模内贴箔装饰的自动化生产

详细介绍了一种新型装饰工艺－模内贴箔工艺的自动化过程及生产要求。     

Parallel source separation system for heart and lung sounds

The Journal of Supercomputing - In this paper, we propose a parallel source separation system designed to extract heart and lung sounds from single-channel mixtures. The proposed system is based on...     

塑料包装应用及技术进展

塑料在包装领域有着广泛的应用，其中聚酯（PET）性能优良，应用领域不断扩大。介绍了塑料包装不断通现的新技术，以及塑料包装环保问题的几点思路。     

L波段微波功率合成技术研究

无人机机载功率放大器的性能一直是限制无人机技术发展的主要因素,为此提出了将功率合成技术应用于无人机数据系统的方法解决上述问题。利用微带线技术结合系统性的电路调试方法,辅以Advanced Design System仿真软件优化设计,同时采用实频技术法进行宽带功放设计,成功研制了频段在1.3 GHz~1.7 GHz的功率放大器,单路功率放大器采用级联的技术输出功率为8 W,两路合成后,实测总输出功率为15.67 W,合成效率达97%,性能稳定,达到实用水平。     

Trust-based group services selection in web-based service-oriented environments

Multi-agent technologies have been widely employed for the development of web-based systems, including web-based e-markets, web-based grid computing, e-governments and service-oriented software systems. In these service-oriented systems, service provider agents and service consumer agents are autonomous and rational entities, which can enter and leave the environments freely. For simplicity, we use terms ‘provider’ and ‘consumer’ to represent this two types of agents. How to select the most suitable service providers according to a service request from a consumer in such an open environment is a very challenging issue. In this paper, we propose an innovative trust model, called the GTrust model, for service group selection in general service-oriented environments. In the GTrust model, the trust evaluation for a service group is based on the functionality coverage of the group, the dependency relationships among individual services in the group, the ratings of individual services on the attributes of the service request and a similarity measurement of the extent to which reference reports can reflect the service request in terms of the priority distribution of attributes. The experimental results and analysis demonstrate the good performance of the GTrust model on the service group selection in service-oriented environments.     

Optimizing content placement in a peer-assisted VoD architecture

Recently, a new peer-assisted architecture to build content delivery systems has been presented. This architecture is based on the use of the storage capacity of end-users’ set-top boxes (STBs), connected in a peer-to-peer (P2P) manner in order to help the content servers in the delivery process. In these systems, the contents are usually split into a set of smaller pieces, called sub-streams, which are randomly injected at the STBs. The present paper is focused on Video on Demand (VoD) streaming and it is assumed that the STB-based content delivery system is deployed over the global Internet, where the clients are distributed over different ISP networks. In this scenario, three different strategies are studied for increasing the percentage of data uploaded by peers, in order to offload the content servers as much as possible. First of all, a new mechanism is presented which determines which sub-stream has to be placed at which STB by a Non-Linear Programming (NLP) formulation. A different strategy for reducing the content server load is to take advantage of the available bandwidth in the different ISP networks. In this sense, two new mechanisms for forwarding the VoD requests to different ISP networks are presented. Finally, the present paper also shows that in some situations the available uplink bandwidth is associated with STBs that do not have the required sub-streams. Regarding this concern, a new mechanism has been designed that dynamically re-allocates some streams, which are being transmitted from specific STBs, to different STBs, in order to find the necessary resources to start new streaming sessions.     

基于ICA的非线性自适应特征融合的人耳识别

针对单一特征的人耳识别对旋转角度鲁棒性差的问题,提出一种非线性自适应特征融合的方法.首先提取人耳的2种具有互补性质的独立成分特征,然后将它们加权串联形成高维融合特征;最后通过核主元分析方法实现非线性降维.实验结果表明,当人耳有姿态旋转时,融合特征较单一特征的识别率有显著提升,且文中方法比传统的串联融合的识别结果更好.     

创造性思维培养与表现——刍议创意素描教学

创意素描教学,就是要培养学生创造性思维能力,掌握创意设计的理念和方法,通过对学生创造性思维的培养,从具象到抽象、从写实到意象的训练,学生无限的创造力一定会大大激发出来。