将10 bit的R、G、B信号分割成高8 bit数据和低2 bit数据,低2 bit数据经过空间处理后平均分到4个相邻的8 bit数据上,然后把这8 bit数据继续分割成高6 bit数据和低2 bit数据,其中高6 bit数据用于幅值调制,低2 bit数据用于帧速率控制调制,从而实现1 024个灰度等级显示。试验结果表明,该系统具有良好的显示效果和较高的显示灰度等级。     

基于Matlab/Simulink的硬件在回路无人机仿真系统设计

随着无人机在军事和民用领域的应用前景,高效率的地面控制操控训练替代实装飞行是保证系统安全、提高效率和节省经费的重要手段,针对无人机飞行控制系统仿真的特点和人在回路仿真系统的要求,提出利用Matlab/Simulink提供仿真环境进行人在回路的无人机仿真系统的设计方案,该方案将PC机作为实时飞控系统,从而将其作为飞行控制的仿真平台,相对于传统手工编写代码的方式,基于Simulink模块构建的仿真模型具有灵活、快速、高效和低成本等特点,对无人机模拟训练系统中飞行动态仿真模型的设计和人在同路的仿真训练具有很高的实用价值.     

基于超声波的围岩松动圈实时监测系统设计

实时地掌握围岩松动圈的范围对矿藏的安全生产具有重要的意义。利用超声波探测的灵活性和准确性,本文提出了一种基于超声波的围岩松动圈监测系统设计方法。此方案利用超声波在岩体中的传播速度与岩体的受力状态和裂隙程度的关系来实时地监测围岩松动圈的情况,具有方便、灵活、易于操作等特点。