http://hdl.handle.net/10397/53 Search the Channel search http://repository.lib.polyu.edu.hk/jspui/simple-search http://hdl.handle.net/10397/5575 Title: Adapting a main-stream internet switch architecture for multihop real-time industrial networks<br/><br/>Authors: Wang, Qixin; Gopalakrishnan, Sathish<br/><br/>Abstract: As real-time industrial control systems scale up, single real-time local area network (LAN) is no longer sufficient; instead, we need real-time switches to merge many real-time LANs into real-time wide area networks (WANs). However, nowadays commercially-off-the-shelf WAN switches are designed for best-effort Internet traffic rather than real-time traffic. To address this problem, we propose a real-time crossbar switch design that minimally modifies, and even simplifies the de facto industrial standard switch design of iSLIP. Specifically, we change the iSLIP request-grant-accept negotiation to deterministic grant. The switch runs periodically with an M cell-time clock-period. Every input port runs per-flow queueing, and every output port deterministically grants input port per-flow queues according to its own M cell-time clock-period schedule. The schedules are created offline. We prove that the global scheduling can be reduced to a preemptive open shop scheduling problem; as long as every input/output needs to send/fetch no more than M cells per M cell-time clock-period, all outputs schedules do not conflict; and the scheduling algorithm takes O(N4) time (N is the number of input/output ports). Such design serves real-time periodic/aperiodic traffic in a time-division multiple-access (TDMA) fashion. This simplifies analysis, provides isolation, and results in a close-form end-to-end delay bound. We implemented the proposed real-time switch using Xilinx field programmable gate arrays (FPGAs), and built a distributed control test bed upon the switched networks. Using the test bed, we carried out experiments to compare the implemented real-time switches and iSLIP switches. The results prove the necessity of using real-time switches for real-time industrial control.<br/><br/>Description: DOI: 10.1109/TII.2010.2051557 Sun, 01 Aug 2010 00:00:00 GMT http://hdl.handle.net/10397/5201 Title: Implementation and applications of chaotic oscillatory based neural network for wind prediction problems<br/><br/>Authors: Kwong, K. M.; Tee, F. W.; Liu, James N. K.; Chan, P. W.<br/><br/>Abstract: La cizalladura del viento y los cambios repentinos en su dirección y velocidad son un peligro familiar para la aviación, así como un fenómeno complejo y difícil de predecir. Las causas de las cizalladuras pueden variar según el lugar. En algunos sitios se deben a reventones, columnas localizadas de aire descendente, mientras que en otros lugares las cizalladuras pueden ser consecuencia de fenómenos meteorológicos de mesoescala. Por lo tanto, los algoritmos y técnicas que se utilizan para predecir las cizalladuras del viento causadas por reventones, como en Wolfson et al. (1994), no serán aplicables en un aeropuerto donde la cizalladura del viento y la turbulencia surgen de las condiciones locales pero de escala mayor. Este trabajo presenta la implementación y aplicación de redes neuronales caóticas oscilatorias (CONN) para predecir la brisa marina y la cizalladura del viento que se originan en los fenómenos meteorológicos de mesoescala en el Aeropuerto Internacional de Hong Kong. Utilizando datos históricos locales proporcionados por el Observatorio de Hong Kong se muestra, a partir de simulaciones, que CONN es capaz de predecir los movimientos del viento y hasta cizalladuras con un nivel razonable de precisión.; Wind shear, sudden change in the wind direction and speed, is a familiar hazard to aviation as well as a complex and hard-to-predict phenomenon. The causes of wind shear may be different in different locations. In some places it is caused by microbursts, viz. localized columns of sinking air brought by thunderstorms, while in other places wind shear may result from mesoscale weather phenomena. Thus, algorithms and techniques used to predict wind shear caused by microbursts, as in Wolfson et al. (1994), will not be applicable at an airport where wind shear and turbulence arise from larger-scale but local conditions. This paper presents the implementation and applications of chaotic oscillatory-based neural networks (CONN) for predicting sea breeze and wind shear arising from mesoscale weather phenomenon at the Hong Kong International Airport. Using historical local data provided by the Hong Kong Observatory, we show from simulations that CONN is able to forecast the short-term wind evolution and even wind shear events with a reasonable level of accuracy. Sat, 01 Jan 2011 00:00:00 GMT http://hdl.handle.net/10397/5118 Title: Unsupervised fuzzy pattern discovery in gene expression data<br/><br/>Authors: Wu, Gene P. K.; Chan, Keith C. C.; Wong, Andrew K. C.<br/><br/>Abstract: Background: Discovering patterns from gene expression levels is regarded as a classification problem when tissue classes of the samples are given and solved as a discrete-data problem by discretizing the expression levels of each gene into intervals maximizing the interdependence between that gene and the class labels. However, when class information is unavailable, discovering gene expression patterns becomes difficult.; Methods: For a gene pool with large number of genes, we first cluster the genes into smaller groups. In each group, we use the representative gene, one with highest interdependence with others in the group, to drive the discretization of the gene expression levels of other genes. Treating intervals as discrete events, associationpatterns of events can be discovered. If the gene groups obtained are crisp gene clusters, significant patterns overlapping different gene clusters cannot be found. This paper presents a new method of “fuzzifying” the crisp gene clusters to overcome such problem.; Results: To evaluate the effectiveness of our approach, we first apply the above described procedure on a synthetic data set and then a gene expression data set with known class labels. The class labels are not being used in both analyses but used later as the ground truth in a classificatory problem for assessing the algorithm’seffectiveness in fuzzy gene clustering and discretization. The results show the efficacy of the proposed method. The existence of correlation among continuous valued gene expression levels suggests that certain genes in the gene groups have high interdependence with other genes in the group. Fuzzification of a crisp gene cluster allows the cluster to take in genes from other clusters so that overlapping relationship among gene clusters could beuncovered. Hence, previously unknown hidden patterns resided in overlapping gene clusters are discovered. From the experimental results, the high order patterns discovered reveal multiple gene interaction patterns in cancerous tissues not found in normal tissues. It was also found that for the colon cancer experiment, 70% of the top patterns and most of the discriminative patterns between cancerous and normal tissues are among thosespanning across different crisp gene clusters; Conclusions: We show that the proposed method for analyzing the error-prone microarray is effective even without the presence of tissue class information. A unified framework is presented, allowing fast and accurate pattern discovery for gene expression data. For a large gene set, to discover a comprehensive set of patterns, gene clustering, gene expression discretization and gene cluster fuzzification are absolutely necessary.<br/><br/>Description: DOI: 10.1186/1471-2105-12-S5-S5 Wed, 27 Jul 2011 00:00:00 GMT http://hdl.handle.net/10397/5094 Title: WiCop: engineering WiFi temporal white-spaces for safe operations of wireless body area networks in medical applications<br/><br/>Authors: Wang, Yufei; Wang, Qixin; Zeng, Zheng; Zheng, Guanbo; Zheng, Rong<br/><br/>Abstract: ZigBee and other wireless technologies operating in the (2.4GHz) ISM band are being applied in Wireless Body Area Networks (WBAN) for many medical applications. However, these low duty cycle, low power, and low data rate medical WBANs suffer from WiFi co-channel interferences. WiFi interference can lead to longer latency and higher packet losses in WBANs, which can be particularly harmful to safety-critical applications with stringent temporal requirements. Existing solutions to WiFi-WBAN coexistence either require modifications to WiFi or WBAN devices, or have limited applicability. In this paper, by exploiting the Clear Channel Assessment (CCA) mechanisms in WiFi devices, we propose a novel policing framework, WiCop, that can effectively control the temporal white-spaces between WiFi transmissions. Specifically, the WiCop Fake-PHY-Header policing strategy uses a fake WiFi PHY preamble-header broadcast to mute other WiFi interferers for the duration of WBAN active interval, while the WiCop DSSS-Nulling policing strategy uses repeated WiFi PHY preamble (with its spectrum side lobe nulled by a band-pass filter) to mute other WiFi interferers throughout the duration of WBAN active interval. The resulted WiFi temporal white-spaces can be utilized for delivering low duty cycle WBAN traffic. We have implemented and validated WiCop on SORA, a software defined radio platform. Experiments show that with the assistance of the proposed WiCop policing schemes, the packet reception rate of a ZigBee-based WBAN can increase by up to 43.8% in presence of a busy WiFi interferer.<br/><br/>Description: DOI: 10.1109/RTSS.2011.23 Thu, 01 Dec 2011 00:00:00 GMT