基于MoCA标准的家庭网络研究

本文描述了一种基于MOCA标准的家庭网络,并对该网络及设备进行了基本性能的测试.本文首先介绍了家庭网络的发展现状,对目前的各种家庭网络标准进行了比较.在此基础上详细描述了基于MOCA标准的家庭网络,并对该网络的设计,实现、网络性能进行了详述.然后对该网络进行了测试并得出了相关的测试结论.最后指出该网络的不足及改进之处.     

镁钴铝类水滑石催化合成安息香甲醚

采用共沉淀法制备了镁钴铝类水滑石化合物(MgCoAl-HTLcs),并用 X 射线衍射、扫描电子显微镜、NH_3程序升温脱附等方法对 MgCoAl-HTLcs 进行了表征,并以 MgCoAl-HTLcs 为催化剂催化苯甲醛与甲醇反应合成安息香甲醚,研究了n(Mg):n(Co):n(Al)、催化剂用量、原料配比、反应温度、反应时间对合成反应的影响。表征结果显示,MgCoAl-HTLcs 的晶相完整,表面主要为弱酸、弱碱性。催化合成安息香甲醚的适宜条件为:MgCoAl-HTLcs 催化剂用量0.10 g(约为原料总质量的0.23%),n(Mg):n(Co):n(Al)=0.4:1.6:1.0,V(苯甲醛):V(甲醇)=3:50,反应温度50℃,反应时间150 min。在此条件下,苯甲醛的平衡转化率达77.49%,安息香甲醚选择性接近100%。为洁净合成安息香甲醚开辟了一条新的途径。     

Recrystallization of phenylbutazone using supercritical fluid antisolvent process

Phenylbutazone was recrystallized from its solutions by using a supercritical fluid antisolvent process. It was dissolved in acetone and supercritical carbon dioxide was injected into the solution, thereby inducing supersaturation and particle formation. Variation in the physical properties of the recrystallized phenylbutazone was investigated as a function of the crystallizing temperature and the carbon dioxide injection rate. The recrystallized particles showed cleaner surfaces and more ordered morphology compared to the particles obtained by other methods such as solvent evaporation. X-ray diffraction patterns indicated that the crystallinity of the particles had been modified upon the recrystallization. Differential scanning calorimetry measurement revealed that the crystallizing temperature influenced the thermal stability of the resulting crystals. Larger crystals were produced when the carbon dioxide injection rate was reduced.     

Photochemical reduction of molecular weight and number of double bonds in natural rubber film

Natural rubber (NR) can be degraded depending on various factors such as heat, mechanical force, chemical reaction, and light. Light is a very interesting factor because it can cause the NR to degrade under low temperature and pressure. The photo-degradation of NR films was carried out to investigate the effects of the light and the temperature on the reduction of the weight-average molecular weight (Mw) and the double bonds in the NR films. The NR films, with and without catalysts, titanium dioxide (TiO₂), and potassium persulfate (K₂S₂O₈), were exposed to light from a mercury light bulb at 7,000 and 36,000 lux, and at the temperature of 25 °C and 80 °C for 192 hrs. After exposure, the Mw of the NR films was analyzed by gel permeation chromatography (GPC). Changes in the Mw were used to construct a kinetic model for the process, (1/Mw)=(1/Mw₀)+(kt/2M₀) where k is the rate constant, and M₀ is the Mw of the monomer unit. The linear relationship between 1/Mw and time suggested pseudo first-order processes with random scission. The Mw distribution information from the GPC was used to calculate the number of double bonds in the NR films. The trend of the double bonds reduction curves was quite similar to the result obtained from the calculation from the FTIR spectra. This indicated that this calculation method might possibly be another alternative way to obtain the number of double bonds in the NR.     

涤纶复合丝（POY＋DTY）的研发

DTY和POY网络复合丝是以聚酯直纺生产的两种不同规格的POY丝为原料,通过对加弹机进行适当改造,利用不同的加工路线,使一股POY丝经过加捻后形成DTY,再与另一股POY丝网络合股形成包芯复合丝.该复合丝利用POY丝和DTY丝的收缩差异和染色差异等不同风格特性,使得布面形成一种具有雪花状的色丁效果.该复合丝属于差别化纤维,是国家鼓励发展的项目,它具有优良的吸湿排汗性能和弹性保暖性能,是保暖内衣的首选面料,市场前景广阔.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Simulating a Smartboard by Real-Time Gesture Detection in Lecture Videos

Gesture plays an important role for recognizing lecture activities in video content analysis. In this paper, we propose a real-time gesture detection algorithm by integrating cues from visual, speech and electronic slides. In contrast to the conventional “complete gesture” recognition, we emphasize detection by the prediction from “incomplete gesture”. Specifically, intentional gestures are predicted by the modified hidden Markov model (HMM) which can recognize incomplete gestures before the whole gesture paths are observed. The multimodal correspondence between speech and gesture is exploited to increase the accuracy and responsiveness of gesture detection. In lecture presentation, this algorithm enables the on-the-fly editing of lecture slides by simulating appropriate camera motion to highlight the intention and flow of lecturing. We develop a real-time application, namely simulated smartboard, and demonstrate the feasibility of our prediction algorithm using hand gesture and laser pen with simple setup without involving expensive hardware.