Assessment of commercial sand barge radar for detecting overwintering diving ducks at Lough Neagh

Overwintering diving ducks at Lough Neagh have declined dramatically in recent years, but it has been suggested that on-to-offshore redistribution may have led to an underestimate of numbers. Most species feed nocturnally and their distribution at night is unknown. We used radar and visual observations from on board commercial sand barges to determine the diurnal distribution of diving duck flocks in an effort to assess the feasibility of using standard
boat-mounted radar to describe their nocturnal feeding distribution. Sand barge radar was poor in identifying flocks compared to independent visual observations as it was sensitive to interference by waves during windy conditions. However, visual observations were useful in describing diurnal distribution. Sand barges were on average 1.5km from shore when a flock of diving ducks was observed and the probability of detection declined with distance from shore. This supports the reliability of shore-based counts in monitoring and surveillance. Given the poor performance of commercially available boatmounted radar systems, we recommend the use of specialised terrestrial Bird Detecting Radar to determine the movements of diving ducks at Lough Neagh.

Work-related training and the probability of transitioning from non-permanent to permanent employment

It is widely believed that work-related training increases a worker’s probability of moving up the job-quality ladder. This is usually couched in terms of effects on wages, but it has also been argued that training increases the probability of moving from non-permanent forms of employment to more permanent employment. This hypothesis is tested using nationally representative panel data for Australia, a country where the incidence of non-permanent employment, and especially casual employment, is high by international standards. While a positive association between participation in work-related training and the subsequent probability of moving from either casual or fixed-term contract employment to permanent employment is observed among men, this is shown to be driven not by a causal impact of training on transitions but by differences between those who do and do not receive training; i.e., selection bias.

Threshold Optimization for Energy Detection-Based Spectrum Sensing Over Hyper-Rayleigh Fading Channels

Spectrum sensing is a key function of cognitive radio systems. Sensing performance is determined by three main factors including the wireless channel between the primary system and the cognitive radio nodes, the detection threshold, and the sensing time. In this letter a closed-form expression for the average probability of detection for energy detection based spectrum sensing over two-wave with diffuse power fading channels is derived. This expression is then used to optimize the detection threshold for cognitive radio nodes, which operate in confined structures that exhibit worse than Rayleigh fading conditions. Such fading conditions can represent a behavioral model of cognitive machine-to-machine systems deployed in enclosed structures such as in-vehicular environments.

Energy Detection based Spectrum Sensing over Two-wave with Diffuse Power Fading Channels

One of the most important factors that affects the performance of energy detection (ED) is the fading channel between the wireless nodes. This article investigates the performance of ED-based spectrum sensing, for cognitive radio (CR), over two-wave with diffuse power (TWDP) fading channels. The TWDP fading model characterizes a variety of fading channels, including well-known canonical fading distributions, such as Rayleigh and Rician, as well as worse than Rayleigh fading conditions modeled by the two-ray fading model. Novel analytic expressions for the average probability of detection over TWDP fading that account for single-user and cooperative spectrum sensing as well as square law selection diversity reception are derived. These expressions are used to analyze the behavior of ED-based spectrum sensing over moderate, severe and extreme fading conditions, and to investigate the use of cooperation and diversity as a means of mitigating the fading effects. Our results indicate that TWDP fading conditions can significantly degrade the sensing performance; however, it is shown that detection performance can be improved when cooperation and diversity are employed. The presented outcomes enable us to identify the limits of ED-based spectrum sensing and quantify the trade-offs between detection performance and energy efficiency for cognitive radio systems deployed within confined environments such as in-vehicular wireless networks.

Development of Detection Systems for the Sporangia of Peronospora Destructor

A monoclonal antibody that recognises components of the wall of sporangia of Peronospora destructor was raised. Tests using spores of higher fungi and other species of mildew demonstrated the specificity of the monoclonal. The antibody was used to develop lateral flow devices for sporangia of P. destructor. A competitive lateral flow format was developed which could detect onion downy mildew sporangia. Five-microliter gold anti-mouse IgM solution pre-mixed with 10 μl of P. destructor monoclonal antibody (EMA 242) proved the optimal concentration for detection of sporangia of P. destructor when applied to sample pads of lateral flow devices. Limits of approximately 500 sporangia of P. destructor could be detected by the absence of a test line on the lateral flow device within test samples. Using a scanning densitometer improved the sensitivity of detection. Further development and validation of the test is required if it is to be used for risk assessments of onion downy mildew in the field.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Volume-Synchronized Probability of Informed Trading (VPIN), Market Volatility, and High-Frequency Liquidity

We assess the predictive ability of three VPIN metrics on the basis of two highly volatile market events of China, and examine the association between VPIN and toxic-induced volatility through conditional probability analysis and multiple regression. We examine the dynamic relationship on VPIN and high-frequency liquidity using Vector Auto-Regression models, Granger Causality tests, and impulse response analysis. Our results suggest that Bulk Volume VPIN has the best risk-warning effect among major VPIN metrics. VPIN has a positive association with market volatility induced by toxic information flow. Most importantly, we document a positive feedback effect between VPIN and high-frequency liquidity, where a negative liquidity shock boosts up VPIN, which, in turn, leads to further liquidity drain. Our study provides empirical evidence that reflects an intrinsic game between informed traders and market makers when facing toxic information in the high-frequency trading world.

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

Quantification of the probability of containment failure caused by an in-vessel steam explosion for the Sizewell B PWR

AEA Technology has provided an assessment of the probability of α-mode containment failure for the Sizewell B PWR. After a preliminary review of the methodologies available it was decided to use the probabilistic approach described in the paper, based on an extension of the methodology developed by Theofanous et al. (Nucl. Sci. Eng. 97 (1987) 259–325). The input to the assessment is 12 probability distributions; the bases for the quantification of these distributions are discussed. The α-mode assessment performed for the Sizewell B PWR has demonstrated the practicality of the event-tree method with input data represented by probability distributions. The assessment itself has drawn attention to a number of topics, which may be plant and sequence dependent, and has indicated the importance of melt relocation scenarios. The α-mode failure probability following an accident that leads to core melt relocation to the lower head for the Sizewell B PWR has been assessed as a few parts in 10 000, on the basis of current information. This assessment has been the first to consider elevated pressures (6 MPa and 15 MPa) besides atmospheric pressure, but the results suggest only a modest sensitivity to system pressure.