The data set deals with a typicla charge-discharge cycle of a supercapacitor (here a NICHICON UM series, 2.7V, 1F):

  • Very fast charge of the EDLC
  • Discharge at more or less constant power

Data have been sampled at 10 Hz with the biologic VMP3 potentiostat.

 

Categories:
12 Views

Parallel fractional hot-deck imputation (P-FHDI) is a general-purpose, assumption-free tool for handling item nonresponse in big incomplete data by combining the theory of FHDI and parallel computing. FHDI cures multivariate missing data by filling each missing unit with multiple observed values (thus, hot-deck) without resorting to distributional assumptions. P-FHDI can tackle big incomplete data with millions of instances (big-n) or 10, 000 variables (big-p).

Instructions: 

This repository includes three types of data: incomplete data with massive instances (big-n data), incomplete data with many variables (big-p data), incomplete data with tremendous instances and high dimensionality (ultra data). Overall, there exist six big-n datasets, four big-p datasets, and four ultra datasets. For instructions, see Readme files in the dataset folder for the step-by-step use of UP-FHDI with different types of incomplete datasets.

Categories:
75 Views

Database for a moderation of technological acceptance research

Categories:
29 Views

This is a dataset is an example of a distribution of 20 correlated Bernoulli random variables.

Instructions: 

Q_joint ... is 5 cells each consists of the joint distributions of 4,8,12,16,20 bits, respectively. The dimension of each cell is 2^n X 1, .e., a vertical column and n=4,8,12,16,20.

Q_conditional... is 5 cells each consists of the conditional distributions of 4 bits given 0, 4, 8,12,16 bits, respectively. In other words, 1:4 bits, 5:8 bits given 1:4 bits, 9:12 bits given 1:8 bits, 13:16 bits given 1:12 bits, 17:20 given 1:16 bits. The dimension of each cell is 2^4=16 X 2^n, i.e., a vertical column and n=4,8,12,16.

Q_ marginal... is 5 cells each consists of the marginal distributions of each 4 consecutive bits, i.e., 1:4 - 5:8 - 9:12 - 13:16 - 17:20, respectively.  The dimension of each cell is 16 X 1, i.e., q vertical column.

Also, a MATLAB code is uploaded to extract conditional and marginal distributions from any given discrete distribution.

Categories:
149 Views

This is the result found by multi-tree-search.</p>

Categories:
26 Views

Extensive experimental measurement campaigns of more than 30,000 data points of end-to-end latency measurements for the following network architecture schemes is available:

  • Unlicensed IoT (standalone LoRa)
  • Cellular IoT (standalone LTE-M)
  • Concatenated IoT (LoRa interfaced with LTE-M)

Download Data.zip to access all relevant files for the open data measurements.

Related Paper:

Categories:
1073 Views

The data are associated with a submitted journal paper.

Categories:
17 Views

The dataset was meteorological data (London Meteorological data) downloaded from http://www.urban-climate.net/content/data/9-data for 2016 consisting of 8784 data. This dataset had many features, but researchers only selected attributes related to wind speed prediction

Normal
0

false
false
false

EN-US
X-NONE
X-NONE

Categories:
75 Views

This dataset supports researchers in the validation process of solutions such as Intrusion Detection Systems (IDS) based on artificial intelligence and machine learning techniques for the detection and categorization of threats in Cyber Physical Systems (CPS). To that aim, data have been acquired from a water distribution hardware-in-the-loop testbed which emulates water passage between nine tanks via solenoid-valves, pumps, pressure and flow sensors. The testbed is composed by a real partition which is virtually connected to a simulated one.

Instructions: 

This dataset has related to the paper "A hardware-in-the-loop Water Distribution Testbed (WDT) dataset for cyber-physical security testing".
We provide four different acquisitions:
1) A normal acquisition without attacks ("normal.csv" for network traffic and "dataset_norm.csv" for physical measures)
2) Three acquisitions where different types of attacks and physical faults are reproduced ("attack_1.csv", "attack_2.csv" and "attack_3.csv" for network traffic and "dataset_att_1.csv", "dataset_att_2.csv" and "dataset_att_3.csv" for physical measures)
In addition to .csv files we provide four .pcap files ("attack_1.pcap", "attack_2.pcap", "attack_3.pcap" and "normal.pcap") which refer to network acquisitions for the four previous scenarios.
A README.xlsx file summarizes the key features of the entire dataset.

Categories:
161 Views

Pages