Results 61 to 70 of about 338,585 (297)

Why do biomedical researchers learn to program? An exploratory investigation

Journal of the Medical Library Association, 2020
Objective: As computer programming becomes increasingly important in the biomedical sciences and more libraries offer programming classes, it is crucial for librarians to understand how researchers use programming in their work.
Ariel Deardorff
doaj   +1 more source

PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a ...
L. Annala, M. A. Eskelinen, J. Hämäläinen, A. Riihinen, I. Pölönen   +4 more
doaj   +1 more source

Python tutorial [PDF]

, 1995
Python is a simple, yet powerful programming language that bridges the gap between C and shell programming, and is thus ideally suited for ``throw-away programming'' and rapid prototyping.
Rossum, G. (Guido) van
core  

FAIR and Structured Data: A Domain Ontology Aligned with Standard‐Compliant Tensile Testing

Advanced Engineering Materials, EarlyView.
The digitalization in materials science and engineering is discussed, emphasizing the importance of digital workflows and ontologies in managing diverse experimental data. Challenges such as quality assurance and data interoperability are tackled with semantic web technologies, focusing and introducing the tensile test ontology (TTO).
Markus Schilling, Bernd Bayerlein, Philipp von Hartrott, Jörg Waitelonis, Henk Birkholz, Pedro Dolabella Portella, Birgit Skrotzki   +6 more
wiley   +1 more source

Semantic Representation of Low‐Cycle‐Fatigue Testing Data Using a Fatigue Test Ontology and ckan.kupferdigital Data Management System

Advanced Engineering Materials, EarlyView.
This article introduces an automated approach for converting the raw research data (use case of low‐cycle‐fatigue testing dataset) to machine‐readable resource description framework ones and storing them in an open digital repository. As two main prerequisites for this data digitalization process, the development of fatigue testing ontology and ckan ...
Hossein Beygi Nasrabadi, Thomas Hanke, Birgit Skrotzki   +2 more
wiley   +1 more source

An Automatized Simulation Workflow for Powder Pressing Simulations Using SimStack

Advanced Engineering Materials, EarlyView.
The implementation of Workflow active Nodes (WaNos) for the convenient execution and automated evaluation of discrete element method calculations of powder pressing is showcased. Purposeful combination of WaNos creates timesaving and resource‐effective computational workflows.
Bjoern Mieller, Masood Valavi, Celso Ricardo Caldeira Rêgo   +2 more
wiley   +1 more source

Algorithmic Programming Language Identification [PDF]

, 2011
Motivated by the amount of code that goes unidentified on the web, we introduce a practical method for algorithmically identifying the programming language of source code. Our work is based on supervised learning and intelligent statistical features.
Klein, David, Murray, Kyle, Weber, Simon
core  

Automated Workflow for Phase‐Field Simulations: Unveiling the Impact of Heat‐Treatment Parameters on Bainitic Microstructure in Steel

Advanced Engineering Materials, EarlyView.
In this study, OpenPhase software is used to simulate low‐carbon bainitic steels. The lower holding temperature sample exhibits smaller and finer grains. Grain thickness measurements of bainitic ferrite from simulations align with the experimental observations at high temperature. Bainitic steels are extensively utilized across various sectors, such as
Dhanunjaya K. Nerella, Muhammad Adil Ali, Hesham Salama, Oguz Gulbay, Marc Ackermann, Oleg Shchyglo, Ulrich Krupp, Ingo Steinbach   +7 more
wiley   +1 more source

Simplifying Parallelization of Scientific Codes by a Function-Centric Approach in Python [PDF]

, 2010
The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallel communication is implemented. We provide specific examples on such layers of code, and these examples may act as templates for parallelizing a wide set of serial scientific codes.
arxiv   +1 more source

A Syntactic Neural Model for General-Purpose Code Generation

, 2017
We consider the problem of parsing natural language descriptions into source code written in a general-purpose programming language like Python. Existing data-driven methods treat this problem as a language generation task without considering the ...
Neubig, Graham, Yin, Pengcheng
core   +1 more source