This tool can be used to generate single or multiple occupancy and related occupancy-driven electrical demand and hot water demand profiles. The data output can be deployed in activities such as building performance simulation, stock modelling, district heating analysis, energy flexibility analysis and smart grid analysis. The input is information on the population of people being modelled. The programme is written in Python.
This paper is made up of a series of performance evaluations of computer vision algorithms, namely detectors and descriptors. The OpenCV 3.1 implementations of these algorithms were used for these evaluations. The main purpose behind these evaluations was to determine the best algorithms to use for a unmanned aerial vehicle (UAV) guidance system.
This dataset has the images and source code which were used to create the results from the paper. Be aware relative performance will have changed in different versions of OpenCV.
Paper published for 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV).
The script takes energy supply and demand time series data along with requirements for storage duration in order to calculate an appropriate storage capacity. The algorithm is technology agnostic and so can be used to for any type of energy system.
The dataset contains the source MATLAB version of the figures included in the paper, which is available through the link: https://doi.org/10.1016/j.jcde.2018.02.001. Moreover, the dataset contains two examples of boundary points detection (BPD). The examples show the use of the compiled version of the published BPD algorithm, which is described in the paper. The two examples show that all boundary points are correctly detected for the point clouds of a fan blade curved surface and the point cloud of half Stanford bunny. The prerequisites to run the compiled version of the BPD algorithm (boundaryPoints.exe) are: - 64-bit Windows operating system; - MATLAB Compiler Runtime (MCR) R2016a (9.0.1); It is possible to download the MCR installer for MATLAB R2016a from the MathWorks Web site, by navigating to: http://www.mathworks.com/products/compiler/mcr/index.html You will need administrator rights to run the MCR installer. For more information about the MCR and the MCR installer, see Distribution to End Users in the MATLAB Compiler documentation in the MathWorks Documentation Center.
Robots are increasingly present in industry. Achieving effective integration and the full potential of robotic systems presents significant challenges. Robots, sensors and end-effector tools are often not necessarily designed to be put together and form a system. This manual introduces a C++ language-based toolbox, designed to facilitate the integration of industrial robotic arms with server computers, sensors and actuators. The toolbox, named as Interfacing Toolbox for Robotic Arms (ITRA), contains fundamental functionalities for robust connectivity, real-time control in Cartesian and joint space and auxiliary functions to set or get key functional variables. It is designed to run on a remote computer connected with one or multiple robot controllers. All embedded functions can be used through high-level programming language platforms (e.g. MATLAB®, LabVIEW®), providing the opportunity to speed-up robust integration of robotic systems. Emerging applications aim to use robot arms in changing environments with movable obstacles or where the shape of the surroundings is changing. In such situations, the robots need to adapt their tasks/behaviors. ITRA contains functions designed to enable real-time adaptive robot behavior, maximizing the robot promptness and respecting constraints (maximum accelerations and velocities). The toolbox is compatible with all KUKA robotic arms, based on the fourth generation of KUKA controllers and equipped with the Robot Sensor Interface (RSI) software add-on. The current version of the DLL is available for Windows 32bit and 64bit platforms.
This programmes constructs and executes the Christoffel equation. The wave velocities for user selected directions of propagation are returned along with the polarization vectors.
Data embargo 01/11/2018
This dataset contains beam hardening correction macros, running on ImageJ software. It does not require any a priori knowledge of the material, distance from the source or the scan conditions (current, energy), nor any segmentation of phases or calibration scan on phantom data. It is suitable for expert and non-expert use alike.
Workflow is included in "Step by step procedure" file.
Two versions of the code are provided. Please use the “BeamHardening_Correction_plugin_NOaverage_profile” ijm file, if there is a gradient in average gray values from top to bottom of your sample.
- ImageJ/FIJI. Download available at https://imagej.net/Fiji/Downloads
- Radial Profile Extended plug-in (Carl P., 2006). Download available at https://imagej.nih.gov/ij/plugins/radial-profile-ext.html
If you intend to use this code or create derivative works, please give proper attribution to this work and authors by citing the DOI provided.
For more info and questions, please contact the creator Carla Romano via the contact address provided on this page.
SYSSTAT software (http://sebastien.godard.pagesperso-orange.fr/) version 11.6.0 binaries to run on Arm Cortex-A9 and Cortex-A53 processors on Avnet ZedBoard and Xilinx ZCU102 respectively. This dataset was created by cross-compiling the SYSSTAT software, created by Sebastien Godard, to execute on the ZedBoard and ZCU102. The SYSSTAT software is a set of utilities for performance monitoring made available under the GNU General Public License version 2, a copy of which is included. For further details see README file.
DCMTK (https://dicom.offis.de/dcmtk.php.en) version 3.6.1_20160630 libraries and binaries compiled to run on the Arm Cortex-A9 and Cortex-A53 processors on the Avnet ZedBoard and Xilinx ZCU102 development boards respectively. This dataset was generated by cross-compiling the DCMTK software, created by Offis e.V., to execute on the ZedBoard and ZCU102. The DCMTK software implements large parts of the DICOM standard. Further details on the data contained here, including copyright notice, can be found in the README file.