Microwave photonic filtering using Gaussian-profiled superstructured fibre Bragg grating and dispersive fibre

Microwave photonic filtering is realised using a superstructured fibre Bragg grating. The time delay of the optical taps is precisely controlled by the grating characteristics and fibre dispersion. A bandpass response with a rejection level of >45 dB is achieved.

An Ontology- Content-based Filtering Method

Traditional content-based filtering methods usually utilize text extraction and classification techniques for building user profiles as well as for representations of contents, i.e. item profiles. These methods have some disadvantages e.g. mismatch between user profile terms and item profile terms, leading to low performance. Some of the disadvantages can be overcome by incorporating a common ontology which enables representing both the users' and the items' profiles with concepts taken from the same vocabulary. We propose a new content-based method for filtering and ranking the relevancy of items for users, which utilizes a hierarchical ontology. The method measures the similarity of the user's profile to the items' profiles, considering the existing of mutual concepts in the two profiles, as well as the existence of "related" concepts, according to their position in the ontology. The proposed filtering algorithm computes the similarity between the users' profiles and the items' profiles, and rank-orders the relevant items according to their relevancy to each user. The method is being implemented in ePaper, a personalized electronic newspaper project, utilizing a hierarchical ontology designed specifically for classification of News items. It can, however, be utilized in other domains and extended to other ontologies.

From bilateral to trilateral governance in local government contracting in France

In France, the tradition of contracting out local public services has been predominantly one of partnership and co-operation rather than competition and antagonism. However, in recent years the traditional approach has come under intense criticism, something which has far-reaching implications for public-private governance. Adopting the socio-legal approach to the study of contract governance set out by Peter Vincent-Jones, this paper explores the discrepancy between descriptions of a traditional French approach to local public services governance, in which the bilateral values of trust and co-operation are emphasized, and a new discourse of local public services governance, which argues for detailed contract planning and close contract monitoring. It is argued that this discrepancy reveals the beginning of a shift in the governance of public service exchange relationships from relatively noncontractual and bilateral to relatively contractual and trilateral. The French case highlights the importance of regulatory and accountability frameworks to the manner in which contracting parties perceive exchange governance. © Blackwell Publishing Ltd. 2005.

Partial Quasi-Bilateral Generating Function Involving some Special Functions

A group-theoretic method of obtaining more general class of generating functions from a given class of partial quasi-bilateral generating functions involving Hermite, Laguerre and Gegenbaur polynomials are discussed.

Bilateral visual outcomes and service utilization of patients treated for 3 years with ranibizumab for neovascular age-related macular degeneration

Background: The aim of this study was to describe bilateral visual outcomes and the effect of incomplete follow-up after 3 years of ranibizumab therapy for neovascular age-related macular degeneration. Secondarily, the demands on service provision over a 3-year period were described. Methods: Data on visual acuity, hospital visits, and injections were collected over 36 months on consecutive patients commencing treatment over a 9-month period. Visual outcome was determined for 1) all patients, using last observation carried forward for missed visits due to early discontinuation and 2) only those patients completing full 36-month follow-up. Results: Over 3 years, 120 patients cumulatively attended hospital for 1,823 noninjection visits and 1,365 injection visits. A visual acuity loss of <15 letters (L) was experienced by 78.2% of patients. For all patients (n=120), there was a mean loss of 1.68 L using last observation carried forward for missing values. Excluding five patients who died and 30 who discontinued follow-up, mean gain was 1.47 L. In bilateral cases, final acuity was on average 9 L better in second eyes compared to first eyes. Also, 91% of better-seeing eyes continued to be the better-seeing eye. Conclusion: We have demonstrated our approach to describing the long-term service provision and visual outcomes of ranibizumab therapy for neovascular age-related macular degeneration in a consecutive cohort of patients. Although there was a heavy burden with very frequent injections and clinic visits, patients can expect a good level of visual stability and a very high chance of maintaining their better-seeing eye for up to 3 years. © 2014 Chavan et al. This work is published by Dove Medical Press Limited.

Making hiring decisions:a grounded theory approach to a practise-based study of filtering in selection

This thesis objective is to discover “How are informal decisions reached by screeners when filtering out undesirable job applications?” Grounded theory techniques were employed in the field to observe and analyse informal decisions at the source by screeners in three distinct empirical studies. Whilst grounded theory provided the method for case and cross-case analysis, literature from academic and non-academic sources was evaluated and integrated to strengthen this research and create a foundation for understanding informal decisions. As informal decisions in early hiring processes have been under researched, this thesis contributes to current knowledge in several ways. First, it locates the Cycle of Employment which enhances Robertson and Smith’s (1993) Selection Paradigm through the integration of stages that individuals occupy whilst seeking employment. Secondly, a general depiction of the Workflow of General Hiring Processes provides a template for practitioners to map and further develop their organisational processes. Finally, it highlights the emergence of the Locality Effect, which is a geographically driven heuristic and bias that can significantly impact recruitment and informal decisions. Although screeners make informal decisions using multiple variables, informal decisions are made in stages as evidence in the Cycle of Employment. Moreover, informal decisions can be erroneous as a result of a majority and minority influence, the weighting of information, the injection of inappropriate information and criteria, and the influence of an assessor. This thesis considers these faults and develops a basic framework of understanding informal decisions to which future research can be launched.

An Approach to Collaborative Filtering by ARTMAP Neural Networks

Recommender systems are now widely used in e-commerce applications to assist customers to find relevant products from the many that are frequently available. Collaborative filtering (CF) is a key component of many of these systems, in which recommendations are made to users based on the opinions of similar users in a system. This paper presents a model-based approach to CF by using supervised ARTMAP neural networks (NN). This approach deploys formation of reference vectors, which makes a CF recommendation system able to classify user profile patterns into classes of similar profiles. Empirical results reported show that the proposed approach performs better than similar CF systems based on unsupervised ART2 NN or neighbourhood-based algorithm.

The impact of pump phase-modulation and filtering on WDM signals in a fibre optical parametric amplifier

WDM signal degradation from pump phase-modulation in a one-pump 20dB net-gain fibre optical parametric amplifier is experimentally and numerically characterised for the first time using 10x59Gb/s QPSK signals.

A Unified Group-Theoretic Method on Improper Partial Semi-Bilateral Generating Functions

2000 Mathematics Subject Classification: 33A65, 33C20.

Visual and quality outcomes following bilateral implantation of a trifocal intraocular lens

Purpose: To examine visual outcomes following bilateral implantation of the FineVision trifocal intraocular lens (IOL; PhysIOL, Liège, Belgium). Methods: 26 patients undergoing routine cataract surgery were implanted bilaterally with the FineVision Trifocal IOL and followed up post-operatively for 3 months. The FineVision optic features a combination of 2 diffractive structures, resulting in distance, intermediate (+1.75 D add) and near vision (+3.50 D add) zones. Apodization of the optic surface increases far vision dominance with pupil aperture. Data collected at the 3 month visit included uncorrected and corrected distance (CDVA) and near vision; subjective refraction; defocus curve testing (photopic and mesopic); contrast sensitivity (CSV-1000); halometry glare testing and a questionnaire (NAVQ) to gauge near vision function and patient satisfaction. Results: The cohort comprised 15 males and 11 females, aged 52.5–82.4 years (mean 70.6 ± 8.2 years). Mean post-operative UDVA was 0.22 ± 0.14 logMAR, with a mean spherical equivalent refraction of +0.02 ± 0.35 D. Mean CDVA was 0.13 ± 0.10 logMAR monocularly, and 0.09 ± 0.07 logMAR binocularly. Defocus curve testing showed an extensive range of clear vision in both photopic and mesopic conditions. Patients showed high levels of satisfaction with their near vision (mean ± 0.9 ± 0.6, where 0 = completely satisfied, and 4 = completely unsatisfied) and demonstrated good spectacle independence. Conclusion: The FineVision IOL can be considered in patients seeking spectacle dependence following cataract surgery, and provide good patient satisfaction with uncorrected vision.

Switching among pulse-generation regimes in passively mode-locked fibre laser by adaptive filtering

We show both numerically and experimentally that dispersion management can be realized by manipulating the dispersion of a filter in a passively mode-locked fibre laser. A programmable filter the dispersion of which can be software configured is employed in the laser. Solitons, stretched-pulses, and dissipative solitons can be targeted reliably by controlling the filter transmission function only, while the length of fibres is fixed in the laser. This technique shows remarkable advantages in controlling operation regimes in ultrafast fibre lasers, in contrast to the traditional technique in which dispersion management is achieved by optimizing the relative length of fibres with opposite-sign dispersion. Our versatile ultrafast fibre laser will be attractive for applications requiring different pulse profiles such as in optical signal processing and optical communications.

On stopwords, filtering and data sparsity for sentiment analysis of Twitter

Sentiment classification over Twitter is usually affected by the noisy nature (abbreviations, irregular forms) of tweets data. A popular procedure to reduce the noise of textual data is to remove stopwords by using pre-compiled stopword lists or more sophisticated methods for dynamic stopword identification. However, the effectiveness of removing stopwords in the context of Twitter sentiment classification has been debated in the last few years. In this paper we investigate whether removing stopwords helps or hampers the effectiveness of Twitter sentiment classification methods. To this end, we apply six different stopword identification methods to Twitter data from six different datasets and observe how removing stopwords affects two well-known supervised sentiment classification methods. We assess the impact of removing stopwords by observing fluctuations on the level of data sparsity, the size of the classifier's feature space and its classification performance. Our results show that using pre-compiled lists of stopwords negatively impacts the performance of Twitter sentiment classification approaches. On the other hand, the dynamic generation of stopword lists, by removing those infrequent terms appearing only once in the corpus, appears to be the optimal method to maintaining a high classification performance while reducing the data sparsity and substantially shrinking the feature space

A case of bilateral perisylvian syndrome with reading disability

Bilateral Perisylvian Syndrome (BPS) often presents with epilepsy and significant behavioral impairments that can include mental retardation, dysarthria, delayed speech development, and delayed fine motor development (Graff-Radford et al., 1986 and Kuzniecky et al., 1993). While a small subset of BPS cases have been described as having relatively isolated language delays (Leventer et al., 2010), BPS is not expected in children with dyslexia. As part of a Medical University of South Carolina, IRB approved multi-site study involving retrospective and de-identified dyslexia data, we unexpectedly identified a 14.05 year old male with evidence of BPS whose father had been diagnosed with dyslexia and dysgraphia. This child had been recruited for a neuroimaging study on dyslexia from a school specializing in educating children with dyslexia. The T1-weighted MRI scan from this child demonstrated a highly unusual perisylvian sulcal/gyral patterning that is a defining feature of BPS (Fig. 1). BPS cases exhibit bilateral dysgenesis of the Sylvian fissure and surrounding gyri, which appears to occur because of a limited or absent arcuate fasciculus (Kilinc, Ekinci, Demirkol, & Agan, 2015). This BPS case also had a relatively enlarged atrium of the lateral ventricle that is consistent with the BPS anatomical presentation and reduction of parietal white matter (Graff-Radford et al., 1986, Kilinc et al., 2015 and Toldo et al., 2011).

An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.