Internal changes of the specimen of 0.86 to 0.88. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.7 to 0.75. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.87 to 0.9. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.74 to 0.76. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen 1.55 to 1.60. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 1.70 to 1.75. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.89 to 1. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

<b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b> by Marly G F Costa (19812192)

“…<p dir="ltr"><b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b></p><p dir="ltr">The code was developed in the Google Collaboratory environment, using Python version 3.7.13, with TensorFlow 2.8.2. …”

Number of tweets collected over time. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Descriptive measures of the dataset. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Corpora from the articles in order of size. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Media information. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Information from interactions. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Table of the database statistical measures. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Tweets information. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Examples of tweets texts (Portuguese). by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Methodological flowchart. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Number of tweets collected per query and type. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Examples of tweets texts (English). by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”

Users information. by Sylvia Iasulaitis (8301189)

“…Python algorithms were developed to model each primary collection type. …”