End-to-end framework for fault management for open source clusters

2010 ◽  
Author(s):  
John L. Hammond ◽  
Tommy Minyard ◽  
Jim Browne
Keyword(s):  
Open Source ◽  
Fault Management ◽  
End To End

scholarly journals End-To-End Computer Vision Framework: An Open-Source Platform for Research and Education

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3691
Author(s):  
Ciprian Orhei ◽  
Silviu Vert ◽  
Muguras Mocofan ◽  
Radu Vasiu
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Computer Vision ◽  
Open Source ◽  
Visual Processing ◽  
Research Field ◽  
Learning Models ◽  
Research Activity ◽  
End To End ◽  
Machine Learning Models

Computer Vision is a cross-research field with the main purpose of understanding the surrounding environment as closely as possible to human perception. The image processing systems is continuously growing and expanding into more complex systems, usually tailored to the certain needs or applications it may serve. To better serve this purpose, research on the architecture and design of such systems is also important. We present the End-to-End Computer Vision Framework, an open-source solution that aims to support researchers and teachers within the image processing vast field. The framework has incorporated Computer Vision features and Machine Learning models that researchers can use. In the continuous need to add new Computer Vision algorithms for a day-to-day research activity, our proposed framework has an advantage given by the configurable and scalar architecture. Even if the main focus of the framework is on the Computer Vision processing pipeline, the framework offers solutions to incorporate even more complex activities, such as training Machine Learning models. EECVF aims to become a useful tool for learning activities in the Computer Vision field, as it allows the learner and the teacher to handle only the topics at hand, and not the interconnection necessary for visual processing flow.

Open-source RTP Library for End-to-End Encrypted Real-Time Video Streaming Applications

2021 ◽  
Author(s):  
Joni Rasanen ◽  
Aaro Altonen ◽  
Alexandre Mercat ◽  
Jarno Vanne
Keyword(s):  
Open Source ◽  
Real Time ◽  
Video Streaming ◽  
Streaming Applications ◽  
End To End

scholarly journals OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis

2014 ◽  
Vol 10 (8) ◽  
pp. e1003806 ◽  
Author(s):  
Greg Finak ◽  
Jacob Frelinger ◽  
Wenxin Jiang ◽  
Evan W. Newell ◽  
John Ramey ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Data Analysis ◽  
Open Source ◽  
Flow Cytometry Data ◽  
End To End

MobiGlam

2012 ◽  
pp. 333-352
Author(s):  
Fatma Meawad ◽  
Geneen Stubbs
Keyword(s):  
Open Source ◽  
Learning Environments ◽  
Mobile Devices ◽  
Mobile Learning ◽  
Real World ◽  
Virtual Learning Environments ◽  
Learning Activities ◽  
Wide Acceptance ◽  
End To End ◽  
Institutional Challenges

This chapter discusses the principles underpinning the design and the development of a framework, MobiGlam, which supports ubiquitous and scalable access to learning activities. The framework allows full end to end interconnectivity among open source virtual learning environments (VLEs) and Java-enabled mobile devices. Through this framework, interoperability and adaptivity techniques are combined to address the technical, pedagogical, and institutional challenges of mobile learning. The discussed framework achieved a level of flexibility and simplicity that resulted in a wide acceptance of the framework institutionally, allowing its use in various real world settings.

OpenSAR: An Open Source Automated End-to-end SAR ADC Compiler

2021 ◽  
Author(s):  
Mingjie Liu ◽  
Xiyuan Tang ◽  
Keren Zhu ◽  
Hao Chen ◽  
Nan Sun ◽  
...  
Keyword(s):  
Open Source ◽  
Sar Adc ◽  
End To End

scholarly journals An open-source, end-to-end workflow for multidimensional photoemission spectroscopy

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
R. Patrick Xian ◽  
Yves Acremann ◽  
Steinn Y. Agustsson ◽  
Maciej Dendzik ◽  
Kevin Bühlmann ◽  
...  
Keyword(s):  
Open Source ◽  
Electronic Band Structure ◽  
Photoemission Spectroscopy ◽  
Physical Parameters ◽  
Light Sources ◽  
Database Integration ◽  
Single Event ◽  
Electronic Band ◽  
End To End ◽  
Band Mapping

AbstractCharacterization of the electronic band structure of solid state materials is routinely performed using photoemission spectroscopy. Recent advancements in short-wavelength light sources and electron detectors give rise to multidimensional photoemission spectroscopy, allowing parallel measurements of the electron spectral function simultaneously in energy, two momentum components and additional physical parameters with single-event detection capability. Efficient processing of the photoelectron event streams at a rate of up to tens of megabytes per second will enable rapid band mapping for materials characterization. We describe an open-source workflow that allows user interaction with billion-count single-electron events in photoemission band mapping experiments, compatible with beamlines at 3rd and 4rd generation light sources and table-top laser-based setups. The workflow offers an end-to-end recipe from distributed operations on single-event data to structured formats for downstream scientific tasks and storage to materials science database integration. Both the workflow and processed data can be archived for reuse, providing the infrastructure for documenting the provenance and lineage of photoemission data for future high-throughput experiments.

scholarly journals TAPAS: an open-source software package for Translational Neuromodeling and Computational Psychiatry

2021 ◽  
Author(s):  
Stefan Frässle ◽  
Eduardo A. Aponte ◽  
Saskia Bollmann ◽  
Kay H. Brodersen ◽  
Cao T. Do ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Open Source ◽  
Software Package ◽  
Clinical Decision Making ◽  
Building Blocks ◽  
Clinical Decision ◽  
Patient Specific ◽  
Computational Psychiatry ◽  
Open Source Software Package ◽  
End To End

ABSTRACTPsychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients. This has motivated the genesis of two closely intertwined fields: (i) Translational Neuromodeling (TN), which develops “computational assays” for inferring patient-specific disease processes from neuroimaging, electrophysiological, and behavioral data; and (ii) Computational Psychiatry (CP), with the goal of incorporating computational assays into clinical decision making in everyday practice. In order to serve as objective and reliable tools for clinical routine, computational assays require end-to-end pipelines from raw data (input) to clinically useful information (output). While these are yet to be established in clinical practice, individual components of this general end-to-end pipeline are being developed and made openly available for community use.In this paper, we present the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) software package, an open-source collection of building blocks for computational assays in psychiatry. Collectively, the tools in TAPAS presently cover several important aspects of the desired end-to-end pipeline, including: (i) tailored experimental designs and optimization of measurement strategy prior to data acquisition, (ii) quality control during data acquisition, and (iii) artifact correction, statistical inference, and clinical application after data acquisition. Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized pipelines for predictions about individual patients. We hope that the openly available tools in TAPAS will contribute to the further development of TN/CP and facilitate the translation of advances in computational neuroscience into clinically relevant computational assays.

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