chase | Cyber Hate detection And tracking on Social mEdia
kandi X-RAY | chase Summary
kandi X-RAY | chase Summary
This repository contains experimental code for the work described in: Zhang, Z., Robinson, D., Tepper, J. (2018). Detecting Hate Speech on Twitter Using a Convolution-GRU Based Deep Neural Network. In Proceedings of the 2018 Extended Semantic Web Conference. For the datasets used in this research (including the one created by this work), please download them here. Please give credits to their original data distributors. CONTACT CHANGE Please direct all emails to ziqi do zhang at sheffield dot ac dot uk, as I no longer have acess to my NTU email.
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- Create a final model with concatenation
- Adds the sklearn model to the list of models
- Create a L1L2L2L2L2L2
- Create a list of Conv1D Conv1D
- Process data received
- Index keywords
- Ignores retweet
- Create a pre - trained model from the given model descriptor
- Creates a SequentialModel from input layers
- Creates an array of authors based on the vote
- Calculate stats for i2UU
- Compute weighted vote corpus
- Collect wrong predictions for wrong prediction
- Apply feature scaling
- Read preselected features
- Get tweets by timespan
- Finds the number of instances that have a given IDW
- Replace and create a single class
- Calculates the class unique features for each class
- Perform grid search
- Wrapper for GridSearch
- Check the stats of the class1 and class2
- Create a list of settings for training
- Index tweet data
- Calculate the weight distribution of a tweet
- Train a single classifier
chase Key Features
chase Examples and Code Snippets
Community Discussions
Trending Discussions on chase
QUESTION
Cut to the chase:
I've got a class User, which holds an instance of Security:
...ANSWER
Answered 2021-Jun-01 at 15:02To be able to get Security as a full object you just need to save it specifically when uploading on the Firestore database.
QUESTION
I am batch processing data using auto-scaling preemptible nodes on a GKE zonal cluster. Every now and then, GPUs become scarce. Rather than switching zones to chase GPUs (which I've already done), I've tried changing to a multi-zonal configuration. From my point of view, things seem to be working OK on some light- to medium-scale workloads.
I see warnings in the UI about unbalanced node pools, as the node pools seem to be scaling up in zones where there are available resources. Is this warning serious? What are the ramifications of different node numbers in different zones? Should I instead run separate pools per zone?
I have a fair amount of communication between nodes -- how much is my bandwidth impacted by workers being in separate zones? The GKE docs indicate no ingress limitation, and only that egress is slower than within-zone and faster than between-region.
...ANSWER
Answered 2021-Jun-01 at 14:10As per the Bandwidth summary table, there is no limitation on ingress and with respect to egress, the bandwidth connectivity between your nodes deployed in multi-zone is slightly lower compared to connectivity within a zone.
Cluster autoscaler only balance across zones during a scale-up event. Cluster autoscaler scales down underutilized nodes regardless of the relative sizes of underlying managed instance groups in a node pool which can cause the nodes to be distributed unevenly across zones.
If you specify a minimum of zero nodes, an idle node pool can scale down completely. However, at least one node must always be available in the cluster to run system Pods.
Refer to link for more information about balanced node groups.
QUESTION
I would like to create a column of 100 checkboxes to select rows.
I can create the checkboxes but as they go further down the sheet the checkboxes slowly diverge from the desired rows.
Checkbox labeled for row 101 - chkbox101 ends up in row 102. checkbox labeled chkbox101 in row 102
ANSWER
Answered 2021-May-28 at 18:46The issue was caused by running the spreadsheet on the extended desktop monitor and having fix scaling for apps turned on.
I am using a laptop with the display extended over to a second monitor. The when the spreadsheet is completely on the laptop monitor, the code achieves the expected results (Column A) (why I couldn't get it to happen above). When the code is run with the spreadsheet even partially on the external monitor the issue of non alignment shows up (Column C) - the checkboxes do not stay in the appropriate rows.
Which monitor the code is run on changes the output when fix scaling for apps is turned on.
I also changed the macro a little to allow changing the output column.
QUESTION
I following tutorial here to make the NPC or enemy character chasing the player but the NPC can't detect where the player is. The player is a prefabs that not placed in the scene, it calls when the game start. So when I'm trying another object in the scene and make it as an object to follow by NPC, the NPC can follow it. Please help me to fix it, I'm new to game development. And because its a multiplayer game, can the NPC choose which player to chase?
...ANSWER
Answered 2021-May-21 at 02:04Consider checking every now and then if the player is spawned.
You can do this a couple ways.
This post covers a lot of different ways, I would recommend checking every couple frames.
For example you can find any object by it's tag, name, or even stuff like the components it has on it.
One way you could do it is to check for tag for example.
QUESTION
I have a task in which it is necessary to determine the presence of a friendly connection. Let me explain, there is a checkpoint at work. The employee, passing through it, gets into the database, where his time of passage and his name are recorded. If an employee often passes through the point with the same person, then it is possible to assume with some probability that there is a friendly relationship between them. It is also necessary to take into account the difference in time with which they passed, if the difference in the passage is large, then they probably did not even see each other. For example, I made a small time Series:
...ANSWER
Answered 2021-May-19 at 21:23No need for clustering algorithms. Such algorithms are useful if your data has multiple traits. In this case, there is only one: arrival time. Simply keep track of how often pairs arrive "together".
QUESTION
I am wanting to customize the popup boxes (I believe called tooltips) on a highcharter chart made in R.
...ANSWER
Answered 2021-May-19 at 19:58You could use hc_tooltip and create a custom JS formatter.
Graph data is accessible through the this.point. property.
QUESTION
So, I tried a couple ideas about finding coefficient of variation, per ID, but nothing has worked out so far. I thought I could add it to my existing dataframe, like this.
...ANSWER
Answered 2021-May-17 at 21:59You can try one of the following two solutions:
1: groupby with transform
QUESTION
Here is my setup.
...ANSWER
Answered 2021-May-14 at 19:00IIUC,
QUESTION
I'm trying to use workbox-webpack-plugin.InjectManifest and all the examples I find look something like the code below, but I can't find an example of what src/sw.js is supposed to look like. I tried searching for example's of service worker files and feel like I might be starting a goose chase learning way more about service workers that I need to without actually getting an example. All I'm trying to do is include my manifest settings with my service worker. I thought I would be able to do this, considering the name of the function is called InjectManifest
ANSWER
Answered 2021-May-14 at 16:20It very much depends on the functionality you'd like in your service worker. This section of the Workbox getting started guide walks through a few use cases, including precaching and runtime caching, and the accompanying code is what would appear in your sw.js file.
At its most basic, if all you're interested in is precaching all of the assets in your webpack build, the following could be used as your sw.js:
QUESTION
let playerX;
let playerY;
let playerSize = 15;
let playerSpeed = (playerSize / Math.pow(playerSize, 1.44)) * 10;
let Newcelltimer = 0;
let cell = []
let zoom = 1;
let n = 0;
let Xgrid = 600;
let Ygrid = 600;
let cpu = [];
let x = 0;
let y = 10;
let OffSetX = [];
let OffSetY = [];
let CPUteam = 2;
function setup() {
smooth();
frameRate(999)
createCanvas(600, 450);
playerX = 500;
playerY = 100;
}
function draw() {
let cellDist = [];
let cpuDist = [];
background(220);
push();
//Changes the FOV depending on your size
let Newzoom = 10 / playerSize
let newnewZoom = 1.3 * lerp(0.9, 10 / playerSize, 0.5)
Newzoom = lerp(zoom, Newzoom, 0.3)
translate(Xgrid / 2, Ygrid / 2 - 50);
scale(newnewZoom)
translate(-playerX, -playerY);
// Player's speed
playerSpeed = round((playerSize / Math.pow(playerSize, 1.44)) * 10000) / 1000
Newcelltimer++;
//Adds in new cells
if (Newcelltimer % 40 == 0) {
cell.push(ceil(random(0 - Xgrid, 2 * Xgrid)),
ceil(random(0 - Ygrid, 2 * Ygrid)))
}
//Adds in new AI's
if (Newcelltimer % 200 == 0) {
cpu.push(ceil(random(-Xgrid, 2 * Xgrid)), ceil(random(-Ygrid, 2 * Ygrid)), 20, CPUteam)
OffSetX.push(ceil(random(0, 1000000)))
OffSetY.push(ceil(random(1000000, 2000000)))
CPUteam++;
}
//Creates AI when you start playing
if (Newcelltimer == 1 || Newcelltimer == 2) {
cpu.push(ceil(random(-Xgrid, 2 * Xgrid)), ceil(random(-Ygrid, 2 * Ygrid)), 20, CPUteam)
OffSetX.push(ceil(random(0, 1000000)))
OffSetY.push(ceil(random(1000000, 2000000)))
cell.push(ceil(random(0 - Xgrid, 2 * Xgrid)),
ceil(random(0 - Ygrid, 2 * Ygrid)))
CPUteam++;
}
//Checks if cell is eaten
for (let i = 0; i < cell.length / 2; i++) {
let d = int(dist(cell[i * 2], cell[i * 2 + 1], playerX, playerY))
if (d <= playerSize / 2) {
playerSize += 5;
cell.splice(i * 2, 2)
celliseaten = true;
}
else{
fill(0,255,255,180);
circle(i*2,i*2+1,8);
}
}
//The cells disappear after a bit
if (Newcelltimer % 200 == 0) {
cell.splice(0, 2)
}
//Everything to do with the AI system
for (let j = 0; j < (cpu.length / 4); j++) {
let cpuDist = [];
let distance = int(dist(cpu[j * 4], cpu[j * 4 + 1], playerX, playerY)) //Distance between AI and player
if (distance <= playerSize / 2 && cpu[j * 4 + 2] < playerSize) {
playerSize += floor(cpu[j * 4 + 2]);
cpu.splice(j * 4, 4)
}
else if(distance<=cpu[j*4+2]/2&&cpu[j*4+2] cpu[j * 4 + 2]) ? cpu[m * 4 + 2] : cpu[j * 4 + 2];
if (higher > distant) {
if (cpu[m * 4 + 2] > cpu[j * 4 + 2]) {
cpu[m * 4 + 2] += cpu[j * 4 + 2]
cpu.splice(j * 4, 4)
} else {
cpu[j * 4 + 2] += cpu[m * 4 + 2]
cpu.splice(m * 4, 4)
} //Else
} //If
//If AI didn't eat another AI, return the distance
else {
cpuDist.push(distant);
} //Else
} //If
} //If
} //For
let ClosestCpu = min(cpuDist);
let ClosestCpupos;
//Index value of the closest cpu (NOT WORKINGS)
for (var q = 0; q < cpu.length / 4; q++) {
if (ClosestCpu == int(dist(cpu[q * 4], cpu[q * 4 + 1], cpu[j * 4], cpu[j * 4 + 1]))) {
ClosestCpupos = q;
break;
}
}
//Checks if AI ate cell
for (let n = 0; n < cell.length / 2; n++) {
let dis = int(dist(cell[n * 2], cell[n * 2 + 1], cpu[j * 4], cpu[j * 4 + 1]))
if (dis <= cpu[j * 4 + 2] / 2) {
cpu[j * 4 + 2] += 5;
cell.splice(n * 2, 2)
} else {
//If it didn't eat the cell, does the same idea with the AI from before
cellDist.push(dis)
}
}
let ClosestCell = min(cellDist);
let ClosestCellpos;
for (let r = 0; r < cell.length / 2; r++) {
if (ClosestCell == int(dist(cell[r * 2], cell[r * 2 + 1], cpu[j * 4], cpu[j * 4 + 1]))) {
ClosestCellpos = r;
break;
}
}
//AI sppeed
let amp = round((cpu[j * 4 + 2] / Math.pow(cpu[j * 4 + 2], 1.44)) * 70000) / 7000;
if (dist(playerX, playerY, cpu[j * 4], cpu[j * 4 + 1]) < 150 && playerSize > cpu[j * 4 + 2]) {
let distXpos = cpu[j * 4]-playerX;
let distYpos = cpu[j * 4 + 1]-playerY;
let higherVal = (abs(distXpos) > abs(distYpos)) ? distXpos : distYpos;
let MultVal = 150/abs(higherVal);
distXpos*=MultVal;
distYpos*=MultVal;
distXpos = map(distXpos, -150, 150, -1, 1);
distYpos = map(distYpos, -150, 150, -1, 1);
cpu[j * 4] += distXpos * amp;
cpu[j * 4 + 1] += distYpos * amp;
} else if (dist(playerX, playerY, cpu[j * 4], cpu[j * 4 + 1]) < 150 && playerSize < cpu[j * 4 + 2]) {
let distXpos = cpu[j * 4]-playerX;
let distYpos = cpu[j * 4 + 1]-playerY;
let higherVal = (abs(distXpos) > abs(distYpos)) ? distXpos : distYpos;
let MultVal = 150/abs(higherVal);
distXpos*=MultVal;
distYpos*=MultVal;
distXpos = map(distXpos, -150, 150, -1, 1);
distYpos = map(distYpos, -150, 150, -1, 1);
cpu[j * 4] -= distXpos * amp;
cpu[j * 4 + 1] -= distYpos * amp;
}
else if (dist(cpu[ClosestCpupos * 4], cpu[ClosestCpupos * 4 + 1], cpu[j * 4], cpu[j * 4 + 1]) < 150 && cpu[j * 4 + 2] > cpu[ClosestCpupos * 4 + 2]) {
let distXpos = cpu[ClosestCpupos * 4] - cpu[j * 4];
let distYpos = cpu[ClosestCpupos * 4 + 1] - cpu[j * 4 + 1];
let higherVal = (abs(distXpos) > abs(distYpos)) ? distXpos : distYpos;
let MultVal = 150/abs(higherVal);
distXpos*=MultVal;
distYpos*=MultVal;
distXpos = map(distXpos, -150, 150, -1, 1);
distYpos = map(distYpos, -150, 150, -1, 1);
cpu[j * 4] += distXpos * amp;
cpu[j * 4 + 1] += distYpos * amp;
} else if (dist(cpu[ClosestCpupos * 4], cpu[ClosestCpupos * 4 + 1], cpu[j * 4], cpu[j * 4 + 1]) < 150 && cpu[j * 4 + 2] > cpu[ClosestCpupos * 4 + 2]) {
let distXpos = cpu[ClosestCpupos * 4] - cpu[j * 4];
let distYpos = cpu[ClosestCpupos * 4 + 1] - cpu[j * 4 + 1];
let higherVal = (abs(distXpos) > abs(distYpos)) ? distXpos : distYpos;
let MultVal = 150/abs(higherVal);
distXpos*=MultVal;
distYpos*=MultVal;
distXpos = map(distXpos, -150, 150, -1, 1);
distYpos = map(distYpos, -150, 150, -1, 1);
cpu[j * 4] -= distXpos * amp;
cpu[j * 4 + 1] -= distYpos * amp;
} else if (dist(cell[ClosestCellpos * 2], cell[ClosestCellpos * 2 + 1], cpu[j * 4], cpu[j * 4 + 1]) < 150) {
let distXpos = cell[ClosestCellpos * 2] - cpu[j * 4];
let distYpos = cell[ClosestCellpos * 2 + 1] - cpu[j * 4 + 1];
let higherVal = (abs(distXpos) > abs(distYpos)) ? distXpos : distYpos;
let MultVal = 150/abs(higherVal);
distXpos*=MultVal;
distYpos*=MultVal;
distXpos = map(distXpos, -150, 150, -1, 1);
distYpos = map(distYpos, -150, 150, -1, 1);
cpu[j * 4] += distXpos * amp;
cpu[j * 4 + 1] += distYpos * amp;
} else {
x += 0.003;
y += 0.003;
let offsetX = map(noise(x + OffSetX[j]), 0, 1, -1, 1) * amp;
let offsetY = map(noise(y + OffSetY[j]), 0, 1, -1, 1) * amp;
cpu[j * 4] += offsetX;
cpu[j * 4 + 1] += offsetY;
}
if (cpu[j * 4 + 3] % 2 == 0) {
fill(0, 0, 255)
circle(cpu[j * 4], cpu[j * 4 + 1], cpu[j * 4 + 2]);
} else {
fill(255, 0, 0)
circle(cpu[j * 4], cpu[j * 4 + 1], cpu[j * 4 + 2])
} // Else
} //Cpu for
//Draws player
fill(255, 255, 0)
circle(playerX, playerY, playerSize)
pop();
}
ANSWER
Answered 2021-May-12 at 19:02This is happening because the AI moves more quickly and more efficiently than the player. Suppose the CPU moves 3 pixels per frame and the player moves 1. Now consider the following:
- The CPU is 149 pixels away from the player, so it moves 3 pixels away from the player and the player moves 1 pixel toward the CPU
- Next frame: CPU is 151 pixels away, so it reverts to its normal behavior.
- Next frame: the player has moved closer, so it reverts to being chased.
- repeat
This alternating between states is what causes the vibration you see. How do you solve this? One solution is to give each CPU a boolean value for being chased. You can set this to true when the CPU comes within 150 of the player, and then set it back to false when it gets to be 200 away. That way, it won't oscillate because it needs to move 50 pixels in order to change behavior. In order to do this, you need to change all of the instances of j * 4 to j * 5 and give cpu[j * 5 + 4] an initial boolean value. Here's my solution for testing:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install chase
You can use chase like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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