Open-access mega-journals: The future of scholarly communication or academic dumping ground? A review.

Dieser Artikel liefert die empirische Grundlage fur eine Beurteilung der Einstellung geisteswissenschaftlicher Zeitschriftenherausgeber*innen gegenuber Open Access. Im Rahmen des deutschen Open Library of Humanities-Projekts (OLH-DE) wurde an der Universitat Konstanz eine Online-Umfrage unter 416 Herausgeber*innen deutschsprachiger geisteswissenschaftlicher Zeitschriften durchgefuhrt. Dabei wurde nicht nur nach ihren Einstellungen, Befurchtungen und relevanten Aspekten zu Open Access im Allgemeinen gefragt, sondern auch uber das konsortiale Open-Access-Modell der Open Library of Humanities (OLH) informiert. Die Ergebnisse zeigen, dass die Einstellungen unter geisteswissenschaftlichen Zeitschriftenherausgeber*innen zu Open Access nicht so negativ sind wie oft befurchtet und sich viele Bedenken durch ihre konkrete Adressierung im Rahmen der Vorstellung von OLH deutlich abschwachen lassen. Der Verlust der Printversion blieb ein signifikanter Open-Access-Hinderungsgrund, wodurch „print on demand“ Open-Access-Geschaftsmodelle vielversprechend waren. Insgesamt konnte nach der Vorstellung des konkreten Modells der OLH eine erhohte Bereitschaft zur Transformation unter den Herausgeber*innen geisteswissenschaftlicher Zeitschriften beobachtet werden als grundsatzlich zu Open-Access-Modellen angegeben wurde. Dieses Ergebnis unterstreicht die Relevanz von Open-Access-Projekten wie OLH-DE: Nur durch eine gezielte Open-Access-Vermittlung kann eine fortschreitende Open-Access-Transformation unter geisteswissenschaftlichen Herausgeber*innen und deren Zeitschriften gelingen.

https://www.o-bib.de/article/download/5512/8094

Bereitschaft zu Open Access in den Geisteswissenschaften

Digital Twin (DT) plays a crucial role in intelligent bridge management, and the geometric DT (gDT) serves as its foundation. Notably, the fast and high-precision generation of bridge gDT models has gained increasing attention. This research presents a method for generating high-precision and fast RC bridges with chambers for gDT using terrestrial laser scanning. The method begins with a proposed fast point cloud data collection technique designed specifically for bridges with internal chambers. Subsequently, Euclidean clustering and grid segmentation algorithms are developed to automatically extract contour features from the sliced point clouds. Finally, a framework based on the Dynamo–Revit reverse modelling method is introduced, enabling the automatic generation of gDT models from the identified point cloud features. To validate the feasibility and accuracy of the proposed method, a concrete variable section bridge is used. A comparison is made between the generated gDT model and the point cloud model in terms of 3D deviation, revealing a maximum deviation of 6.6 mm and an average deviation of 3 mm. These results affirm the feasibility of the proposed method.

Fast and Accurate Generation Method of Geometric Digital Twin Model of RC Bridge with Box Chambers Based on Terrestrial Laser Scanning

Despite growing interest in Open Access (OA) to scholarly literature, there is an unmet need for large-scale, up-to-date, and reproducible studies assessing the prevalence and characteristics of OA. We address this need using oaDOI, an open online service that determines OA status for 67 million articles. We use three samples, each of 100,000 articles, to investigate OA in three populations: (1) all journal articles assigned a Crossref DOI, (2) recent journal articles indexed in Web of Science, and (3) articles viewed by users of Unpaywall, an open-source browser extension that lets users find OA articles using oaDOI. We estimate that at least 28% of the scholarly literature is OA (19M in total) and that this proportion is growing, driven particularly by growth in Gold and Hybrid. The most recent year analyzed (2015) also has the highest percentage of OA (45%). Because of this growth, and the fact that readers disproportionately access newer articles, we find that Unpaywall users encounter OA quite frequently: 47% of articles they view are OA. Notably, the most common mechanism for OA is not Gold, Green, or Hybrid OA, but rather an under-discussed category we dub Bronze: articles made free-to-read on the publisher website, without an explicit Open license. We also examine the citation impact of OA articles, corroborating the so-called open-access citation advantage: accounting for age and discipline, OA articles receive 18% more citations than average, an effect driven primarily by Green and Hybrid OA. We encourage further research using the free oaDOI service, as a way to inform OA policy and practice.

The State of OA: A large-scale analysis of the prevalence and impact of Open Access articles

Three-dimensional indoor models have wide applications in fields such as indoor navigation, civil engineering, virtual reality, and so on. With the development of LiDAR technology, automatic reconstruction of indoor models from point clouds has gained significant attention. We propose a new framework for generating indoor 3D digital models from point clouds. The proposed method first generates a room instance map of an indoor scene. Walls are detected and projected onto a horizontal plane to form line segments. These segments are extended, intersected, and, by solving an integer programming problem, line segments are selected to create room polygons. The polygons are converted into a raster image, and image connectivity detection is used to generate a room instance map. Then the roofs of the point cloud are extracted and used to perform an overlap analysis with the generated room instance map to segment the entire roof point cloud, obtaining the roof for each room. Room boundaries are defined by extracting and regularizing the roof point cloud boundaries. Finally, by detecting doors and windows in the scene in two steps, we generate the floor plans and 3D models separately. Experiments with the Giblayout dataset show that our method is robust to clutter and furniture point clouds, achieving high-accuracy models that match real scenes. The mean precision and recall for the floorplans are both 0.93, and the Point–Surface Distance (PSD) and standard deviation of the PSD for the 3D models are 0.044 m and 0.066 m, respectively. 

A New Framework for Generating Indoor 3D Digital Models from Point Clouds

The newly released refine option of Open Access on the Web of Science platform makes it possible to analyze the article-level OA content across the whole Web of Science database, including more than sixty million documents. In this study, employing the OA filter option of Web of Science, we perform a large-scale evaluation of the OA state of countries from 1990 to 2016. Particularly, for each country, we consider not only the absolute number of Gold OA literature but also the ratio of them among all literature. We compare the rates and evolutions of OA across countries. Our results show that the number of OA articles have increased quickly in the last decades. Currently, one quarter of the Web of Science articles are Gold OA articles; In contrast, in 1990, the percentage of OA articles is less than 8%. Brazil is found to be the most active country in OA publishing. In contrast, Russia, India and China have the lowest OA ratios. In addition, the temporal trend analysis shows that the OA percentage of Brazil has been decreasing dramatically in recent years, while the OA percentages of China, UK and Netherlands have been increasing.

https://scholarlypublications.universiteitleiden.nl/access/item%3A2729143/view

The state and evolution of Gold Open Access: A country level analysis

Abstract. Indoor point cloud data is easy to obtain and contains a large amount of data, but there is no connectivity, no structural attributes, and no semantic information between point clouds. It is very difficult to extract interior components. In order to solve the problem that it is difficult to extract the closed door in the indoor point cloud, and the indoor scanning point cloud data is noisy and redundant, a point cloud segmentation method is proposed to reduce the amount of data and the impact of noise. Because most of the indoor components are not on the same horizontal plane, different component information can be obtained by slicing the point cloud at different heights. In these slices, the component that always exists is the wall. By comparing other data with the point cloud data with a more complete wall, the required component can be extracted. The experimental results show that this method can accurately extract the indoor door component information and beam component information, providing a data basis for building model refinement.


/pdf/point-cloud-slicing-based-extraction-of-indoor-components-2gbhw6x4.pdf

Point cloud slicing-based extraction of indoor components

The influencing factors causing fracture failure while installing a fastening device&apos;s YS20 polyimide insulating sleeve were addressed using a combination of simulations and experiments to study the influence of the friction coefficient and additional bending moments caused by installing the breaking torque. The results showed that the neck is subject to the highest stress during the breaking process of the polyimide sleeve and is prone to fracture. The insulating sleeve&apos;s breaking torques are 5.6 and 8.1 N˙m when the friction coefficients are 0.2 and 0.3, respectively, and the breaking torque shows an increasing trend when the friction coefficient is 0.2 to 0.3. The additional bending moment in the installation process can decrease the breaking torque up to 44%, therefore, additional bending moments should be avoided. The maximum wrenching torque should be controlled at ≤7.5 N˙m, and the recommended installation torque is 4.5 N˙m. 

Factors causing installation failure of special polyimide insulating sleeves

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The state and evolution of Gold Open Access: A country level analysis

Point cloud slicing-based extraction of indoor components

Factors causing installation failure of special polyimide insulating sleeves