BNC! Handle with care! Spelling and tagging errors in the BNC

"You loose your no-claims bonus," instead of "You lose your no-claims bonus," is an example of a real-word spelling error. One way to enable a spellchecker to detect such errors is to prime it with information about likely features of the context for "loose" (verb) as compared with "lose". To this end, we extracted all the examples of "loose" used as a verb from the BNC (World edition, text). There were, apparently, 159 occurrences of "loose" (VVB or VVI). However, on inspection, well over half of these were not verbs at all (tagging errors) and over half of the rest were misspellings of "lose". Only about 15% were actual occurrences of "loose" as a verb. This prompted us to undertake a small investigation into errors in the BNC. We report on some words that occur more often as misspellings than in their own right - only one of the 63 occurrences of "ail", for example, is correct (possibly OCR errors) - and some words that are always mistagged, such as "haulier" and "glazier" (never NN), and "hanker" and "loiter" (never VV). We note in particular that, if a rare word resembles a common word (in spelling), it is more likely to appear as a misspelling of the common word than as a correct spelling of the rare word. These cases require some modification of an earlier conclusion (Damerau and Mays, 1989) on misspellings of rare words. We conclude with a discussion of the desirability, or otherwise, of correcting errors in corpora such as the BNC. The results may be of interest to people who use the BNC as training data or for teaching

From the Internet of things to the Internet of physical world

International audienceThis article describes the different kinds of RFID tags. It details passive and active RFID tags different functions and uses

Quantitative geometric analysis of rib, costal cartilage and sternum from childhood to teenagehood

Better understanding of the effects of growth on children’s bones and cartilage is necessary for clinical and biomechanical purposes. The aim of this study is to define the 3D geometry of children’s rib cages: including sternum, ribs and costal cartilage. Three-dimensional reconstructions of 960 ribs, 518 costal cartilages and 113 sternebrae were performed on thoracic CT-scans of 48 children, aged four months to 15 years. The geometry of the sternum was detailed and nine parameters were used to describe the ribs and rib cages. A "costal index" was defined as the ratio between cartilage length and whole rib length to evaluate the cartilage ratio for each rib level. For all children, the costal index decreased from rib level one to three and increased from level three to seven. For all levels, the cartilage accounted for 45 to 60% of the rib length, and was longer for the first years of life. The mean costal index decreased by 21% for subjects over three years old compared to those under three (p<10-4). The volume of the sternebrae was found to be highly age dependent. Such data could be useful to define the standard geometry of the paediatric thorax and help to detect clinical abnormalities.Grant from the ANR (SECUR_ENFANT 06_0385) and supported by the GDR 2610 “Biomécanique des chocs” (CNRS/INRETS/GIE PSA Renault

Variability of Child Rib Bone Hounsfield Units using in vivo Computed Tomography

The variability assessment of the rib bone mechanical properties during the growth process is still missing. These properties could not be obtained in vivo on children. Relationships have been obtained between Hounsfield Units from computed tomography (CT) and mechanical properties (e.g. for the cortical bone on adults). As a first step for investigation of the mechanical properties of child ribs, the aim of this study was to determine the Hounsfield Units variation of child ribs from CT‐scan data, by rib level, along the rib and within the rib sections. Twenty‐seven right ribs of levels 4, 6 and 9 were processed from 11 thoracic CT scans of children without bone lesions aged between 1 and 10 years. A first set of 10 equidistributed cross‐sections normal to the rib midline were extracted. Sixteen equally distributed elements defined 4 areas into the cortical band: internal, external, caudal and cranial. Within the rib sections, Hounsfield Units were found significantly higher in internal and external areas than in caudal and cranial. In a further step using calibrated CT scans, it would be possible to derive the mechanical properties of in vivo child ribs using bone density correlation with Hounsfield Units

A Turnover based Adaptive HELLO Protocol for Mobile Ad Hoc and Sensor Networks

International audienceWe present a turnover based adaptive HELLO protocol (TAP), which enables nodes in mobile networks to dynamically adjust their HELLO messages frequency depending on the current speed of nodes. To the best of our knowledge, all existing solutions are based on specific assumptions (\eg{} slotted networks) and/or require specific hardware (\eg{} GPS) for speed evaluation. One of the key aspects of our solution is that no additional hardware is required since it does not need this speed information. TAP may be used in any kind of mobile networks that rely on HELLO messages to maintain neighborhood tables and is thus highly relevant in the context of ad hoc and sensor networks. In our solution, each node has to monitor its neighborhood table to count new neighbors whenever a HELLO is sent. This \emph{turnover} is then used to adjust HELLO frequency. To evaluate our solution, we propose a theoretical analysis based on some given assumptions that provides the optimal turnover when these assumptions hold. Our experimental results demonstrate that when this optimal value is used as the targeted turnover in TAP, the HELLO frequency is correctly adjusted and provides a good accuracy with regards to the neighborhood tables

Towards Unified Tag Data Translation for the Internet of Things

International audienceFollowing the ``Internet of Things'' concept, each object will be associated with a unique identifier which will allow to retrieve information about it in large databases. In the process of retrieving information, this identifier (ID) may have to be translated into different formats (e.g. domain name style format for object name service query, binary, legacy,...). The Tag Data Translation (TDT) is responsible for the translation of IDs into these different formats. We propose a general TDT system which extends the standards of EPCGlobal which only targets Electronic Product Code (EPC). We integrate other RFID and smart cards standards (such as ISO 14443 and 15693) and GS1 standards which are more general as they also deal with bar code (EAN/UPC)

Mobility Prediction Based Neighborhood Discovery for Mobile Ad Hoc Networks

Hello protocol is the basic technique for neighborhood discovery in wireless ad hoc networks. It requires nodes to claim their existence/aliveness by periodic `hello' messages. Central to any hello protocol is the determination of `hello' message transmission rate. No fixed optimal rate exists in the presence of node mobility. The rate should in fact adapt to it, high for high mobility and low for low mobility. In this paper, we propose a novel mobility prediction based hello protocol, named ARH ({\em Autoregressive Hello protocol}). In this protocol, each node predicts its own position by an ever-updated autoregression-based mobility model, and neighboring nodes predict its position by the same mobility model. The node transmits `hello' message (for location update) only when the predicted location is too different from the true location (causing topology distortion), triggering mobility model correction on both itself and each of its neighbors. ARH evolves along with network dynamics, and seamlessly tunes itself to the optimal configuration on the fly using local knowledge only. Through extensive simulation, we demonstrate the effectiveness and efficiency of ARH, in comparison with the best known competitive protocol TAP (Turnover based Adaptive hello Protocol). It comes out that ARH achieves the same high neighborhood discovery performance as TAP with dramatically less message overhead (about 50% lower `hello' rate)

An energy efficient adaptive HELLO algorithm for mobile ad hoc networks

HELLO protocol or neighborhood discovery is essential in wireless ad hoc networks. It makes the rules for nodes to claim their existence/aliveness. In the presence of node mobility, no fix optimal HELLO frequency and optimal transmission range exist to maintain accurate neighborhood tables while reducing the energy consumption and bandwidth occupation. Thus a Turnover based Frequency and transmission Power Adaptation algorithm (TFPA) is presented in this paper. The method enables nodes in mobile networks to dynamically adjust both their HELLO frequency and transmission range depending on the relative speed. In TFPA, each node monitors its neighborhood table to count new neighbors and calculate the turnover ratio. The relationship between relative speed and turnover ratio is formulated and optimal transmission range is derived according to battery consumption model to minimize the overall transmission energy. By taking advantage of the theoretical analysis, the HELLO frequency is adapted dynamically in conjunction with the transmission range to maintain accurate neighborhood table and to allow important energy savings. The algorithm is simulated and compared to other state-of-the-art algorithms. The experimental results demonstrate that the TFPA algorithm obtains high neighborhood accuracy with low HELLO frequency (at least 11% average reduction) and with the lowest energy consumption. Besides, the TFPA algorithm does not require any additional GPS-like device to estimate the relative speed for each node, hence the hardware cost is reduced

Towards an efficient QoS based selection of neighbors in QOLSR

International audienceOLSR is a well-known proactive protocol for wireless networks. Although very efficient by many points, it suffers from the drawbacks of not taking into account QoS metrics such as delay or bandwidth. To overcome this pitfall, some QOLSR (QoS OLSR) solutions have been designed. Nevertheless, they still provide weak performance regarding QoS metrics. In this paper, we introduce a novel and simple neighbor selection to allow routing with OLSR along quasi-optimal QoS paths

End-to-End Energy Efficient Geographic Path Discovery With Guaranteed Delivery in Ad Hoc and Sensor Networks

International audienceWe propose a novel localized routing protocol for wireless sensor networks (WSN) that is energy-efficient and guarantees delivery. We prove that it is constant factor of the optimum for dense networks. To forward a packet, a node $s$ in graph $G$ computes the cost of the energy weighted shortest path (SP) between $s$ and each of its neighbors which are closer to the destination than itself. It then selects node $x$ which minimizes the ratio of the cost of the SP to the progress towards the destination. It then sends the message to the first node on the SP from $s$ to $x$: say node $x'$. Node $x'$ restarts the same greedy routing process until the destination is reached or the routing fails. To recover from failure, our algorithm invokes Face routing that guarantees delivery. This work is the first to optimize energy consumption of Face routing. First, we build a connected dominating set from graph $G$, second we compute its Gabriel graph to obtain the planar graph $G'$. Face routing is applied on $G'$ only to decide which edges to follow in the recovery process. On each edge, greedy routing is used. This two-phase (greedy-Face) End-to-End routing process (EtE) reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on energy consumption metric