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.

Drug treatment of macular oedema secondary to central retinal vein occlusion: a network meta-analysis

Objective
To indirectly compare aflibercept, bevacizumab, dexamethasone, ranibizumab and triamcinolone for treatment of macular oedema secondary to central retinal vein occlusion using a network meta-analysis (NMA).

Design
NMA.

Data sources
The following databases were searched from January 2005 to March 2013: MEDLINE, MEDLINE In-process, EMBASE; CDSR, DARE, HTA, NHSEED, CENTRAL; Science Citation Index and Conference Proceedings Citation Index-Science.

Eligibility criteria for selecting studies
Only randomised controlled trials assessing patients with macular oedema secondary to central retinal vein occlusion were included. Studies had to report either proportions of patients gaining ≥3 lines, losing ≥3 lines, or the mean change in best corrected visual acuity. Two authors screened titles and abstracts, extracted data and undertook risk of bias assessment. Bayesian NMA was used to compare the different interventions.

Results
Seven studies, assessing five drugs, were judged to be sufficiently comparable for inclusion in the NMA. For the proportions of patients gaining ≥3 lines, triamcinolone 4 mg, ranibizumab 0.5 mg, bevacizumab 1.25 mg and aflibercept 2 mg had a higher probability of being more effective than sham and dexamethasone. A smaller proportion of patients treated with triamcinolone 4 mg, ranibizumab 0.5 mg or aflibercept 2 mg lost ≥3 lines of vision compared to those treated with sham. Patients treated with triamcinolone 4 mg, ranibizumab 0.5 mg, bevacizumab 1.25 mg and aflibercept 2 mg had a higher probability of improvement in the mean best corrected visual acuity compared to those treated with sham injections.

Conclusions
We found no evidence of differences between ranibizumab, aflibercept, bevacizumab and triamcinolone for improving vision. The antivascular endothelial growth factors (VEGFs) are likely to be favoured because they are not associated with steroid-induced cataract formation. Aflibercept may be preferred by clinicians because it might require fewer injections.

Performance analysis of switch-and-stay combining in two-way relay systems with analog network coding and time-division broadcast protocols

In this paper, weconsider switch-and-stay combining (SSC) in two-way relay systems with two amplify-and-forward relays, one of which is activated to assist the information exchange between the two sources. The system operates in either analog network coding (ANC) protocol where the communication is only achieved with the help of the active relay or timedivision broadcast (TDBC) protocol where the direct link between two sources can be utilized to exploit more diversity gain. In both cases, we study the outage probability and bit error rate (BER) for Rayleigh fading channels. In particular, we derive closed-form lower bounds for the outage probability and the average BER, which remain tight for different fading conditions. We also present asymptotic analysis for both the outage probability and the average BER at high signalto-noise ratio. It is shown that SSC can achieve the full diversity order in two-way relay systems for both ANC and TDBC protocols with proper switching thresholds. Copyright © 2014 John Wiley & Sons, Ltd.

Functional and genetic analysis of the colon cancer network

Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

Bayesian network data imputation with application to survival tree analysis

Retrospective clinical datasets are often characterized by a relatively small sample size and many missing data. In this case, a common way for handling the missingness consists in discarding from the analysis patients with missing covariates, further reducing the sample size. Alternatively, if the mechanism that generated the missing allows, incomplete data can be imputed on the basis of the observed data, avoiding the reduction of the sample size and allowing methods to deal with complete data later on. Moreover, methodologies for data imputation might depend on the particular purpose and might achieve better results by considering specific characteristics of the domain. The problem of missing data treatment is studied in the context of survival tree analysis for the estimation of a prognostic patient stratification. Survival tree methods usually address this problem by using surrogate splits, that is, splitting rules that use other variables yielding similar results to the original ones. Instead, our methodology consists in modeling the dependencies among the clinical variables with a Bayesian network, which is then used to perform data imputation, thus allowing the survival tree to be applied on the completed dataset. The Bayesian network is directly learned from the incomplete data using a structural expectation–maximization (EM) procedure in which the maximization step is performed with an exact anytime method, so that the only source of approximation is due to the EM formulation itself. On both simulated and real data, our proposed methodology usually outperformed several existing methods for data imputation and the imputation so obtained improved the stratification estimated by the survival tree (especially with respect to using surrogate splits).

Analysis of electric vehicle charging using the traditional generation expansion planning analysis tool WASP-IV

Electric vehicles (EV) are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems. Optimal benefits can only be achieved, if EVs are deployed effectively, so that the exhaust emissions are not substituted by additional emissions in the electricity sector, which can be implemented using Smart Grid controls. This research presents the results of an EV roll-out in the all island grid (AIG) in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV (WASP-IV) tool to measure carbon dioxide emissions and changes in total energy. The model incorporates all generators and operational requirements while meeting environmental emissions, fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch. In the study three distinct scenarios are investigated base case, peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.

Network Connectivity Proxy: Architecture, Implementation, and Performance Analysis

Several studies in the last decade have pointed out that many devices, such as computers, are often left powered on even when idle, just to make them available and reachable on the network, leading to large energy waste. The concept of network connectivity proxy (NCP) has been proposed as an effective means to improve energy efficiency. It impersonates the presence of networked devices that are temporally unavailable, by carrying out background networking routines on their behalf. Hence, idle devices could be put into low-power states and save energy. Several architectural alternatives and the applicability of this concept to different protocols and applications have been investigated. However, there is no clear understanding of the limitations and issues of this approach in current networking scenarios. This paper extends the knowledge about the NCP by defining an extended set of tasks that the NCP can carry out, by introducing a suitable communication interface to control NCP operation, and by designing, implementing, and evaluating a functional prototype.

Knowledge Exchange, Spatial Analysis & Healthy Urban Environments (KESUE): Project Report

The Knowledge Exchange, Spatial Analysis and Healthy Urban Environments (KESUE) project has extended work previously undertaken by a QUB team of inter-disciplinary researchers engaged with the Physical Activity in the Regeneration of Connswater (PARC) project (Tully et al, 2013). The PARC project focussed on parts of East Belfast to assess the health impact of the Connswater Community Greenway. The KESUE project has aimed to extend some of the tools used initially in East Belfast so that they have data coverage of all of Belfast and Derry-Londonderry. The purpose of this has been to enable the development of evidence and policy tools that link features of the built environment with physical activity in these two cities. The project has used this data to help shape policy decisions in areas such as physical activity, park management, public transport and planning.

Working with a range of local partners who part-funded the project (City Councils in Belfast and Derry-Londonderry, Public Health Agency, Belfast Healthy Cities and Department of Regional Development), this project has mapped all the footpaths in the two cities (covering 37% of the NI population) and employed this to develop evidence used in strategies related to healthy urban planning. Using Geographic Information Systems (GIS), the footpath network has been used as a basis for a wide range of policy-relevant analyses including pedestrian accessibility to public facilities, site options for new infrastructure and assessing how vulnerable groups can access services such as pharmacies. Key outputs have been Accessibility Atlases and maps showing how walkability of the built environment varies across the two cities.

In addition to generating this useful data, the project included intense engagement with potential users of the research, which has led to its continued uptake in a number of policies and strategies, creating a virtuous circle of research, implementation and feedback. The project has proved so valuable to Belfast City Council that they have now taken on one of the researchers to continue the work in-house.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Homogenization and analysis of an expanded long-term monthly rainfall network for the Island of Ireland (1850–2010)

Long-term precipitation series are critical for understanding emerging changes to the hydrological cycle. To this end we construct a homogenized Island of Ireland Precipitation (IIP) network comprising 25 stations and a composite series covering the period 1850–2010, providing the second-longest regional precipitation archive in the British-Irish Isles. We expand the existing catalogue of long-term precipitation records for the island by recovering archived data for an additional eight stations. Following bridging and updating of stations HOMogenisation softwarE in R (HOMER) homogenization software is used to detect breaks using pairwise and joint detection. A total of 25 breakpoints are detected across 14 stations, and the majority (20) are corroborated by metadata. Assessment of variability and change in homogenized and extended precipitation records reveal positive (winter) and negative (summer) trends. Trends in records covering the typical period of digitization (1941 onwards) are not always representative of longer records. Furthermore, trends in post-homogenization series change magnitude and even direction at some stations. While cautionary flags are raised for some series, confidence in the derived network is high given attention paid to metadata, coherence of behaviour across the network and consistency of findings with other long-term climatic series such as England and Wales precipitation. As far as we are aware, this work represents the first application of HOMER to a long-term precipitation network and bodes well for use in other regions. It is expected that the homogenized IIP network will find wider utility in benchmarking and supporting climate services across the Island of Ireland, a sentinel location in the North Atlantic.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

Managing the transition to work: the role of the planning network in British town planning education

The development of town planning education in the United Kingdom can be traced back over at least sixty years and has always enjoyed a close relationship with practitioners, employers and the professional body, the Royal Town Planning Institute (RTPI). In order to ensure an intake of sufficient quality to a growing profession, the Institute offered its own exams until the 1980s and then initiated the current system of accrediting both undergraduate and postgraduate programmes of study. This system of accreditation emphasises the importance of relevant knowledge, skills and values as well as core and specialised studies. The vocational nature of town planning requires that graduates have the breadth of understanding as well as the practical skills in order to practice effectively. Thus accredited courses have over time developed strong links with employers and practitioners. Rapid developments in the scope and range of planning, and the skills needed to work in it, have reflected changes in public policy and growing number of agencies concerned with the built environment. The system of regular quinquennial visits to accredit courses has helped ensure that this acceptance of change has become part of the culture of planning schools.