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.     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

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.     

Analysis of the Datagram Congestion Control Protocol’s connection management procedures using the sweep-line method

State space explosion is a key problem in the analysis of finite state systems. The sweep-line method is a state exploration method which uses a notion of progress to allow states to be deleted from memory when they are no longer required. This reduces the peak number of states that need to be stored, while still exploring the full state space. The technique shows promise but has never achieved reductions greater than about a factor of 10 in the number of states stored in memory for industrially relevant examples. This paper discusses sweep-line analysis of the connection management procedures of a new Internet standard, the Datagram Congestion Control Protocol (DCCP). As the intuitive approaches to sweep-line analysis are not effective, we introduce new variables to track progress. This creates further state explosion. However, when used with the sweep-line, the peak number of states is reduced by over two orders of magnitude compared with the original. Importantly, this allows DCCP to be analysed for larger parameter values. Somsak Vanit-Anunchai was partially supported by an Australian Research Council Discovery Grant (DP0559927) and Suranaree University of Technology. Guy Edward Gallasch was supported by an Australian Research Council Discovery Grant (DP0559927).     

Real-time measurement of pointing action by using DSP

This paper presents an approach of measuring in real-time the vector of finger that is pointing to an object. DSP is used in the operation processing unit in order to do the real-time processing. The steps include the extraction of flesh-colored regions from an image, the labeling of the flesh-colored regions, and the detection of two characteristic positions on the finger so that the direction that the finger is pointing at will be calculated. The entire process takes about 29 msec, which makes it possible to have the frame rate of 34 fps. With this frame rate, this measurement approach is considered real-time and promising to be merged into other application systems. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

含V、N无缝钢管表面外折缺陷产生原因的分析

通过对鞍钢生产的部分批号V、N微合金强化无缝钢管及生产该钢管的原料连铸坯和连轧管坯的表面缺陷进行研究，分析了含V、N钢管表面外折缺陷的成因，提出了改善钢管表面质量的方法。采用改进后工艺生产的无缝管，其表面外折废品量大幅度降低。