Using the Balance Function to study the charge correlations of hadrons

We present the recent Balance Function (BF) results obtained by the NA49 collaboration for the pseudo-rapidity dependence of non-identified charged particle correlations for two SPS energies. Experimental results indicate a clear centrality dependence only in the mid-rapidity region. The results of an energy dependence study of the BF throughout the whole SPS energy range will also be discussed. In addition, the correlation of identified hadrons is studied and presented for the first time. The study of hadron correlation has also been extended in order to cope with the high multiplicity environment that is expected to be seen at LHC. We will present the latest results from simulations concerning the extension of these studies to the ALICE experiment.Comment: To appear in the proccedings of the "Quark Confinement and Hadron Spectrum VII" conferenc

The effect of Parylene coating on the surface roughness of PMMA after brushing

Acrylic resins, used in the manufacturing of different types of intra-oral prostheses, are vulnerable to, colonisation by microorganisms which potentially endanger the general health of the prostheses, wearers. The aim of this study was to investigate the influence of a novel coating (Parylene) on, surface roughness of poly-methyl-methacrylate (PMMA) samples after simulated cleansing using an, electric toothbrush and two brushing media (paste and pumice)

Survey on the use of CAD-CAM technology by UK and Irish dental technicians

Statement of the problem Digital workflows (CAD/CAM) have been introduced in dentistry during recent years. No published information exists on dental technicians' use and reporting of this technology.Purpose The aim of this cross sectional survey was to identify the extent digital technology has infiltrated the workplace and to investigate the factors affecting the use of CAD-CAM technology by dental laboratory technicians within Ireland and the UK.Materials and methods A web-based questionnaire was composed (Opinio, Object Planet Inc. Oslo, Norway) and distributed to UK and Irish dental technicians. Answers to all questions were anonymous and grouped such that general information was gathered initially, followed by branching of the survey into two sections depending on whether or not the respondent worked with CAD-CAM technology. Results were compiled and statistical analysis (Fisher's Exact test, SPSS, IBM, Armonk, New York, USA) was performed in order to investigate any correlation between various demographic variables and the answers provided.Results The survey was distributed to 760 UK technicians and 77 Irish technicians. The total number of completed surveys was 105, which yielded a total response rate of 14%. Most technicians reported using some form of CAD/CAM aspect in the workflow, and this was more significant for technicians working in large laboratories. Most training received was company-led. Large laboratories were also significantly correlated with less outsourcing of CAD/CAM work and a change in dental material use leading to the increase of zirconia and the decrease of noble alloys. Dental technicians did not report any significant change in working relationships and staffing as a result of CAD/CAM incorporation. High initial investment cost was the most common reason quoted from non-users, along with the lack of such technology in their working environment

Cooperative and coordinated Mobile Femtocells technology in high-speed vehicular environments: mobility and interference management

In future networks, most users who will be accessing wireless broadband will be vehicular. Serving those users cost-effectively and improving their signal quality has been the main concern of many studies. Thus, the deployment of Mobile Femtocell (Mobile-Femto) technology on public transportation is seen to be one of the promising solutions. Mobile-Femto comes with its mobility and interference challenges. Therefore, eliminating the Vehicular Penetration Loss (VPL) and interference while improving signal quality and mobility for train passengers is the main concern of this paper. The initial system-level evaluation showed that the dedicated Mobile-Femto deployment has great potential in improving users’ experience inside public transportation. The Downlink (DL) results of the Proposed Interference Management Scheme (PIMS) showed significant improvement in Mobile-Femto User Equipment (UE) gains (up to 50%) without impacting the performance of macro UEs. In contrast, the Uplink (UL) results showed noticeable gains for both macro UEs and Mobile-Femto UEs

Predicting fraud in mobile money transfer using case-based reasoning

This paper proposes an improved CBR approach for the identification of money transfer fraud in Mobile Money Transfer (MMT) environments. Standard CBR capability is augmented by machine learning techniques to assign parameter weights in the sample dataset and automate k-value random selection in k-NN classification to improve CBR performance. The CBR system observes users’ transaction behaviour within the MMT service and tries to detect abnormal patterns in the transaction flows. To capture user behaviour effectively, the CBR system classifies the log information into five contexts and then combines them into a single dimension, instead of using the conventional approach where the transaction amount, time dimensions or features dimension are used individually. The applicability of the proposed augmented CBR system is evaluated using simulation data. From the results, both dimensions show good performance with the context of information weighted CBR system outperforming the individual features approach

Audio-visual object localization and separation using low-rank and sparsity

The ability to localize visual objects that are associated with an audio source and at the same time seperate the audio signal is a corner stone in several audio-visual signal processing applications. Past efforts usually focused on localizing only the visual objects, without audio separation abilities. Besides, they often rely computational expensive pre-processing steps to segment images pixels into object regions before applying localization approaches. We aim to address the problem of audio-visual source localization and separation in an unsupervised manner. The proposed approach employs low-rank in order to model the background visual and audio information and sparsity in order to extract the sparsely correlated components between the audio and visual modalities. In particular, this model decomposes each dataset into a sum of two terms: the low-rank matrices capturing the background uncorrelated information, while the sparse correlated components modelling the sound source in visual modality and the associated sound in audio modality. To this end a novel optimization problem, involving the minimization of nuclear norms and matrix ℓ1-norms is solved. We evaluated the proposed method in 1) visual localization and audio separation and 2) visual-assisted audio denoising. The experimental results demonstrate the effectiveness of the proposed method

End-to-end visual speech recognition with LSTMS

Traditional visual speech recognition systems consist of two stages, feature extraction and classification. Recently, several deep learning approaches have been presented which automatically extract features from the mouth images and aim to replace the feature extraction stage. However, research on joint learning of features and classification is very limited. In this work, we present an end-to-end visual speech recognition system based on Long-Short Memory (LSTM) networks. To the best of our knowledge, this is the first model which simultaneously learns to extract features directly from the pixels and perform classification and also achieves state-of-the-art performance in visual speech classification. The model consists of two streams which extract features directly from the mouth and difference images, respectively. The temporal dynamics in each stream are modelled by an LSTM and the fusion of the two streams takes place via a Bidirectional LSTM (BLSTM). An absolute improvement of 9.7% over the base line is reported on the OuluVS2 database, and 1.5% on the CUAVE database when compared with other methods which use a similar visual front-end

System Size and Centrality Dependence of the Electric Charge Correlations in A+A and p+p Collisions at the SPS Energies

The Balance Function analysis method was developed in order to study the long range correlations in pseudo-rapidity of charged particle. The final results on p+p, C+C, Si+Si and centrality selected Pb+Pb collisions at $\sqrt{s_{NN}} = 17.2$ GeV and the preliminary data at $\sqrt{s_{NN}} = 8.8$ GeV are presented. The width of the Balance Function decreases with increasing system size and centrality of the collisions. This could suggest a delayed hadronization scenario.Comment: To appear in the proceedings of NPDC18, Prague, Czech Republic, 23-28 Aug. 200

Exposing knowledge: providing a real-time view of the domain under study for students

With the amount of information that exists online, it is impossible for a student to find relevant information or stay focused on the domain under study. Research showed that search engines have deficiencies that might prevent students from finding relevant information. To this end, this research proposes a technical solution that takes the personal search history of a student into consideration and provides a holistic view of the domain under study. Based on algorithmic approaches to assert semantic similarity, the proposed framework makes use of a user interface to dynamically assist students through aggregated results and wordcloud visualizations. The effectiveness of our approach is finally evaluated through the use of commonly used datasets and compared in line with existing research