52 resultados para Sensing, Smartphone, Sensori


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A new methodology based on combining active and passive remote sensing and simultaneous and collocated radiosounding data to study the aerosol hygroscopic growth effects on the particle optical and microphysical properties is presented. The identification of hygroscopic growth situations combines the analysis of multispectral aerosol particle backscatter coefficient and particle linear depolarization ratio with thermodynamic profiling of the atmospheric column. We analyzed the hygroscopic growth effects on aerosol properties, namely the aerosol particle backscatter coefficient and the volume concentration profiles, using data gathered at Granada EARLINET station. Two study cases, corresponding to different aerosol loads and different aerosol types, are used for illustrating the potential of this methodology. Values of the aerosol particle backscatter coefficient enhancement factors range from 2.1 ± 0.8 to 3.9 ± 1.5, in the ranges of relative humidity 60–90 and 40–83%, being similar to those previously reported in the literature. Differences in the enhancement factor are directly linked to the composition of the atmospheric aerosol. The largest value of the aerosol particle backscatter coefficient enhancement factor corresponds to the presence of sulphate and marine particles that are more affected by hygroscopic growth. On the contrary, the lowest value of the enhancement factor corresponds to an aerosol mixture containing sulphates and slight traces of mineral dust. The Hänel parameterization is applied to these case studies, obtaining results within the range of values reported in previous studies, with values of the γ exponent of 0.56 ± 0.01 (for anthropogenic particles slightly influenced by mineral dust) and 1.07 ± 0.01 (for the situation dominated by anthropogenic particles), showing the convenience of this remote sensing approach for the study of hygroscopic effects of the atmospheric aerosol under ambient unperturbed conditions. For the first time, the retrieval of the volume concentration profiles for these cases using the Lidar Radiometer Inversion Code (LIRIC) allows us to analyze the aerosol hygroscopic growth effects on aerosol volume concentration, observing a stronger increase of the fine mode volume concentration with increasing relative humidity.

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An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

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Crowdsourcing linguistic phenomena with smartphone applications is relatively new. Apps have been used to train acoustic models for automatic speech recognition (de Vries et al. 2014) and to archive endangered languages (Iwaidja Inyaman Team 2012). Leemann and Kolly (2013) developed a free app for iOS—Dialäkt Äpp (DÄ) (>78k downloads)—to document language change in Swiss German. Here, we present results of sound change based on DÄ data. DÄ predicts the users’ dialects: for 16 variables, users select their dialectal variant. DÄ then tells users which dialect they speak. Underlying this prediction are maps from the Linguistic Atlas of German-speaking Switzerland (SDS, 1962-2003), which documents the linguistic situation around 1950. If predicted wrongly, users indicate their actual dialect. With this information, the 16 variables can be assessed for language change. Results revealed robustness of phonetic variables; lexical and morphological variables were more prone to change. Phonetic variables like to lift (variants: /lupfə, lʏpfə, lipfə/) revealed SDS agreement scores of nearly 85%, i.e., little sound change. Not all phonetic variables are equally robust: ladle (variants: /xælə, xællə, xæuə, xæɫə, xæɫɫə/) exhibited significant sound change. We will illustrate the results using maps that show details of the sound changes at hand.

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Background: Sensor-based recordings of human movements are becoming increasingly important for the assessment of motor symptoms in neurological disorders beyond rehabilitative purposes. ASSESS MS is a movement recording and analysis system being developed to automate the classification of motor dysfunction in patients with multiple sclerosis (MS) using depth-sensing computer vision. It aims to provide a more consistent and finer-grained measurement of motor dysfunction than currently possible. Objective: To test the usability and acceptability of ASSESS MS with health professionals and patients with MS. Methods: A prospective, mixed-methods study was carried out at 3 centers. After a 1-hour training session, a convenience sample of 12 health professionals (6 neurologists and 6 nurses) used ASSESS MS to capture recordings of standardized movements performed by 51 volunteer patients. Metrics for effectiveness, efficiency, and acceptability were defined and used to analyze data captured by ASSESS MS, video recordings of each examination, feedback questionnaires, and follow-up interviews. Results: All health professionals were able to complete recordings using ASSESS MS, achieving high levels of standardization on 3 of 4 metrics (movement performance, lateral positioning, and clear camera view but not distance positioning). Results were unaffected by patients’ level of physical or cognitive disability. ASSESS MS was perceived as easy to use by both patients and health professionals with high scores on the Likert-scale questions and positive interview commentary. ASSESS MS was highly acceptable to patients on all dimensions considered, including attitudes to future use, interaction (with health professionals), and overall perceptions of ASSESS MS. Health professionals also accepted ASSESS MS, but with greater ambivalence arising from the need to alter patient interaction styles. There was little variation in results across participating centers, and no differences between neurologists and nurses. Conclusions: In typical clinical settings, ASSESS MS is usable and acceptable to both patients and health professionals, generating data of a quality suitable for clinical analysis. An iterative design process appears to have been successful in accounting for factors that permit ASSESS MS to be used by a range of health professionals in new settings with minimal training. The study shows the potential of shifting ubiquitous sensing technologies from research into the clinic through a design approach that gives appropriate attention to the clinic environment.

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Smartphone-App zur Kohlenhydratberechnung Neue Technologien wie Blutzuckersensoren und moderne Insulinpumpen prägten die Therapie des Typ-1-Diabetes (T1D) in den letzten Jahren in wesentlichem Ausmaß. Smartphones sind aufgrund ihrer rasanten technischen Entwicklung eine weitere Plattform für Applikationen zur Therapieunterstützung bei T1D. GoCARB Hierbei handelt es sich um ein zur Kohlenhydratberechnung entwickeltes System für Personen mit T1D. Die Basis für Endanwender stellt ein Smartphone mit Kamera dar. Zur Berechnung werden 2 mit dem Smartphone aus verschiedenen Winkeln aufgenommene Fotografien einer auf einem Teller angerichteten Mahlzeit benötigt. Zusätzlich ist eine neben dem Teller platzierte Referenzkarte erforderlich. Die Grundlage für die Kohlenhydratberechnung ist ein Computer-Vision-gestütztes Programm, das die Mahlzeiten aufgrund ihrer Farbe und Textur erkennt. Das Volumen der Mahlzeit wird mit Hilfe eines dreidimensional errechneten Modells bestimmt. Durch das Erkennen der Art der Mahlzeiten sowie deren Volumen kann GoCARB den Kohlenhydratanteil unter Einbeziehung von Nährwerttabellen berechnen. Für die Entwicklung des Systems wurde eine Bilddatenbank von mehr als 5000 Mahlzeiten erstellt und genutzt. Resümee Das GoCARB-System befindet sich aktuell in klinischer Evaluierung und ist noch nicht für Patienten verfügbar.

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African trypanosomes, which divide their life cycle between mammals and tsetse flies, are confronted with environments that differ widely in temperature, nutrient availability and host responses to infection. In particular, since trypanosomes cannot predict when they will be transmitted between hosts, it is vital for them to be able to sense and adapt to their milieu. Thanks to technical advances, significant progress has been made in understanding how the parasites perceive external stimuli and react to them. There is also a growing awareness that trypanosomes use a variety of mechanisms to exchange information with each other, thereby enhancing their chances of survival.