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International audience; The High Level Trigger (HLT) of the ATLAS experiment at the Large Hadron Collider receives events which pass the LVL1 trigger at ~75 kHz and has to reduce the rate to ~200 Hz while retaining the most interesting physics. It is a software trigger and performs the reduction in two stages: the LVL2 trigger and the Event Filter (EF). At the heart of the HLT is the Steering software. To minimise processing time and data transfers it implements the novel event selection strategies of seeded, step-wise reconstruction and early rejection. The HLT is seeded by regions of interest identified at LVL1. These and the static configuration determine which algorithms are run to reconstruct event data and test the validity of trigger signatures. The decision to reject the event or continue is based on the valid signatures, taking into account pre-scale and pass-through. After the EF, event classification tags are assigned for streaming purposes. Several powerful new features for commissioning and operation have been added: comprehensive monitoring is now built in to the framework; for validation and debugging, reconstructed data can be written out; the steering is integrated with the new configuration (presented separately), and topological and global triggers have been added. This paper will present details of the final design and its implementation, the principles behind it, and the requirements and constraints it is subject to. The experience gained from technical runs with realistic trigger menus will be described.

Ever-increasing amount of multimedia available online necessitates the development of new techniques and methods that can overcome the semantic gap problem. The said problem, encountered due to major disparities between inherent representational characteristics of multimedia and its semantic content sought by the user, has been a prominent research direction addressed by a great number of semantic augmentation approaches originating from such areas as machine learning, statistics, natural language processing, etc. In this paper, we review several of these recently developed techniques that bring together low-level representation of multimedia and its semantics in order to improve the efficiency of access and retrieval. We also present a distance-based discriminant analysis (DDA) method that defines the design of a basic building block classifier for distinguishing among a selected number of semantic categories. In addition to that, we demonstrate how a set of DDA classifiers can be grouped into a hierarchical ensemble for prediction of an arbitrary set of semantic classes.

Almost entirely overlooked throughout the 20th century, neglected by contemporary medical manuals, the clitoris has gradually returned centre stage thanks to Western feminism.

Preliminary biostratigraphic and geochronological results obtained from a 44 m-long core drilled on the northern coast of Mayaguana Island (SE Bahamas) show that the topmost layers of the core date from the Burdigalian (Early Miocene), whereas the deepest units are of Chattian (Late Oligocene) or Aquitanian (Earliest Miocene) age. Accordingly, the platform aggraded 44 m of sediments in a 10 to 3 my time span, from the Chattian/Aquitanian to the Burdigalian, whereas previous surface investigations of the island showed that only 11 m of carbonates were accumulated in a 17 my-long period, between the Burdigalian and the Early Pleistocene. This new record shows that the accumulation rate of the Mayaguana Bank was much higher during the Late Paleogene/Early Miocene than during the time interval from the Middle Miocene to the Pleistocene. This decrease is likely due to vertical tectonic motions related to the late phases of the Cuban orogeny which reduced accommodation on the platform top. These results designate the Mayaguana Bank as an accurate gauge to record the elevation of sea-level highstands during the Neogene

MedSLT is a unidirectional medical speech translation system intended for use in doctor-patient diagnosis dialogues, which provides coverage of several different language pairs and subdomains. Vocabulary ranges from about 350 to 1000 surface words, depending on the language and subdomain. We will demo both the system itself and the development environment, which uses a combination of rule-based and data-driven methods to construct efficient recognisers, generators and transfer rule sets from small corpora.

The most salient geological features observed during a recent reconnaissance trip to Crooked Island, SE Bahamas, include: (1) altered bioclastic calcarenites of probable Early Pleistocene age; and (2) an elevated intertidal notch carved in last interglacial deposits, indicating that sea level peaked at a higher elevation than previously estimated during that time period. Four main lithostratigraphic units were identified on Crooked Island: (1) highly weathered bioclastic calcarenites that yielded unreliable alloisoleucine/isoleucine (A/I) ratios, and two valid 87Sr/86Sr ratios averaging 0.709147; (2) well-lithified bioclastic/peloidal eolianites, forming low sea cliffs, that gave one A/I ratio of 0.523; (3) a complex and extensive unit including scarce coral framestone, exposed up to +1.2 m above sea level, and oolitic-peloidal calcarenites deposited in subtidal, beach, and eolian environments that yielded A/I ratios averaging 0.411 (n=5); and (4) poorly lithified bioclastic beach ridges congruent with modern sea level. Moreover, a prominent ridge along the north coast of the island shows, at +11 m above sea level, an intertidal notch carved in Unit 3 eolianite and filled by Unit 3 beach facies. Units 4, 3 and 2 can be compared, respectively, to the Rice Bay (Holocene), the Grotto Beach (Late Pleistocene) and the Owl's Hole (Middle Pleistocene) formations, previously identified on many other Bahamian islands. Of probable Early Pleistocene age (between 0.6 and 1 Ma), Unit 1 could represent the lowermost part of the Owl's Hole Formation and the top of the underlying, mostly marine Misery Point Formation recently discovered on Mayaguana. The unequivocal occurrence of an intertidal notch carved in, and sealed by, last-interglacial deposits at +11 m shows that the peak elevation reached by sea level during that time interval was much higher than previously assessed. Finally, stratigraphic units decrease in age from N to S, suggesting that the island grew differently than other Bahamian islands or, alternatively, that the northern margin of the Crooked-Acklins bank collapsed in a recent past.

This chapter is concerned with the organization of categorical sequence data. We first build a typology of sequences distinguishing for example between chronological sequences and sequences without time content. This permits to identify the kind of information that the data organization should preserve. Focusing then mainly on chronological sequences, we discuss the advantages and limits of different ways of representing time stamped event and state sequence data and present solutions for automatically converting between various formats, e.g., between horizontal and vertical presentations but also from state sequences into event sequences and reciprocally. Special attention is also drawn to the handling of missing values in these conversion processes.

When developing NLP tools for low-resource languages, one is often confronted with the lack of annotated data. We propose to circumvent this bottleneck by training a supervised HMM tagger on a closely related language for which annotated data are available, and translating the words in the tagger parameter files into the low-resource language. The translation dictionaries are created with unsupervised lexicon induction techniques that rely only on raw textual data. We obtain a tagging accuracy of up to 89.08% using a Spanish tagger adapted to Catalan, which is 30.66% above the performance of an unadapted Spanish tagger, and 8.88% below the performance of a supervised tagger trained on annotated Catalan data. Furthermore, we evaluate our model on several Romance, Germanic and Slavic languages and obtain tagging accuracies of up to 92%.

V International Conference on Corpus Linguistics (CILC2013); International audience; The paper presents the early stage of the CRISTAL project, an original French project involving linguists, computer researchers and a firm specializing in multilingual text management. What is at stake from a linguistic point of view is a deeper analysis of the notion of Knowledge Rich Context proposed by Meyer (2001). Using comparable corpora, it analyzes how the notion of KRC can vary according to text genre and/or type of users.

We consider methods for handling incomplete (elliptical) utterances in spoken phraselators, and describe how they have been implemented inside BabelDr, a substantial spoken medical phraselator. The challenge is to extend the phrase matching process so that it is sensitive to preceding dialogue context. We contrast two methods, one using limited-vocabulary strict grammar-based speech and language processing and one using large-vocabulary speech recognition with fuzzy grammar-based processing, and present an initial evaluation on a spoken corpus of 821 context-sentence/elliptical-phrase pairs. The large-vocabulary/fuzzy method strongly outperforms the limited-vocabulary/strict method over the whole corpus, though it is slightly inferior for the subset that is within grammar coverage. We investigate possibilities for combining the two processing paths, using several machine learning frameworks, and demonstrate that hybrid methods strongly outperform the large-vocabulary/fuzzy method.