The Experts below are selected from a list of 270 Experts worldwide ranked by ideXlab platform
Rasoulzadeh, Mendeley A Data) - One of the best experts on this subject based on the ideXlab platform.
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Variational Path Optimization of Linear Pentapods with a Simple Singularity Variety
2020Co-Authors: Rasoulzadeh, Mendeley A Data)Abstract:This file is part of joint work between A. Rasoulzadeh and G. Nawratil at Center for Geometry and Computational Design (GCD), Vienna University of Technology (TU Wien). It is created on October 10th, 2019. ABSTRACT: The class of linear pentapods with a simple singularity variety is obtained by imposing architectural restrictions on the design of a linear pentapod in a way that the manipulator's singularity variety is linear in orientation/position variables. It turns out that such a simplification leads to crucial computational advantages while maintaining the machine's applications in some fundamental industrial tasks such as 5-axis milling and laser cutting. Assuming that a singularity-free path between a given start- and end-pose of the end-effector within the manipulator's workspace is known, an optimization process of this path is proposed in such a way that the robot increases its distance to the singularity loci while the motion is being smoothed. In this case the computation time of the optimization is improved as one deals with the pentapods having a simple singularity variety allowing symbolic solutions for the local extrema of the singularity-distance function. The whole process is called variational path optimization and takes place through defining a novel cost function. This optimization process takes the physical limits of prismatic joints and base spherical joints into account. HOW TO USE: In order to use the algorithm please type "variational_path_optimization" in the MATLAB "Command Window". The code then asks the user a range of questions from "architectural aspects of your manipulator" to plot options. For most of these questions the user can simply ignore (if he/she does not wish a very specific optimization or plot) by pressing enter. However some of these questions are obligatory to answer. Therefore we ask the user to type "help variational_path_optimization" in in the MATLAB "Command Window" for a thorough description of his/her available options. Please note that a DEFAULT SETTING is made available for the code by which the user can observe how the algorithm works on a predefined simple pentapod and a predefined singularity-free initial motion (as a sample we recommend using the special curve "twisted"). Finally, if the user has access to MAPLE, then he/she can visualize the full results alongside the shape of the manipulator. In order to do so please run "variational_path_optimization" on a case, then execute the files "pentapod.mw" and "plot.mw" respectively. WARNING: Note that the rest of the MATLAB functions in the folder are just nested functions in the file "variational_path_optimization.m". The help option is also available for all these nested functions which demonstrates their specific role within the main code. The MATLAB files will be subject to minor updates including the addition of a GUI (graphical user interface)
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Variational Path Optimization of Linear Pentapods with a Simple Singularity Variety
2020Co-Authors: Rasoulzadeh, Mendeley A Data)Abstract:This file is part of joint work between A. Rasoulzadeh and G. Nawratil at Center for Geometry and Computational Design (GCD), Vienna University of Technology (TU Wien). It is created on October 10th, 2019. ABSTRACT: The class of linear pentapods with a simple singularity variety is obtained by imposing architectural restrictions on the design of a linear pentapod in a way that the manipulator's singularity variety is linear in orientation/position variables. It turns out that such a simplification leads to crucial computational advantages while maintaining the machine's applications in some fundamental industrial tasks such as 5-axis milling and laser cutting. Assuming that a singularity-free path between a given start- and end-pose of the end-effector within the manipulator's workspace is known, an optimization process of this path is proposed in such a way that the robot increases its distance to the singularity loci while the motion is being smoothed. In this case the computation time of the optimization is improved as one deals with the pentapods having a simple singularity variety allowing symbolic solutions for the local extrema of the singularity-distance function. The whole process is called variational path optimization and takes place through defining a novel cost function. This optimization process takes the physical limits of prismatic joints and base spherical joints into account. HOW TO USE: In order to use the algorithm please type "variational_path_optimization" in the MATLAB "Command Window". The code then asks the user a range of questions from "architectural aspects of your manipulator" to plot options. For most of these questions the user can simply ignore (if he/she does not wish a very specific optimization or plot) by pressing enter. However some of these questions are obligatory to answer. Therefore we ask the user to type "help variational_path_optimization" in in the MATLAB "Command Window" for a thorough description of his/her available options. Please note that a DEFAULT SETTING is made available for the code by which the user can observe how the algorithm works on a predefined simple pentapod and a predefined singularity-free initial motion (as a sample we recommend using the special curve "twisted"). Finally, if the user has access to MAPLE, then he/she can visualize the full results alongside the shape of the manipulator. In order to do so please run "variational_path_optimization.m" on a case, then execute the files "pentapod.mw" and "plot.mw" consecutively. NOTE: 9 videos (GIF files) of motions of a sample is provided for you in the folder "Sample Videos". WARNING: Note that the rest of the MATLAB functions in the folder are just nested functions in the file "variational_path_optimization.m". The help option is also available for all these nested functions which demonstrates their specific role within the main code. The MATLAB files will be subject to minor updates including a GU
Vidya Singh - One of the best experts on this subject based on the ideXlab platform.
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Dynamic Performance of UASB Reactor Treating MunicipalWastewater
2016Co-Authors: Vidya SinghAbstract:The simultaneous dynamic equations for substrate and biomass mass were used to assess the UASB reactor performance of municipal wastewater. The dynamic model equations were solved by using a m.file in MATLAB2011a Command Window and dynamic equations for substrate and biomass. The objectives of this paper are (1) To develop a simple CSTR model for simulation of UASB reactors performance assuming the flow regime in UASB reactor as CSTR (2) To evaluate the dynamic performances of UASB reactor treating municipal wastewater using the experimental results of Alveraz et al. 2008.
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Evaluation of Dynamic Performance in Terms of Effluent COD and Biomass Concentrations of UASB Reactor Treating Low Strength Wastewater
2016Co-Authors: Vidya Singh, N. D. Pandey, R. P. SinghAbstract:The present paper devoted to explore the suitability of using a simple CSTR model for evaluating the dynamic performance of UASB reactor treating low strength wastewater. Depending upon the idealization of UASB reactor as a single CSTR, the dynamic state model equations available in the literature. The simultaneous dynamic equations for substrate and biomass mass were used to assess the UASB reactor performance of low strength wastewater. The dynamic model equations were solved by using a m.file in MATLAB2011a Command Window and dynamic equations for substrate and biomass. The objectives of this paper are to evaluate the dynamic performances of UASB reactor treating low strength wastewater using the experimental results of Singh and Viraraghavan 1998 research.
Kevin Crow - One of the best experts on this subject based on the ideXlab platform.
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Stata tip 75: Setting up Stata for a presentation
The Stata Journal: Promoting communications on statistics and Stata, 2009Co-Authors: Kevin CrowAbstract:If you plan to use Stata in a presentation, you might consider changing a few settings so that Stata is easy for your audience to view. How you set up Stata for presenting will depend on several factors like the size and layout of the room, the length of the Stata Commands you will issue, the datasets you will use, the resolution of the projector, etc. Changing the settings and saving those settings as a custom preference before you present can save you time and frustration. Also having a custom layout preference allows you to restore your setup should something happen in the middle of your presentation. How you manipulate Stata’s settings is platform dependent. This article assumes you are using Windows. If you use Stata for Macintosh or Unix, the advice is the same but the manipulations are slightly different. First, make Stata’s Windows fill the screen. The maximize button is in the top right-hand corner of Stata (the maximize button is in the same place for all Windows in Stata). After maximizing Stata, you will also want to maximize the Results Window. Once Stata is maximized, you will probably want to move the Command Window. For most room layouts, you will want the Command Window at the top of Stata so that your audience can see the Commands you are typing. You achieve this by changing your Windowing preferences to allow docking. In Stata, select Edit > Preferences > General Preferences..., and then select the Windowing tab in the dialog box that appears. Make sure that the check box for Enable ability to dock, undock, or tab Windows is checked, and then click on the OK button. Next double-click on the blue title bar of the Command Window and drag the Window to the top docking button. Once the Command Window is docked on top, it is a good idea to go back to the General Preferences dialog box and uncheck the box you changed. Doing this will ensure that your Command Window stays at the top of Stata and does not accidentally undock. Depending on the projector resolution, you will probably want to change the font, font style, and font size of the Command Window. To change the font settings of a Window in Stata, right-click within the Window and select Font.... The font you choose is up to you, but we recommend Courier New as a serif font or Lucida Console as a sans serif font. You will also want to change the font size (14 is a good starting size) and change the font style to bold. Finally, we recommend that you resize the Command Window so that you can see two lines (with the font and font size changed, you might find that long Stata Commands do not fit on one line).
Qingqing Liu - One of the best experts on this subject based on the ideXlab platform.
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LIANXH: Stata module to Search and share Stata resources and blogs within Stata Command Window
Statistical Software Components, 2020Co-Authors: Lian Yu-jun, Junjie Kang, Qingqing LiuAbstract:lianxh make it easy for users to search blog posts and useful links from within Stata Command Window. You can also list common Stata resource links, including Stata official website, Stata FAQs, Statalist, Stata Journal, Stata online tutorial, replication data & programs etc.
Philipp S. Sommer - One of the best experts on this subject based on the ideXlab platform.
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Chilipp/psyplot-conda: v1.0.1: Conda installers for psyplot - The interactive visualization framework
2017Co-Authors: Philipp S. SommerAbstract:psyplot-conda provides standalone installers for the psyplot interactive visualization framework. psyplot is an open source python project that mainly combines the plotting utilities of matplotlib (Hunter, 2007) and the data management of the xarray package (Hoyer & Hamman, 2017). The main purpose is to have a framework that allows a fast, attractive, flexible, easily applicable, easily reproducible and especially an interactive visualization of your data. The ultimate goal is to help scientists and especially climate model developers in their daily work by providing a flexible visualization tool that can be enhanced by their own visualization scripts. psyplot can be used through the python Command line and through the psyplot-gui module which provides a graphical user interface for an easier interactive usage. These installers contains all necessary dependencies for psyplot, psyplot-gui, psy-simple, psy-maps and psy-reg plus the conda package for managing virtual environments. The installers have been created using using the conda constructor package and the packages from the conda-forge channel. Other ways to install psyplot can be found in the psyplot docs: http://psyplot.readthedocs.io Source files These files contain the source python code for the psyplot-conda repository (tag v1.0.1) and it's submodules psyplot (tag v1.0.0), psy-simple (tag v1.0.0), psy-maps (tag v1.0.0), psy-reg (tag v1.0.0) and psyplot-gui (tag v1.0.1). psyplot-conda-1.0.1.zip: The zipped source files including reference figures for psy-simple and psy-maps psyplot-conda-1.0.1-no-refs.zip: The zipped source files without reference figures Documentation files These files contain the documentation for psyplot, psy-maps, psy-reg, psy-simple and psyplot-gui from http://psyplot.readthedocs.io/en/latest/, downloaded on August, 21st, 2017. docs-epub.zip: Documentation files in epub format docs-pdf.zip: Documentation files in pdf format docs-html.zip: Documentation files in html format Standalone installers These installers have been created using the conda constructor package and can be used to install psyplot, psy-simple, psy-maps, psy-reg and psyplot-gui. Installation instructions can be found in the Additional Notes. psyplot-conda-1.0.1-Linux-x86-64.sh: Bash installer for 64-bit Linux systems psyplot-conda-1.0.1-MacOSX-x86-64.sh: Bash installer for 64-bit Mac OS X systems psyplot-conda-1.0.1-MacOSX-x86-64.pkg: Package installer for 64-bit Mac OS X systems psyplot-conda-1.0.1-Windows-x86-64.exe: Windows installer for 64-bit systems psyplot-conda-1.0.1-Windows-x86.exe: Windows installer for 32-bit systems psyplot-conda-1.0.1-Windows-no-shortcut-x86-64.exe: Windows installer for 64-bit systems without menu shortcut psyplot-conda-1.0.1-Windows-no-shortcut-x86.exe: Windows installer for 32-bit systems without menu shortcut Packages These files contain packages for psyplot (1.0.0.post1), psy-simple (1.0.0), psy-maps (1.0.0), psy-reg (1.0.0) and psyplot-gui (1.0.1). python-packages.zip: Python packages from pipy.org conda-packages.zip: Conda packages from https://anaconda.org/conda-forge Installation instructions for standalone installers Installation on Linux Download the bash script and open a terminal Window. Type: bash '' and simply follow the instructions. For more information on the Command line options type: bash '' --help It will ask you, whether you want to add a psyplot alias to your .bashrc, such that you can easily start the terminal and type psyplot to start the GUI. You can avoid this by setting NO_PSYPLOT_ALIAS=1. Hence, to install psyplot-conda without any terminal interaction, run: NO_PSYPLOT_ALIAS=1 bash '' -b -p Uninstallation on Linux Just delete the folder where you installed psyplot-conda. By default, this is $HOME/psyplot-conda, so just type: rm -rf $HOME/psyplot-conda If you added a psyplot alias to your .bashrc or chose to add the bin directory to your PATH variable during the installation, open your $HOME/.bashrc in an editor of your choice and delete those parts. Installation on OS X You can either install it from the terminal using a bash-script (.sh file), or you can install a standalone app using an installer (.pkg file). The bash script will install a conda installation in your desired location. Both will create a Psyplot.app (see below). Installation using the OS X package This should be straight-forward, however Apple does not provide free Developer IDs for open-source developers. Therefore our installers are not signed and you have to give the permissions to open the files manually. The 4 steps below describe the process. Just download the .pkg file To open it, you have to Right-click on the file, then Open With, then Installer. In the appearing Window, click the Open button. Follow the instructions. It will create a Psyplot.app in the specified location. To open the app the first time, change to the chosen installation directory for the App (by default $HOME/Applications), right-click the Psyplot app and click on Open. In the appearing Window, again click on Open. Installation using the bash script Download the bash script (file ending on '.sh' for MacOSX) and open a terminal Window. Type: bash '' and simply follow the instructions. For more informations on the Command line options type: bash '' --help By default, the installer asks whether you want to install a Psyplot.app into your Applications directory. You can avoid this be setting NO_PSYPLOT_APP=1. Furthermore it will ask you, whether you want to add a psyplot alias to your .bash_profile, such that you can easily start the terminal and type psyplot to start the GUI. You can avoid this by setting NO_PSYPLOT_ALIAS=1. Hence, to install psyplot-conda without any terminal interaction, run: NO_PSYPLOT_APP=1 NO_PSYPLOT_ALIAS=1 bash '' -b -p Uninstallation on OSX The uninstallation depends on whether you have used the package installer or the bash script for the installation. Uninstall the App installed through the OS X package Just delete the app from your Applications folder. There have been no changes made to your PATH variable. Uninstall the App installed via bash script As for linux, just delete the folder where you installed psyplot-conda. By default, this is $HOME/psyplot-conda. Open a terminal and just type: rm -rf $HOME/psyplot-conda If you added a psyplot alias to your .bash_profile or chose to add the bin directory to your PATH variable during the installation, open your $HOME/.bash_profile in an editor of your choice and delete those parts. If you chose to add a Psyplot app, just delete the symbolic link in /Applications or $HOME/Applications. Installation on Windows Just download the installer for 64-bit or 32-bit, double click the downloaded file and follow the instructions. The installation will create an item in the Windows menu (Start -> Programs -> Psyplot) which you can use to open the GUI. You can, however, also download installers that create no shortcut from below. In any case, if you chose to modify your PATH variable during the installation, you can open a Command Window (cmd) and type psyplot. Uninstallation on Windows Just double-click the Uninstall-Anaconda.exe file in the directory where you installed psyplot-conda and follow the instructions. This will also revert the changes in your PATH variable. Acknowledgements The author thanks the Swiss National Science Foundation (SNF) for their support. Funding for the author came from the ACACIA grant (CR10I2_146314) and the HORNET grant (200021_169598)