Energy

Dataset consists of various open GIS data from the Netherlands as Population Cores, Neighbhourhoods, Land Use, Neighbourhoods, Energy Atlas, OpenStreetMaps, openchargemap and charging stations. The data was transformed for buffers with 350m around each charging stations. The response variable is binary popularity of a charging pool.

135 views
  • Machine Learning
  • Last Updated On: 
    Thu, 10/31/2019 - 07:05

    Attempts to prevent invasion of marine biofouling on marine vessels are demanding. By developing a system to detect marine fouling on vessels in an early stage of fouling is a viable solution. However, there is a  lack of database for fouling images for performing image processing and machine learning algorithm.

    145 views
  • Artificial Intelligence
  • Last Updated On: 
    Wed, 10/30/2019 - 10:06

    This is a reservoir dataset including a large number of figures. Reservoir simulation, an important part of the petroleum industry, a powerful tool helping oil companies understand the reservoir better.

    In this dataset, there more than 10,000 figures are showing in different period oilfield development. From the beginning to the end, we keep some variables constant while some changes to make clear the influences of different parts.

  • Machine Learning
  • Energy
  • Last Updated On: 
    Wed, 10/30/2019 - 03:16

    This study was conducted in Mayaguez – Puerto Rico, and an area of around 18 Km2 was covered, which were determined using the following classification of places:

    ·         Main Avenues: Wide public ways that has hospitals, vegetation, buildings, on either side

    ·         Open Places: Mall parking lots and public plazas

    ·         Streets & Roads: Dense residential and commercial areas on both sides

         Vendor             Equipment                  Description      

    KEYSIGHT®      N9343C                    Handheld Spectrum Analyzer

    259 views
  • IoT
  • Last Updated On: 
    Sun, 10/27/2019 - 21:54

    This folder contains two csv files and one .py file. One csv file contains NIST ground PV plant data imported from https://pvdata.nist.gov/. This csv file has 902 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST ground PV plant data.

    756 views
  • Machine Learning
  • Last Updated On: 
    Fri, 12/27/2019 - 12:52

    The paper is aimed at an investigation of the features of a tubular-linear synchronous quasi-Halbach machine (T-LSM) where the radially-magnetized PMs are substituted by four equal segments with parallel magnetization. Such a substitution is done in an attempt to improve the machine cost-effectiveness which makes it a viable candidate to equip free-piston engine-based series

    16 views
  • Energy
  • Last Updated On: 
    Fri, 10/04/2019 - 04:02

    A synthetic dataset supporting a submission.

    25 views
  • Energy
  • Last Updated On: 
    Sat, 09/28/2019 - 22:36

    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.

    281 views
  • Energy
  • Last Updated On: 
    Wed, 10/30/2019 - 09:48

    The standard for measurement of solar irradiance utilizes the units of watts per meter squared (W/m2).  Irradiance meters are both costly and limited in the ability to measure low irradiance values.  With a lower cost and higher sensitivity in low light conditions, light meters measure illuminance utilizing the unit of Lux.  A conversion factor would enable the use of light meters to evaluate PV performance under low solar irradiance conditions.  This conversion is a supplement to Luminous Efficacy that compares atmospheric light in units of lumens to solar irradiance in un

    2122 views
  • Energy
  • Last Updated On: 
    Fri, 09/20/2019 - 14:45

    A computational efficient battery pack model with thermal consideration is essential for simulation before real-time embedded implementation. The proposed temperature-dependent battery model (LiFePO4 battery cell, ANR26650M1-B from A123 Systems) will increase the lifespan of the battery. The simulation outputs are validated by a set of independent experimental data at a different ambient temperature using the dataset collected at 5 °C, 15 °C, 25 °C, 35 °C and 45 °C.

    204 views
  • Energy
  • Last Updated On: 
    Wed, 10/30/2019 - 09:50

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