crowd | Dockerized Atlassian Crowd | Continuous Deployment library

Can someone please tell me how to solve this question? And the thought process - like how do you think while solving this. It is driving me crazy. :(

Question - The attendance table logs the number of people counted in a crowd each day an event is held. Write a query to return a table showing the date and visitor count of high-attendance periods, defined as three consecutive entries (not necessarily consecutive dates) with more than 100 visitors.

Question code on oracle -

In Vaadin 14.6.1, I tried to create a Vaadin heatmap foollowing the documentation / example from here.

However, I encountered a few problems/questions, listed in descending order of importance below:

1. The heatmap supported 30 rows by 30 columns; but when I tried 40 rows by 40 columns, the entire heatmap showed a single color (blue in my case).
2. Is it possible to manually set the minimum numeric value and maximum numeric value for the color scheme. This way, if I plot my data one day and it has values in the range of 0 to 1, but on another dataset from another day, the numeric values range from between 0 and 0.5, the color scheme range won't automatically change (to being between 0 and 0.5) and confuse the user.
3. In the documentation, it has the following methods listed, but they do not seem to exist in Vaadin 14.6.1

I am using this tutorial for instance segmentation in PyTorch. The test data the tutorial uses includes images and accompanying image masks from a dataset available here. I have an example of one of the image masks from that data set here (example data for this question). That mask looks like this by default in the dataset:

The tutorial uses this code:

I can't find an exact solution for this on SO. I have a Crowd class which consists of a Crowd object which is an arraylist of type People. People is a class with properties String name, Double bankBalance, Integer numberOfCarsOwned.

In my crowd class I have the following method whereby I seek to filter by names beginning with the letter P and return these an arraylist of type String:

I have a small peculiar task at hand and I couldn't figure out how to best implement a solution.

I have three workstations that are connected to a NAS running Ubuntu 20.04 LTS, via InfiniBand with 40gbps of bandwidth. This NAS is equipped with a 2TB NVMe SSD as write cache, and 7 RAID0 units as the main storage.

These workstations will spit out raw data to this NAS for later use, each of these machines will spit out somewhere around 6TB of data files each day, sizing from 100 - 300 GB each file. In order to prevent the network gets too crowded, I have them output the data to the NVMe cache first, then I plan to distribute the data files from there - exactly one file to each of the RAID0 units concurrently to maximize disk IO. For example, file1 goes to array0, file2 goes to array1, file3 goes to array2, and so on.

Now I am writing a script on the NAS side (preferably as a systemd service, but I can do with nohup) to monitor the cache, and send the file to these RAID arrays.

Here's what I come up with, and it is very close to my goal thanks to this post.

I am attempting to run a crowd estimation model that classifies the images into three different broad categories depending on how many people there are in the images. 1200 images are used for training, with 20% of it used for validation. I used sentdex's tutorial on Youtube as reference to load the image data into the model; I load the images as a zip file, extract it and categorise them based on the folders they are in.

My issue is that whenever I attempt to train the model, I noticed that the loss and validation loss is always 0, which has resulted in the model not exactly training and the validation accuracy remaining the same throughout, as seen here. How can I get the loss to actually change? Is there something I am doing wrong in terms of implementation?

So far, what I have attempted is:

1. I tried to add a third convolutional layer, with little results.
2. I have also tried to change the last Dense layer to model.add(Dense(3)), but I got an error saying "Shapes (None, 1) and (None, 3) are incompatible"
3. I tried using a lower learning rate (0.001?), but the model ended up returning a 0 for validation accuracy
4. Changing the optimizer did not seem to generate any changes for me

Below is a snippet of my code so far showing my model attempt:

So, I've implemented this custom dropdown list in Vue JS (2.x) and pretty much have what I need, except once the list is open, I would like for a click outside the component (anywhere on the parent page or component) to close the list. I tried catching the blur event of the root div of my component, but it understandably didn't work, because divs don't get focus and hence cannot be blurred. So at this moment, the solution seems to be - to be able to listen for a click event outside the component. Is that possible? Can a child listen for events on its parent in Vue? If or even if not, what is the best and/or the easiest way to achieve this behavior?

Here's my code in a CodeSandbox, and I am also reproducing it below for convenience - https://codesandbox.io/s/romantic-night-ot7i8

Dropdown.vue

I have a dataset to plot with a structure like this:

The average daily sales are part of a graph which is why I am struggling to scrape the data. If there is a way to scrape the data from the graph(mainly the sales per day) help would be much appreciated.