Fault Location on a Distribution Network Using a Decentralised Analysis Process

A reduction in the time required to locate and restore faults on a utility's distribution network improves the customer minutes lost (CML) measurement and hence brings direct cost savings to the operating company. The traditional approach to fault location involves fault impedance determination from high volume waveform files dispatched across a communications channel to a central location for processing and analysis. This paper examines an alternative scheme where data processing is undertaken locally within a recording instrument thus reducing the volume of data to be transmitted. Processed event fault reports may be emailed to relevant operational staff for the timely repair and restoration of the line.

Loss-of-Mains Detection by Internet Based ROCOF

This paper considers the enhancement of loss-of-mains detection by use of a differential rate-of-change-of-frequency relay to reduce nuisance tripping and improve sensitivity to small excursions in frequency. The telecommunications media which might carry the differential ROCOF signal are reviewed with a focus on channel latency, bandwidth and security.

A Wavelet Approach to the Selective Computation of Domninant Eigenvalues

This paper introduces an algorithm that calculates the dominant eigenvalues (in terms of system stability) of a linear model and neglects the exact computation of the non-dominant eigenvalues. The method estimates all of the eigenvalues using wavelet based compression techniques. These estimates are used to find a suitable invariant subspace such that projection by this subspace will provide one containing the eigenvalues of interest. The proposed algorithm is exemplified by application to a power system model.

Data Reduction of Power System Disturbances using Wavelet Transforms for Network Operation and Control

Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the reduction properties of the wavelet transform using real power system data and discusses the application of the reduction method for information transfer in network communications.

Voltage Dip Benchmarking in Power Quality and Disturbance Monitoring

This paper examines power quality benchmarks in the electricity supply industry (ESI) and impact of standards for the reduction of voltage dip incidents. The paper considers adherence to particular standards and is supported by several case studies from incidents where voltage dips have been detected and assessed by the power systems division of Scottish Power and where improvements have been implemented to help militate against subsequent incidents.

ASIP: developments, challenges and trends

Application Specific Instruction Set Processor (ASIP) becomes an attractive substitute for ASIC as transistor density, logic complexity and market competition boost. Similar to ASIC, ASIP is based on customized and tailored architectures. In this way, ASIP delivers high performances with low overheads on cost and power whilst taking the advantages of high flexibility and fast time-to-market as a processor-based solution. To demonstrate this effective solution for embedded applications, this paper performs an overall investigation on ASIP's developments, challenges, trends in terms of architectures and design methodologies.

Design Method for Circularly Polarized Fabry-Perot Cavity Antennas

A new class of circularly polarized (CP) Fabry-Perot cavity antennas is introduced that maintain the simplicity of a linearly polarized primary feed and a single cavity structure. The proposed antennas employ a double-sided partially reflective surface (PRS), which allows independent control of the magnitude and phase responses for the reflection and transmission coefficients. In conjunction with an anisotropic high-impedance surface (HIS) ground plane, this arrangement allows for the first time a single cavity antenna to produce a specified gain in CP from a linearly polarized primary source. A design procedure for this class of antennas is introduced. The method exploits a simple ray optics model to calculate the magnitude and phase of the electric field in the cavity upon plane wave excitation. Based on this model, analytical expressions are derived, which enforce the resonance condition for both polarizations at a predetermined PRS reflectivity (and hence predetermined antenna gain) together with a 90 degrees differential phase between them. The validity of the concept is confirmed by means of an example entailing an antenna with gain of approximately 21 dB at 15 GHz. Full-wave simulation results and experimental testing on a fabricated prototype are presented and agree well with the theoretical predictions.

Circular polarisation frequency selective surface operating in Ku and Ka band

Single and double layer frequency selective surfaces (FSS) for Circular polarization (CP) operation were designed. The designed FSS provide reflection in the Ku-band (11.7 – 12.75 GHz) and transmission in the Ka-band (17.3 – 20.2 GHz). CP is conserved in each of the bands. For the double layer design over the Ku-band the reflection loss was less than 0.05 dB for TE and TM polarizations while the axial ratio was below 0.2 dB. Over the Ka-band transmission loss and axial ratio were each less than 0.25 dB.

Linear to Circular Polarization Reflector with Transmission Band

A frequency selective surface (FSS) which can be utilized as a diplexer for circular polarization (CP) applications is proposed. The structure consists of two dipole-based FSS placed parallel to each other. The dipoles in one array are rotated by 90° with respect to those in the other. For an angle of incidence of 45° at one frequency band the structure allows a CP signal to be transmitted while at a further band it converts a linearly polarized (LP) signal to CP upon reflection. Full-wave simulation results validated the concept.

Incorporating Severity and Risk as Factors to the Fardal Cost-Effectiveness Model to Create a Cost-Benefit Model for Periodontal Treatment

Background: A previously described economic model was based on average values for patients diagnosed with chronic periodontitis (CP). However, tooth loss varies among treated patients and factors for tooth loss include CP severity and risk. The model was refined to incorporate CP severity and risk to determine the cost of treating a specific level of CP severity and risk that is associated with the benefit of tooth preservation.

Methods: A population that received and another that did not receive periodontal treatment were used to determine treatment costs and tooth loss. The number of teeth preserved was the difference of the number of teeth lost between the two populations. The cost of periodontal treatment was divided by the number of teeth preserved for combinations of CP severity and risk.

Results: The cost of periodontal treatment divided by the number of teeth preserved ranged from (US) $ 1,405 to $ 4,895 for high or moderate risk combined with any severity of CP and was more than $ 8,639 for low risk combined with mild CP. The cost of a three-unit bridge was $ 3,416, and the cost of a single-tooth replacement was $ 4,787.

Conclusion: Periodontal treatment could be justified on the sole basis of tooth preservation when CP risk is moderate or high regardless of disease severity.

Efficiency improvement study for small wind turbines through flow control

In this study, a constant suction technique for controlling boundary layer separation at low Reynolds numbers was designed and tested. This was later implemented on small wind turbines. Small wind turbines need to operate in low wind speeds, that is, in low Reynolds number regimes – typically in the range 104–105. Airfoils are prone to boundary layer separation in these conditions, leading to a substantial drop in aerodynamic performance of the blades. Under these conditions turbines will have reduced energy output. This paper presents experimental results of applying surface-suction over the suction-surface of airfoils for controlling boundary layer separation. The Reynolds numbers for the experiments are kept in the range 8×104–5×105. The air over the surface of the airfoil is drawn into the airfoil through a slit. It is found that the lift coefficient of the airfoils increases and the drag reduces. Based on the improved airfoil characteristics, an analysis of increase in Coefficient of Power (CP), versus input power for a small wind turbine blade with constant suction is presented.

Up-regulated MSI2 is associated with more aggressive chronic myeloid leukemia

A better understanding of events triggering chronic myeloid leukemia progression are critical to optimised clinical management of chronic myeloid leukemia (CML). We sought to validate that increased Musashi 2 (MSI2), a post transcription regulator, expression is associated with progression and prognosis. Screening of 152 CML patients showed MSI2 was significantly decreased among CML patients in CP at diagnosis (p<0.0001), but found no significant difference between the normal control group and treated CML patients in CP. Moreover it was significantly increased (p<0.0001) in advance disease (AD) CML patients. Furthermore, our human hematopoietic cell line data imply MSI2 and BCR-ABL1 mRNA expression correlate. However, these data cast a doubt on earlier reports that MSI2 effects HES1 expression via NUMB-NOTCH signaling.

Towards Multi-Sensor Spectral Alignment Through Post Measurement Calibration Correction

Semiconductor manufactures are increasing reliant on optical emission spectroscopy (OES) to source information on plasma characteristics and process change. However, nonlinearities in the response of OES sensors and errors in their calibration lead to discrepancies in observed wavelength detector response. This paper presents a technique for the retrospective spectral calibration of multiple OES sensors. Underlying methodology is given, and alignment performance is evaluated using OES recordings from a semiconductor plasma process. The paper concludes with a discussion of results and suggests avenues for future work.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.