The "Dynamic Scenes" Dataset is provided for testing visual loop closure detection algorithms in highly dynamic scenes. It has a strong background in some crucial applications such as autonomous driving systems.

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429 Views

This dataset corresponds to a paper published in IEE Transactions on Power Systems entitled: "High-Speed 2x25kV Traction System Model and Solver for Extensive Network Simulations"

 

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568 Views

when iter time =50 ,we  can obtain this picture

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This data is the real-time Estimated time of departure in the airspace of China in Feb 10 2019.  

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67 Views

The present dataset is based on implementing of 3 approaches  with respect to the acquisition of driver data. The same one that we propose to use a sensor of concentration of alcohol in the environment (physiological), a sensor that measure the temperature of the defined points on driver’s face (biological) and another one that allows to identify and recognize the thickness of the pupil (visual characteristics).

 

Instructions: 

The present dataset is based on implementing 3 approaches with respect to the acquisition of driver data. The same one that we propose to use a sensor of the concentration of alcohol in the environment (physiological), a sensor that measures the temperature of the defined points on driver’s face (biological) and another one that allows to identify and recognize the thickness of the pupil (visual characteristics).

 

 Number of Instances: 390 (217 for no alcohol presence

                                          173 for alcohol presence with 

                                                   different concentration)

 

 Number of Attributes: 5 numeric, predictive attributes and the class

 

 Attribute Information:

   1. acohol concentration in the car environment in ml/L

   2. car environment temperature in degrees Celsius

   3. face temperature min in degrees Celsius

   4. face temperature max in degrees Celsius

   5. pupil ratio

   6. class: 

       1 No acohol presence

       2 acohol presence

 

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934 Views

This work quantifies water contamination in jet fuel (Jet A-1), using silica-based Bragg gratings. The optical sensor geometry exposes the evanescent optical field of a guided mode to enable refractometery. Quantitative analysis is made in addition to the observation of spectral features consistent with emulsification of water droplets and Stokes’ settling. Measurements are observed for cooling and heating cycles between ranges of 22oC and -60oC. The maximum spectral sensitivity for water contamination was 2.4 pm/ppm-v with a resolution of < 5 ppm-v.

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104 Views

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This work quantifies water contamination in jet fuel (Jet A-1), using silica-based Bragg gratings. The optical sensor geometry exposes the evanescent optical field of a guided mode to enable refractometery. Quantitative analysis is made in addition to the observation of spectral features consistent with emulsification of water droplets and Stokes’ settling. Measurements are observed for cooling and heating cycles between ranges of 22oC and -60oC. The maximum spectral sensitivity for water contamination was 2.4 pm/ppm-v with a resolution of < 5 ppm-v.

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29 Views

DECA is widely used as a protocol to describe the fuel economy and battery load of vehicles. Meanwhile, Carsim is universally accepted as a reliable tool to analyze vehicle dynamics. Therefore, it is of great importance to simulate the DECA with Carsim and provide a proper way to measure the virtual fuel economy of vehicles. It may also contribute to explement related experiments. 

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221 Views

An effective use of electrochemical Energy Storage Systems (ESSs) is mandatory for improving the performances of next generation electric vehicles and hybrid electric vehicles, as well as of smart grid and microgrid systems.In particular, Battery Management Systems (BMSs) are useful devices aiming at monitoring, managing, and controlling the battery pack. One of the main task of any BMS is performing State of Charge estimation of the cells composing the ESS.

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3140 Views

This dataset is a highly versatile and precisely annotated large-scale dataset of smartphone sensor data for multimodal locomotion and transportation analytics of mobile users.

The dataset comprises 7 months of measurements, collected from all sensors of 4 smartphones carried at typical body locations, including the images of a body-worn camera, while 3 participants used 8 different modes of transportation in the southeast of the United Kingdom, including in London.

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837 Views

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