antelope | Antelope Realtime Events framework for feature engineering

I want to install MOODLE 3.10.1 in the local server (xampp windows 10 pc) for my own learning. According to the installation guide I need to Compile the following

"Your database uses Antelope as the file format. Full UTF-8 support in MySQL and MariaDB requires the Barracuda file format. Please switch to the Barracuda file format. See the documentation MySQL full Unicode support for details."

According to the moodle installation guide (https://docs.moodle.org/310/en/MySQL_full_unicode_support), I ran the following SQL command and I am getting the following error.

#1238 - Variable 'innodb_file_format' is a read only variable

Other details of PHP MYADMIN

• PHP Version 7.3.26
• System Windows NT DESKTOP-LTTS1D7 10.0 build 18363 Windows 10) AMD64
• Build Date Jan 5 2021 15:04:15
• Compiler MSVC15(Visual C++ 2017)

I already tried uninstalling and reinstalling but it does not work. In PHP 7.1 version this problem doesn't occur but moodle installation required PHP 7.2 or above.

Thank you in advance.

Say for example I have this text:

hello world **ant*** lorem **cat** opposum** *** ***antelope*** *rabbit __dog__

I would like to match strings that only have ** and __ as its preceding and concluding characters. So in the case above, the matches that I would only want are "cat" and "dog". This means that I have to cancel or negate the match if there are extra surrounding characters. For example, ***dog** or __dog___ should fail.

I've tried to solve this using a negative look around http://www.regular-expressions.info/lookaround.html to no avail.

Here's the current pattern I have

I have the following dataset:

I'm struggling to reorder the bars in the plot and the legend, following the data structure (SD,MB,FI,FO,NP). Here is my data;

I have a query regarding the extraction of VGG16/VGG19 features for my experiments.

The pre-trained VGG16 and VGG19 models have been trained on ImageNet dataset having 1000 classes (say c1,c2, ... c1000) and normally we extract the features from first and second fully connected layers designated ('FC1' and 'FC2'); these 4096 dimensional feature vectors are then used for computer vision tasks.

My question is that can we use these networks to extract features of an image that does not belong to any of the above 1000 classes ? In other words, can we use these networks to extract features of an image with label c1001 ? Remember that c1001 does not belong to the Imagenet classes on which these networks were initially trained on.

In the article available on https://www.pyimagesearch.com/2019/05/20/transfer-learning-with-keras-and-deep-learning/, I am quoting the following -

When performing feature extraction, we treat the pre-trained network as an arbitrary feature extractor, allowing the input image to propagate forward, stopping at pre-specified layer, and taking the outputs of that layer as our features

From the above text, there is no restriction to whether the image must necessarily belong to one of the Imagenet classes.

Kindly spare some time to uncover this mystery.

In the research papers, the authors simply state that they have used features extracted from VGG16/VGG19 network pre-trained on Imagenet dataset without giving any further details.

I am giving a case study for reference:

Animal with Attribute dataset (see https://cvml.ist.ac.at/AwA2/) is a very popular dataset with 50 animal classes for image recognition task. The authors have extracted ILSVRC-pretrained ResNet101 features for the above dataset images. This ResNet 101 network has been pre-trained on 1000 imagenet classes (different imagenet classes are available at https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a#file-imagenet1000_clsidx_to_labels-txt).

Also, the AWA classes are put as follows:

I have two different dataframes: A, B. The column Event has similar data that I'm using to compare the two dataframes. I want to give Dataframe A a new column, dfA.newContext#.

In order to do this, I'll need to use the Event column. I want to iterate through Dataframe A to find a match for Event and assign the dfB.context# to dfA.newContext#

I think a loop would be the best way since I have a few conditions that I need to check.

This might be asking a bit much but I'm really stuck.. I want to do something like this:

Question

I would like to reorder my facet_wrap by the values in the title. Currently, the lowest value is in the upper left corner with the highest value (percentage) in the lower right corner. Is there any way to reorder the facets so the highest value is in the top left and the lowest in the bottom right?

Current Code

Request

I was able to identify the minimum and maximum in_state_total values by the group. I would like to add another column that calculates the percent difference between the maximum value and the minimum value for each group. The result should occupy both rows for each group so I can further sort the data before plotting. I would prefer a dplyr approach, but am open to exploring other options in order to deepen my understanding of the issue and the potential solutions.

Current Code

I would like to have a dynamic/perfect box/rectangle/table outside of a text.

In this example, I've a few variables arranged in 3 rows.

The problem started when the length of the strings are different.

How do I fix this problem?

Sample code