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18,658 results for “impacts”
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 1, dates: 13 July 2023-28 July 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 7, dates: 16 December 2023-30 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 7, dates: 24 August 2023-11 October 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 7, dates: 16 December 2023-30 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 1, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 1, dates: 16 December 2023-30 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 1, dates: 24 August 2023-11 October 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 1, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 7, dates: 27 June 2023-04 July 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 7, dates: 24 August 2023-11 October 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 1, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: IDENTITY, days: 7, dates: 16 December 2023-30 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 7, dates: 13 July 2023-28 July 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Public data on WIT's 18 years impact survey
<p>Dataset (answers and codebooks) related to research on the impact that wrote the history of <strong>WIT during 18 years</strong>. The artifacts were used for the <strong>quantitative and qualitative analyses</strong>.</p>
The Impact of Biases on Health Disinformation Research
Open the record for dataset details and reuse information.
Replication Package for "On The Impact of Adopting AI Libraries in Open Source Projects. A Large Scale Study"
<p># Replication Package for the Paper: "On The Impact of Adopting AI Libraries in Open Source Projects. A Large Scale Study"</p> <p>This replication package includes the raw data, questionnaire answers, and a Python notebook to reproduce the results detailed in the paper "On The Impact of Adopting AI Libraries in Open Source Projects. A Large Scale Study"</p> <p>## Repository Structure<br>1. **Results:** Contains Excel files with the responses from the 2 human experts and the 5 models and the review of the 3 human reviewers.<br>2. **Tables:** Contains the full Wilcoxon Test Results for H01 and H02 as well as the Anderson Darling test for normality and the Spearmans' Rho.</p> <p>## Replication Process<br>To replicate the results of our study, open the provided Python Notebook in Google Colab and follow the instructions to reproduce the results seamlessly.</p> <p># Instructions for Use<br>To utilize this replicability package, refer to the steps outlined in the notebook file.</p> <p># Remarks<br>If you encounter any issues or have any questions, please get in touch with the paper's authors. We will be glad to assist you!</p>
Enhancing Change Impact Prediction by Integrating Evolutionary Coupling with Software Change Relationships
<div> <div><strong>Replication Package For Paper: Enhancing Change Impact Prediction by Integrating Evolutionary Coupling with Software Change Relationships</strong></div> <br> <div>IMPER is a change <strong>IM</strong>pact <strong>P</strong>rediction method that integrates <strong>E</strong>volutionary coupling with software change <strong>R</strong>elationships. The approach consists of following four main steps:</div> <br> <div><em>Step 1</em>: Relevant Transaction Filtering. Filtering the relevant transaction set based on the given query $<em>Q</em>$.</div> <div><em>Step 2</em>: Association Rule Generation. Generating association rules and obtaining the impact candidate set.</div> <div><em>Step 3</em>: Spatial-Temporal Window Processing. Considering the temporal and spatial change relationships to obtain the impact candidate set.</div> <div><em>Step 4</em>: Candidates Integrating and Ranking. Making a union of these two sets to find the final impact set.</div> <br> <div>The repo provides files for the paper replication. It includes::</div> </div> <div> </div> <div><strong>git_repo.zi</strong>p: Git repository used in the study.</div> <div><em><strong>***-rec-database-1107.tar.gz</strong>:</em> Neo4j dataset containing entity-level software relationship graphs and change information (changed classes, member member methods, member member variables, and files) from over 19,003 versions of six well-maintained projects.</div> <div><strong><em>code_entiy_genealogy</em></strong>: Data for code entity genealogy.<br> <div><em><strong>imper_jar.zip</strong>:</em> Tool for the study, including: 1) Generating qualified queries; 2) Change prediction using four approaches (ROSE, TARMAQ, IMPER, IMPER-ST); 3) Evaluation. The tool outputs evaluation results for each query and average metrics (MAP, Precision, Recall, and F1-score).</div> <div><strong><em>evaluation_metrics_details.zip</em></strong>: Detailed evaluation metric results for different projects.</div> <div><strong><em>Imper_evaluation_results.xlsx</em></strong>: Summary of evaluation metric results for all projects.</div> <div> </div> <br> <div>Users are suggested to refer to the research paper for more detials.</div> <br> <div>This project is still in an early stage of development, and we are improving the implementation and documentation. Please feel free to contact ******(author) for the replication package.</div> <br><strong>Environment</strong><br> <div>- java 11+</div> <div>- <a href="https://neo4j.com/download-center/#community">neo4j 4.2</a> </div> <div>- memory 64G+</div> <br><strong>Quick Start</strong>:<br>To begin our study, follow these steps. Note that only one project can be analyzed at a time.</div> <div><br><strong><em>Step 1: Database Setup</em></strong></div> <div> </div> <div>Copy the relevant database to the folder `data` (in the root path of the Neo4j database), copy the plugins to the plugin folder, and open the database using Neo4j 4.2 (Recommended).</div> <div><br><strong><em>Step 2: Configure application-dev.yml</em></strong></div> <div> </div> <div>Adjust the application-dev.yml file in the folder `imper_jar` to match your configuration. If you're using an existing database, simply configure the database address, username, and password. <div> <p> </p> </div> </div> <div><strong><em>Step 3: Run imper-study.jar</em></strong></div> <div><br>Command: `<em>java -jar imper-study.jar -imp -config ./application-dev.yml -rd /home/user/code_rec -pj commons-io -fi commons-io_file(Map)_1031.txt -mi commons-io_functionInfo(Map).txt -tw 35 -mc 20 -od /home/user/code_rec</em>`.</div> <div><br> <div>-imp: Used to run IMPER</div> <div>-config: Path of `<em>application-dev.yml</em>`.</div> <div>-rd: Root path of code entiy genealogy, e.g., `<em>/home/user/code_rec</em>`.</div> <div>-pj: Project name, e.g., `<em>commons-io</em>`.</div> <div>-fi: the code entiy genealogy (file), e.g., `<em>commons-io_file(Map)_1031.txt</em>` (the absolute path is `<em>/home/user/code_rec/commons-io/commons-io_file(Map)_1031.txt</em>`).</div> <div>-mi: the code entiy genealogy (method), e.g., `<em>commons-io_functionInfo(Map).txt</em>` (the absolute path is `<em>/home/user/code_rec/commons-io/commons-io_functionInfo(Map).txt</em>`).</div> <div>-tw: Time window (half), e.g., <em>-tw 35 (the time window size is 70).</em></div> <div>-mc: Maxium commit size in the time window.</div> <div>-od: Output root path for evaluation results (MAP, Precison, Recall and F1-score), e.g., `<em>/home/user/code_rec</em>`.</div> </div>
The derived data in manuscript Oblique impact adjacent to Chang'E-5 landing site: Fine-scale analysis and implication on the provenance of returned samples
<p>This website contains the derived data in the <em>manuscript <span>Oblique impact adjacent to Chang’E-5 landing site: </span><span>F</span><span>ine-scale analysis and implication on the provenance of returned samples </span></em>by <span>Wenhui Wu</span><span>, </span><span>Zhaopeng Chen</span><span>, Xin Ren</span><span>, Dawei Liu</span><span>,</span><span> </span><span>Xingguo Zeng, Yuan Chen, Wangli Chen, Wei Yan, Bin Liu,Xiaoxia Zhang, Jianjun Liu</span> for <em><span>Journal of Geophysical Research: Planets</span></em></p>
Study on the degradation pattern of impact crater communities in Yutu-2's rovering area
<p>Here are the DEM data and DOM data created using images taken by the Yutu-2 rover along the route between the 27th and 33rd moon days.</p> <p>And the extracted impact craters contain their degradation levels.</p> <p>All impact craters are classified into 5 categories (A-AB-B-BC-C)</p>
Hydrothermal conditions modulate the impact of climate extremes on vegetation growth in the Northern Hemisphere
<p><strong><span>Aim</span></strong></p> <p>Climate extremes are becoming more frequent under global warming, with substantial repercussions for vegetation growth. The degree to which climate extremes increase the risk of high-impact events on vegetation growth is of high concern.</p> <p><strong>Location</strong></p> <p>Northern Hemisphere (north of 30° N)<span>.</span></p> <p><strong>Time Period</strong></p> <p><span>F</span>rom 2001 to 2022<span>.</span></p> <p><strong>Major Taxa Studied</strong></p> <p><span>P</span><span>l</span><span>ants</span><span>.</span></p> <p><strong>Methods</strong></p> <p><span>W</span>e utilized solar-induced chlorophyll fluorescence (SIF) and the normalized difference vegetation index (NDVI) as proxies for vegetation growth and performed event coincidence and sensitivity analyses to attribute satellite-derived vegetation growth extremes to diverse climate extremes (extreme heat, cold, wet, and drought) in the Northern Hemisphere.</p> <p><strong>Results</strong></p> <p>Our results showed that extreme heat and cold were the main climatic extremes that induced positive and negative vegetation growth extremes north of 30° N, respectively, mainly in cold and humid ecosystems (boreal and temperate forests). Water-related extreme events accounted for less than one-third of vegetation extremes. The contribution of drought to positive vegetation growth extreme events (approximately 17%), mainly in cold and humid ecosystems, was even slightly higher than that of extreme wet (approximately 12%), which predominantly impacted relatively warm and arid ecosystems (croplands and temperate grasslands). We further identified potential climatic thresholds that could induce a reversal of vegetation growth responses to climate extremes and showed that the past <span>two</span> decades of warming and precipitation changes did not induce a shift in the main climatic drivers of vegetation extremes across northern ecosystems.</p> <p><strong>Main Conclusions</strong></p> <p>Our results emphasize the crucial role of background hydrothermal conditions in the attribution of vegetation growth extremes to diverse climate extremes across northern ecosystems and have substantial implications for predicting how Northern Hemisphere vegetation will respond to increasing climate extremes in the future.</p>
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