IFR-2000阻燃聚丙烯热性能研究

研究了用无卤膨胀型阻燃剂IFR-2000作阻燃剂的阻燃聚丙烯的热性能和阻燃性能。     

聚氨酯防水涂料及其市场发展概况

聚氨酯防水涂料是当今最有效的柔性防水材料之一，介绍了聚氨酯防水涂料的发展状况，并对其市场前景进行了展望。     

NBR／EPDM的增容共混研究

本文采用第三组份增容途径,改善了NBR/EPDM并用胶的相容性、加工性和力学性能。通过对不同增容体系的研究对比,发现不同增容剂的增容效果差异很大,其巾以EVA-14增容效果最为显著,加入该增容剂的并用胶,在适当的工艺条件及硫化体系下,可获得最佳力学性能。本文还研究了不同增容剂对并用炭黑胶各种性能的影响,可以做到在不降低并用胶的力学性能的同时,提高并用胶的耐热空气老化、耐大气老化和耐臭氧老化性能.透射电镜实验和动态力学谱图证明了加与未加增容剂时,NBR/EPDM并用胶均为两相结构,增容剂起表面活性剂的作用,加强了两相界面间的相互作用,使分散相EPDM细微化和均匀化。     

基于多步迭代算法的数字预失真技术

为了更好地补偿功率放大器的非线性,提出一种新型多步迭代算法来求取数字预失真器。新算法结合了多步迭代算法与频域削峰技术,使功放在保证工作效率的同时更大程度提高其线性度。实验结果显示,该方法较传统的线性化技术有明显优势,功放输出信号的ACPR可改善20.66 dB。     

透明聚烯烃用成核剂合成的研究

介绍了聚烯烃成核剂合成反应所用助剂选择,反应条件的确立,利用均匀设计实现最佳配比实验,对不同侧基苯甲醛缩合反应进行了研究。     

凉山彝族自治州水电站接入电力通信网方案探讨

"十二五"期间,国网凉山供电公司电网智能化程度日益提高,但由于受地域条件和经济发展的限制,地处凉山彝族自治州偏远山区的水电站基本没有覆盖电力通信网络,电厂自动化信息等无法上传至电力调度控制中心。对此,本文提出了两种不同的方案来解决并网电厂通信通道的瓶颈问题,以期满足并网电厂与电力调度控制中心的实时数据交互。     

基于XC2287M的工程机械ECU设计

ECU是工程机械电控系统的核心部件,目前国内中高端ECU市场基本被国外厂商所垄断。设计了一款基于XC2287M微控制器的工程机械智能ECU,采用CODESYS软PLC作为编程平台,支持IEC 61131-3定义的5种标准PLC语言进行编程。所设计的ECU拥有丰富的I/O资源和完善的安全保护机制,能够广泛应用于各种工程机械控制系统,打破国外厂商对ECU市场的垄断。     

A saliency-driven robotic head with bio-inspired saccadic behaviors for social robotics

This paper presents a robotic head for social robots to attend to scene saliency with bio-inspired saccadic behaviors. Scene saliency is determined by measuring low-level static scene information, motion, and object prior knowledge. Towards the extracted saliency spots, the designed robotic head is able to turn gazes in a saccadic manner while obeying eye–head coordination laws with the proposed control scheme. The results of the simulation study and actual applications show the effectiveness of the proposed method in discovering of scene saliency and human-like head motion. The proposed techniques could possibly be applied to social robots to improve social sense and user experience in human–robot interaction.     

Toward seed-insensitive solutions to local community detection

Local community detection aims at finding a community structure starting from a seed which is a given vertex in a network without global information, such as online social networks that are too large and dynamic to ever be known fully. Nonetheless, the existing approaches to local community detection are usually sensitive to seeds, i.e., some seeds may lead to missing of some true communities. In this paper, we present a seed-insensitive method called GMAC and its variation iGMAC for local community detection. They estimate the similarity among vertices by investigating vertices’ neighborhoods, and reveal a local community by maximizing its internal similarity and minimizing its external similarity simultaneously. Extensive experimental results on both synthetic and real-world data sets verify the effectiveness of our algorithms.     

Multi-scale patch-based sparse appearance model for robust object tracking

When objects undergo large pose change, illumination variation or partial occlusion, most existing visual tracking algorithms tend to drift away from targets and even fail to track them. To address the issue, in this paper we propose a multi-scale patch-based appearance model with sparse representation and provide an efficient scheme involving the collaboration between multi-scale patches encoded by sparse coefficients. The key idea of our method is to model the appearance of an object by different scale patches, which are represented by sparse coefficients with different scale dictionaries. The model exploits both partial and spatial information of targets based on multi-scale patches. Afterwards, a similarity score of one candidate target is input into a particle filter framework to estimate the target state sequentially over time in visual tracking. Additionally, to decrease the visual drift caused by frequently updating model, we present a novel two-step object tracking method which exploits both the ground truth information of the target labeled in the first frame and the target obtained online with the multi-scale patch information. Experiments on some publicly available benchmarks of video sequences showed that the similarity involving complementary information can locate targets more accurately and the proposed tracker is more robust and effective than others.