Using Sensor Metadata Streams to Identify Topics of Local Events in the City

In this paper, we study the emerging Information Retrieval (IR) task of local event retrieval using sensor metadata streams. Sensor metadata streams include information such as the crowd density from video processing, audio classifications, and social media activity. We propose to use these metadata streams to identify the topics of local events within a city, where each event topic corresponds to a set of terms representing a type of events such as a concert or a protest. We develop a supervised approach that is capable of mapping sensor metadata observations to an event topic. In addition to using a variety of sensor metadata observations about the current status of the environment as learning features, our approach incorporates additional background features to model cyclic event patterns. Through experimentation with data collected from two locations in a major Spanish city, we show that our approach markedly outperforms an alternative baseline. We also show that modelling background information improves event topic identification

CentralNet: a Multilayer Approach for Multimodal Fusion

This paper proposes a novel multimodal fusion approach, aiming to produce best possible decisions by integrating information coming from multiple media. While most of the past multimodal approaches either work by projecting the features of different modalities into the same space, or by coordinating the representations of each modality through the use of constraints, our approach borrows from both visions. More specifically, assuming each modality can be processed by a separated deep convolutional network, allowing to take decisions independently from each modality, we introduce a central network linking the modality specific networks. This central network not only provides a common feature embedding but also regularizes the modality specific networks through the use of multi-task learning. The proposed approach is validated on 4 different computer vision tasks on which it consistently improves the accuracy of existing multimodal fusion approaches

601 metal-on-metal total hip replacements with 36 mm heads a 5 minimum year follow up: Levels of ARMD remain low despite a comprehensive screening program

BACKGROUND: We conducted a retrospective study to assess the clinical outcome, failure rate, and reason for failure of a large consecutive series of 36 mm MoM Corail/Pinnacle total hip replacements (THRs). METHODS: Between 2006 and 2011, 601 consecutive 36 mm MoM THRs were performed (585 patients). Patients were followed according to the UK Medicines and Healthcare Products Regulatory Agency (MHRA) guidelines. All patients were accounted for and 469 patients (78%) were clinically and radiographically assessed. 328 females and 141 males with a median age of 73 (range 36-94 years) and a median follow up of 7.2 years (range 5.2-9.7 years) were followed. Clinical data included blood cobalt and chromium, Oxford Hip Score (OHS), plain radiograph, ultrasound of hip and intra-operative findings in those patients who had revision surgery. RESULTS: 56 patients died of causes unrelated to their hip replacement. The mean survivorship of the implant was 92.8% (range 91.6-94%, 95% CI) at a median time to follow up of 84 months (62-113 months). The functional outcome was good with a median OHS of 38 out of 48 (23-44). The dislocation rate was 0.99%, with all these 6 cases requiring revision. 476 patients had blood tests. 100 patients (21%) had elevated levels of either cobalt above MHRA guidelines of 7 parts per billion (120 and 135 nmol/L respectively for cobalt and chromium). Cobalt was elevated independently of chromium in 75% of the cases (but never vice versa). The mean cup inclination angle was 42°. Each incremental stem size increase resulted in a decrease in cobalt by 11 nmol/L. The most common reason for revision was adverse reaction to metal debris (ARMD) (12 cases). CONCLUSION: This paper is the largest and longest follow up of 36 mm MoM THRs. Using the MHRA guidelines for follow up, the revision rates of this cohort has remained low compared to other studies, but unacceptably higher than that of other bearing surfaces. LEVEL OF EVIDENCE: III

Assessment of the equivalence of a generic to a branded femoral stem.

AIMS: The aim of this study was to compare the design of the generic OptiStem XTR femoral stem with the established Exeter femoral stem. MATERIALS AND METHODS: We obtained five boxed, as manufactured, implants of both designs at random (ten in total). Two examiners were blinded to the implant design and independently measured the mass, volume, trunnion surface topography, trunnion roughness, trunnion cone angle, Caput-Collum-Diaphyseal (CCD) angle, femoral offset, stem length, neck length, and the width and roughness of the polished stem shaft using peer-reviewed methods. We then compared the stems using these parameters. RESULTS: We found that the OptiStems were lighter (p < 0.001), had a rougher trunnion surface (p < 0.001) with a greater spacing and depth of the machined threads (p < 0.001), had greater trunnion cone angles (p = 0.007), and a smaller radius at the top of the trunnion (p = 0.007). There was no difference in stem volume (p = 0.643), CCD angle (p = 0.788), offset (p = 0.993), neck length (p = 0.344), stem length (p = 0.808), shaft width (p = 0.058 to 0.720) or roughness of the polished surface (p = 0.536). CONCLUSION: This preliminary investigation found that whilst there were similarities between the two designs, the generic OptiStem is different to the branded Exeter design. Cite this article: Bone Joint J 2017;99-B:310-16

Investigating non-classical correlations between decision fused multi-modal documents

Correlation has been widely used to facilitate various information retrieval methods such as query expansion, relevance feedback, document clustering, and multi-modal fusion. Especially, correlation and independence are important issues when fusing different modalities that influence a multi-modal information retrieval process. The basic idea of correlation is that an observable can help predict or enhance another observable. In quantum mechanics, quantum correlation, called entanglement, is a sort of correlation between the observables measured in atomic-size particles when these particles are not necessarily collected in ensembles. In this paper, we examine a multimodal fusion scenario that might be similar to that encountered in physics by firstly measuring two observables (i.e., text-based relevance and image-based relevance) of a multi-modal document without counting on an ensemble of multi-modal documents already labeled in terms of these two variables. Then, we investigate the existence of non-classical correlations between pairs of multi-modal documents. Despite there are some basic differences between entanglement and classical correlation encountered in the macroscopic world, we investigate the existence of this kind of non-classical correlation through the Bell inequality violation. Here, we experimentally test several novel association methods in a small-scale experiment. However, in the current experiment we did not find any violation of the Bell inequality. Finally, we present a series of interesting discussions, which may provide theoretical and empirical insights and inspirations for future development of this direction

iCLAP: Shape Recognition by Combining Proprioception and Touch Sensing

The work presented in this paper was partially supported by the Engineering and Physical Sciences Council (EPSRC) Grant (Ref: EP/N020421/1) and the King’s-China Scholarship Council Ph.D. scholarship