Batimetria fluvial estimada com dados orbitais: Estudo de caso no alto curso do rio Paraguai com o sensor ASTER

The Paraguay River is the main tributary of the Paraná River and has an extension of 1.693 km in Brazilian territory. The navigability conditions are very important for the regional economy because most of the central-west Brazilian agricultural and mineral production is transported by the Paraguay waterway. Increased sedimentation along the channel requires continuous dredging to waterway maintenance. Systematic bathymetric surveys are periodically carried out in order to check depth condition along the channel using echo-sounding devices. In this paper, digital image processing and geostatistical analysis methods were used to analyze the applicability of the ASTER sensor to estimate channel depths in a segment of the upper Paraguay River. The results were compared with field data in order to choose the band with better adjustment and to evaluate the standard deviation. Comparing the VNIR bands, the best fit was presented by the red wavelength (band 2; 0,63 - 0,69 μm), showing a good representation of the channel depths shallow than 1,7 m. Applying geostatistical methods, the model accuracy was enhanced from 43 cm to 36 cm and undesired components were slacked. It was concluded that the digital number of band 2, converted to bathymetry information allows a good estimation of river depths and channel morphology.

Ultrasonic sensor for the presence of oily contaminants in water

The determination of the complex reflection coefficient of ultrasonic shear-waves at the solid-liquid interface is a technique employed for the measurement of the viscoelastic properties of liquids. An interesting property of the measurement technique is the very small penetration depth of the shear-waves into the liquid sample, which permits measurements with liquid films of some micrometers thick. This property, along with the adhesion of oily substances to surfaces, can be used for the detection of oily contaminants in water. In this work, the employment of the ultrasonic shear-wave reflection technique to the detection of oily contaminants in water is proposed and the theoretical and experimental concepts involved are discussed. Preliminary experimental results show the measurement technique can detect SAE 40 automotive oil in water in volume proportions less than 0.5%.

On the use of a low-cost thermal sensor to improve kinect people detection in a mobile robot

[EN]Detecting people is a key capability for robots that operate in populated environments. In this paper, we have adopted a hierarchical approach that combines classifiers created using supervised learning in order to identify whether a person is in the view-scope of the robot or not. Our approach makes use of vision, depth and thermal sensors mounted on top of a mobile platform.

Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision

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.

Visualizing the Simulation of 3-D Underwater Sensor Networks

The majority of sensor network research deals with land-based networks, which are essentially two-dimensional, and thus the majority of simulation and animation tools also only handle such networks. Underwater sensor networks on the other hand, are essentially 3D networks because the depth at which a sensor node is located needs to be considered as well. Due to that additional dimension, specialized tools need to be used when conducting simulations for experimentation. The School of Engineering’s Underwater Sensor Network (UWSN) lab is conducting research on underwater sensor networks and requires simulation tools for 3D networks. The lab has extended NS-2, a widely used network simulator, so that it can simulate three-dimensional networks. However, NAM, a widely used network animator, currently only supports two-dimensional networks and no extensions have been implemented to give it three-dimensional capabilities. In this project, we develop a network visualization tool that functions similarly to NAM but is able to render network environments in full 3-D. It is able to take as input a NS-2 trace file (the same file taken as input by NAM), create the environment, position the sensor nodes, and animate the events of the simulation. Further, the visualization tool is easy to use, especially friendly to NAM users, as it is designed to follow the interfaces and functions similar to NAM. So far, the development has fulfilled the basic functionality. Future work includes fully functional capabilities for visualization and much improved user interfaces.

Multi-sensor global compilation of mid-Holocene sea surface temperatures, based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst

We present and examine a multi-sensor global compilation of mid-Holocene (MH) sea surface temperatures (SST), based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst census counts. We assess the uncertainties originating from using different methodologies and evaluate the potential of MH SST reconstructions as a benchmark for climate-model simulations. The comparison between different analytical approaches (time frame, baseline climate) shows the choice of time window for the MH has a negligible effect on the reconstructed SST pattern, but the choice of baseline climate affects both the magnitude and spatial pattern of the reconstructed SSTs. Comparison of the SST reconstructions made using different sensors shows significant discrepancies at a regional scale, with uncertainties often exceeding the reconstructed SST anomaly. Apparent patterns in SST may largely be a reflection of the use of different sensors in different regions. Overall, the uncertainties associated with the SST reconstructions are generally larger than the MH anomalies. Thus, the SST data currently available cannot serve as a target for benchmarking model simulations.

Near-bottom zooplankton aggregations in Kongsfjorden with link to images from the optical zooplankton sensor MOKI

Near-bottom zooplankton communities have rarely been studied despite numerous reports of high zooplankton concentrations, probably due to methodological constraints. In Kongsfjorden, Svalbard, the near-bottom layer was studied for the first time by combining daytime deployments of a remotely operated vehicle (ROV), the optical zooplankton sensor moored on-sight key species investigation (MOKI), and Tucker trawl sampling. ROV data from the fjord entrance and the inner fjord showed high near-bottom abundances of euphausiids with a mean concentration of 17.3 ± 3.5 n/100 m**3. With the MOKI system, we observed varying numbers of euphausiids, amphipods, chaetognaths, and copepods on the seafloor at six stations. Light-induced zooplankton swarms reached densities in the order of 90,000 (euphausiids), 120,000 (amphipods), and 470,000 ind/m**3 (chaetognaths), whereas older copepodids of Calanus hyperboreus and C. glacialis did not respond to light. They were abundant at the seafloor and 5 m above and showed maximum abundance of 65,000 ind/m**3. Tucker trawl data provided an overview of the seasonal vertical distribution of euphausiids. The most abundant species Thysanoessa inermis reached near-bottom concentrations of 270 ind/m**3. Regional distribution was neither related to depth nor to location in the fjord. The taxa observed were all part of the pelagic community. Our observations suggest the presence of near-bottom macrozooplankton also in other regions and challenge the current view of bentho-pelagic coupling. Neglecting this community may cause severe underestimates of the stock of elagic zooplankton, especially predatory species, which link secondary production with higher trophic levels.