Predictive edge computing for time series of industrial IoT and large scale critical infrastructure based on open-source software analytic of big data

2017 ◽  
Author(s):  
Emmanuel Oyekanlu
Keyword(s):  
Time Series ◽  
Big Data ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Critical Infrastructure ◽  
Edge Computing ◽  
Industrial Iot

scholarly journals District-Heating-Grid Simulation in Python: DiGriPy

Computation ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 72
Author(s):  
Lena Vorspel ◽  
Jens Bücker
Keyword(s):  
Time Series ◽  
Open Source ◽  
Network Model ◽  
Temperature Control ◽  
Open Source Software ◽  
Large Scale ◽  
District Heating ◽  
Grid Simulation ◽  
Heating Networks ◽  
Python Package

DiGriPy is a newly developed Python tool for the simulation of district heating networks published as open-source software in GitHub and offered as a Python package on PyPI. It enables the user to easily build a network model, run large-scale demand time series, and automatically compare different temperature-control conditions. In this paper, implementation details and usage instructions are given. Tests showing the results of different scenarios are presented and interpreted.

scholarly journals PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Metals And Alloys ◽  
Analysis Tool ◽  
Computational Framework ◽  
Crystal Plasticity Finite Element ◽  
Polycrystalline Metals ◽  
Simulation Based ◽  
Open Source Framework

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

2021 ◽  
Author(s):  
Fabian Kovacs ◽  
Max Thonagel ◽  
Marion Ludwig ◽  
Alexander Albrecht ◽  
Manuel Hegner ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Medical Records ◽  
Healthcare Sector ◽  
Study Cohort ◽  
Decision Making Processes ◽  
Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

Developing a Dynamic and Responsive Online Learning Environment

2011 ◽  
pp. 92-109 ◽  
Author(s):  
Janet Buchan
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Appropriate Technology ◽  
Online Learning Environment ◽  
Institutional Level ◽  
Learning And Teaching ◽  
Community Source

Charles Stuart University adopted the open source software, Sakai, as the foundation for the university’s new, integrated Online Learning Environment. This study explores whether a pedagogical advantage exists in adopting such an open source learning management system. Research suggests that the community source approach to development of open source software has many inherent pedagogical advantages, but this paper examines whether this is due to the choice of open source software or simply having access to appropriate technology for learning and teaching in the 21st century. The author also addresses the challenges of the project management methodology and processes in the large-scale implementation of an open-source courseware management solution at the institutional level. Consequently, this study outlines strategies that an institution can use to harness the potential of a community source approach to software development to meet the institutional and individual user needs into the future.

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