scholarly journals OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features

SoftwareX ◽  
2020 ◽  
Vol 11 ◽  
pp. 100401
Author(s):  
Ting Li ◽  
Lawrence V. Stanislawski ◽  
Tyler Brockmeyer ◽  
Shaowen Wang ◽  
Ethan Shavers
2020 ◽  
Author(s):  
Richard West ◽  
Robert Kee ◽  
Kyle Niemeyer ◽  
Steven C. DeCaluwe ◽  
C. Goldsmith ◽  
...  

2020 ◽  
Author(s):  
Bradley M. Conrad ◽  
Matthew R. Johnson

Abstract. Gas flaring is an important source of atmospheric soot/black carbon, especially in sensitive Arctic regions. However, emissions have traditionally been challenging to measure and remain poorly characterized, confounding international reporting requirements and adding uncertainty to climate models. The sky-LOSA optical measurement technique has emerged as a powerful means to quantify flare black carbon emissions in the field, but broader adoption has been hampered by the complexity of its deployment, where decisions during setup in the field can have profound, non-linear impacts on achievable measurement uncertainties. To address this challenge, this paper presents a prescriptive measurement protocol and associated open-source software tool that simplifies acquisition of sky-LOSA data in the field. Leveraging a comprehensive Monte Carlo-based General Uncertainty Analysis (GUA) to predict measurement uncertainties over the entire breadth of possible measurement conditions, general heuristics are identified to guide a sky-LOSA user toward optimal data collection. These are further extended in the open-source software utility, SetupSkyLOSA, which interprets the GUA results to provide detailed guidance for any specific combination of location, date/time, and flare, plume, and ambient conditions. Finally, a case study of a sky-LOSA measurement at an oil and gas facility in Mexico is used to demonstrate the utility of the software tool, where potentially small region(s) of optimal instrument setup are easily and quickly identified. It is hoped that this work will help increase the accessibility of the sky-LOSA technique and ultimately the availability of field measurement data for flare black carbon emissions.


Author(s):  
Pushpa Singh ◽  
Rajeev Agrawal

This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.


2019 ◽  
Vol 19 (3) ◽  
pp. 237-243 ◽  
Author(s):  
Sofia Z. Sheikh

AbstractIt can be difficult to develop an effective and balanced search strategy in SETI, especially from a funding perspective, given the diverse methodologies and myriad orthogonal proposals for the best technosignatures. Here I propose a framework to compare the relative advantages and disadvantages of various proposed technosignatures based on nine ‘axes of merit’. This framework was first developed at the NASA Technosignatures Workshop in Houston in 2018 and published in that report. I give the definition and rationale behind the nine axes as well as the history of each axis in the SETI and technosignature literature. These axes are then applied to three classes of technosignature searches as an illustration of their use. An open-source software tool is available to allow technosignature researchers to make their own version of the figure.


Procedia CIRP ◽  
2016 ◽  
Vol 49 ◽  
pp. 178-182 ◽  
Author(s):  
Jairson C. Dinis ◽  
Thiago F. Moraes ◽  
Paulo H.J. Amorim ◽  
Mario R. Moreno ◽  
Amanda A. Nunes ◽  
...  

2016 ◽  
Vol 5 (7) ◽  
pp. 774-780 ◽  
Author(s):  
Sebastian M. Castillo-Hair ◽  
John T. Sexton ◽  
Brian P. Landry ◽  
Evan J. Olson ◽  
Oleg A. Igoshin ◽  
...  

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