Auto industry basks in a ‘false sense of security’ over trade
The risk of potential tariffs on auto parts imported into the U.S. is not yet completely removed despite the assumption by most industry watchers to the contrary, a BofA analyst warned.
Since no action was taken or announced on November 14 -- which marked the expiry of a 180 day period that President Donald Trump triggered in May to postpone tariffs on imported autos and auto parts pending bilateral trade negotiations -- there is now a broader belief that Trump has effectively lost his authority on implementing those tariffs, analyst John Murphy explained.
However, he questioned whether the industry has been lulled into a "false sense of security” as it’s possible that Trump may attempt to exert his authority and impose these tariffs on any relevant country at any point during the course of trade negotiations, further prolonging uncertainty.
"Trump may/can still attempt to implement Section 232 Autos tariffs,” the analyst added, noting that such an action could be vulnerable to court challenge.
Europe is the key trading bloc where the tariff pressures appear to be most acute, Murphy said, while Japan and Korea are likely in the clear. The analyst noted that according to the Center for Automotive Research, should the Section 232 tariffs be implemented on current non-exempt countries, the incremental price per unit would be around $2,750 per vehicle or a reduction in sales of about 1.3 million units.
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Hi,
I have rebooted my raspberry pi and emonhub is no longer receiving anything. In the emonhub log file the error "Device communication error - check setting" is reported.
Here below an extract of my emonhub log file.
2016-02-12 19:37:07,305 DEBUG MainThread SIGINT received.
2016-02-12 19:37:07,307 INFO MainThread Exiting hub...
2016-02-12 19:37:07,496 INFO MainThread Exit completed
2016-02-12 19:37:21,745 INFO MainThread EmonHub emonHub 'emon-pi' variant v1.1
2016-02-12 19:37:21,757 INFO MainThread Opening hub...
2016-02-12 19:37:21,765 INFO MainThread Logging level set to DEBUG
2016-02-12 19:37:21,775 INFO MainThread Creating EmonHubJeeInterfacer 'RFM2Pi'
2016-02-12 19:37:21,800 DEBUG MainThread Opening serial port: /dev/ttyAMA0 @ 9600 bits/s
2016-02-12 19:37:23,808 WARNING MainThread Device communication error - check settings
2016-02-12 19:37:23,815 INFO MainThread Setting RFM2Pi frequency: 433 (4b)
2016-02-12 19:37:24,825 INFO MainThread Setting RFM2Pi group: 210 (210g)
2016-02-12 19:37:25,834 INFO MainThread Setting RFM2Pi quiet: 0 (0q)
2016-02-12 19:37:26,839 INFO MainThread Setting RFM2Pi baseid: 15 (15i)
2016-02-12 19:37:27,850 INFO MainThread Setting RFM2Pi calibration: 230V (1p)
2016-02-12 19:37:28,856 DEBUG MainThread Setting RFM2Pi subchannels: ['ToRFM12']
2016-02-12 19:37:28,866 DEBUG MainThread Interfacer: Subscribed to channel' : ToRFM12
2016-02-12 19:37:28,871 DEBUG MainThread Setting RFM2Pi pubchannels: ['ToEmonCMS']
2016-02-12 19:37:28,882 DEBUG MainThread Interfacer: Subscribed to channel' : ToRFM12
2016-02-12 19:37:28,893 INFO MainThread Creating EmonHubMqttInterfacer 'MQTT'
2016-02-12 19:37:28,910 INFO MainThread MQTT Init mqtt_host=<IP_ADDRESS> mqtt_port=1883 mqtt_user=emonpi
2016-02-12 19:37:28,937 DEBUG MainThread MQTT Subscribed to channel' : ToEmonCMS
2016-02-12 19:37:28,947 INFO MainThread Creating EmonHubEmoncmsHTTPInterfacer 'emoncmsorg'
2016-02-12 19:37:28,966 DEBUG MainThread emoncmsorg Subscribed to channel' : ToEmonCMS
2016-02-12 19:37:29,057 INFO MQTT Connecting to MQTT Server
2016-02-12 19:37:29,092 INFO MQTT connection status: Connection successful
2016-02-12 19:37:29,118 DEBUG MQTT CONACK => Return code: 0
2016-02-12 19:37:29,239 INFO MQTT on_subscribe
2016-02-12 19:37:59,045 INFO emoncmsorg sending: http://emoncms.org/input/bulk.json?apikey=E-M-O-N-C-M-S-A-P-I-K-E-Y&data=[]&sentat=1455302279
2016-02-12 19:37:59,605 DEBUG emoncmsorg acknowledged receipt with 'ok' from http://emoncms.org
2016-02-12 19:38:29,013 INFO emoncmsorg sending: http://emoncms.org/myip/set.json?apikey=E-M-O-N-C-M-S-A-P-I-K-E-Y
2016-02-12 19:38:30,267 INFO emoncmsorg sending: http://emoncms.org/input/bulk.json?apikey=E-M-O-N-C-M-S-A-P-I-K-E-Y&data=[]&sentat=145530231
Note that before the reboot of the raspberry pi it was working properly.
Any tips regarding how I can fix this?
many thanks,
jan
Re: emonhub: "Device communication error - check settings"
Hi,
I did a hard reboot (unplugged the adaptor) and this fixed it.
I have the impression that a soft reboot (using reboot unix command) doesn't completely reset the state of the RFM69Pi.
kr
Jan.
Re: emonhub: "Device communication error - check settings"
I can't say why the rfm2pi stopped, but you are right, there is no way for it to be reset by doing a soft reboot. Currently, the rfm2pi board runs autonomously using the unswitched 3.3v power from the Pi, only interrupting the power or grounding the reset line will cause the rfm2pi to reset.
As it happens, I am currently working on adding functionality to emonhub to enable it to reset the device if required.
Paul
Re: emonhub: "Device communication error - check settings"
Thanks Paul for the response.
In my case I think that the soft reboot of the raspberry pi (using the unix comment "sudo reboot") triggered the problem.
Indeed it would be good to add functionality to emonhub to reset the device.
For the moment everything is working fine and next time when rebooting the raspberry pi I know that I need to check if emonhub is receiving signals.
Jan


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| Language Used most to least | |
|---|---|
| Javascript | Intermediate |
| Python | Intermediate |
| CSS | Intermediate |
| HTML | Intermediate |
| GDScript | novice |
| Ruby | novice |
| Java | novice |
I am a Highschool graduate with some college credits in general studies. Currently I am pursuing a career in programing with the CodeCrew Program.


Address Displaying an address
This is an HMRC pattern
This pattern is used in the Personal tax account
When to use this pattern
Use this pattern when you need to tell a user the address or addresses that you hold for them.
Your address
You have lived at this address since 7 January 2014.
11 Street NameTown
County
GH14 7ED

You have lived at this address since 7 January 2014.

<address class="">
11 Street Name

Town

County

GH14 7ED
</address>

<input type="submit" class="button" value="Change your address">

How to use this pattern
When telling a user the address an organisation holds for them:
- tell them the last date that the information was changed
- give them the opportunity to edit the address if the information is wrong
- tell them if there are any consequences to them for the organisation holding the wrong address


Project Description
This voting dApp is a distributed application. It does not run on a server, but on a public blockchain instead.
Its functionality consists in two different parts:
- Force rank class projects/presentations.
- Evaluate teammates based on their effort to the project.


This is a two-player game of Tennis. A ball will bounce between each player's zone. Press your key once to serve the ball. Hold your key down to ready your swing. Release your key when the ball enters your hit zone.


Welcome to Play
Play @version
Why do you see this page?
The conf/routes
file defines a route that tells Play to invoke the ExampleController.index
action
whenever a browser requests the /
URI using the GET method:
# Home page
GET / controllers.ExampleController.index
Play has invoked the controllers.ExampleController.index
method to obtain the Action
to execute:
def index = Action { implicit request: Request[AnyContent] =>
Ok(views.html.index("Your new application is ready!"))
}
The template is defined in the app/views/index.scala.html
file and compiled as a Scala function.
@@(message: String)
@@main("Welcome to Play") {
@@welcome(message)
}


Corona in Bihar
Resources
Covid-19 Dashboard for Bihar
Click on the district name for block wise details
Total samples collected:
Info!
Recovered data is subject to further verification.


CommunicationError
@todoc
Bus
send
broadcast
ComputeChecksumTestCase
BusTestCase
setUp
Hook method for setting up the test fixture before exercising it.
tearDown
Hook method for deconstructing the test fixture after testing it.


I am a final year Graduate Student in the department of Computer Science at Rochester Institute of Technology. My focus in Computer Science is Data Analytics and Computer Vision. Some of the projects that I worked on are listed above.
Inventory Module:
Student Detail Module:
Data Imports:
Security:
Technology stack: PHP, JavaScript, JQuery, HTML, CSS, MYSQL Workbench, Git version control, PowerShell


- canRemove(User) - Method in class model.Event
-
Can remove.
- ChooseProfileImageListener - Class in controller
-
The Class ChooseProfileImageListener.
- ChooseProfileImageListener(HomePanel, User) - Constructor for class controller.ChooseProfileImageListener
-
Instantiates a new choose profile image listener.
- colorEventary - Static variable in class view.Frame
-
The Constant colorEventary.
- colorEventaryError - Static variable in class view.Frame
-
The Constant colorEventaryError.
- connect(String, String) - Static method in class database.UserDAO
-
V�rifie si l'utilisateur ayant le login/mdp existe.
- ConnectionController - Class in controller
-
The Class ConnectionControler.
- ConnectionPanel - Class in view
-
The Class ConnectionPanel.
- connexion(String, String) - Method in class model.Context
-
Connexion.
- Context - Class in model
-
The Class Context.
- Context() - Constructor for class model.Context
-
Instantiates a new context.
- controller - package controller
-
- Controller - Class in controller
-
The Class Controler.
- Controller() - Constructor for class controller.Controller
-
Instantiates a new controler.
- createEvent(String, String, Date, Date, int, User, Organization, Room, String) - Static method in class model.Event
-
Creates the event.
- CreateEventPanel - Class in view
-
The Class CreateEventPanel.


Description
This library aims to provide a unified API for all the major storage systems out there (filesystem, AWS S3, Google Cloud Storage etc.). It also provides an easy way to manipulate data streams as they are being uploaded/downloaded from those storage systems (compression/ checksum calculation/encryption etc.).
Use cases
- Single API to rule them all
- Easy way to transform incoming/outgoing data
- Work with filesystem storage during development, AWS S3 in production without changing code
- Insert your idea here
Available adapters
| Amazon S3 | GridFS (WIP) | Google Cloud Storage | Local Filesystem |
Available transforms
See Pipelines and Transforms section for more info.
| checksum | compress | progress (WIP) | crypto (WIP) |
|---|---|---|---|
| Checksum Calculator | Stream (de)compressor | Progress monitor | Stream (en/de)cryption |
Usage
Installation
The first step is to install nodestream into your project:
npm install --save nodestream
The next thing is to decide which adapter you want to use. An adapter is an interface for nodestream to be able to interact with a particular storage system. Let's use local filesystem for a start:
npm install --save nodestream-filesystem
Configuration
Let's create and configure a nodestream instance with which your application can then interact:
// Require the main Nodestream class
const Nodestream = require('nodestream')
const nodestream = new Nodestream({
// This tells nodestream which storage system it should interact with
// Under the hood, it will try to require `nodestream-filesystem` module
adapter: 'filesystem',
// This object is always specific to your adapter of choice - always check
// the documentation for that adapter for available options
config: {
// The `filesystem` adapter requires a `root` configuration option, so let's provide one
root: [__dirname, '.storage']
}
})
Great! At this point, nodestream is ready to transfer some bytes!
Actions
Uploading
You can upload any kind of readable stream. Nodestream does not care where that stream comes from, whether it's an http upload or a file from your filesystem or something totally different.
For this example, we will upload a file from our filesystem.
We will be uploading the file to our local filesystem as well as reading it from the same filesystem. Normally you would probably use a source different from the target storage, but Nodestream does not really care.
const fs = require('fs')
// This is the file we will upload - create a readable stream of that file
const profilePic = fs.createReadStream('/users/me/pictures/awesome-pic.png')
nodestream.upload(profilePic, {
// directory and name are supported by all storage adapters, but each
// adapter might have additional options you can use
directory: 'avatars',
name: 'user-123.png'
})
.then(results => {
// results can contain several properties, but the most interesting
// and always-present is `location` - you should definitely save this
// somewhere, you will need it to retrieve this file later!
console.log(results.location)
})
.catch(err => {
// U-oh, something blew up 😱
})
Congratulations, you just uploaded your first file!
Downloading
Downloading a file is quite straight-forward - all you need is the file's location as returned by the upload()
method and a destination stream to which you want to send the data. This can be any valid writable stream. Again, Nodestream does not care where you are sending the bytes, be it local filesystem, an http response or even a different Nodestream instance (ie. S3 to GridFS transfer).
// Let's create a destination for the download
const fs = require('fs')
const destination = fs.createWriteStream('/users/me/downloads/picture.png')
// We are hardcoding the location here, but you will probably want to
// retrieve the file's location from a database
nodestream.download('avatars/user-123.png', destination)
.then(() => {
// All good, destination received all the data!
})
.catch(err => {
// Oh well...
})
Removing
Just pass the file's location to the .remove()
method.
nodestream.remove('avatars/user-123.png')
.then(location => {
// The file at this location has just been removed!
})
.catch(err => {
// Oh no!
})
Pipelines and Transforms
Nodestream supports two features which are meant to be used together - pipelines and transforms.
- Transform: A plugin which takes an input stream and produces an output stream
- Pipeline: A re-usable, ordered collection of transforms
The real power of pipelines is that you only have to create a single pipeline, tell it which transforms it should use and then you just keep sending files to or retrieving files from it - all files will be processed in exactly the same way.
Here are some ideas what a transform can be used for. With pipelines, you can combine them to your heart's liking:
- Calculating checksums
- Compressing/decompressing data
- Modifying the data completely, ie. appending headers/footers and whatnot
Registering a transform
All transforms must be first registered with your Nodestream instance before you can use them in a pipeline. Registering is easy and is generally recommended to be done immediately after your application is started, because requiring a module is a synchronous, blocking operation, so you want to get it done before you start doing something important.
Once you configure your Nodestream instance, you can register a transform using the .registerTransform()
function.
// Let's register a compression transform! The following will try to require
// `nodestream-transform-compress` package.
nodestream.registerTransform('compress')
// You can also register an actual implementation of the transform!
const compress = require('nodestream-transform-compress')
nodestream.registerTransform(compress)
Using pipelines
To use a pipeline, you must first create one! Once you have your pipeline, you can then go on and tell it to use any of the registered transforms. Pipelines are reusable, so the general practice is to create one pipeline and use it for all uploads/downloads.
You may want to create multiple pipelines per project to accommodate different processing needs for your files, ie. you might have one pipeline for image uploads (with a transform plugin to calculate checksums and one to crop the images) and another pipeline for other files (with just the checksum transform). Any combination can be achieved.
// Let's create our first pipeline
const pipeline = nodestream.pipeline()
// Now, we can tell the pipeline to use any of the registered transforms
// The second parameter is specific to each transform so always check the
// transform's docs to see what you can set
pipeline
.use('checksum', { algorithm: 'md5' })
.use('compress', { algorithm: 'gzip' })
// You can use a single pipeline for multiple file uploads/downloads
// Aaand, you can also pass per-file, transform-specific options here
pipeline.upload(file, { name: 'pic.png', compress: { mode: 'compress' } })
WARNING!
The order in which transforms are added to a pipeline using
.use()
matters! Transforms are applied to the stream in the order they were added. For example, if you first add a checksum calculation transform and then a compress transform, the checksum will be calculated from the uncompressed data. Switching the order would cause the checksum to be calculated from the compressed data. There are use cases for both situations, so the choice of ordering is completely up to you.
Accessing transform results
You might have noticed that Nodestream returns a Promise which is resolved with a results
object. In addition to the location
property, this object also contains results of all applied transformations (if there are any).
Each transform declares its "identity" - a string which will be used as a "scope" to publish its results or to provide a mechanism to customise the transform's options. Check each of the transforms' documentation to learn what is its identity
string.
For the checksum
transform, its identity is, surprisingly, "checksum". When used, the calculated checksum can be obtained as follows:
nodestream
.pipeline()
.use('checksum')
.upload(file, { name: 'pic.png' })
.then(results => {
// The `results` object will have a "checksum" property, because that's
// the transform's identity
console.log(results.checksum.value)
})
There is no limit to the amount of transforms which can be registered per Nodestream instance, although there are some practical limitations which restrict you to only one particular transform type per Nodestream instance (ie. only one checksum transform with only one compress transform).
License
This software is licensed under the BSD-3-Clause License. See the LICENSE file for more information.


Send them here and we'll add them to the page!


a5e
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RAID-2RAID level 2 is data striping done at the bit level. It is a theoretical concept only; no manufacturer has yet built a RAID-2 disk controller. RAID-3RAID level 3 is sector striping. As is true for RAID-2, RAID-3 is considered a theoretical concept. RAID-4RAID level 4 is known as drive parity, or data guarding. In RAID-4, one of four drives is used for data parity. If any one of the four disks fails, the other three continue running. Because the algorithms used in RAID-4 are considered obsolete, RAID-4 is not used much. RAID-4 has essentially been replaced by RAID-5. When you use RAID-4, many extra I/Os are generated. To calculate the parity, RAID-4 reads data from all the drives in the set. As you can imagine, the overhead involved with RAID-4 is very high. RAID-5RAID-5 is also known as distributed data guarding. In distributed data guarding, enough information is stored about each drive so that any one drive in the set can fail; the data is restored by using all the other drives. The space you get from RAID-5 is equal to the following: Drive Space = ( N - 1 ) * Drive Size In this equation, N is the number of drives in the logical volume. In other words, if you are running 12 disk drives with RAID-5, you get the space of 11 disk drives. As with RAID-4, there is a penalty associated with RAID-5. For each write to disk, two reads take place, a calculation of the parity is done, and then two writes are done. Although a read generates only one I/O, a write generates four I/Os.
Fault-Tolerance ConcernsIf you use RAID technology, there are essentially three modes in which you can run your database:
Although disk drives have become much more reliable in the past few years, they are still the component most likely to fail. The reason that disk drives are susceptible to failure is because they are mostly mechanical devices. Disks are made up of sophisticated electronics and motors. Forces such as heat, dust, and friction can cause even the most well-built disk drive to fail. No matter how well you take care of your system, it is inevitable that you will one day see a disk failure.
No Data ProtectionIn No Data Protection mode, no fault tolerance is used and the data is completely unprotected. Any disk failure causes you to reload all the affected files from the last backup. If the failure occurred on a data volume, you can restore the data (if you are running in ARCHIVELOG mode, you can use the archive log files to restore the database up to the point of failure). Even so, when a disk drive fails, you must restore the entire volumewhich may mean tens of gigabytes of data. If the failure occurred on the volume containing your redo log files, you can recover only up to the last good archived log file. At instance recovery, you can recover only up to the point at which the LGWR started writing to the damaged log file(s). If the failure occurred on the volume containing the OS and Oracle binaries, you must restore from a backup or reinstall the operating system, reload Oracle, and then restart Oracle. As you can see, in each of these unprotected situations, the recovery interval can be quite long. No failure of an unprotected system is easy to recover from. Full Data ProtectionFull Data Protection is by far the most secure option. If you have fault tolerance on every disk drive in the system, any single failure does not cause a system failure. Depending on the level of fault tolerance you run, many multidisk failures can be tolerated. The level of fault tolerance you run depends on the performance you require and the budget you have. In the last few years, the cost of disk drives has dropped so dramatically that it is not unusual to see entire systems run with disk mirroring. The cost of the extra drives needed to support fault tolerance usually outweighs the cost incurred by extended downtime. In assessing the level of fault tolerance, look at your required I/O rates. If possible, use RAID-1 (it gives the best performance). If RAID-1 is not in your budget, perhaps you can use RAID-1 for at least your OS and redo log volumes. The redo log volumes usually demand the highest protection available.
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Chapter 7 Statistical Modeling and Model Interpretation
7.1 Parametric statistical tests
T-test, analysis of variance, and linear regression are all parametric statistical tests. They are used when the dependent variable is an interval/ratio data variable, such as length, height, weight.
Advantages: - your audience will likely be familiar with the techniques and interpretation of the results. - These tests are also often more flexible and more powerful than their nonparametric analogues.
Drawback: - all parametric tests assume something about the distribution of the underlying data. If these assumptions are violated, the resultant test statistics will not be valid, and the tests will not be as powerful as for cases when assumptions are met. - Count data may not be appropriate for common parametric tests. Instead, count data could be analyzed either by using tests for nominal data or by using regression methods appropriate for count data, such as Poisson regression, negative binomial regression, and zero-inflated Poisson regression.
Assumptions - Random sampling The data captured in the sample are randomly chosen from the population as a whole. Selection bias will obviously affect the validity of the outcome of the analysis.
Independent observations Tests will also assume that observations are independent of one another, except when the analysis takes non-independence into account. For example, in repeated measures experiments, the same subject is observed over time. Students with a high test score on one date to have a high test score on subsequent dates. In this case the observation on one date would not be independent of observations on other dates.The independence of observation is often assumed from good experimental design. Also, data or residuals can be plotted, for example to see if observations from one date are correlated to those for another date.
Normal distribution of data or residuals Parametric tests assume that the data come from a population of known distribution, such as normal distribution. That is, the data are normally distributed once the effects of the variables in the model are taken into account.
Practically speaking, this means that the residuals from the analysis should be normally distributed. This will usually be assessed with a histogram of residuals, a density plot, or with quantile–quantile plot.
A select number of tests (limited to one-sample t-test, two-sample t-test, and paired t-test) will require that data itself be normally distributed.For other tests, the distribution of the residuals will be investigated.
Residuals from an analysis are also commonly called errors. They are the difference between the observations and the value predicted by the model. For example, if the calculated mean of a sample is 10, and one observation is 12, the residual for this observation is 2. If another observation is 7, the residual for this observation is –3.
Be careful not to get confused about this assumption. You may see discussion about how “data” should be normally distributed for parametric tests. This is usually wrong-headed. The t-test assumes that the observations for each group are normally distributed, but if there is a difference in the groups, we might expect a bi-modal distribution, not a simple normal distribution, for the combined data. This is why in most cases we look at the distribution of the residuals, not the raw data.
Assessing model assumptions
- Using formal tests to assess normality of residuals There are formal tests to assess the normality of residuals. Common tests include Shapiro-Wilk, Anderson–Darling, Kolmogorov–Smirnov, and D’Agostino–Pearson. However, their results are dependent on sample size. When the sample size is large, the tests may indicate a statistically significant departure from normality, even if that departure is small. And when sample sizes are small, they won’t detect departures from normality. In each case, the null hypothesis is that the data distribution is not different from normal. That is, a significant p-value (p < 0.05) suggests that data are not normally distributed.
library(tidyverse)
head(diamonds)
## # A tibble: 6 x 10
## carat cut color clarity depth table price x y z
## <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
## 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
## 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
## 4 0.290 Premium I VS2 62.4 58 334 4.2 4.23 2.63
## 5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
## 6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48
summary(diamonds)
## carat cut color clarity
## Min. :0.2000 Fair : 1610 D: 6775 SI1 :13065
## 1st Qu.:0.4000 Good : 4906 E: 9797 VS2 :12258
## Median :0.7000 Very Good:12082 F: 9542 SI2 : 9194
## Mean :0.7979 Premium :13791 G:11292 VS1 : 8171
## 3rd Qu.:1.0400 Ideal :21551 H: 8304 VVS2 : 5066
## Max. :5.0100 I: 5422 VVS1 : 3655
## J: 2808 (Other): 2531
## depth table price x
## Min. :43.00 Min. :43.00 Min. : 326 Min. : 0.000
## 1st Qu.:61.00 1st Qu.:56.00 1st Qu.: 950 1st Qu.: 4.710
## Median :61.80 Median :57.00 Median : 2401 Median : 5.700
## Mean :61.75 Mean :57.46 Mean : 3933 Mean : 5.731
## 3rd Qu.:62.50 3rd Qu.:59.00 3rd Qu.: 5324 3rd Qu.: 6.540
## Max. :79.00 Max. :95.00 Max. :18823 Max. :10.740
##
## y z
## Min. : 0.000 Min. : 0.000
## 1st Qu.: 4.720 1st Qu.: 2.910
## Median : 5.710 Median : 3.530
## Mean : 5.735 Mean : 3.539
## 3rd Qu.: 6.540 3rd Qu.: 4.040
## Max. :58.900 Max. :31.800
##
test_data = diamonds%>%
filter(cut %in% c("Fair", "Ideal" ),
carat == 0.7,
color %in% c("G", "F" ),
clarity %in% c("SI1", "VS2" ))
table(test_data$cut)
##
## Fair Good Very Good Premium Ideal
## 21 0 0 0 113
ggplot(test_data,
aes(price, fill = cut)) +
geom_density(position="dodge",
alpha = 0.6)
## Warning: Width not defined. Set with `position_dodge(width = ?)`
#Define a linear model
model = lm(price ~ cut + color,
data = test_data)
#Shapiro–Wilk normality test
x = residuals(model)
shapiro.test(x)
##
## Shapiro-Wilk normality test
##
## data: x
## W = 0.96048, p-value = 0.0006383
# Anderson-Darling normality test
if(!require(nortest)){install.packages("nortest")}
## Loading required package: nortest
library(nortest)
x = residuals(model)
ad.test(x)
##
## Anderson-Darling normality test
##
## data: x
## A = 1.7123, p-value = 0.0002071
# One-sample Kolmogorov-Smirnov test
x = residuals(model)
ks.test(x,
"pnorm",
mean = mean(x),
sd = sd(x))
## Warning in ks.test(x, "pnorm", mean = mean(x), sd = sd(x)): ties should not
## be present for the Kolmogorov-Smirnov test
##
## One-sample Kolmogorov-Smirnov test
##
## data: x
## D = 0.096286, p-value = 0.1666
## alternative hypothesis: two-sided
# D'Agostino Normality Test
if(!require(fBasics)){install.packages("fBasics")}
## Loading required package: fBasics
## Loading required package: timeDate
##
## Attaching package: 'timeDate'
## The following objects are masked from 'package:PerformanceAnalytics':
##
## kurtosis, skewness
## Loading required package: timeSeries
##
## Attaching package: 'timeSeries'
## The following object is masked from 'package:zoo':
##
## time<-
## The following object is masked from 'package:psych':
##
## outlier
##
## Attaching package: 'fBasics'
## The following object is masked from 'package:psych':
##
## tr
library(fBasics)
x = residuals(model)
dagoTest(x)
##
## Title:
## D'Agostino Normality Test
##
## Test Results:
## STATISTIC:
## Chi2 | Omnibus: 10.2249
## Z3 | Skewness: 3.1412
## Z4 | Kurtosis: 0.5981
## P VALUE:
## Omnibus Test: 0.006021
## Skewness Test: 0.001683
## Kurtosis Test: 0.5498
##
## Description:
## Sun Dec 01 10:44:58 2019 by user: Juqiang Chen
- Skew and kurtosis There are no definitive guidelines as to what range of skew or kurtosis are acceptable for considering residuals to be normally distributed.
In general, I would not recommend relying on skew and kurtosis calculations, but instead use histograms and other plots.
If I were forced to give advice for skewness calculations, I might say, be cautious if the absolute value is > 0.5, and consider it not normally distributed if the absolute value is > 1.0. Some authors use 2.0 as a cutoff for normality, and others use a higher limit for kurtosis.
library(psych)
x = residuals(model)
describe(x,
type=2)
## vars n mean sd median trimmed mad min max range skew
## X1 1 134 0 284.79 -40.84 -20.5 262.42 -543.69 839.01 1382.7 0.7
## kurtosis se
## X1 0.18 24.6
Using visual inspection to assess the normality of residuals Usually, the best method to see if model residuals meet the assumptions of normal distribution and homoscedasticity are to plot them and inspect the plots visually.
Histogram with normal curve A histogram of the residuals should be approximately normal, without excessive skew or kurtosis. Adding a normal curve with the same mean and standard deviation as the data helps to assess the histogram.
x = residuals(model)
library(rcompanion)
plotNormalHistogram(residuals(model))
Kernel density plot with normal curve A kernel density plot is similar to a histogram, but is smoothed into a curve. Sometimes a density plot gives a better representation of the distribution of data, because the appearance of the histogram depends upon how many bins are used.
The plotNormalDensity function will produce this plot. Options include those for the plot function, as well as adjust, bw, and kernel which are passed to the density function. col1, col2, and col3 change plot colors, and lwd changes line thickness.
library(rcompanion)
x = residuals(model)
plotNormalDensity(x,
adjust = 1) ### Decrease this number
### to make line less smooth
7.2 formal tests for homogeneity of variance
In each case, the null hypothesis is that the variance among groups is not different. That is, a significant p-value (p < 0.05) suggests that the variance among groups is different.
#Define a linear model
model = lm(price ~ cut + color,
data = test_data)
#Bartlett’s test for homogeneity of variance
#Bartlett’s test is known to be sensitive to non-normality in samples. That is, non-normal samples can result in a significant test due to the non-normality.
x = residuals(model)
bartlett.test(x ~ interaction(cut, color),
data = test_data)
##
## Bartlett test of homogeneity of variances
##
## data: x by interaction(cut, color)
## Bartlett's K-squared = 39.068, df = 3, p-value = 1.679e-08
# Levene’s test for homogeneity of variance
# Levene’s test is an alternative to Bartlett’s that is supposedly less sensitive to departures from normality in the data.
if(!require(car)){install.packages("car")}
## Loading required package: car
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:fBasics':
##
## densityPlot
## The following object is masked from 'package:psych':
##
## logit
## The following object is masked from 'package:dplyr':
##
## recode
## The following object is masked from 'package:purrr':
##
## some
library(car)
x = residuals(model)
leveneTest(x ~ cut * color,
data=test_data,
center=mean) ### Use the original Levene’s test
## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 3 8.76 2.468e-05 ***
## 130
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# Brown–Forsythe or robust Levene’s test
# The Brown–Forsythe modification of Levene’s test makes it more robust to departures in normality of the data.
#if(!require(car)){install.packages("car")}
library(car)
x = residuals(model)
leveneTest(x ~ cut * color, data=test_data)
## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 3 8.5541 3.163e-05 ***
## 130
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#if(!require(lawstat)){install.packages("lawstat")}
library(lawstat)
##
## Attaching package: 'lawstat'
## The following object is masked from 'package:car':
##
## levene.test
x = residuals(model)
levene.test(x, interaction(test_data$cut, test_data$color))
##
## Modified robust Brown-Forsythe Levene-type test based on the
## absolute deviations from the median
##
## data: x
## Test Statistic = 0.51854, p-value = 0.6702
# Fligner-Killeen test
# The Fligner-Killeen test is another test for homogeneity of variances that is robust to departures in normality of the data.
x = residuals(model)
fligner.test(x ~ interaction(cut, color), data=test_data)
##
## Fligner-Killeen test of homogeneity of variances
##
## data: x by interaction(cut, color)
## Fligner-Killeen:med chi-squared = 11.948, df = 3, p-value =
## 0.007562


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{% macro displayPitches(pitches_list) %} {% for pitch in pitches_list[::-1] %}
Posted on:{{ pitch.date.strftime('%y-%m-%d') }}
{{comment.user.username}}
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Posted on:{{pitch.date}}
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05.Write a function that counts how many times given number appears in given array. Write a test function to check if the function is working correctly.
Input comma or space separated list of numbers:
Input searched number:
Count


Here is a collection of different presentations that I have made. The source for all of these can be found on GitHub.
When on a remark.js slidehow press the 'P' key to open the presenation mode. This allows you to see the presentation notes for each slide. To clone the slideshow view (for presenting the slides on another monitor) press the 'C' key.
Most of these pages are powered by remark.js which is a way to turn markdown documents into slide show presentations. Powerpoint presentations are hosted via OneDrive. Grunt.js is used to do all of the heavy lifting. Each child page for the presentations have a comment section which is powered by Disqus. Everything is hosted on GitHub Pages.
| Date | Notes |
|---|---|
| 2016-01-19 | Added slides from CUSEC 2016 |
| 2014-12-09 | Added 'Why Crashes Happen' exercises and 'How Computers Work' coding answers. |
| 2014-12-04 | Added 'Why Crashes Happen' subpage. |
| 2014-11-28 | Added the 'How Computers Work' child page. Added 'amswers' for previous practical work. |
| 2014-11-21 | Added the 'Language Syntax' child page. |
| 2014-11-14 | Added child pages for each presentations. This is were the practical work and comments are kept. |
| # | Presentation |
|---|---|
| 1 | Programmer Talk |
| 2 | Language Syntax |
| 3 | How Computers Work |
| 4 | Why Crashes Happen |
| 5 | Make Your Own Program |
| 6 | Post Mortem |
| # | Presentation |
|---|---|
| 1 | Pitfalls Of Peer-to-peer Networking In Games |


Deprecated - use ucar.nc2.ft2.coverage
A grid has a georeferencing "gridded" CoordinateSystem, which implies a connected topology such that values next to each other in index space are next to each other in coordinate space. In the VisAD data model, a grid is a sampled Field. Note: these classes should be considered experimental and may be refactored in the next release.


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jQuery Floating List
Sam Sehnert, Phil Taylor
1.2.4
- Version 1.2.3 & 1.2.4
- jQuery Plugin website compatibilitiy.
- Version 1.2.2
- Merged pull requests from GitHub: #1, #2
- Version 1.2.1
- Fixed the destory method for new wrapper method
- Improved automated styles (including removing styles in destroy)
- Added support for elements using max-height css property.
- Version 1.2.0
- Added ability to define scrolltarget element. Plugin watches for scrolling on this element, and positions header based on scroll level.
- Added ability to set animation easing and completion function for scrollTo method.
- Fixed triggering of headingChange method so that it would trigger even when reversing mid scroll.
- Fixed styling to pick up computed style of header element.
- Changed plugin wrapper method. Now wraps list items for scrolling, and adds list header under original list, outside wrapper.
- Version 1.1.2
- Added scrollTo method for automatically scrolling to a given heading index.
- Version 1.1.1
- Updated unload script so destroying plugin and restoring DOM is possible.
- Version 1.1.0
- Added headingChange event, triggers when the calendars heading changes from one to another.
- Added plugin log method for debugging information.
- Improved code commenting and documentation.
- Updated version method to return VID if required (numeric version number).
- Version 1.0.0
- Implemented basic plugin functionality.


Full-featured select component with support for remote (AJAX) data source.
data class AjaxOptions
Data class for AJAX options. |
|
enum class DATATYPE
Data type for the AJAX call. |
|
enum class HTTPTYPE
HTTP protocol type for the AJAX call. |
|
enum class SELECTWIDTHTYPE
Select width types. See Bootstrap Select width. |
|
open class Select : SimplePanel, StringFormControl
The form field component for Select control. |
|
open class SelectInput : SimplePanel
The basic component for Select control. |
|
open class SelectOptGroup : SimplePanel
The helper container for adding option groups to Select. |
|
open class SelectOption : Widget
The helper component for adding options to Select or SelectOptGroup. |
fun AjaxOptions.toJs(emptyOption: Boolean): dynamic
Convert AjaxOptions to JavaScript JSON object. |


Here's what it's like inside Facebook's first Singapore cafe, where the adorable emoji pancakes and coffee are completely free, Business Insider - Business Insider Singapore
by Jessica LinIf you think Facebook is spying on your conversations, you should probably head down to the social media giant’s first-ever cafe takeover in Singapore this weekend.
Despite numerous clarifications that it does not use the microphone on your smartphone to find out what you’re eating for lunch, there are still people who believe the conspiracy theories are true, Arianne Jimenez, a privacy and public policy manager at Facebook, said at the Five Oars Coffee Roasters on Friday (Nov 22).
Just to set the record straight, Facebook does not eavesdrop on your conversaions, it does not decide what you see on your Newsfeed, and it also “never” sells your data to companies, Jimenez said.
But in a world where digital crime is rife and identity theft is no longer shocking, who can blame social media users for being skeptics?
With its first Singapore pop-up cafe, Facebook is allowing members of the general public to find out more about how to protect their own privacy on its various platforms, namely Facebook, Instagram and WhatsApp.
Open from Friday to Sunday this week, volunteers from Facebook’s own staff will be at the cafe at 39 Tanjong Pagar Road to help guide visitors through a privacy quiz that will determine just how well they understand the privacy tools available on these platforms.
According to Facebook, around 3,000 people had already indicated interest in the free event before its launch on Friday afternoon.
Instagrammable coffees and pancakes are up for grabs at S$0 while stocks last, so be prepared to queue.
We paid a visit before the cafe opened to public, here’s what it was like.
The first-ever Facebook Cafe in Singapore is open for business – but only for one weekend.
It is open from 2pm to 6pm on November 22, and from 9am to 6pm on November 23 and 24.
Facebook has held similar events at cafes in other cities, including Jakarta, Tokyo, Dublin and London.
The entire Five Oars has been decorated like it’s an actual Facebook cafe.
source
Business Insider/Jessica Lin
The first thing you will be given is a pen and quiz sheet with six questions.
There are no winners or losers, but how you score is still important for reasons we’ll explain later.
The quiz tests members of the public on their knowledge of privacy controls on Facebook’s three platforms.
source
Business Insider/Jessica Lin
Depending on your score, you’ll get one of three badges based on Facebook’s popular reaction emojis.
I got the “love” emoji, but I secretly really wanted the “sad” face.
source
Business Insider/Jessica Lin
Next up, order a drink from the counter.
You will need to order before taking a seat. You can have the drink to-go as well.
source
Business Insider/Jessica Lin
There’s a wide range of drinks available, from coffee to soda.
Just one drink per person.
source
Business Insider/Jessica Lin
My choice was the lychee rose iced tea. And I chose a seat in the lovely non-air-conditioned part of the cafe.
The greenery in this section was beautiful and a nice break from the concrete jungle out there.
source
Business Insider/Jessica Lin
But if you prefer an air-conditioned room, you can take a seat indoors instead.
source
Business Insider/Jessica Lin
Every table is decorated with icons related to Facebook’s privacy tools.
source
Business Insider/Jessica Lin
Since I was given a “love” pin, my coffee also came with the “love” emoji.
No doubt one of the best coffees on Tanjong Pagar Road.
source
Business Insider/Jessica Lin
Even my assigned pancake was “love” themed.
And no, you don’t get to choose what flavour to have. What you get depends on your score in the quiz.
We’re keeping the exact flavour a secret, so you can be surprised. But the “love” pancakes were obviously centred on berries and came with sugared nuts.
source
Business Insider/Jessica Lin
There’s also the “wow” pancake for those with the corresponding pin…
Hint: This pancake contains ricotta.
source
Business Insider/Jessica Lin
… and one for those with the “sad” pin.
It’s a sad but very pretty pancake.
source
Business Insider/Jessica Lin
Even the coffee was “sad”. But at least it was delicious.
Totally Instagrammable, of course.
source
Business Insider/Jessica Lin
Read also:


Test Click
CallNative 01 Click
This is a sample file created to test a simple "WebView".
Modify this file to test the "WebView" content.


Irfan Zeb, Shah Fahad
Masters thesis, slightly odd english, and fairly amateur style, but very up-to-date and with similar scope - understanding how communication between those specifying digital systems can communicate most effectively with users as part of co-design..
"Main Question: How is it possible to create a better communication
between system designers and users
during co-design in order to enhance the usability of a designed
information system?
Sub Questions:
Interpretivist, Interviews, Literature Reviews


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I'm a Software Engineer based in Silicon Valley specializing in building web and mobile application.
I'm a Software Engineer based in Palo Alto, California.
I enjoy engaging in challenging projects and learning new languages and modern frameworks.
Here are a few technologies I've been working with recently:
Rivian is an American Electric Vehicle Automaker where I assist in developing digital experience outside the vehicle across web, mobile, and in-store.
React ~ React Native ~ Redux ~ GraphQL ~ TypeScript
Biggby Coffee is an American coffeehouse chain where I help developed the online ordering app and the in-store point of sale systems.
React ~ Redux ~ GraphQL ~ Node.js ~ TypeScript ~ Stripe ~ MySQL
Glytch is an e-sports location-based entertainment. I designed and developed a prototype application for its entertainment center.
React Native ~ Redux ~ Node.js ~ MySQL ~ InVision
Chore Ninja is a business service sector that allows consumers to find immediate help with everyday tasks.
React Native ~ Redux ~ Node.js ~ Express.js ~ MySQL ~ MongoDB ~ Passport.js ~ InVision
Portfolio Template is a protoype template that I develop using Vanilla Javascript, HTML, and SASS.
Javascript ~ HTML ~ SASS
KEN Theaters is a movie theater that I learn to develop using Vanilla Javascript, HTML, and CSS.
Javascript ~ HTML ~ CSS
Global Exchange Rate is a live exchange rate calculator that I developed using Vanilla Javascript, HTML, CSS, and ExchangeRate API.
Javascript ~ HTML ~ CSS ~ ExchangeRate API
A Tic Tac Toe game with Artificial Intelligence that has a winning rate of up to 95%.
Java ~ Java Swing ~ AI


Somehow, I had managed to avoid the "Cowboy Musicals" for many years, but this time they finally caught up with me, as I did Calamity Jane.
On the positive side, I think that this was my first proper stage kiss. On the negative side, one has to say that Danny Gilmartin is one of the most boring people in all of stage musicals!
The show was good fun to do, though from memory the naked lady above the bar of the Golden Garter didn't even survive to the first night!


Fyre Festival Resort
Book your villa and dining experience here!
Here are the perks to each tier available to our guests:
- The Emperor
- Personal "Mansion"
- 24/7 on call Butler
- Private Beach
- Elephant
- The Premier
- Custom ordered companion
- 24/7 on call Posse
- Slightly smaller Elephant
- The Upper Middle Class
- Island Pass
- Personal Travel Mule
- Tent (On Request)


Omar Charles Gedeon
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Contact
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Have a question or want to work together?
Located : San Francisco
California, USA.
Phone: 1(415) 342 9479
<EMAIL_ADDRESS>-->


PTA-Fuzz
Contact
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>Summary
SVF:
9
(total)
sea-dsa:
1
(total)
Phasar:
4
(total)
Here we list the issues found by PTA-Fuzz.
SVF
https://github.com/SVF-tools/SVF/issues/313
https://github.com/SVF-tools/SVF/issues/314
https://github.com/SVF-tools/SVF/issues/315
https://github.com/SVF-tools/SVF/issues/316
https://github.com/SVF-tools/SVF/issues/320
https://github.com/SVF-tools/SVF/issues/315#issuecomment-694721074
https://github.com/SVF-tools/SVF/issues/313#issuecomment-699962579
https://github.com/SVF-tools/SVF/issues/334
https://github.com/SVF-tools/SVF/issues/341
sea-dsa
https://github.com/seahorn/sea-dsa/issues/101
canary
Phasar
Phsar can use CFLAnders and CFLSteens from LLVM; it also implements CHA, VTA, etc.
https://github.com/secure-software-engineering/phasar/issues/192
https://github.com/secure-software-engineering/phasar/issues/194
https://github.com/secure-software-engineering/phasar/issues/197
https://github.com/secure-software-engineering/phasar/issues/198


Hello, welcome back! Let's get started.
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Nothing to copy, kindly first make a request.


I am a UX consultant with a focus on interaction design, UI prototyping, and usability research.
My process borrows heavily from traditional user-centered design methods, but is optimized for each situation and client.
I have 15 years of hands-on experience designing and doing research for startups and Fortune 500 companies.
I've worked with some great clients, both directly and through agencies like Blink, Fell Swoop, LiveAreLabs, IF/THEN, Copacino+Fujikado, Methodologie, Wunderman, and the pinoerring Sitewerks (RIP).
My portfolio includes desktop and mobile projects for e-commerce, social, software, entertainment, education, science, health care, and profession services. Please contact me if you would like to see samples and learn more.
Recent News:
The Seattle Cancer Care Alliance is a world-class cancer treatment center. I was recently hired to conduct a personas workshop with a small group of their key staff members. The outcome of the workshop characterized the primary user types of their website and defined the participants for a baseline usability study.


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Shared |
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Data | Share | Duplicate | Edit | Delete |
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selected {{selection.selected.length}} items
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CodeMagix is small software house based in Leeds, West Yorkshire. We specialize in utilzing IT to solve every day business problems our clients face.
Our mission
We will always strive for comprehensive and thought-through solution to your problem, keeping you at centre of our work. We strongly believe there is a right balance between simplicity and elegance, without compromising on quality.
Understanding your business model and priorities is the most important part of our job. We will help you to identify and measure your needs, identify any potential gaps in your IT infrastructure, advise you on industry best practices and support you in software implementation.
With over decade of experience, we can deliver any software, regardless of its size and complexity.
We deliver bespoke solutions to meet your business requirements 100%. We will collaborate with you to improve your specification and provide feasibility study.
We cover all aspects of database design and development from T-SQL coding, indexing and performance optimization.
We can offer customised group-based or one-to-one training and mentoring to kick start your SQL Server based projects and develop your team.
Our extensive knowledge of Microsoft's platform means we are ideally placed to help define flexible data architecture for your business.


25+ 2017 Nissan Leaf Sl UK. Used 2017 nissan leaf interior. Search over 3,700 listings to find the best local deals.
Available styles include sl 4dr hatchback (electric dd), sv 4dr which used 2017 nissan leafs are available in my area? 80 kw, 254 nm, top speed: 90.1 mph / 145.0 km/h, battery:
The 2017 nissan leaf remains available in a trio of trims:
Leaf sl hatchback package includes. 80 kw, 254 nm, top speed: Our 2017 nissan leaf is excellent! Used 2017 nissan leaf sl with fwd, navigation system, keyless entry, fog lights, spoiler, leather seats, heated seats, heated steering wheel, bucket.


wissel.net
Usability - Productivity - Business - The web - Singapore & Twins
--- permalink: /404.html ---
Usability - Productivity - Business - The web - Singapore & Twins
I try to keep links nice and tidy around here, but stuff can happen.
Why not try one of the links below, or check the latest entries!


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| Position: | | Geographic Information Systems Analyst / Intern |
| Employer: | | Audubon Appleton-Whittell Research Ranch |
| Location: | | Elgin, AZ |
| Period: | | June 2002 - August 2003 |
| Web: |
|
Audubon Research Ranch |
| Responsibilities: |
|
- Data editing
- Data warehouse/metadata library design/development
- GPS data collection
- Public, governmental agencies, advocacy groups liason
- Habitat/development land-use analysis
- Thematic and presentation mapping
|
|
Experience:
|
|
My work with the Audubon Research Ranch in Elgin, AZ, included a range of basic GIS tasks.
I catalogued the facility's collection of GIS layers and data into an organized data warehouse
with associated metadata. The academic and organizational staff conducting research at the Ranch
tasked me with collecting site information via GPS. I met with representatives of geospatial
stakeholders in the surrounding area to broaden and update the Ranch's GIS library.
As the sole "GIS person" on site I received and completed multiple ad-hoc requests for data preparation
and map production.
|


Simple Interest Calculator
Amount
Rate
10%
No. of Years
Interest :
Compute
© Everyone Can Get Rich - Lucas Conde 2021
AGAIN


The output y
performs a logarithmic frequency
sweep. The logarithm of frequency w
performs a linear
ramp from log10(wMin)
to log10(wMax)
. The
output is the decimal power of this logarithmic ramp.
For time < startTime
the output is equal to
wMin
.
For time > startTime+duration
the output is
equal to wMax
.


"x" "1" "LEBEDEV,AV LEVITSKAYA,EL TIKHONOVA,EV AND IVANOVA,MV, ANTIOXIDANTPROPERTIES, AUTOOXIDATION, AND MUTAGENIC ACTIVITY OF ECHINOCHROME A COMPAREDWITH ITS ETHERIFIED DERIVATIVE, BIOCHEMISTRY (MOSCOW, RUSS. __ FED.) 66(8):885-893,2001"


--- layout: post title: How IT Support Services Are Changing date: '2012-03-14T15:12:23-07:00' tags: tumblr_url: http://alexhwilliams.tumblr.com/post/19309324317/how-it-support-services-are-changing ---
http://bit.ly/A37Ds2


Gas Guzzlers Extreme will be released on PS4 later this month
by Aran SuddiIceberg Interactive and Gamepires have confirmed that Gas Guzzlers Extreme, the Twisted Metal like vehicle combat game, will be released for PS4 on November 26th. The gameplay is all about team combat and players will start with low powered vehicles and make their way up to more powerful vehicles.
Gas Guzzlers Extreme on PS4 will also include the Full Metal Frenzy and Full Metal Zombie DLCs. The second DLC is all about using your vehicle to take out the zombie hordes, but they have weapons and killing too many means the ground becomes slick which can lead to your own vehicle crashing out and being overrun. There’s a total of 42 tracks, 12 game modes and arenas, 21 cars, 12 weapons, 22 zombie types, and eight environments.
Source: Press Release