1,720,976 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
How to reach the circularity goal in a growing residential construction sector: A case study of the Municipality of Leiden and BAM
No full textThe Dutch government aims to become fully circular in 2050 and to reduce the virgin material demand by 50% in 2030 (Rijksoverheid, 2016). For a country that has relied on a linear economy for centuries, this will prove to be a major challenge (Circle Economy, 2020; Rijksoverheid, 2016). Simultaneously, due to urbanization, the Dutch government intends to build one million dwellings between 2016 and 2030 (Ministerie van Binnenlandse Zaken, 2020). These two goals conflict because the first one aims to reduce material demand, whereas the second indirectly increases it. So far no study has paid attention to the impact of different circular construction solutions on the abiotic material demand. This is the gap that this thesis aims to fill, using the city of Leiden as a use case. To help solve this problem, three steps were taken: 1) create a baseline of the total material demand for the residential sector, starting from the assumption that we continue to build in a linear way; 2) examine the views on circular solutions among experts; and 3) quantify the impact of certain circular solutions on the baseline in order to assess whether the goals defined by the government can be reached. The main aim of this thesis is to create a model that enables us to quantify the impact of five solutions in six different scenarios. In the first scenario the research on the potential of urban mining materials from Verhagen et al. (2020) is expanded and followed up by a second scenario in which the loadbearing structure was replaced by a (partly) wooden alternative. Thirdly, other elements of the building (e.g. facade and interior walls) were replaced by a biobased variant. In the fourth scenario the floor area of the apartments is decreased and in the fifth scenario the basements commonly built under high-rise apartment buildings are removed, whereas in the sixth, and last, scenario the first five are combined. From the analysis results that the two goals mentioned above are only achievable through a combination of multiple solutions. The total virgin abiotic material demand for an average year between 2020 and 2030 would be around 155,000-tons in the business-as-usual scenario. The biggest impact came from switching the concrete loadbearing structure to a wooden (CLT) alternative, which leads to a reduction of 46% of the virgin abiotic material demand. The second largest impact resulted from converting the low- and high-rise apartments into micro-apartments in combination with downsizing the single-family dwelling size by a quarter, which leads to a reduction of 27% of the virgin abiotic material demand. Similar to this solution is excluding basements for parking under high-rise apartment buildings, which gives a 24% reduction. This is followed by the Urban Mining scenario, in which the released circular demolition waste is recycled/reused. This scenario had an impact of 19% on the total virgin abiotic material demand but is less difficult to implement compared to downsizing living space or parking spots. The scenario with the lowest impact was replacing abiotic material in the fit-out of a building, which only yields 7% of the virgin abiotic material demand. All solutions combined the total reduction was 91%, which clearly transcends the absolute goal of 69%. The results of the quantitative part of this thesis were in line with the results from the interviews, where changing the structure was mentioned as “the biggest fish” and changing the fit-out “rumbling in the margins”.Industrial Ecolog
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
GIS Dataset: The Hague Buildings and Residences and Dutch Building Energy Labels
No full textThis dataset contains raw GIS data sourced from the BAG (Basisregistratie Adressen en Gebouwen; Registry of Addresses and Buildings). It provides comprehensive information on buildings, including advanced height data and administrative details. It also contains geographic divisions within The Hague. Additionally, the dataset incorporates energy label data, offering insights into the energy efficiency and performance of these buildings. This combined dataset serves as the backbone for an analysis on residential and space cooling demand in The Hague and its environmental impacts, which can be found in this Github repository: https://github.com/simonvanlierde/msc-thesis-ie
Geographic divisions
The outline of The Hague municipality through the Municipal boundaries (Gemeenten) layer, sourced from the Administrative boundaries (Bestuurlijke Gemeenten) dataset on the PDOK WFS service.
District (Wijken) and Neighbourhood (Buurten) layers were downloaded from the PDOK WFS service (from the CBS Wijken en Buurten 2022 data package) and clipped to the outline of The Hague.
The 4-digit postcodes layer was downloaded from PDOK WFS service (CBS Postcode4 statistieken 2020) and clipped to The Hague's outline. The postcodes within The Hague were subsequently stored in a csv file.
The census block layer was downloaded from the PDOK WFS service (from the CBS Vierkantstatistieken 100m 2021 data package) and also clipped to the outline of The Hague.
BAG data
BAG data was acquired through the download of a BAG GeoPackage from the BAG ATOM download page.
In the resulting GeoPackage, the Residences (Verblijfsobject) and Building (Pand) layers were clipped to match The Hague's outline.
3D BAG
Due to limitations imposed by the PDOK WFS service, which restricts the number of downloadable buildings to 10,000, it was necessary to acquire 145 individual GeoPackages for tiles covering The Hague from the 3D BAG website.
These GeoPackages were merged using the ogr2ogr append function from the GDAL library in bash.
Roof elevation data was extracted from the LoD 1.2 2D layer from the resulting GeoPackage.
Ground elevation data was obtained from the Pand layer.
Both of these layers were clipped to match The Hague's outline.
Roof and ground elevation data from the LoD 1.2 2D and Pand layers were joined to the Pand layer in the BAG dataset using the BAG ID of each building.
Energy labels
Energy labels were downloaded from the Energy label registry (EP-online)
GIS Data and Analysis for Cooling Demand and Environmental Impact in The Hague
No full text<p>This dataset contains raw GIS data sourced from the BAG (<i>Basisregistratie Adressen en Gebouwen</i>; Registry of Addresses and Buildings). It provides comprehensive information on buildings, including advanced height data and administrative details. It also contains geographic divisions within The Hague. Additionally, the dataset incorporates energy label data, offering insights into the energy efficiency and performance of these buildings. This combined dataset serves as the backbone of a Master's thesis in Industrial Ecology, analysing residential and office cooling and its environmental impacts in The Hague, Netherlands. The codebase of this analysis can be found in this Github repository: <a href="https://github.com/simonvanlierde/msc-thesis-ie"><strong>https://github.com/simonvanlierde/msc-thesis-ie</strong></a></p><p>The dataset includes a background research spreadsheet containing supporting calculations. It also presents geopackages with results from the cooling demand model (CDM) for various scenarios: Status quo (SQ), 2030, and 2050 scenarios (Low, Medium, and High)</p><h3>Background research data</h3><p>The <i>background_research_data.xlsx</i><strong> </strong>spreadsheet contains comprehensive background research calculations supporting the shaping of input parameters used in the model. It contains several sheets:</p><ul><li><strong>Cooling Technologies</strong>: Details the various cooling technologies examined in the study, summarizing their characteristics and the market penetration mixes used in the analysis.</li><li><strong>LCA Results of Ventilation Systems</strong>: Provides an overview of the ecoinvent processes serving as proxies for the life-cycle impacts of cooling equipment, along with calculations of the weight of cooling systems and contribution tables from the LCA-based assessment.</li><li><strong>Material Scarcity</strong>: A detailed examination of the critical raw material content in the material footprint of ecoinvent processes, representing cooling equipment.</li><li><strong>Heat Plans per Neighbourhood</strong>: Forecasts of future heating solutions for each neighbourhood in The Hague.</li><li><strong>Building Stock</strong>: Analysis of the projected growth trends in residential and office building stocks in The Hague. AC Market: Market analysis covering air conditioner sales in the Netherlands from 2002 to 2022.</li><li><strong>Climate Change</strong>: Computations of climate-related parameters based on KNMI climate scenarios.</li><li><strong>Electricity Mix Analysis</strong>: Analysis of future projections for the Dutch electricity grid and calculations of life-cycle carbon intensities of the grid.</li></ul><h3>Input data</h3><p><strong>Geographic divisions</strong></p><ul><li>The outline of The Hague municipality through the Municipal boundaries (<i>Gemeenten</i>) layer, sourced from the <a href="http://www.pdok.nl/geo-services/-/article/bestuurlijke-gebieden">Administrative boundaries (<i>Bestuurlijke Gemeenten</i>) dataset</a> on the PDOK WFS service.</li><li>District (<i>Wijken</i>) and Neighbourhood (<i>Buurten</i>) layers were downloaded from the PDOK WFS service (from the <a href="https://www.pdok.nl/geo-services/-/article/cbs-wijken-en-buurten#df0df8fa1c3bab1a71a2f09d990abd7e"><i>CBS Wijken en Buurten 2022</i></a><i> </i>data package) and clipped to the outline of The Hague.</li><li>The 4-digit postcodes layer was downloaded from PDOK WFS service (<a href="http://www.pdok.nl/ogc-webservices/-/article/cbs-postcode4"><i>CBS Postcode4 statistieken 2020</i></a>) and clipped to The Hague's outline. The postcodes within The Hague were subsequently stored in a csv file.</li><li>The census block layer was downloaded from the PDOK WFS service (from the <a href="http://www.pdok.nl/introductie/-/article/cbs-vierkantstatistieken-100m"><i>CBS Vierkantstatistieken 100m 2021</i></a> data package) and also clipped to the outline of The Hague.</li><li>These layers have been combined in the <i>GeographicDivisions_TheHague</i> GeoPackage.</li></ul><p><strong>BAG data</strong></p><ul><li>BAG data was acquired through the download of a BAG GeoPackage from the BAG <a href="https://www.pdok.nl/downloads/-/article/basisregistratie-adressen-en-gebouwen-ba-1">ATOM download page</a>.</li><li>In the resulting GeoPackage, the Residences (<i>Verblijfsobject</i>) and Building (<i>Pand</i>) layers were clipped to match The Hague's outline.</li><li>The resulting residence data can be found in the <i>BAG_buildings_TheHague</i> GeoPackage.</li></ul><p><strong>3D BAG </strong></p><ul><li>Due to limitations imposed by the PDOK WFS service, which restricts the number of downloadable buildings to 10,000, it was necessary to acquire 145 individual GeoPackages for tiles covering The Hague from the <a href="http://3dbag.nl/nl/download">3D BAG website</a>.</li><li>These GeoPackages were merged using the <i>ogr2ogr</i> <i>append</i> function from the <a href="http://gdal.org/index.html">GDAL library </a>in bash.</li><li>Roof elevation data was extracted from the <i>LoD 1.2 2D</i> layer from the resulting GeoPackage.</li><li>Ground elevation data was obtained from the <i>Pand</i> layer.</li><li>Both of these layers were clipped to match The Hague's outline.</li><li>Roof and ground elevation data from the <i>LoD 1.2 2D</i> and <i>Pand</i> layers were joined to the <i>Pand</i> layer in the BAG dataset using the <i>BAG ID</i> of each building.</li><li>The resulting data can be found in the <i>BAG_buildings_TheHague</i> GeoPackage.</li></ul><p><strong>Energy labels</strong></p><ul><li>Energy labels were downloaded from the <a href="http://www.ep-online.nl/PublicData">Energy label registry</a> (<i>EP-online</i>) and stored in <i>energy_labels_TheNetherlands</i>.<i>csv</i>.</li></ul><p><strong>UHI effect data</strong></p><ul><li>A bitmap with the UHI effect intensity in The Hague was retrieved from the from the <a href="https://www.atlasnatuurlijkkapitaal.nl/kaarten?config=58bf95bc-67bf-402d-a355-af211ad33949&gm-x=121187.11870218973&gm-y=467370.5793842884&gm-z=3.1666666666666665&gm-b=1544180834512,true,1;1554714019959,true,0.8;&activateOnStart=layermanager&deactivateOnStart=layercollection">Dutch Natural Capital Atlas</a> (<i>Atlas Natuurlijk Kapitaal</i>) and stored in <i>UHI_effect_TheHague.tiff</i>.</li></ul><h3>Output data</h3><ul><li>The residence-level data joined to the building layer is contained in the <i>BAG_buildings_with_residence_data_full</i> GeoPackage.</li><li>The results for each building, according to different scenarios, are compiled in the <strong>buildings_with_CDM_results_[scenario]_full</strong> GeoPackages. The scenarios are abbreviated as follows:<ul><li><strong>SQ</strong>: Status Quo, covering the 2018-2022 reference period.</li><li><strong>2030</strong>: An average scenario projected for the year 2030.</li><li><strong>2050_L</strong>: A low-impact, best-case scenario for 2050.</li><li><strong>2050_M</strong>: A medium-impact, moderate scenario for 2050.</li><li><strong>2050_H</strong>: A high-impact, worst-case scenario for 2050.</li></ul></li></ul><p> </p>
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