NEURAL NETS SPEED FLOW CALCULATION

Neural Nets Successfully Solve Complex Fluid Flow Problem. Much research is being done in the area of neural networks, and industry is actively seeking successful application to real world problems. We describe here a successful application. We have used neural networks to model complex coolant flow patterns, such as those encountered in design of hypersonic aircraft. Previous calculation methods, while reasonably accurate, are iterative and extremely time consuming. Our new approach uses a hierarchical neural network architecture to model coolant flow distribution in multiple heat exchanger panels. This method is direct, fast, and accurate.     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

Dynamic Survivability in WDM Mesh Networks Under Dynamic Traffic

Network survivability is a crucial requirement in WDM mesh networks. In this paper, we systematically consider the problem of dynamic survivability with dynamic single link failure in WDM networks under dynamic traffic demands. Specifically, we investigate various protection schemes, such as dedicated path protection (DPP), shared path protection (SPP), dedicated link protection (DLP), shared link protection (SLP), and two restoration schemes, path restoration (PR) and link restoration (LR). Moreover, two new shared protection methods are proposed, i.e., SRLG-based shared link protection (SRLG-SLP) and SRLG-based shared path protection (SRLG-SPP). The SRLG (shared risk link group) constraint defines the availability of protection resources to a working path, which requires that any two working paths sharing the same risk of failure (or in the same SRLG) cannot share the same protection resources. Furthermore, in our study, we consider a more practical dynamic single-link failure model, in which the link-failure-interarrival time and link-failure-holding time are considered as two independent parameters. Based on this link-failure model, extensive simulations are done to analyze and compare the dynamic survivable performance of various protection and restoration schemes. Resource utilization, protection efficiency, restoration efficiency, and service disruption ratio are employed as survivable performance metrics versus traffic load, link-failure frequency, and link-failure reparation time to evaluate the survivable performance. Many meaningful results are given. In addition, we show that the developed SRLG-SLP and SRLG-SPP protection schemes perform very well in terms of protection efficiency and service disruption ratio, while sacrificing some performance in terms of resource utilization.     

Sol-gel preparation of a di-ureasil electrolyte doped with lithium perchlorate

Solid polymer electrolytes (SPEs) synthesized by the sol-gel process and designated as di-ureasils have been prepared through the incorporation of lithium perchlorate, LiClO₄, into the d-U(2000) organic-inorganic hybrid network. Electrolytes with lithium salt compositions of n (where n indicates the number of oxyethylene units per Li⁺ ion) between ∞ and 0.5 were characterized by conductivity measurements, cyclic voltammetry at a gold microelectrode, thermal analysis and Fourier transform Raman (FT-Raman) spectroscopy. The conductivity results obtained suggest that this system offers a quite significant improvement over previously characterized analogues doped with lithium triflate [S.C. Nunes, V. de Zea Bermudez, D. Ostrovskii, M.M. Silva, S. Barros, M.J. Smith, R.A. Sá Ferreira, L.D. Carlos, J. Rocha, E. Morales, J. Electrochem. Soc. 152 (2) (2005), A429]. “Free” perchlorate ions, detected in all the samples examined, are identified as the main charge carriers in the sample that yields the highest room temperature conductivity (n = 20). In the di-ureasils with n ≤ 10 ionic association is favoured and the ionic conductivity drops.     

A Review of Wavelets for Digital Wireless Communication

Wavelets have been favorably applied in almost all aspects of digital wireless communication systems including data compression, source and channel coding, signal denoising, channel modeling and design of transceivers. The main property of wavelets in these applications is in their flexibility and ability to characterize signals accurately. In this paper recent trends and developments in the use of wavelets in wireless communications are reviewed. Major applications of wavelets in wireless channel modeling, interference mitigation, denoising, OFDM modulation, multiple access, Ultra Wideband communications, cognitive radio and wireless networks are surveyed. The confluence of information and communication technologies and the possibility of ubiquitous connectivity have posed a challenge to developing technologies and architectures capable of handling large volumes of data under severe resource constraints such as power and bandwidth. Wavelets are uniquely qualified to address this challenge. The flexibility and adaptation provided by wavelets have made wavelet technology a strong candidate for future wireless communication. Madan Kumar Lakshmanan was born in Chennai, India, in 1979. He received the B.E. (with distinction) in electrical engineering from the University of Madras, Chennai, India, in 2000. He joined the Indian Software firm, Polaris Software Labs Ltd., in 2000 where he wrote software for Telecommunication applications. At Polaris, he was awarded the “On The Spot Of Excellence Award” for his efforts. In 2003, he moved to the Indian Institute of Technology-Madras, to develop and establish a wireless communications network for rural connectivity. In 2004, he was awarded the Royal Dutch/Shell Chevning scholarship to pursue a Master degree in Telecommunications at the Delft University of Technology (TUDelft). At TUDelft he is affiliated to the International Research Center for Telecommunications-Transmission and Radar (IRCTR) where he is undertaking research in the field of wavelets applications in Wireless Communications. Homayoun Nikookar received his Ph.D. in Electrical Engineering from Delft University of Technology (TUDelft), The Netherlands, in 1995. From 1995 to 1998 he was a postdoc researcher at the International Research Center for Telecommunications-Transmission and Radar, TUDelft, where since 1999 he has been an Assistant Professor. Dr. Nikookar has done research on different areas of wireless communications, including wireless channel modeling, UWB, MIMO, multicarrier transmission, Wavelet-based OFDM and CDMA. He is a senior member of the IEEE.     

Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor

Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was used to classify the experimental cutting force data of milling operations previously. Preprocessing (PreP) of the approximation coefficients of the WT is proposed just before the classification by using the Adaptive Resonance Theory (ART2) type NNs. Genetic Algorithm (GA) was used to estimate the weights of each coefficient of the PreP. The WT-PreP-NN (ART2) combination worked at lower vigilances by creating only a few meaningful categories without any errors. The WT-NN (ART2) combination could obtain the same error rate only if very high vigilances are used and many categories are allowed.     

图像压缩编码方法分析

介绍图像压缩编码技术发展过程,对图像压缩编码,特别是自适应预测编码、模型法编码、分形编码、小波变换压缩编码、神经网络压缩编码原理和特点进行分析,并阐述图像压缩编码的作用.     

Application of artificial neural networks to the analysis of two‐dimensional fluorescence spectra in recombinant E coli fermentation processes

A two‐dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E coli for the production of 5‐aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyzed using artificial neural networks, ie self‐organizing map (SOM) and feedforward backpropagation neural network (BPNN). The SOM‐based classification of the whole spectral data has made it possible to qualitatively associate some process parameters with the normalized weights and variances, and to select some useful combinations of excitation and emission wavelengths. Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process's performance, eg forecasting the process's performance. Copyright © 2005 Society of Chemical Industry     

人类HLA-DRB1基因型与民族和人群的神经网络无监督模式分类

HLA-DRB1等位基因主要参与人类的抗原免疫功能,对其进行比较研究,有助于追溯人类的进化迁移史,开发类群特异性药物.本研究以Matlab为平台,用自组织竞争网络(Self-Organizing Competitive Neural Network),对世界54个民族和人群、14个HLA-DRB1等位基因,进行了无监督模式分类.结果表明,各民族之间存在差异性,同民族的各人群之间有相似性.西伯利亚各人群,澳洲各土著人群,黑人各人群,南美印第安各人群,犹太族各人群,日本各人群,及欧美白人各人群有相对独立性:南美印第安人与西伯利亚人有高度相似性;中国民族在南方人群和北方人群间存在较大差异;中国汉族中,广东汉族地位特殊,与少数民族如拉祜族、瑶族关系密切.     

Linearly many faults in Cayley graphs generated by transposition trees

We prove that when linearly many vertices are deleted in a Cayley graph generated by a transposition tree, the resulting graph has a large connected component containing almost all remaining vertices.