scholarly journals EpyNN: Educational python for Neural Networks

2021 ◽  
Author(s):  
Florian Malard ◽  
Laura Danner ◽  
Emilie Rouzies ◽  
Jesse G Meyer ◽  
Ewen Lescop ◽  
...  

AbstractSummaryArtificial Neural Networks (ANNs) have achieved unequaled performance for numerous problems in many areas of Science, Business, Public Policy, and more. While experts are familiar with performance-oriented software and underlying theory, ANNs are difficult to comprehend for non-experts because it requires skills in programming, background in mathematics and knowledge of terminology and concepts. In this work, we release EpyNN, an educational python resource meant for a public willing to understand key concepts and practical implementation of scalable ANN architectures from concise, homogeneous and idiomatic source code. EpyNN contains an educational Application Programming Interface (API), educational workflows from data preparation to ANN training and a documentation website setting side-by-side code, mathematics, graphical representation and text to facilitate learning and provide teaching material. Overall, EpyNN provides basics for python-fluent individuals who wish to learn, teach or develop from scratch.AvailabilityEpyNN documentation is available at https://epynn.net and repository can be retrieved from https://github.com/synthaze/epynn.ContactStéphanie Olivier-Van-Stichelen, [email protected] InformationSupplementary files and listings.

2019 ◽  
Vol 35 (21) ◽  
pp. 4424-4426 ◽  
Author(s):  
Soohyun Lee ◽  
Jeremy Johnson ◽  
Carl Vitzthum ◽  
Koray Kırlı ◽  
Burak H Alver ◽  
...  

Abstract Summary We introduce Tibanna, an open-source software tool for automated execution of bioinformatics pipelines on Amazon Web Services (AWS). Tibanna accepts reproducible and portable pipeline standards including Common Workflow Language (CWL), Workflow Description Language (WDL) and Docker. It adopts a strategy of isolation and optimization of individual executions, combined with a serverless scheduling approach. Pipelines are executed and monitored using local commands or the Python Application Programming Interface (API) and cloud configuration is automatically handled. Tibanna is well suited for projects with a range of computational requirements, including those with large and widely fluctuating loads. Notably, it has been used to process terabytes of data for the 4D Nucleome (4DN) Network. Availability and implementation Source code is available on GitHub at https://github.com/4dn-dcic/tibanna. Supplementary information Supplementary data are available at Bioinformatics online.


Author(s):  
Vasily Scherbakov

The paper discusses the main aspects of the practical implementation of software and user interfaces for managing models of neuromorphic computing systems.


2021 ◽  
Vol 23 (06) ◽  
pp. 1672-1681
Author(s):  
Vinay Balamurali ◽  
◽  
Prof. Venkatesh S ◽  

Servers are required to monitor the health of the various I/O cards connected to it to alert the required personnel to service these cards. The Data Collection Unit (DCU) is responsible for detecting the I/O cards, sending their inventory as well as monitoring their health. Currently, the keys required to detect these I/O cards are manually coded into the source code. Such a task is highly laborious and time-consuming. To eliminate this manual work, a Software Pluggable Module was devised which would read the I/O card-related information from the I/O component list. This software design aims at using Data Science and OOPS concepts to automate certain tasks on server systems. The proposed methodology is implemented on a Linux system. The software design is modular in nature and extensible to accommodate future requirements. Such an automation framework can be used to track information maintained in Excel Spreadsheets and access them using an Application Programming Interface (API).


2018 ◽  
Author(s):  
Soohyun Lee ◽  
Jeremy Johnson ◽  
Carl Vitzthum ◽  
Koray Kırlı ◽  
Burak H. Alver ◽  
...  

AbstractSummaryWe introduce Tibanna, an open-source software tool for automated execution of bioinformatics pipelines on Amazon Web Services (AWS). Tibanna accepts reproducible and portable pipeline standards including Common Workflow Language (CWL), Workflow Description Language (WDL) and Docker. It adopts a strategy of isolation and optimization of individual executions, combined with a serverless scheduling approach. Pipelines are executed and monitored using local commands or the Python Application Programming Interface (API) and cloud configuration is automatically handled. Tibanna is well suited for projects with a range of computational requirements, including those with large and widely fluctuating loads. Notably, it has been used to process terabytes of data for the 4D Nucleome (4DN) Network.AvailabilitySource code is available on GitHub at https://github.com/4dn-dcic/tibanna.


2020 ◽  
Vol 20 (4) ◽  
pp. 1029-1036
Author(s):  
VIOREL MIRON-ALEXE

This article represents a prototype experiment regarding the practical implementation of an affordable, wireless, and online monitoring pulse oximetry device, for a Covid-19 infected patient that is quarantined at home. By using an Arduino based IoT (Internet of Things) embedded platform and a free online API (Application Programming Interface) live data stream server, the family physician can remotely monitor the patient’s pulse and blood oxygen level, by using a mobile phone, a tablet or a computer, without any contamination risk or contact, with the infected patient.


Author(s):  
Benjamin Elsworth ◽  
Tom R Gaunt

ABSTRACT Summary The field of literature-based discovery is growing in step with the volume of literature being produced. From modern natural language processing algorithms to high quality entity tagging, the methods and their impact are developing rapidly. One annotation object that arises from these approaches, the subject–predicate–object triple, is proving to be very useful in representing knowledge. We have implemented efficient search methods and an application programming interface, to create fast and convenient functions to utilize triples extracted from the biomedical literature by SemMedDB. By refining these data, we have identified a set of triples that focus on the mechanistic aspects of the literature, and provide simple methods to explore both enriched triples from single queries, and overlapping triples across two query lists. Availability and Implementation: https://melodi-presto.mrcieu.ac.uk/. Supplementary information Supplementary data are available at Bioinformatics online.


2021 ◽  
Author(s):  
George Kopsiaftis ◽  
Ioannis Georgoulas ◽  
Ioannis Rallis ◽  
Ioannis Markoulidakis ◽  
Kostis Tzanettis ◽  
...  

This paper analyzes the architecture of an application programming interface (API) developed for a novel customer experience tool. The CX tool aims to monitor the customer satisfaction, based on several experience attributes and metrics, such as the Net Promoter Score. The API aims to create an efficient and user-friendly environment, which allow users to utilize all the available features of the customer experience system, including the exploitation of state-of-the-art machine learning algorithms, the analysis of the data and the graphical representation of the results.


Author(s):  
D. Oxoli ◽  
H.-K. Kang ◽  
M. A. Brovelli

<p><strong>Abstract.</strong> The open and direct collaboration at the creation, improvement, and documentation of source code and software applications &amp;ndash; enabled by the web &amp;ndash; is recognized as a peculiarity of the Free and Open Source Software for Geospatial (FOSS4G) projects representing, at the same time, one of their main strengths. With this in mind, it turns out to be interesting to perform an extensive monitoring of both the evolution and the geographical arrangement of the developers’ communities in order to investigate their actual extension, evolution and degree of activity. In this work, a semi-automatic procedure to perform this particular analysis is described. The procedure is mainly based on the use of the GitHub Search Application Programming Interface by means of JavaScript custom modules to perform a census of the users registered with a collaborator role to the repositories of the most popular FOSS4G projects, hosted on the GitHub platform. The collected data is processed and analysed using Python and QGIS. The results &amp;ndash; presented through tables, charts, and thematic maps &amp;ndash; allow describing both dimensions as well as the geographical heterogeneity of the contributing community of each individual project, while enabling to identify the most active countries &amp;ndash; in terms of the number of contributors &amp;ndash; in the development of the most popular FOSS4G. The limits of the analysis, including technical constraints and considerations on the significance of the developers' census, are finally highlighted and discussed.</p>


2021 ◽  
Vol 11 (1) ◽  
pp. 135-145
Author(s):  
Matúš Sulír ◽  
Jaroslav Porubän

Abstract After a voice control system transforms audio input into a natural language sentence, its main purpose is to map this sentence to a specific action in the API (application programming interface) that should be performed. This mapping is usually specified after the API is already designed. In this paper, we show how an API can be designed with voice control in mind, which makes this mapping natural. The classes, methods, and parameters in the source code are named and typed according to the terms expected in the natural language commands. When this is insufficient, annotations (attribute-oriented programming) are used to define synonyms, string-to-object maps, or other properties. We also describe the mapping process and present a preliminary implementation called VCMapper. In its evaluation on a third-party dataset, it was successfully used to map all the sentences, while a large portion of the mapping was performed using only naming and typing conventions.


Sign in / Sign up

Export Citation Format

Share Document