This paper utilizes modern statistical and machine learning methodology to track oscillation modes in complex power engineering systems. The damping ratio of the electromechanical oscillation mode is formulated as a function of power of the generators and loads as well as bus voltage magnitudes in the entire power system. The celebrated Lasso algorithm is implemented to solve this high-dimension modeling problem. By the nature of the $L_1$ design, the Lasso algorithm can automatically render a sparse solution, and by eliminating redundant features, it provides desirable prediction power.

  • Power and Energy
  • Last Updated On: 
    Wed, 09/04/2019 - 02:02

    The files in this dataset each contain vectors Time, PEDAL, SPEED, ACCEL, VOLTAGE and CURRENT related to an Electric Vehicle travelling on one of four different roads, mostly in urban areas.  Data is obtained from the CAN bus of the vehicle (a Zhidou ZD model ZD2) resampled in order to obtain a single time coordinate and stored in the dataset.

  • Transportation
  • Last Updated On: 
    Mon, 09/09/2019 - 09:12

    Indoor positioning systems based on radio frequency systems such as UWB inherently present multipath related phenomena. This causes ranging systems such as UWB}to lose accuracy by detecting secondary propagation paths between two devices. If a positioning algorithm uses ranging measurements without considering these phenomena, it will make important errors in estimating the position. This work analyzes the performance obtained in a localization system when combining location algorithms with machine learning techniques for a previous classification and mitigation of the propagation effects.

  • Sensors
  • Last Updated On: 
    Tue, 09/03/2019 - 17:02

    The Underwater Acoustic & Navigation Lab in University of Haifa conducted a shallow water long-range underwater acoustic communication experiment across the shores of Northern Israel in March 2019. The experiment was designed to verified the adaptive modulation scheme for long-range underwater acoustic communicaiton proposed by the authors. To make the work reproducible, the authors freely share the estimated channel impulse responses from the sea experiment.

  • Communications
  • Last Updated On: 
    Thu, 08/08/2019 - 00:20

    Database for FMCW THz radars (HR workspace) and sample code for federated learning 

  • Communications
  • Last Updated On: 
    Wed, 08/07/2019 - 07:53

    Data from measurements in Åre during the winter 2018-2019.

  • Weather
  • Last Updated On: 
    Sun, 07/14/2019 - 18:59

    This data is for training and validating the neural networks.

  • Sensors
  • Last Updated On: 
    Sun, 07/14/2019 - 09:19

    We proposed a new dataset, HazeRD, for benchmarking dehazing algorithms under realistic haze conditions. As opposed to prior datasets that made use of synthetically generated images or indoor images with unrealistic parameters for haze simulation, our outdoor dataset allows for more realistic simulation of haze with parameters that are physically realistic and justified by scattering theory. 

  • Standards Research Data
  • Last Updated On: 
    Tue, 06/11/2019 - 11:36

    This image is geometry of distributed radar netwrok for parameter estimation. In this distributed radar netwrok, three echo signals are computed by uisng VIRAF software and CAD model of cone-shaped warhead with micro-motion dynamics.

  • Digital signal processing
  • Last Updated On: 
    Tue, 04/16/2019 - 01:51