Search

• Preparing to achieve higher levels of UX maturity of desktop-based FOSS projectsis imperative for the projects' success. • The FOSS community has limited studies,techniques, and analytical lenses forassessing its preparation for projects achieving higher levels of UX maturity. • The Current preparation interventions are not consistently applied across projects and lack methodological rigor. • This study adopted the fuzzy delphi method to create and rank ten (10) lenses to determine the preparation of the desktop-based FOSS projects to achieve higher levels of UX maturity. • Recommendations and suggestions for future studies derived from the results are presented. User eXperience (UX) significantly influences the success of free and open source software (FOSS) projects and is measured using UX capability maturity models (UXCMMs). Every organization desires higher levels of UX maturity; however, it requires upfront preparations and process quality control. Harmonizing processes and analytical lenses for determining preparation for UX maturity are still challenging, and studies to create them are limited. The analysis is ad hoc and based on the actors' will and experiences. This study proposes and validates analytical lenses. Findings show that UX experts agreed that the lenses could be used with a consensus percentage of 81 %, the threshold value (d) = 0.112, and crisp values greater than α-cut = 0.5. On validation, 47.57 % of stakeholders agreed, and 52.43 % strongly agreed they were relevant. Results help evaluate the status quo and change culture and policies toward ideal preparation. Two areas are suggested for future research. [ABSTRACT FROM AUTHOR]

Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response and management. Uncrewed Aerial Systems (UAS; aka drones) offer post-fire management teams the ability to quickly mobilize and survey burned areas with very high-resolution imagery (∼1 cm), facilitating emergency management and post-fire hazard assessment. However, adoption of this technology by hazard response teams may be hindered by complicated workflows for UAS data acquisition, image processing and analysis. We present an open-source workflow using mature Geographic Information Systems (GIS) software and Python packages in a Jupyter Notebook environment that guides users through classification of true-color UAS imagery to generate high resolution burn severity maps which can then be scaled across larger watersheds using Sentinel-2 normalized burn ratio (NBR) images. Soil burn severity classifications using a weighted brightness (WB) image and Char Index (CI) generated from UAS imagery were validated with in-situ data and random stratified points, resulting in the CI having the highest overall accuracy of 87.5%. CI also displayed a marginally stronger relationship over the WB with the post-fire Sentinel-2 NBR, R2 = 0.79 and R2 = 0.78 respectively. Our methods offer the unique opportunity to standardize GIS workflows, promoting replication through transparency, while improving the user's understanding of scientific GIS functionality. • UAS can provide landscape-level burn-severity assessments, potentially lowering costs and time spent in dangerous terrain. • We present an open-source workflow that guides users through UAS burn severity classification and scaling to satellite. • Our best classification showed overall accuracy of 87.5%. • Regression modelling of UAS, and Sentinel-2 data can provide a final risk assessment product to assist post-fire management. [ABSTRACT FROM AUTHOR]

This paper introduces a free and open-source geographic information system (GIS) plug-in, named PolyMorph-2D, for morphometric analysis of vector-based polygon features (PFs) in OpenJUMP. Written in Java™ programming language, the plug-in allows researchers from various earth and spatial science-related disciplines to compute morphometric parameters of 2D input vector features forming a polygon (i.e., a closed curve) which may represent outer boundaries or contours of various natural and/or man-made entities that differ in size, shape, complexity and drawing scale (e.g., craters, sinkholes, cirques, drainage basins, land parcels, buildings, lakes, ponds, peaks, pits, playas, pockmarks, coral mounds, seamounts, landslides, drumlins, islands, atolls, granular materials, mineral crystals, fossils, etc.). Using this plug-in, a number of basic tasks (e.g., calculations related to location, length, width, perimeter, radius, area, and orientation) can be performed and derived parameters (i.e., shape and size measures) of PFs (e.g., axis ratios, ellipticity, circularity, compactness, dispersion, complexity, elongation, regularity, convexity, concavity, solidity, rectangularity, roundness, and sphericity) are computed and written to input polygon layer's attribute table, through a simple point-and-click interface. The derived parameters calculated by the plug-in are invariant to the PF's location, scale (size), and rotation. The plug-in is also capable of performing aforementioned morphometric calculations on overlapping PFs with or without holes, provided they are topologically correct. The extensive data matrix (consisting of 39 parameters) obtained from this route can be further subjected to a number of multivariate statistical analysis methods to decipher underlying processes and/or environmental factors responsible for formation of these shapes and to classify them into homogeneous subtypes or typologies featuring similar characteristics. [Display omitted] • PolyMorph-2D, written in Java™, is a new GIS plug-in for the OpenJUMP software. • The host program and plug-in are free, easy-to-use, open-source and cross-platform. • Plug-in allows calculation of 39 morphometric parameters for vector-based 2D polygons. • Plug-in can also handle overlapping polygons with holes, differing in size and shape. • Plug-in has been benchmarked and validated against artificial and real-world datasets. [ABSTRACT FROM AUTHOR]

We investigated the application of consensus scoring using the freely available and open source structure-based virtual screening docking programs AutoDock Vina, smina and idock. These individual programs and several simple consensus scoring methods were tested for their ability to identify hits against 20 DUD-E benchmark targets using the AUC and EF1 metrics. We found that all of the consensus scoring methods, however normalized, fared worse, on average, than simply using the output from a single program, smina. Additionally, the effect of a significant increase in the run time of all three programs was tested to find if a longer run time yielded improved results. Our results indicated that a longer run time than the default had little impact on the performance of these three programs or on consensus scoring methods based on their output. Thus, we have found that using the smina program alone at default settings is the best approach for researchers that do not have access to a suite of commercial docking software packages. Image 1 • Consensus scoring using Vina, smina and idock was no better than smina alone. • Increasing the run length from the default did not improve performance. • The min consensus method led to the best consensus scoring results. • The method of normalization of data had no effect on the consensus scoring results. [ABSTRACT FROM AUTHOR]