Shallow Dialogue Processing Using Machine Learning Algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.

Expanded Clinical Spectrum of Multiple Evanescent White Dot Syndrome with Multimodal Imaging

PURPOSE: To evaluate and characterize multiple evanescent white dot syndrome abnormalities with modern multimodal imaging modalities. METHODS: This retrospective cohort study evaluated fundus photography, fluorescein angiography, indocyanine green angiography, optical coherence tomography, enhanced depth imaging optical coherence tomography, short-wavelength autofluorescence, and near-infrared autofluorescence. RESULTS: Thirty-four multiple evanescent white dot syndrome patients with mean age of 28.7 years were studied (range, 14-49 years). Twenty-six patients were women, and eight were men. Initial mean visual acuity was 0.41 logMAR. Final mean visual acuity was 0.03 logMAR. Fluorescein angiography shows a variable number of mid retinal early fluorescent dots distributed in a wreathlike pattern, which correlate to fundus photography, fundus autofluorescence, and indocyanine green angiography. Indocyanine green angiography imaging shows the dots and also hypofluorescent, deeper, and larger spots, which are occasionally confluent, demonstrating a large plaque of deep retinal hypofluorescence. Optical coherence tomography imaging shows multifocal debris centered at and around the ellipsoid layer, corresponding to the location of spots seen with photography, indocyanine green angiography, and fluorescein angiography. Protrusions of the hyperreflectant material from the ellipsoid layer toward the outer nuclear layer correspond to the location of dots seen with photography, indocyanine green angiography, and fluorescein angiography. CONCLUSION: Multimodal imaging analysis of the retina in patients with multiple evanescent white dot syndrome shows additional features that may help in the diagnosis of the disease and in further understanding its etiology. Multiple evanescent white dot syndrome is predominantly a disease of the outer retina, centered at the ellipsoid zone, but also involving the interdigitation zone and the outer nuclear layer.

Information-Centric Content Retrieval for Delay-Tolerant Networks

The shift from host-centric to information-centric networking (ICN) promises seamless communication in mobile networks. However, most existing works either consider well-connected networks with high node density or introduce modifications to {ICN} message processing for delay-tolerant Networking (DTN). In this work, we present agent-based content retrieval, which provides information-centric {DTN} support as an application module without modifications to {ICN} message processing. This enables flexible interoperability in changing environments. If no content source can be found via wireless multi-hop routing, requesters may exploit the mobility of neighbor nodes (called agents) by delegating content retrieval to them. Agents that receive a delegation and move closer to content sources can retrieve data and return it back to requesters. We show that agent-based content retrieval may be even more efficient in scenarios where multi-hop communication is possible. Furthermore, we show that broadcast communication may not be necessarily the best option since dynamic unicast requests have little overhead and can better exploit short contact times between nodes (no broadcast delays required for duplicate suppression).

Mapping spectroscopic uncertainties into prospective methane retrieval errors from Sentinel-5 and its precursor

Sentinel-5 (S5) and its precursor (S5P) are future European satellite missions aiming at global monitoring of methane (CH4) column-average dry air mole fractions (XCH4). The spectrometers to be deployed onboard the satellites record spectra of sunlight backscattered from the Earth's surface and atmosphere. In particular, they exploit CH4 absorption in the shortwave infrared spectral range around 1.65 mu m (S5 only) and 2.35 mu m (both S5 and S5P) wavelength. Given an accuracy goal of better than 2% for XCH4 to be delivered on regional scales, assessment and reduction of potential sources of systematic error such as spectroscopic uncertainties is crucial. Here, we investigate how spectroscopic errors propagate into retrieval errors on the global scale. To this end, absorption spectra of a ground-based Fourier transform spectrometer (FTS) operating at very high spectral resolution serve as estimate for the quality of the spectroscopic parameters. Feeding the FTS fitting residuals as a perturbation into a global ensemble of simulated S5- and S5P-like spectra at relatively low spectral resolution, XCH4 retrieval errors exceed 0.6% in large parts of the world and show systematic correlations on regional scales, calling for improved spectroscopic parameters.

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Multimodal Imaging of Cotton Wool Spots in Branch Retinal Vein Occlusion.

PURPOSE: To describe and follow cotton wool spots (CWS) in branch retinal vein occlusion (BRVO) using multimodal imaging. METHODS: In this prospective cohort study including 24 patients with new-onset BRVO, CWS were described and analyzed in color fundus photography (CF), spectral domain optical coherence tomography (SD-OCT), infrared (IR) and fluorescein angiography (FA) every 3 months for 3 years. The CWS area on SD-OCT and CF was evaluated using OCT-Tool-Kit software: CWS were marked in each single OCT B-scan and the software calculated the area by interpolation. RESULTS: 29 central CWS lesions were found. 100% of these CWS were visible on SD-OCT, 100% on FA and 86.2% on IR imaging, but only 65.5% on CF imaging. CWS were visible for 12.4 ± 7.5 months on SD-OCT, for 4.4 ± 3 months and 4.3 ± 3.4 months on CF and on IR, respectively, and for 17.5 ± 7.1 months on FA. The evaluated CWS area on SD-OCT was larger than on CF (0.26 ± 0.17 mm(2) vs. 0.13 ± 0.1 mm(2), p < 0.0001). The CWS area on SD-OCT and surrounding pathology such as intraretinal cysts, avascular zones and intraretinal hemorrhage were predictive for how long CWS remained visible (r(2) = 0.497, p < 0.002). CONCLUSIONS: The lifetime and presentation of CWS in BRVO seem comparable to other diseases. SD-OCT shows a higher sensitivity for detecting CWS compared to CF. The duration of visibility of CWS varies among different image modalities and depends on the surrounding pathology and the CWS size.

A multimodal tablet-based interface for designing and reviewing 3D engineering models

The ability to view and interact with 3D models has been happening for a long time. However, vision-based 3D modeling has only seen limited success in applications, as it faces many technical challenges. Hand-held mobile devices have changed the way we interact with virtual reality environments. Their high mobility and technical features, such as inertial sensors, cameras and fast processors, are especially attractive for advancing the state of the art in virtual reality systems. Also, their ubiquity and fast Internet connection open a path to distributed and collaborative development. However, such path has not been fully explored in many domains. VR systems for real world engineering contexts are still difficult to use, especially when geographically dispersed engineering teams need to collaboratively visualize and review 3D CAD models. Another challenge is the ability to rendering these environments at the required interactive rates and with high fidelity. In this document it is presented a virtual reality system mobile for visualization, navigation and reviewing large scale 3D CAD models, held under the CEDAR (Collaborative Engineering Design and Review) project. It’s focused on interaction using different navigation modes. The system uses the mobile device's inertial sensors and camera to allow users to navigate through large scale models. IT professionals, architects, civil engineers and oil industry experts were involved in a qualitative assessment of the CEDAR system, in the form of direct user interaction with the prototypes and audio-recorded interviews about the prototypes. The lessons learned are valuable and are presented on this document. Subsequently it was prepared a quantitative study on the different navigation modes to analyze the best mode to use it in a given situation.