The uncertainties in diesel engine parameters often result in an inaccurate model. The data describe the actual data to identify the faults using exploratory data analysis to avoid high shipping cost.

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Noise control is required to ensure crew habitability onboard an offshore platform. Applying noise prediction is important to identify the potential noise problem at the early stage of the offshore platform design to avoid costly retrofitting in the implementation stage. Noise data were collected. The 4 output targets are namely: spatial sound pressure level (SPL), spatial average SPL, structure-borne noise and airborne noise at different octave frequencies (e.g. 125Hz, 250Hz, 500Hz, 1000Hz, 2000Hz, 4000Hz, 8000 Hz).

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The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.

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This dataset accompanies the IEEE Journal of Oceanic Engineering Special Issue on Verification and Validation of Airgun Source Signature and Sound Propagation Models. The special issue has is its origins in the International Airgun Modelling Workshop (IAMW) held in Dublin, Ireland, on 16 July 2016 (Ainslie et al., 2016).

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We have labeled 683 images and 2015 bounding boxes in total for now. We used 80% of the dataset which are 546 images for training and the rest of 20% which are 137 images for evaluation, and all images in the dataset have the same resolution at 1920*1080. Table.I summaries the statistics of the dataset, the category of floating leaves region has the most bounding box labels and the category of floating weeds region has the largest average size of bounding boxes.

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It is possible to construct "aerosol cytometers" based on different types of Zhulanov's laser  aerosol counters | diffusion aerosol spectrometers (DAS) [1-8] and "hydrosol cytometers" based on hydrosol particle counters (adopted for ocean marine, ocean and hydrothermal conditions [9,10]).

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232 Views

Emergency  managers  of  today  grapple  with  post-hurricane damage assessment that is often labor-intensive, slow,costly,   and   error-prone.   As   an   important   first   step   towards addressing  the   challenge,   this   paper   presents   the   development of  benchmark  datasets  to  enable  the  automatic  detection  ofdamaged buildings from post-hurricane remote sensing imagerytaken  from  both  airborne  and  satellite  sensors.  Our  work  has two  major  contributions:  (1)  we  propose  a  scalable  framework to  create  benchmark  datasets  of  hurricane-damaged  buildings

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Data can be used for object detection algorithms to properly annotate post disaster buildings as either damaged or non damaged aiding disaster response. This dataset contains ESRI Shapefiles of bounding boxes of buildings labeled as either non-damaged or damaged. Those labeled as damaged also have four degrees of damage from minor to catastrophic. Importantly, each bounding box is also indexed to one of the images in the NOAA post Harvey hurricane imagery dataset allowing users to match the bounding boxes with the correct imagery for training the algorithm.

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2077 Views

With the advent of Wireless Sensor Networks, the ability to predict nutrient-rich discharges, using on-node prediction models, offers huge potential for enabling real-time water reuse and management within an agriculturally-dominated catchment Existing discharge models use multiple parameters and large historical data which are difficult to extract and this, coupled with constraints on network nodes (battery life, computing power, sensor availability etc.) makes it necessary to develop low-dimensional models.

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The files found here are regularly-updated, complete copies of the OpenStreetMap.org database, and those published before the 12 September 2012 are distributed under a Creative Commons Attribution-ShareAlike 2.0 license, those published after are Open Data Commons Open Database License 1.0 licensed.

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