Computational Intelligence

Network traffic analysis, i.e. the umbrella of procedures for distilling information from network traffic, represents the enabler for highly-valuable profiling information, other than being the workhorse for several key network management tasks. While it is currently being revolutionized in its nature by the rising share of traffic generated by mobile and hand-held devices, existing design solutions are mainly evaluated on private traffic traces, and only a few public datasets are available, thus clearly limiting repeatability and further advances on the topic.

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  • Communications
  • Last Updated On: 
    Mon, 10/07/2019 - 10:02

    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.

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

    Even though intelligent systems such as Siri or Google Assistant are enjoyable (and useful) dialog partners, users can only access predefined functionality. Enabling end-users to extend the functionality of intelligent systems will be the next big thing. To promote research in this area we carried out an empirical study on how laypersons teach robots new functions by means of natural language instructions. The result is a labeled corpus consisting of 3168 submissions given by 870 subjects.

    81 views
  • Computational Intelligence
  • Last Updated On: 
    Tue, 10/15/2019 - 11:29

    This pre-trained Word2Vec model has 300-dimensional vectors for more than 0.5 million Nepali words and phrases. A separate Nepali language text corpus was created using the news contents freely available in the public domain. The text corpus contained more than 100 million running words.

    Word2Vec model details: Embeddings Dimension: 300, Architecture: Continuous - BOW, Training algorithm: Negative sampling = 15, Context (window) size: 10, Token minimum count: 2, Encoded in UTF-8.

    810 views
  • Computational Intelligence
  • Last Updated On: 
    Fri, 10/25/2019 - 04:49

    This data set comprises 4223 videos from a laser surface heat treatment process (also called laser heat treatment) applied to cylindrical workpieces made of steel. The purpose of the dataset is to detect anomalies in the laser heat treatment learning a model from a set of non-anomalous videos.In the laser heat treatment, the laser beam is following a pattern similar to an "eight" with a frequency of 100 Hz. This pattern is sometimes modified to avoid obstacles in the workpieces.The videos are recorded at a frequency of 1000 frames per second with a thermal camera.

    211 views
  • Image Processing
  • Last Updated On: 
    Wed, 09/11/2019 - 06:29

    This is the dataset for the manuscript entitled "Physics-prior Bayesian neural networks in semiconductor processing", IEEE Access

    124 views
  • Computational Intelligence
  • Last Updated On: 
    Thu, 09/05/2019 - 12:15

    This contains data for ISFET based pH sensor drift compensation using machine learning techniques

    132 views
  • Sensors
  • Last Updated On: 
    Wed, 08/21/2019 - 08:49

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

    393 views
  • Communications
  • Last Updated On: 
    Mon, 09/23/2019 - 12:13

    Reinforcement Learning (RL) agents can learn to control a nonlinear system without using a model of the system. However, having a model brings benefits, mainly in terms of a reduced number of unsuccessful trials before achieving acceptable control performance. Several modelling approaches have been used in the RL domain, such as neural networks, local linear regression, or Gaussian processes. In this article, we focus on a technique that has not been used much so far:\ symbolic regression, based on genetic programming.

    108 views
  • Computational Intelligence
  • Last Updated On: 
    Fri, 07/26/2019 - 03:46

    Real life business processes change over time, in both planned and unexpected ways. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. The following logs were generated synthetically in order to prove the quality of different concept drift detection algorithms.

    82 views
  • Computational Intelligence
  • Last Updated On: 
    Tue, 07/09/2019 - 14:07

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