This study seeks to obtain data which will help to address machine learning based malware research gaps. The specific objective of this study is to build a benchmark dataset for Windows operating system API calls of various malware. This is the first study to undertake metamorphic malware to build sequential API calls. It is hoped that this research will contribute to a deeper understanding of how metamorphic malware change their behavior (i.e. API calls) by adding meaningless opcodes with their own dissembler/assembler parts.

  • Security
  • Last Updated On: 
    Tue, 07/30/2019 - 11:07

    Monitoring cell viability and proliferation in real-time provides a more comprehensive picture of the changes cells undergo during their lifecycle than can be achieved using traditional end-point assays. Our lab has developed a CMOS biosensor that monitors cell viability through high-resolution capacitance measurements of cell adhesion quality. The system consists of a 3 × 3 mm2 chip with an array of 16 sensors, on-chip digitization, and serial data output that can be interfaced with inexpensive off-the-shelf components.

  • Image Processing
  • Last Updated On: 
    Mon, 07/22/2019 - 10:20

    This dataset uses a newly introduced method for the analysis of the effects on WCET of the tools used in real-time systems. It is the result of a full factorial experiment comparing SCADE code generation tools (SCADE 5 and 6), compilers (Wind River, GCC, Code Warrior), optimization settings, and WCET analysis tools (high water mark measurement, Rapita RVS, Otawa, AbsInt aiT). SCADE generated software is targeted due to its prevalence in hard real-time systems and the ease with which it can be randomly varied.

  • Other
  • Last Updated On: 
    Wed, 07/24/2019 - 14:30

    Data set contains logs from OptiTrack motion camera system and flex sensor information from a smart glove. Participants performed finger taps for 10 secs.

  • Remote Sensing
  • Last Updated On: 
    Mon, 07/15/2019 - 16:47

    These datasets are of the hydraulically actuated robot HyQ’s proprioceptive sensors. They include absolute and relative encoders, force and torque sensors, and MEMS-based and fibre optic-based inertial measurement units (IMUs). Additionally, a motion capture system recorded the ground truth data with millimetre accuracy. In the datasets HyQ was manually controlled to trot in place or move around the laboratory. The sequence includes: forward and backwards motion, side-to-side motion, zig-zags, yaw motion, and a mix of linear and yaw motion.

  • Sensors
  • Last Updated On: 
    Tue, 07/30/2019 - 03:27

    The rawdata.csv profile indicates the traffic analysis based mobility patterns. we extract human trips from Call Records Detail data. Combining traffic analysis zone dataset, we map each trip record to the zones with the same origin zones and destination zones. After  this, we can obtain this dataset. This dataset stores the hourly number of departure and arrival trips in each traffic analysis zone.

    The POI-importance.csv profile indicates the term frequency-inverse doument frequency(TF-IDF) of each category of poi the in each traffic analysis zone.

  • Transportation
  • Last Updated On: 
    Thu, 06/06/2019 - 03:05





  • Communications
  • Last Updated On: 
    Wed, 06/05/2019 - 22:25

    We introduce a benchmark of distributed algorithms execution over big data. The datasets are composed of metrics about the computational impact (resource usage) of eleven well-known machine learning techniques on a real computational cluster regarding system resource agnostic indicators: CPU consumption, memory usage, operating system processes load, net traffic, and I/O operations. The metrics were collected every five seconds for each algorithm on five different data volume scales, totaling 275 distinct datasets.

  • Standards Research Data
  • Last Updated On: 
    Thu, 06/06/2019 - 13:58

    Video dataset of 102 participants for the paper "Learning deep representations for video-based intake gesture detection"

  • Health
  • Last Updated On: 
    Thu, 05/16/2019 - 04:41

    Archival bundle of District Information System for Education (DISE) Delhi primary to upper-primary level schools in academic session 2012-2013. DISE is a school-level dataset consisting of government-recognized schools. It is a joint initiative of the Government of India, UNICEF and the National University of Education and Planning (NUPEA).

  • Education
  • Last Updated On: 
    Sat, 04/06/2019 - 01:33