Download Anonymous 2022 Zip
Download File ===> https://blltly.com/2tlQD5
In the settings, choose 'Anonymous submissions'. When students submit assignments, their names will be replaced by randomly-generated participant numbers so you will not know who is who. Note that this is not totally anonymous because you can reveal their identities in the assignment settings and you can work out identities from the logs - so this might not be suitable if your establishment has very precise privacy requirements.
In the settings, choose "Offline grading worksheet". When students have submitted, click "View/grade all submissions" and you can download their assignments from the link "Download all submissions" and download the grading sheet from the link "Download grading worksheet". You can then edit grades and re-upload the grading worksheet. You can also upload multiple feedback files in a zip from this drop down menu. See Assignment settings for an explanation of how to use the "upload multiple feedback files as zip" feature.
If you need to divide submissions between more than one person, you can apply groups to the assignment and let markers know which group(s) to mark. Note that because group membership is not itself anonymised, this may make anonymised submissions that bit less anonymous, though as long as the groups aren't very small this should be acceptable.
Note: To ensure that comments display to students as the marker intends, do instruct students to download the annotated PDF rather than just previewing it. Preview sometimes displays comments in a way which obscures the original text.
File submissions will be downloaded in the format uploaded by the student. Online text submissions will be downloaded as html files. Each file in the zip will be named with the student first and last name followed by a unique identifier (not the user ID number).
If each submission is more than a single file, then submissions may be downloaded in folders by ticking the option 'Download submissions in folders' (below the grading table). Each submission is put in a separate folder, with the folder structure kept for any subfolders, and files are not renamed. Each folder will be named with the student first and last name followed by a unique identifier (not the user ID number).
Note: Helpfully that downloaded worksheet will contain any existing grades and summary comments which have already been given for that assignment i.e. if marking has already started. However, to see pre-existing comments fully you may need to set your spreadsheet to 'wrap text' within cells.
Use the form above to download these files. To automate or download multiple datasets, you can download a program called wget. Due to increased web security, the anonymous FTP server is no longer available.
The second download option "Legend File" will help you reproduce the color scheme we are using. If using ArcView, you will need to copy it into your c:\esri\av_gis30\arcview\legend_avl\ directory and load it manually through the legend editor. This file does not change from day to day.
NOTE -- Latitude and Longitude are not explicitly stated in the netCDF file. The second download option "HRAP-to-LatLon" contains source code for a C-program. The program contains a function that reprojects HRAP coordinates to Lat-Lon coordinates. The fully compiled program reads the netCDF files and writes ascii files with the following fields:
ICML 2022 supports the submission of two kinds of supplementary material -- supplementary manuscripts and code/data. In particular, if an anonymous reference is made in the paper, authors should upload the referenced papers, so that the reviewers can check the results in the referred paper. The supplementary material must also be anonymized.
For code submissions, we expect authors to anonymize the submitted code. This means that author names and licenses should be removed. Submission of code through anonymous github repositories is allowed; however, they have to be on a branch that will not be modified after the submission deadline.