Using rainbow net simulation to measure fault tolerance in a multiprocessor

The Rainbow net simulation technique is applied to modelling the impact of system load and fault handling on the availability of a fault-tolerant multiprocessor architecture. Rainbow nets are described along with the motivation for creating this modelling technique. A Rainbow net fault-handling model is created for the fault-tolerant multiprocessor architecture and the topology is shown to remain constant in size, independent of the number of processor, memory and I/O elements configured in the system. Simulation is performed with a varying load in terms of the number of active jobs the system must support. Results are given showing how the fault-tolerant capability varies with load. Two new metrics for evaluating fault tolerance are introduced; namely full fault-tolerability and partial fault-tolerability. They are based on simple observations in the model.     

Targets and methods for the detection of processed animal proteins in animal feedstuffs

Bovine spongiform encephalopathy (BSE), or ‘mad cow disease’, is one of several transmissable spongiform encephalopathies (TSEs) known to affect certain mammals and is spread through the ingestion of infected animal tissue. It is believed that the inadvertent contamination of meat and bone meal (MBM) with infected animal tissue and the subsequent use of this material as a feed supplement contributed to the spread of the disease in cattle. As a result, the use of processed animal proteins (PAPs) in animal feeds is regulated in many parts of the world. Although feed testing is the only definitive means to certify compliance, regulatory compliance often relies solely on paper certification. Recently, rapid methods have become available that can be used by regulators to determine compliance during routine inspections. We describe a rapid, immunochromatographic strip test that can detect 0.1% MBM in animal feed. The test takes 15 min to perform and large numbers of samples can be screened for PAPs simultaneously.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

Cross-Border Migration of Hong Kong Residents Under the 'One Country, Two Systems' Policy

Hong Kong is known as a migrant city because its population was sourced from mainland China, and because there has always been outflows of people to overseas countries, especially from the mid-1980s to mid-1990s. Emigration to mainland China has become a significant recent trend. This article discusses this phenomenon in the theoretical contexts of migration and trans-border residential development. It contends that the trend will intensify more quickly than other cross-border movements because the two systems are separated by a political border within one country, and because there are common cultural ties and rapid economic integration.     

Exergoeconomic analysis and evaluation of energy-conversion plants—I. A new general methodology

A new approach to the combination of exergetic and economic analysis (exergoeconomic analysis) for the investigation of energy-conversion processes is presented. This approach allows the monetary evaluation of costs caused by irreversibilities (exergy losses), as well as comparisons between these costs and the investment and operating costs for each component of a plant. The present analysis permits identification and evaluation of inefficiencies in an energy-conversion plant and of opportunities for improvement.     

The Geography of Opportunity and Unemployment: An Integrated Model of Residential Segregation and Spatial Mismatch

Abstract: This article combines the neighborhood effects and spatial mismatch frameworks into a single model explaining how geographic factors contribute to unemployment. Using National Longitudinal Survey of Youth (1979) data, I estimate a two‐step model that separately models the effects of segregation and spatial mismatch. The first model predicts educational attainment as a function of exposure to residential segregation as a youth. The second model predicts unemployment probability as an adult as a function of educational attainment and spatial mismatch. The empirical results show that segregation does have discernable effects on educational attainment for blacks, but not for whites. I also find that spatial mismatch affects unemployment probability for blacks, but such an effect is hardly present for whites. A partial equilibrium analysis using predictions from the models shows that large changes in either segregation levels or the central city/suburban distribution of the black population would yield only moderate decreases in unemployment probability for the black population overall. Yet despite small predicted effects, these results should be viewed with caution because the general equilibrium effects of a large scale movement of blacks and whites across metropolitan space are largely impossible to predict with current data.