梭式窑火焰数字图像的边缘检测初探

本文介绍了几种典型的边缘检测算法,对它们各自的特点进行了比较。对梭式窑内的一幅原始图像,可用边缘检测算法提取火焰图像的边缘。     

集散控制装置的实验功能开发

以一个模拟生产设备为监控对象,介绍了PCS型集散控制装置的硬件和软件组成,并开发了该装置的各种实验功能,可满足实验教学的要求。     

聚乙烯醇改性固体淀粉胶粘剂的研制

介绍新型固体淀粉胶的制备方法。以淀粉为主要原料，经加热催化分步氧化，再加入聚乙烯醇合成树脂改善其性能，然后用硬脂酸钠作为赋型剂。制得的淀粉胶剪切强度比泡花碱高0.01MPa。     

女性护理液抗炎止痒作用的实验研究

女性护理液为中药苦参醇提液加三氯羟基二苯醚复配而成，根据药理方法学以实验动物建立模型，观察护理液的抗炎、止痒作用。结果，单独使用三氯羟基二苯醚，有较好的抗菌消炎作用，但是止痒作用不明显。以苦参醇提液和三氯羟基二苯醚复配，其抗炎、止痒作用均接近地塞米松磷酸钠注射液。     

双模移动终端主动探测系统的DSP设计与实现

针对移动终端用户身份识别的技术需求,设计了一种基于GSM和CDMA双模制式下基带信号处理的主动探测系统。为了满足主动探测系统的实时处理需求,采用高性能的DSP芯片TMS320C6416作为核心处理器,结合其他器件设计硬件系统,完成基带信号处理板中DSP芯片硬件接口的设计。经现场测试结果验证,系统能够实现对开机状态下GSM和CDMA移动用户身份信息的快速捕获,进而表明本设计可满足系统实时性和可靠性的要求。     

Learning Kernels for Unsupervised Domain Adaptation with Applications to Visual Object Recognition

Domain adaptation aims to correct the mismatch in statistical properties between the source domain on which a classifier is trained and the target domain to which the classifier is to be applied. In this paper, we address the challenging scenario of unsupervised domain adaptation, where the target domain does not provide any annotated data to assist in adapting the classifier. Our strategy is to learn robust features which are resilient to the mismatch across domains and then use them to construct classifiers that will perform well on the target domain. To this end, we propose novel kernel learning approaches to infer such features for adaptation. Concretely, we explore two closely related directions. In the first direction, we propose unsupervised learning of a geodesic flow kernel (GFK). The GFK summarizes the inner products in an infinite sequence of feature subspaces that smoothly interpolates between the source and target domains. In the second direction, we propose supervised learning of a kernel that discriminatively combines multiple base GFKs. Those base kernels model the source and the target domains at fine-grained granularities. In particular, each base kernel pivots on a different set of landmarks—the most useful data instances that reveal the similarity between the source and the target domains, thus bridging them to achieve adaptation. Our approaches are computationally convenient, automatically infer important hyper-parameters, and are capable of learning features and classifiers discriminatively without demanding labeled data from the target domain. In extensive empirical studies on standard benchmark recognition datasets, our appraches yield state-of-the-art results compared to a variety of competing methods.     

腐植酸与普洱茶茶色素

对云南普洱茶特有品质与化学组成(多酚类、儿茶素、黄酮类、茶黄素、茶红素、茶褐素)的关系进行简要地阐述。茶色素被证实是一类具有多种生理活性的物质。依据腐植酸的形成及化学性质、结构特征,提出了普洱茶中茶色素与腐植酸,尤其是茶褐素和黄腐酸,在化学性质方面(结构和官能团)存在一定的相似性。由此提出了腐植酸(黄腐酸)在生理活性及治疗功能方面与茶色素应具有相似性。为腐植酸(黄腐酸)在医药方面的应用研究提出了新思路。     

一种基于固件的云系统策略文件完整性安全机制

针对云系统服务器之间共享策略文件所面临的完整性安全威胁,提出一种新的基于固件的策略安全机制。该机制可在云系统服务器平台之间安全且快速地进行共享策略文件交互,并可对共享策略文件进行完整性校验,进而提高协同工作的服务器所共享策略文件的安全性。实验结果表明,该机制有效实现了云系统环境下共享策略文件的完整性安全,同时提高了云系统管理员的管理效率。     

TuLP: A Family of Lightweight Message Authentication Codes for Body Sensor Networks简

A wireless sensor network （WSN） commonly whilst a body sensor network （BSN） must be secured with requires lower level security for public information gathering, strong authenticity to protect personal health information. In this paper, some practical problems with the message authentication codes （MACs）, which were proposed in the popular security architectures for WSNs, are reconsidered. The analysis shows that the recommended MACs for WSNs, e.g., CBC- MAC （TinySec）, OCB-MAC （MiniSec）, and XCBC-MAC （SenSee）, might not be exactly suitable for BSNs. Particularly an existential forgery attack is elaborated on XCBC-MAC. Considering the hardware limitations of BSNs, we propose a new family of tunable lightweight MAC based on the PRESENT block cipher. The first scheme, which is named TukP, is a new lightweight MAC with 64-bit output range. The second scheme, which is named TuLP-128, is a 128-bit variant which provides a higher resistance against internal collisions. Compared with the existing schemes, our lightweight MACs are both time and resource efficient on hardware-constrained devices.     

基于无线传感器网络的静力载荷测控仪

针对以往静力载荷实验需要大量布线的麻烦,提出了基于无线传感器网络(WSN,wireless sensor networks)的静力载荷测控仪,所有传感器节点组成一个仪器网络。仪器所有的在前端测控仪实验数据通过WSN上传到基站。基站再将数据通过GPRS上传到远程监管中心。实现了每个基站可以同时管理多个前端测控仪,多组试验同时进行。整个系统组成的仪器网络实现了对试验的自动控制,在试验过程中能够快速、实时上传数据,节省了大量的人力、物力和财力。利用WSN进行通信也节省了大量布线的麻烦。