玻纤增强聚苯硫醚复合材料的增韧研究

针对玻纤增强聚苯硫醚材料韧性差的问题，对聚苯硫醚傲璃纤维复合体系的增韧进行了研究，考察了玻纤、改性聚合物、有机超细粒子对复合材料力学性能的影响。采用基体增韧（预增韧）与有机超细粒子增韧技术，在保持复合材料拉伸强度和模量的同时，较大地提高了冲击强度，获得了综合力学性能优异的纤维增强聚苯硫醚材料。     

Case-based context ontology construction using fuzzy set theory for personalized service in a smart home environment

To provide context-based personalized services utilizing smart appliances in a smart home environment, we propose a framework for PersonAlized Service disCovery Using FuZZY-based CBR and Context Ontology (PASCUZZY). Basically, the PASCUZZY framework is implemented on case-based context ontology. To generate and manage the case instances on the case-based context ontology, we adopt the fuzzy set theory to transpose numerical-type context data sensed from the surrounding environment. The context is transposed to linguistic-type context instances on the context ontology. In addition, to formalize and manage the context and services as multi-attributed data, the context ontology was developed reflecting the structure of cases borrowed from case-based reasoning. Furthermore, we propose adaptation methods to adjust the generic fuzzy membership functions depending on the inhabitants’ context. It is performed by modifying the values of the membership number and/or modifying the numbers of the linguistic terms that are based on the inhabitants’ context to affect the membership numbers. The adapted membership functions return the personalized degree of memberships depending on the specialized context of a specific fuzzy variable. Inevitably, the number of cases on the case-based context ontology will be increased from time to time. We apply Ward’s method not only to reduce the search effort via a hierarchical clustering on the case-based context ontology but also to find the most similar service as a solution to the new context. To verify the superiority of the PASCUZZY framework, we perform two kinds of evaluations. First, we evaluate the effectiveness of the adaptation of the fuzzy membership functions. Second, we verify the effectiveness of the application of a clustering method to the case instances of the case-based context ontology to identify the most similar service. Results of the experiment verified the effectiveness and superiority of the PASCUZZY framework.     

A fully autonomous kernel-based online learning neural network model and its application to building cooling load prediction

Building cooling load prediction is critical to the success of energy-saving measures. While many of the computational models currently available in the industry have been developed for this purpose, most require extensive computer resources and involve lengthy computational processes. Artificial neural networks (ANNs) have recently been adopted for prediction, and pioneering works have confirmed the feasibility of this approach. However, users are required to predetermine an ANN model’s parameters. This hinders the applicability of the ANN approach in actual engineering problems, as most engineers may be unfamiliar with soft computing. This paper proposes a fully autonomous kernel-based neural network (AKNN) model for noisy data regression prediction. No part of the model’s mechanism requires human intervention; rather, it self-organises its structure according to the training samples presented. Unlike the other existing autonomous models, the AKNN model is an online learning model. It is particularly suitable for online steps-ahead prediction. In this paper, we benchmark the AKNN model’s performance according to other ANN models. It is also successfully applied to predicting the cooling load of a commercial building in Hong Kong. The occupancy areas and concentration of carbon dioxide inside the building are successfully adopted to mimic the building’s internal cooling load. Training data was adopted from actual measurements taken inside the building. Its results show reasonable agreement with actual cooling loads.     

Real-time stochastic optimal control for traffic signals of multiple intersections

In this paper, a real-time stochastic optimal control method of traffic signal is modified. In addition, H-GA-PSO algorithm is proposed to search optimal traffic signals based on the stochastic model. The H-GA-PSO algorithm is a modified Hierarchical Particle Swarm Optimization (H-PSO) algorithm based on Genetic Algorithm (GA) processing. Finally, the effectiveness of the stochastic optimal control method with H-GA-PSO algorithm is shown through simulations at multiple intersections using a micro-traffic simulator.     

试论供电企业的电力营销管理方法

树立正确的营销意识,丰富营销方法,有利于供电企业更好地适应不断变化的市场,提供质量更高的市场服务。分析了供电企业电力营销中存在的问题,提出了具体的改革方法。     

基于RFID的电动车防盗系统开发

针对目前市面上普通电动车防盗器不能满足广大车主新的防盗要求,为了弥补普通防盗器功能的不足,本防盗系统整合了RFID技术和GSM模块,在电动车被盗时,第一时间通知车主,实现了车主对车辆的24小时监控。系统具有自动感应外接电源电压,如果外电被剪或是无电,均会向车主进行报警。     

聚萘二甲酸乙二醇酯(PEN)的研究及发展

综述了聚萘二甲酸乙二醇酯(PEN)的发展历史,合成工艺,应用领域及其与PET的性能比较。     

粉状聚丙烯耐老化改性

通过添加各种改性和成型加工助剂，有效地解决粉状聚丙烯在加工和其制品实际使用过程中，可能产生的热氧老化问题。在编织袋应用中，其耐老化性能已达到甚至超过粒状聚丙烯生产的同类制品水平。     

Morphologies-Controlled Synthesis and Optical Properties of Bismuth Tungstate Nanocrystals by a Low-Temperature Molten Salt Method

Well-crystallized bismuth tungstate (Bi₂WO₆) powders with different morphologies were successfully synthesized via a low-temperature molten salt method. The powders were characterized by X-ray diffraction, transmission electron microscopy, and UV-Vis, respectively. It was found that the variation of morphology of the obtained Bi₂WO₆ powder mainly depends on the different reaction temperatures and the weight ratio of LiNO₃–NaNO₃ salt to precursor. In addition, the UV-Visible absorption spectra showed that the synthesized powders had strong light absorption properties not only in the ultraviolet light but also in the visible light region.     

The SMSI between supported platinum and CeO2–ZrO2–La2O3 mixed oxides in oxidative atmosphere

CeO₂–ZrO₂–La₂O₃ (CZL) mixed oxides were prepared by citric acid sol–gel method. The as-received gel was calcined at 500, 700, 900 and 1050 °C to obtain the so-called C5, C7, C9 and CK, respectively. The C5, C7 and C9 powders were impregnated with H₂PtCl₆ and then calcined at 500 °C to prepare P5C5, P5C7 and P5C9, respectively. The impregnated CK powders were calcined at 500, 700 and 900 °C to prepare P5CK, P7CK and P9CK, respectively. The XRD and XPS analyses show that the surface distribution of Pt is evidently influenced by the structural and textural properties of the support. The CO adsorption followed by FTIR reveals that the dispersion and the chemisorption sites of Pt are reduced as the calcination temperature of CZL support increases. The chemisorption ability of the CK samples is even completely deactivated. The encapsulation mechanism, which has been applied to explain the so-called strong metal–support interaction (SMSI) after reductive treatment, is introduced here to demonstrate the abnormal observations though the samples were prepared in oxidative atmosphere. The HRTEM results also confirm this explanation. The effects of oxygen vacancies, the chemisorption sites on the Pt surface and Pt/Ce interfacial sites on the three-way catalytic activities are discussed.