scholarly journals GUIDA: A Graphical User Interface for Optical Data Analysis of Isolated Pulsars

2015 ◽  
Vol 127 (955) ◽  
pp. 931-939 ◽  
Author(s):  
F. Ambrosino
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Optical Data

EosFit7-GUI: a new graphical user interface for equation of state calculations, analyses and teaching

2016 ◽  
Vol 49 (4) ◽  
pp. 1377-1382 ◽  
Author(s):  
Javier Gonzalez-Platas ◽  
Matteo Alvaro ◽  
Fabrizio Nestola ◽  
Ross Angel
Keyword(s):  
Thermal Expansion ◽  
Data Analysis ◽  
User Interface ◽  
Equation Of State ◽  
Least Squares ◽  
Graphical User Interface ◽  
Diffraction Data ◽  
Equations Of State ◽  
Least Squares Fitting ◽  
Parametric Data

EosFit7-GUIis a full graphical user interface designed to simplify the analysis of thermal expansion and equations of state (EoSs). The software allows users to easily perform least-squares fitting of EoS parameters to diffraction data collected as a function of varying pressure, temperature or both. It has been especially designed to allow rapid graphical evaluation of both parametric data and the EoS fitted to the data, making it useful both for data analysis and for teaching.

scholarly journals Development of a Software Package for Cattle Identification in Nigeria

2019 ◽  
Vol 23 (10) ◽  
pp. 1825-1828 ◽  
Author(s):  
R.W. Bello ◽  
S. Abubakar
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Software Package ◽  
Smart Phone ◽  
Information Encoding ◽  
Software Application ◽  
Free Range ◽  
Encoding Method ◽  
Tools And Methods

Open grazing or free-range grazing is one of the methods employed by the Nigeria nomadic cattle herders to provide pasture for their cattle. This method of providing pasture for cattle comes with so many challenges among which are cow swapping, ownership disputes, rustling and cow intrusion to farmland. Some existing methods of guiding against these challenges are expensive, injurious, and unreliable to apply. The objective of this paper is to develop an enhanced and affordable software package for cow recognition and identification using a graphical user interface and information encoding method. Data analysis module with software application for the analysis of the generated code is proposed; the software application installed on a computer or smart-phone may be standalone or otherwise. Data about individual cow is digitally collected, coded and stored using necessary resources, tools, and methods. Moreover, by tagging individual cow with the generated code, and matching the code with the ones in the database using code reader, individual cow can be recognized and identified.Keywords: Open grazing; Free-range grazing; Nomadic herder; Cow identification; Pasture.

Computer Microvision for MEMS

1999 ◽  
Vol 605 ◽  
Author(s):  
Dennis M. Freeman
Keyword(s):  
Image Analysis ◽  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
3D Structure ◽  
Ccd Camera ◽  
Optical Microscope ◽  
Stroboscopic Illumination ◽  
Frame Grabber

AbstractWe have developed a versatile instrument for in situ measurement of motions of MEMS. Images of MEMS are magnified with an optical microscope and projected onto a CCD camera. Stroboscopic illumination is used to obtain stop-action images of the moving structures. Stopaction images from multiple focal planes provide information about 3D structure and 3D motion. Image analysis algorithms determine motions of all visible structures with nanometer accuracy.Hardware for the system includes the microscope, CCD camera and associated frame grabber, piezoelectric focusing element, and a modular stimulator that generates arbitrary periodic waveforms and synchronized stroboscopic illumination. These elements are controlled from a Pentium-based computer using a graphical user interface that guides the user through both data collection and data analysis. The system can measure motions at frequencies as high as 5 MHz with nanometer resolution, i.e., well below the wavelength of light.

scholarly journals Cyrface: An interface from Cytoscape to R that provides a user interface to R packages

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 192 ◽  
Author(s):  
Emanuel Gonçalves ◽  
Julio Saez-Rodriguez
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Network Visualization ◽  
R Language ◽  
Software Packages ◽  
Graphical Interfaces ◽  
Basic Understanding ◽  
R Packages

There is an increasing number of software packages to analyse biological experimental data in the R environment. In particular, Bioconductor, a repository of curated R packages, is one of the most comprehensive resources for bioinformatics and biostatistics. The use of these packages is increasing, but it requires a basic understanding of the R language, as well as the syntax of the specific package used. The availability of user graphical interfaces for these packages would decrease the learning curve and broaden their application.   Here, we present a Cytoscape plug-in termed Cyrface that allows Cytoscape plug-ins to connect to any function and package developed in R. Cyrface can be used to run R packages from within the Cytoscape environment making use of a graphical user interface. Moreover, it links the R packages with the capabilities of Cytoscape and its plug-ins, in particular network visualization and analysis. Cyrface’s utility has been demonstrated for two Bioconductor packages (CellNOptR and DrugVsDisease), and here we further illustrate its usage by implementing a workflow of data analysis and visualization. Download links, installation instructions and user guides can be accessed from the Cyrface homepage (http://www.ebi.ac.uk/saezrodriguez/cyrface/).

scholarly journals fuelcell: A Python package and graphical user interface for electrochemical data analysis

2021 ◽  
Vol 6 (59) ◽  
pp. 2940
Author(s):  
Samay Garg ◽  
Julie Fornaciari ◽  
Adam Weber ◽  
Nemanja Danilovic
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Python Package

scholarly journals CIPR: a web-based R/shiny app and R package to annotate cell clusters in single cell RNA sequencing experiments

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
H. Atakan Ekiz ◽  
Christopher J. Conley ◽  
W. Zac Stephens ◽  
Ryan M. O’Connell
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Single Cell ◽  
Graphical User Interface ◽  
R Package ◽  
Web Based ◽  
Cell Clusters ◽  
Shiny App ◽  
Single Cell Rna Sequencing ◽  
R Shiny

Abstract Background Single cell RNA sequencing (scRNAseq) has provided invaluable insights into cellular heterogeneity and functional states in health and disease. During the analysis of scRNAseq data, annotating the biological identity of cell clusters is an important step before downstream analyses and it remains technically challenging. The current solutions for annotating single cell clusters generally lack a graphical user interface, can be computationally intensive or have a limited scope. On the other hand, manually annotating single cell clusters by examining the expression of marker genes can be subjective and labor-intensive. To improve the quality and efficiency of annotating cell clusters in scRNAseq data, we present a web-based R/Shiny app and R package, Cluster Identity PRedictor (CIPR), which provides a graphical user interface to quickly score gene expression profiles of unknown cell clusters against mouse or human references, or a custom dataset provided by the user. CIPR can be easily integrated into the current pipelines to facilitate scRNAseq data analysis. Results CIPR employs multiple approaches for calculating the identity score at the cluster level and can accept inputs generated by popular scRNAseq analysis software. CIPR provides 2 mouse and 5 human reference datasets, and its pipeline allows inter-species comparisons and the ability to upload a custom reference dataset for specialized studies. The option to filter out lowly variable genes and to exclude irrelevant reference cell subsets from the analysis can improve the discriminatory power of CIPR suggesting that it can be tailored to different experimental contexts. Benchmarking CIPR against existing functionally similar software revealed that our algorithm is less computationally demanding, it performs significantly faster and provides accurate predictions for multiple cell clusters in a scRNAseq experiment involving tumor-infiltrating immune cells. Conclusions CIPR facilitates scRNAseq data analysis by annotating unknown cell clusters in an objective and efficient manner. Platform independence owing to Shiny framework and the requirement for a minimal programming experience allows this software to be used by researchers from different backgrounds. CIPR can accurately predict the identity of a variety of cell clusters and can be used in various experimental contexts across a broad spectrum of research areas.

scholarly journals TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 439 ◽  
Author(s):  
Tiago Chedraoui Silva ◽  
Antonio Colaprico ◽  
Catharina Olsen ◽  
Tathiane M Malta ◽  
Gianluca Bontempi ◽  
...  
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Cancer Genomics ◽  
Genomic Data ◽  
Bioconductor Project ◽  
Video Tutorials ◽  
Data Portal ◽  
Advanced Knowledge ◽  
Data Commons

The GDC (Genomic Data Commons) data portal provides users with data from cancer genomics studies. Recently, we developed the R/Bioconductor TCGAbiolinks package, which allows users to search, download and prepare cancer genomics data for integrative data analysis. The use of this package requires users to have advanced knowledge of R thus limiting the number of users. To overcome this obstacle and improve the accessibility of the package by a wider range of users, we developed a graphical user interface (GUI) using Shiny available through the package TCGAbiolinksGUI. The TCGAbiolinksGUI package is freely available within the Bioconductor project at http://bioconductor.org/packages/TCGAbiolinksGUI/. Links to the GitHub repository, a demo version of the tool, a docker image and PDF/video tutorials are available from the TCGAbiolinksGUI site.

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