Signal Reliability Improvement Using Selection Combining Based Macro-Diversity for Off-Body Communications At 868 MHz

This paper investigates the potential improvement in signal reliability for outdoor short-range off-body communications channels at 868 MHz using the macro-diversity offered by multiple co-located base stations. In this study, ten identical hypothetical base stations were positioned equidistantly around the perimeter of a rectangle of length 6.67 m and width 3.3 m. A body worn node was placed on the central chest region of an adult male. Five scenarios, each considering different user trajectories, were then analyzed to test the efficacy of using macro-diversity when the desired link is subject to shadowing caused by the human body. A number of selection combining based macro-diversity configurations consisting of four and then ten base stations were considered. It was found that using a macro-diversity system consisting of four base stations (or equivalently signal branches), a maximum diversity gain of 22.5 dB could be obtained while implementing a 10-base station setup this figure could be improved to 25.2 dB.

Real-Time Channel Model Selection Using Windowed Received Signal Strength Measurements

This paper investigates the potential for using the windowed variance of the received signal strength to select from a set of predetermined channel models for a wireless ranging or localization system. An 868 MHz based measurement system was used to characterize the received signal strength (RSS) of the off-body link formed between two wireless nodes attached to either side of a human thorax and six base stations situated in the local surroundings.

Investigation into DCT Feature Selection for Visual Lip-Based Biometric Authentication

This paper investigated using lip movements as a behavioural biometric for person authentication. The system was trained, evaluated and tested using the XM2VTS dataset, following the Lausanne Protocol configuration II. Features were selected from the DCT coefficients of the greyscale lip image. This paper investigated the number of DCT coefficients selected, the selection process, and static and dynamic feature combinations. Using a Gaussian Mixture Model - Universal Background Model framework an Equal Error Rate of 2.20% was achieved during evaluation and on an unseen test set a False Acceptance Rate of 1.7% and False Rejection Rate of 3.0% was achieved. This compares favourably with face authentication results on the same dataset whilst not being susceptible to spoofing attacks.

Reference gene selection in human periodontal ligament cells

Background: Real-time quantitative PCR (qPCR) is a highly sensitive and specific method which is used extensively for determining gene expression profiles in a variety of cell and tissue types. In order to obtain accurate and reliable gene expression quantification, qPCR data are generally normalised against so-called reference or housekeeping genes. Ideally, reference genes should have abundant and stable RNA transcriptomes under the experimental conditions employed. However, reference genes are often selected rather arbitrarily and indeed some have been shown to have variable expression in a variety of in vitro experimental conditions.
Objective: The objective of the current study was to investigate reference gene expression in human periodontal ligament (PDL) cells in response to treatment with lipopolysaccharide (LPS).
Method: Primary human PDL cells were grown in Dulbecco’s Modified Eagle Medium with L-glutamine supplemented with 10% fetal bovine serum, 100UI/ml penicillin and 100µg/ml streptomycin. RNA was isolated using the RNeasy Mini Kit (Qiagen) and reverse transcribed using the QuantiTect Reverse Transcription Kit (Qiagen). The expression of a total of 19 reference genes was studied in the presence and absence of LPS treatment using the Roche Reference Gene Panel. Data were analysed using NormFinder and Bestkeeper validation programs.
Results: Treatment of human PDL cells with LPS resulted in changes in expression of several commonly used reference genes, including GAPDH. On the other hand the reference genes β-actin, G6PDH and 18S were identified as stable genes following LPS treatment.
Conclusion: Many of the reference genes studied were robust to LPS treatment (up to 100 ng/ml). However several commonly employed reference genes, including GAPDH varied with LPS treatment, suggesting they would not be ideal candidates for normalisation in qPCR gene expression studies.

Recurrent Convolutional Network for Video-based Person Re-Identification

In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent final layer, which allows information to flow between time-steps. The features from all time steps are then combined using temporal pooling to give an overall appearance feature for the complete sequence. The convolutional network, recurrent layer, and temporal pooling layer, are jointly trained to act as a feature extractor for video-based re-identification using a Siamese network architecture.Our approach makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re-identification. Experiments are conduced on the iLIDS-VID and PRID-2011 datasets to show that this approach outperforms existing methods of video-based re-identification.

https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID
Project Source Code

Gendered Candidate Selection and the Representation of Women in Northern Ireland

In an attempt to account for the exceptionally low levels of female representation in Northern Ireland, this paper provides an analysis of the contemporary candidate selection procedures of the region's five main political parties. Drawing on evidence gathered from 29 elite interviews, plus official internal party documents, the study finds that the localised nature of the parties' selection procedures may disadvantage women aspirants. Also important are ‘supply-side’ factors influencing legislative recruitment and female participation rates, namely the strongly embedded social norm of female domestic responsibility, a masculinised political culture and the lack of confidence of potential female candidates.

The Selection of Party Leaders in Northern Ireland

This article provides an analysis of the leadership selection methods adopted by Northern Ireland's five main parties. Drawing on data from interviews with party elites and internal party documents, it sheds light on an important element of intra-party organisation in the region and constitutes a rare case-study of leadership selection in a consociational democracy. By accounting for instances of organisational reform, this article also reveals the extent to which Northern Ireland's parties align with the wider comparative trend of leadership ‘democratisation’. In terms of ‘who’ selects party leaders, the analysis finds a substantial degree of organisational heterogeneity and a reasonably high rate of democratisation. Northern Ireland's parties also prove rather exceptional in their universal adoption of short fixed terms for party leaders and, in the case of three of the parties, their preference for high candidacy thresholds.

Selection of the most appropriate roadside vehicle restraint system – the SAVeRS project

Run Off Road (ROR) crashes are road accidents that often result in severe injuries or fatalities. To reduce the severity of ROR crashes, “forgiving roadsides” need to be designed and this includes identifying situations where there is a need for a Vehicle Restraint System (VRS) and what appropriate VRS should be selected for a specific location and traffic condition. Whilst there are standards covering testing, evaluation and classification of VRS within Europe (EN1317 parts 1 to 8), their selection, location and installation requirements are typically based upon national guidelines and standards, often produced by National Road Authorities (NRA) and/or overseeing organisations. Due to local conditions, these national guidelines vary across Europe.
The European SAVeRS project funded by CEDR has developed a practical and readily understandable VRS guidance document and a user-friendly software tool which allow designers and road administrations to select the most appropriate solution in different road and traffic conditions.
This paper describes the main outcomes of the project, the process to select the most appropriate roadside barrier, and the user friendly SAVeRS tool.

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.