UKCloud Limited (“UKC”) and Virtual Infrastructure Group Limited (“VIG”) (together “the Companies”) – in Compulsory Liquidation
On 25 October 2022, the Companies were placed into Liquidation with the Official Receiver appointed as Liquidator and J Robinson and A M Hudson simultaneously appointed as Special Managers to manage the liquidation process on behalf of the Official Receiver.
Further information regarding the Liquidations can be found here: https://www.gov.uk/government/news/virtual-infrastructure-group-limited-and-ukcloud-limited-information-for-creditors-and-interested-parties
Contact details:
For any general queries relating to the Liquidations please email<EMAIL_ADDRESS>For customer related queries please email<EMAIL_ADDRESS>For supplier related queries please email<EMAIL_ADDRESS>Snapshot Protection FAQs
General
What is a protection technology?
Protection technologies are tools used to enable you to design resilience into your cloud solutions.
They protect data and provide you with the ability to recover from system outages - either caused by a disruption to the physical delivery of a service or a result of a corruption of your primary system.
What protection options does UKCloud offer?
By default, VMs deployed on the UKCloud platform do not come with any protection services enabled.
However, you can opt to utilise one of the platform based protection technologies, such as:
Snapshot protection - automatically takes an image of your VM every 24 hours and stores the image outside the core platform
Journaling protection - creates an almost live copy of your VM and records the VM data and state in a data journal
Additionally, you can implement your own protection technologies.
Utilising our Cloud Storage service, you can keep secondary copies of your data by:
Manually copying data
Using scripts to copy data
Using backup applications such as CommVault, Networker and others.
You can replicate data between sites for even greater data protection.
Can I use my own protection client software?
Yes, you simply install appropriate backup software within the VM and specify the backup location.
A typical scenario might involve using a commercial backup solution (such as Symantec NetBackup, CommVault or EMC NetWorker) that points to services such as our Cloud Storage.
Snapshot protection
How does snapshot protection work?
An automated VM snapshot creates a crash‑consistent snapshot of the VM, which is then copied to our dedicated backup system.
How do I add snapshot protection to my VM?
Use the UKCloud Portal to add snapshot protection to a VM:
Login to the UKCloud Portal and choose the appropriate account.
In the dashboard, click My VMs, then click the appropriate vOrg.
Click the My VMs tab.
Choose the appropriate VDC then click the VMs tab.
In the Snapshot Protection column, click the Manage button.
From the Select Backup Policy list, choose the policy level that you require: 14‑day or 28‑day, then click Submit.
The button changes to indicate your chosen policy.
You can also remove a VM from automated backups by choosing No Backup from the Select Backup Policy list.
How long does it take before the first snapshot is taken?
The time it takes to add snapshot protection to a VM varies depending on how many other requests are in the queue. While the request is processed, the button in the Snapshot Protection column changes to an amber Processing button.
When the process has completed, the button changes back to green and will indicate the snapshot policy you chose for the VM (14‑day or 28‑day). If the process fails, the button changes to a red Failed button. In this situation, contact the UKCloud support team to resolve the issue.
The first snapshot will be taken in the next available backup window. Backup status information is typically updated daily on the UKCloud Portal by 10:00, but typically within minutes of the close of the backup window.
Due to the higher rate of new data on a VM's initial snapshot backup, each new VM is automatically configured with 'overtime' enabled on it's first backup. This enables it to run to successful completion beyond the standard backup window (20:00-08:00) if required. This helps to ensure the initial backup completes on the first attempt, particularly for large or high change rate VMs. The flag is removed after the first successful backup.
Can I change the snapshot policy for my VM at any time?
Yes, there are no restrictions. After your changes have been processed, they will be applied to the snapshot taken in the next backup window.
How are my automated VM snapshots restored?
If you have access to the support ticketing system, you can request restoration of VMs.
We'll restore the whole VM image to your virtual data centre (VDC). You can then manage the restoration of individual files or the whole VM.
Do automated VM snapshots include my VDC configuration?
Configuration of VDC items such as virtual firewalls, load balancers and virtual networks are backed up at a platform level, and cannot be restored on a per‑customer basis.
You can create an individual backup of these items via the vCloud API.
What is the automated VM snapshot frequency?
Once every 24 hours.
How long can I store a backup?
Data is stored for 14 or 28 days, depending on the retention policy you choose.
Can I set my own schedules?
We do not currently support custom schedules.
Can I take a snapshot backup against a VM on demand?
Not with the UKCloud automated VM snapshot service.
If you need to snapshot autonomously, you can install your own protection service and use our Cloud Storage service.
Is the automated VM snapshot backup full or incremental?
We take a full automated backup of the VM.
Can I recover individual files using UKCloud's automated VM snapshot backup?
To restore individual files, you need to extract them from the whole VM image that we restore to a new VM. You can access the new VM, find the data you want and transfer it to the original VM. Standard charges will be incurred for the temporary VM.
Can I set a global policy for all VMs within a VDC?
Yes. You can apply the global policy to new VMs created in the VDC or to all new and existing VMs.
For the steps required to do this, see How to manage Snapshot Protection for your VMs.
Can I change the snapshot retention policy for a VM?
Yes, you can use the UKCloud Portal to change the snapshot retention policy.
For the steps required to do this, see How to manage Snapshot Protection for your VMs.
What type of data is the automated VM snapshot backup solution suitable for?
The service is suitable for data certified as OFFICIAL and OFFICIAL-SENSITIVE and is available on both UKCloud platforms: Assured OFFICIAL (formerly IL2) and Elevated OFFICIAL (formerly IL3).
Do large VMs affect snapshot backups?
For regions 1, 2, 7 and 8, large VMs (2 TiB+) with high change rates are not recommended for Snapshot Protection, as the service will spend longer trying to establish what has changed and then attempt to back all of it up. You should take an alternative backup approach with VMs of this size in these regions.
For regions 5, 6, 13 and 14, you can use Snapshot Protection for large VMs. However, you should still consider the impact of recovery time for large VMs.
Can I restrict the automated VM snapshot backup to specific files or directories?
No, this is not currently possible. You can implement your own protection solution if this is a requirement.
Where is the protected data stored?
By default, all snapshot backups are stored in the opposite site from the one that the VM is running in; so a VM running in Farnborough stores its snapshot in Corsham.
You cannot presently request a preference to change the location.
What SLA do you offer on snapshot backup success?
There's currently no SLA associated with the snapshot backup service, although it is monitored 24x7.
How do I restore data?
You can request restoration of VMs only if you have access to the support ticketing system.
To restore data, administrators can access the UKCloud Portal and, using My Calls, create a support ticket stating the VM and the backup schedule they want to restore. UKCloud operations then complete this task, restoring the entire VM image.
How quickly can you restore a VM?
The larger the VM, the longer the restore time:
When restoring over the existing VM, restore times are reduced by the use of change block tracking.
When restoring alongside an existing service, data restoration must start from scratch. Depending on the size of the VM, this can take many hours.
Do I need to install any software on my VMs?
The automated VM snapshot backup works directly with the cloud platform to capture the entire VM, so there is no need to install any software within the VM.
We do recommend that you install VMware Tools on all VMs running on UKCloud for VMware. For more information, see VMware Tools installation.
If a VM is deleted, how long will existing snapshot backups be retained?
The UKCloud platform automates the deletion of backups as they reach their retention date. Therefore, 14 or 28 days after the VM is deleted, depending on your chosen profile, the last snapshot backup will automatically be removed from the platform and consequently be unavailable for restore.
How and when am I notified of snapshot backup failures?
Backup information, including failures, is updated daily on the UKCloud platform by 10:00, but typically within minutes of the close of the backup window.
For the steps required to access the status of a VM's snapshot backup, see How to manage Snapshot Protection for your VMs.
Note that we do not presently provide real-time alerting on individual VMs.
What is the process for dealing with failures?
UKCloud's internal monitoring tools provide us with advanced warnings regarding any backup failures.
The UKCloud support team receives a daily report of snapshot backup failures. We'll raise a service ticket on your behalf and proactively investigate with you when:
Any VM has a failure count of more than two
Three or more VMs within the same VDC fail within 14 days
What does the proactive investigation consist of?
UKCloud's proactive corrective measures depend on the nature of the snapshot backup failures, but will generally follow this outline:
We evaluate snapshot backup failures and look for emerging patterns.
In the case of a repetitive failure, we'll raise a service request on your behalf.
We'll conduct an investigation into the snapshot backup failure, and take appropriate mitigation steps.
Should the failure persist, we may suggest a customer review to try to resolve the issue.
If we identify that the snapshot backup service is incompatible with your application and intended usage, we'll recommend a session with a Service Delivery Manager or solution architect to work through alternative protection options.
How and when are reruns scheduled?
Backups are attempted during the hours of 20:00 and 08:00.
A backup will not be reattempted in the same backup window, but will be included as normal in the next window.
If a snapshot backup attempt is returned as a failure this will be reported to the UKCloud support team, and any remedial actions will be in place for the backup attempt in the next window.
How is the automated VM snapshot backup service charged?
The service is charged on a per VM basis based on:
The size of the VM you are backing up
The amount of additional data you are backing up
The length of time those backups are held
When I disable snapshot protection on my VM, will billing immediately stop?
Billing stops immediately and you will no longer be charged regardless of the chosen retention period. In addition, you will no longer have access to any snapshots taken.
If I have an existing VDC that includes snapshot protection, is protection automatically added to any new VMs I create?
Yes, if the service level of your VDC includes snapshot protection (either selected for an Essential, Power or Priority VM or the former "STANDARD" or "ENHANCED"), that protection is automatically applied to any VMs you create within that VDC. You can still use the self‑service backup functionality within the UKCloud Portal to remove snapshot protection from a VM or change the retention policy without having to raise a Service Request.
Can I set retention policies at a VDC level?
Yes, you can set retention polices at a VDC level, meaning that all VMs within the VDC will inherit the retention policy set.
What happens if I add VMs to a VDC that has a defined retention policy?
All VMs that are created once a VDC policy is set will be automatically added into the protection policy. If you decide to change the VDC policy, you can choose to apply the new policy to ALL existing VMs in the VDC. Further details can be found in the Snapshot Protection Service Scope and guidance on how to apply protection to VMs and VDCs can be found in the How to manage Snapshot Protection for your VMs.
Are snapshot policies automatically applied to VMs?
Protection products are not automatically applied to VMs running on the UKCloud platform, therefore you must explicitly select the protection option that best meets your requirements.
Feedback
If you find a problem with this article, click Improve this Doc to make the change yourself or raise an issue in GitHub. If you have an idea for how we could improve any of our services, send an email to feedback@ukcloud.com.


Shapes and lines
Last time we've created a simple application which draws a single pixel.
This time we're going to make more complex "picture".
Copy canvas element and javascript includes from previous tut into your new .html file. The "main.js" file should look like:
var View = pxl.View;
var bresenham = pxl.bresenham; //<----
View.activeView = View.create({
"layoutSize": {
width: 128,
height: 128
},
"element": document.querySelector("CANVAS")
});
var options = {
"start": new pxl.Point, //by default, both x and y are equal to 0
"offset": new pxl.Point(1), //both x and y are initialized with 1
"pixel": pxl.RGBA(0, 0, 0, 255) //black, 0x000000FF
};
The only major difference here is a new variable which refer to "bresenham" class. It is main helper with creating sharp lines and shapes.
The semantics is pretty simple: first two parameters are for start position, next two parameters are for end position and last one is a callback, which is called per pixel.
Now let's draw the line:
bresenham.line(0, 0, 127, 50, function(x, y){
//Don't forget about options!
//Each time we have to update its "start" property:
options.start.set(x, y);
//Already familiar method from previous tut:
View.activeView.drawRect(options);
});
Please, run the .html file and as a result you should have a black line on your screen.
The following two methods are the same easy as the previous one:
bresenham.rectangle(32, 32, 100, 100, function(x, y){
//Nothing new here...
options.start.set(x, y);
View.activeView.drawRect(options);
});
Even ellipse drawing is not differ. It still have first four parametrs for positioning and fifth for a callback.
//Ellipse inside an "imagine" rectangle:
bresenham.ellipse(20, 120, 120, 75, function(x, y){
options.start.set(x, y);
View.activeView.drawRect(options);
});
And that's all for this time! There are no more shapes yet.
You can play with parameters to see how it affects on a result. But be careful and don't jump out of screen!


I love solving a good problem! I’m experienced in communicating technical solutions to non-technical people, writing efficient programs, and selflessly contributing to the team.
My true identity is...
GPA: 3.73
GPA: 4.00
Besides programming, I have a variety of other passions. In the winter, you can find me shredding the ski slopes. On the court, I’ll be ripping down rebounds (because my jump shot could use some work). In my YouTube history, you will find remains of funny videos and standup comedy shows. And year round, you can always find me playing ultimate frisbee.
When forced indoors, I watch movies like nobody's business. I am a proud older brother to nine siblings and I love spending as much time with my family as I can.


Fundamentals of
Data Analytics and
Predictions
Regression 1
Xi (Rossi) LUO
Department of Biostatistics and Data Science
School of Public Health
The University of Texas Health Science Center at Houston
Outline
- Regression Analysis History
- Simple Linear Regression Overview
- Multiple Linear Regression
- Other Considerations In The Regression Context
Review of types of Statistical Learning
- Supervised learning
- Unsupervised learning
- Semi-supervised learning
Review of types of Statistical Learning
-
Input variables: predictors, covariates, independent variables
-
Output variables: outcome, responses, dependent variables
- Supervised learning: Use the inputs to predict the output values based on the training data
- Unsupervised learning: No response variable, e.g., clustering—more challenging
- Semi-supervised learning: Some cases with response variables and some cases are not
Supervised Learning
- Variable types:
- Quantitative measurement variables
- Qualitative variables: categorical or discrete variables
- Ordered categorical variables: Ordinal variables
- Prediction tasks
- Regression: mainly predict quantitative outputs
- Classification: predict qualitative outputs
- Regression can also be used to predict qualitative outputs—perform clustering.
Regression Analysis: Definition
- Investigate relationships between a dependent variable (response) and independent variables
(covariates, predictors):
$$
𝑦=𝑓(𝑥_1,𝑥_2,…𝑥_𝑝;𝛽)
$$
- Association: Existing $X$
- Prediction and forecasting: New $X$
Why Linear Regression In This Course?
- Still useful and widely used for prediction
- Lays foundation for many more advanced methods that we will learn about later in the course
- Can sometimes outperform fancier nonlinear models, especially in situations with small numbers
of training cases, low signal-to-noise ratio or sparse data
- Finally, linear methods can be applied to transformations of the inputs and this considerably
expands their scope
Regression Analysis History—1
- Roger Cotes, 1722
The combination of different observations as being the best estimate of the true value; errors
decrease with aggregation rather than increase
- Pierre-Simon Laplace, 1788
The combination of different observations as being the best estimate of the true value; errors
decrease with aggregation rather than increase (explaining the differences in motion of Jupiter
and Saturn)
Regression Analysis History—2
- Adrien-Marie Legendre, 1805
First clear and concise exposition of the method of least squares; algebraic procedure for
fitting linear equations to data
- Carl Friedrich Gauss , 1809, but claimed to have it since 1795
Least Squares, showed arithmetic mean is best estimate of location parameter; then asked what
form the density should have and what method of estimation to get arithmetic mean.
Regression Analysis History—3
- Laplace: proved the central limit theorem in 1810 (give a large sample justification for the
method of least square and the normal distribution)
- The LS idea was independently formulated by the American Robert Adrain in 1808
Regression Analysis History—4
- The term “regression” was coined by Francis Galton in 19th century
- Udny G. Yule and Karl Pearson: 1897, 1903
- R.A. Fisher: 1922-1955
- Research in regression models: still popular
Types of Regression Models—1
- Linear models
- Nonlinear models
- Nonparametric models
- Semiparametric models
- Generalized regression models: non-normal response data
- Regression models for survival data
- Regression for time series data
- Regression for longitudinal data
- Regression for new types of data: curves, functional data, network, graphs, images, object data
etc.
Types of Regression Methods—2
- Robust regression
- Multivariate regression
- Stepwise regression
- Bayesian regression
- Regression with missing data
- Regression with errors in covariates
Motivating Example
The data for this example come from a study by Stamey et al. (1989). They examined the correlation
between the level of prostate-specific antigen and a number of clinical measures in men who were
about to receive a radical prostatectomy. The variables are log cancer volume (lcavol), log prostate
weight (lweight), age, log of the amount of benign prostatic hyperplasia (lbph), seminal vesicle
invasion (svi), log of capsular penetration (lcp), Gleason score (gleason), and percent of Gleason
scores 4 or 5 (pgg45).
Linear Regression
- Simple Linear Model
$Y=\beta_0+\beta_1X+\epsilon$
- Error: Mean 0 and variance $\sigma^2$
- Can also write as $Y\approx\beta_0+\beta_1X$
- Use the training data to estimate the parameters:
$\hat{y}\approx\hat{\beta_0}+\hat{\beta_1}X$
Simple Linear Model
- Given n points ($x_1$, $y_1$), ($x_2$, $y_2$), … , we want to determine a function y=f(x) that
is close to them.
Simple Linear Model: LSE
- Given n points ($x_1$, $y_1$), ($x_2$, $y_2$), … , we will fit them to a line
$y=\beta_0+\beta_1x$
- Predicted y values:$\hat{y_i}=\beta_0+\beta_1x_i$
- Data: $y_i=\beta_0+\beta_1x_i+\epsilon_i$
- Residual:$\epsilon_i=y_i-\hat{y_i}=y_i-(\beta_0+\beta_1x_i)$, data vs estimates
- The least squares method: pick parameters that minimize the sum of squares of the
residuals
$$
L=\sum_{i=1}^{n}(y_i-(\beta_0+\beta_1x_i))^2
$$
- In other words, minimize RSS=$\epsilon_1^2+\epsilon_2^2+...+\epsilon_n^2$
Simple Linear Model: Coefficients
- Using calculus, can solve for the best estimates for $\beta_0$ and $\beta_1$:
$$
\hat{\beta_1}=\frac{\sum_{i=1}^{n}(x_i-\bar{x})(y_i-\bar{y})}{\sum_{i=1}^{n}(x_i-\bar{x})^2}
\quad \hat{\beta_0}=\bar{y}-\hat{\beta_1}\bar{x}
$$
Assessing the Accuracy of Model Coefficient Estimates
- $\beta_0$ - intercept term (expected value of Y when X=0)
- $\beta_1$- slope term (average increase in Y for a unit increase in X)
- Note that our estimates $\beta_0$ and $\beta_1$ are based on a random sample (our
training set)
- Simulation Model
$Y=2+3X+\epsilon$
- Red line: True model
$f(x)=2+3X$
- Blue line: LS estimate
$Y=\beta_0+\beta_1X+\epsilon$
Estimation Error Example
Simple Linear Model: Estimation Error
- LS fitting is not perfect due to errors in parameter estimates
- How to evaluate the goodness-of-fit?
- Estimation standard error (SE):
- $SE(\hat{\beta_0})^2=\sigma^2[\frac{1}{n}+\frac{\bar{x}^2}{\sum_{i=1}^{n}(x_i-\bar{x}^2)}]$
- $SE(\hat{\beta_1})^2=\frac{\sigma^2}{\sum_{i=1}^{n}(x_i-\bar{x})^2}$
- where $\sigma^2=Var(\epsilon)$
- 95% CIs: $\hat{\beta_0}{\displaystyle \pm }2SE(\hat{\beta_0})$,
$\hat{\beta_1}{\displaystyle \pm
}2SE(\hat{\beta_1})$
Simple Linear Model: Fitting Error—1
- Prediction value based on $x_i$($i$th row):
$\hat{y_i}=\hat{\beta_0}+\hat{\beta_1}x_i$
- Residual: $\epsilon_i=y_i-\hat{y_i}$
- Residual sum of squares (RSS):
$$
\epsilon_1^2+\epsilon_2^2+...+\epsilon_n^2=(y_1-\hat{\beta_0}-\hat{\beta_1}x_1)^2 \\ +
(y_2-\hat{\beta_0}-\hat{\beta_1}x_2)^2+...+(y_n-\hat{\beta_0}-\hat{\beta_1}x_n)^2
$$
- Residual standard error (RSE):
$\sqrt{\frac{1}{n-2}RSS}=\sqrt{\frac{1}{n-2}\sum_{i=1}^{n}(y_i-\hat{y_i})^2}$
Simple Linear Model: Fitting Error—2
- RSE: An absolute measure of lack of fit
- An alternative measure is $R^2$: The proportion of variance explained by predictors:
$$
R^2=\frac{TSS-RSS}{TSS}=1-\frac{RSS}{TSS}
$$
$TSS=\sum(y_i-\bar{y_i})^2$ is the total sum of squares
- $R^2$: between 0 and 1
- Residual plots and other tools
Simple Linear Model: Hypothesis Testing
- $H_0$ : No relationship between X and Y
$$H_0:\beta_1=0$$
- $H_1$ : Some relationship between X and Y
$$H_1:\beta_1\neq0$$
- T-statistic:
$$t=\frac{\hat{\beta_1}-0}{SE(\hat{\beta_1})}$$
Simple Linear Model: Prediction
- Learn from a training data set: ($x_1$,$y_1$ ),($x_2$,$y_2$ ), …,($x_n$,$y_n$)
- Association: $Y=\beta_0+\beta_1$X
- For a given new $X^*$, predict the mean response:
$\hat{Y^*}=\hat{\beta_0}+\hat{\beta_1}X^*=\bar{Y}+\hat{\beta_1}(X^*-\bar{X})$
- Prediction error for mean response:
$$ \scriptsize Var(\hat{Y}^*)=Var(\bar{Y})+(X^*-\bar{X})^2Var(\hat{\beta_1})
=\frac{\sigma^2}{n}+\frac{(X^*-\bar{x})^2\sigma^2}{\sum_{i=1}^{n}(X_i-\bar{X})^2}$$
- Estimated SE of mean response:
$\scriptsize Est.SE(\hat{Y}^*
)=\hat{\sigma}\sqrt{\frac{1}{n}+(X^*-\bar{X})^2/\sum_{i=1}^{n}(X_i-\bar{X})^2} $
Simple Linear Model: Individual Response Prediction
- Predicted value of an individual response
$\hat{Y}^*=\hat{\beta_0}+\hat{\beta_1}X^*=\bar{Y}+\hat{
\beta_1}(X^*-\bar{X})$
- The variance for predicted value of an individual response: the actual observed
value of Y
varies about its true mean with variance $\sigma^2$
$Var(\hat{Y}^*)={\color{blue}
{ \sigma^2} }+\frac{\sigma^2}{n}+\frac{(x^*-\bar{x})^2\sigma^2}{\sum_{i=1}^{n}(x_i-\bar{x})^2}$
- Estimated SE of individual response:
$Est.
SE(\hat{Y}^*)=\hat{\sigma}\sqrt{1+\frac{1}{n}+\frac{(x^*-\bar{x})^2}{\sum_{i=1}^{n}(x_i-\bar{x})^2}}$
Simple Linear Model: Mean and Individual Response
- Predicted value of mean response and an individual response: the same
- The variance is different by $\sigma^2$
- 100(1-$\alpha$)% prediction interval:
$$
\hat{Y}^*{\displaystyle \pm }t_{n-2,\alpha/2}(Est.SE(\hat{Y}^*))
$$
Multiple Linear Regression
- In practice, we often have more than one predictor.
- In the prostate cancer data, we also have other information that may help in the
prediction of
the log PSA level.
- Log prostate weight
- Age (years)
- Log of the amount of benign prostatic hyperplasia
- Seminal vesicle invation
- Log of capsular penetration
- Gleason score
- Percent of Gleason score 4 or 5
Extending Simple Linear Regression
- Extend the simple linear regression for p variables:
$$
Y=\beta_0+\beta_1X_1+...+\beta_pX_p+\epsilon
$$
- where $X_j$ represents the jth predictor and $\beta_j$ quantifies the
association between
that predictor and the response (the average effect on Y of a one unit increase
in $X_j$,
holding all other predictors fixed).
Matrix Notation
- The ith observation is ($x_{i1}$, $x_{i2}$,…, $x_{ip}$,$y_j$), leading to
$$
𝑦_𝑖=𝛽_0+𝛽_1 𝑥_{𝑖1}+𝛽_2 𝑥_{𝑖2}+…+𝛽_𝑝 𝑥_{𝑖𝑝}+𝜖_𝑖
$$
- Matrix notation:
$$
𝑦 ⃗=𝑋 𝛽 + 𝜖
$$
- MLE point estimate of $\overrightarrow{\beta}$ is
$\hat{\overrightarrow{{\beta}}} =(𝑋^T 𝑋)^{-1}
𝑋^{T} 𝑦 ⃗$
- Need $X^T X$ to be non-singular and $n ≥ p+1$ (usually a lot bigger)
MLR Estimation
- Using Matrix notation: $y = X \beta + \epsilon$
- Estimation of 𝛽 (LSE or MLE):
$$\hat{\beta}=(X^TX )^{-1} 𝑋^𝑇 𝑦 $$
- Hypothesis testing:
$$𝐻_0:𝛽_1=𝛽_2=⋯𝛽_𝑝=0 $$ vs $$𝐻_𝐴: \mbox{at least one } 𝛽_𝑗 \mbox{ is non-zero}$$
F-test
- The F-test for $H_0$ is based on the decomposition
$$𝑅𝑆𝑆_0=(𝑅𝑆𝑆_0−𝑅𝑆𝑆_1 )+𝑅𝑆𝑆_1$$
- It can be shown that
$$𝑅𝑆𝑆_1∕\sigma^2\sim \chi^2 (n-d)$$
- Under H0
$$(RSS_0-RSS_1)/\sigma^2 \sim\chi^2(q)$$
- And is independent of $𝑅𝑆𝑆_1∕\sigma^2$
F-Test
$$\frac{RSS_0-RSS_1/q}{RSS_1/{n-d}}\sim F_{q,n-d}$$
- An alternative approach to F-test is the likelihood ratio test (LRT)
$$\lambda=2((l(H_1)-l(H_0))→\chi^2(q)$$
- It can be proved that $\lambda=2log(RSS_0/RSS_1)$
- Which is a monotone increasing function of $RSS_0/RSS_1$ , so is F-test. Thus, the
LRT is
equivalent to F-test
Mean and Individual Responses
- Prediction for the true mean response at $x_0$ (row)
$100(1−\alpha$)%$ CI: $$\hat{Y_0}\pm t_{n-k-1,\alpha/2}\sigma
\sqrt{x_0 (X^TX)^{-1}x_0^T}$
- Prediction for an individual response at $x_0$
$100(1−\alpha$)%$ CI: $$\hat{Y_0}\pm t_{n-k-1,\alpha/2}\sigma
\sqrt{ {\color{red} 1 } +x_0(X^TX)^{-1}x_0^T}$
Linear in Parameters
- Even though there may be a strong relationship between $X$s and $Y$, the linearity
assumption may
not hold for a lot of problems. However, transformations of the data can help the
linearity
assumption to be mostly satisfied.
- Can use knowledge of the underlying problem or use graphical methods to visualize
the data to
get an idea of the general form of the function.
- Example:
- Line: $y=\beta_0+\beta_1x$
- Polynomial: $y=\beta_0+\beta_1x+\beta_2x^2+\beta_3x^2$
- Exponential: $y=Ae^{Bx}$
- Sinusoidal: $y=A+B\cos(x)+C\sin(x)$
Linear Regression: Other Issues—1
- Qualitative predictors: Use of “dummy variables”
- Transformation: Log, Exponential, square-root, Box-Cox transformation, etc.
- Convert nonlinear models into linear models
- Random error: more like a normal distribution
- Stabilize variance
Linear Regression: Other Issues—2
- Standardization of your data and coefficients
$$y_i=\beta_0+\beta_1X_{1i}+\beta_2X_{2i}+\beta_3X_{3i}+\epsilon$$
$$\frac{y_i-\bar{y}}{s_y}=\beta_1^*\frac{x_{1i}-\bar{x_1}}{s_{x1}}+\beta_2^*\frac{x_{2i}-\bar{x_2}}{s_{x2}}+\beta_3^*\frac{x_{3i}-\bar{x_3}}{s_{x3}}+\epsilon_i$$
- Better to evaluate relative importance of predictors
Linear Regression: Other Issues—3
- Correlated errors or non-constant variance of errors: Time series regression,
Longitudinal data
models, etc.
- Multiple response variables: Multivariate regression
- Collinearity: Covariates are correlated
- Model selection or variable selection


| DOSE: T+ 0:00 |
1 hit |
oral |
LSD |
(blotter / tab) |
| T+ 0:30 |
1 hit |
oral |
LSD |
(blotter / tab) |
| T+ 2:00 |
1 tablet |
oral |
MDMA |
(pill / tablet) |
First, to give you a little background on myself; I am currently 16 years old. I have been experimenting with drugs for about 3 years. Started with marijuana (which has evolved into 3-4 times per week usage), a brief stint with any kind of painkillers/downers (Perkaset, vicodin), then in High School I was introduced to both LSD and Ecstasy. I had done E twice and LSDonce (both on their own) before the combination I'm about to explain to you.
I had recieved the two hits a LSD from a close female friend who got them at a rave she had gone to. Ironically another friend also attended a rave, and had one E tab left, that she gave to me at the same time. So I took this as a sign (since i had always wanted to candy-flip), and decided to do both on a Friday night.
I now look back on it as a bad decision, but I candy-flipped while going out with 3 of my male friends (I am a male, but am quite feminine) none of which had any acid or E experiences.
I dropped one hit of the lsd at one friends house. We were waiting for our other friend with an automobile to arrive. It had been about 20-25 minutes since the ingestion, and my surroundings became extremely vivid, and everything became sharper.
But once we got in the car and headed off, I dropped the other hit, and was bombarded with questions. I attempted to explain what I was feeling, but from what my friends told me, I wasn't making much sense. Driving in the dark was amazing. The road, and the scenery I could make out, dissolved into one big fantastic blur. Then the yellow lines on the road suddenly stuck out, and started dancing. Visually it was absolutely amazing. By now I was tripping pretty hard, and in trying to communicate, I was spitting out words that didn't make much sense. All of my friends thought this was amazingly funny, and laughed histerically. This brought a cloud of self-conciousness around me, and I stopped talking all together. Then my friends kept trying to scare me by yelling, and lighting a lighter by my foot.
I was glad when we reached our destination, a Fred Meyer's where we were meeting a friend who was going to streak that night. It had been about 2 hours since my first acid hit, so I swallowed down the E-bomb. The inside of the store changed into a new and wierd world. During the 30 minutes we were inside, a figure (cleary an elf), continued to follow me. The 'elf' was nither threatening or comforting, just there. I was still unable to communicate, and still being made fun of. After constantly being made fun of for about 15 minutes, and seriously told my friends to stop it, I was getting scared. Even though they had never experienced it, they seemed to understand, and just became quiet. As they were waiting in line to pay, one of them set me up on a mechanical Donald Duck. As Donald swayed back in forth, I began to feel the E's physical sensation, and my body melted into a steady rythm, which I kept going even after the ride had stopped.
By now the E's empathy, and social understanding kicked in. It was at this time people started emmitting, or vibrating colors. While strangers appeared alien, and no particular color, my friends distinctly gave off 'color vibrations'. Of my three amigos, two glowed in black, while the third was a mellow yellow. Searching the vast cosmos of my brain to understand why, I realized that black symbolized cruelty and a bad attitude. While the yellow symbolized the third friends, sort of neutral actions towards me.
We then hooked up with are 'naturalist' friend. Ironically the streaker's girlfriend was the person who gave me the acid. Both my E and LSD experiences had taken place with her, and I was overjoyed when I found out she had accompanyed her boyfriend. As soon as she was informed I was candyflipping, she came over to me, and asked me what I was feeling, as she rubbed hands. She immediatly vibrated red and was warm to the touch.
It was too early to streak, so they decided to go to a Burger King, and kill an hour. By now my mind was just totally blown, and I went along for the ride. I escaped from the 'bad vibe' car, and rode in the back seat with my wonderful female friend. The physical sensations of the E were pretty intense, and she rubbed my hand, and stroked my skin. I then realized how cold I had been all night, and her warm touch was much welcome.
The hour we spent at Burger King was undescribable. Both substances seemed to be peaking, beautifully at the same time. I sat by my 'red' friend, and she continued to play with my sensitive skin. My whole body vibrated wonderful physical sensations, and colors swirled around the air. I sat in blissful silence for I don't know how long, with a smile imprinted on my face. Remembering they brought a video camera along, somebody broght it in. I was extremely fascinated by the camera. The lcd screen seemed like portal to a new world filled with vibrant colors. I would suggest a camera as a 'toy' for anyone candy-flipping.
What happened next I can't really recall. The guy streaked, and I was waiting in the 'get away vehicle'. When it finally hit me what was going on, I couldn't stop laughing. The guy ran out of the store, hopped in the car, and we sped off. While it was a blur, I found it histerical. The two vehicles got seperated during the indecent exposure, and it took what seemed like an eternity to meet back up with the other car, and more importantly my female friend.
When we finally did reunite, I had been clenching my jaw, so it was sore and I was thirsty. So with my friends in toe, I bravely walked into a Safeway. The bright white floors immediately took the shape of clouds. The other customers, and the loud speaker, talked in a unusually language made up of blips, bleeps, and echoes. I floated across the clouds, purchased my water and candy, and we all headed out to the parking lot. It was getting late, and everybody was talking about going home. While I was planning on spending the night at the driver's house, his parents were going to be home, and he was still 'black'. As luck would have it my female friend's parents were out of town, so I ended up crashing at her place.
By the time we arrived at her house it was 1:30am, but she stayed up and comforted me during the beginning of my comedown, but eventually she fell asleep. She was a wonderful host as usual, and provided me with a big comforter, and soft pillows. After she entered the dream world, I relished in my soft bedding. I layed back and 'melted' into the comforter and pillows. I ended up not sleeping but maybe an hour that night. I passed time by meditating, and reflecting on my reality prior to this chemically-induced change in my surroundings. I also discovered a collection of 'Dr. Suess' books and slowly read all 15 of them.
The greatest thing I got from this experience was a renouned appreciation for my close friend. That night, and since then I have noticed all the wonderful things she does for me. I took about 2 hours telling her this the next day, and since then we have a 'undescribably loving' relationship.
I hope you found my description of the most wonderful feeling, somewhat entertaining. But at the least I hope you will learn from my mistakes, and candy-flip (even LSD, or E by respective selfs) with a close friend, who is both understanding and has your same outlook on life.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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Class Mapbender
Mapbender - The central Mapbender3 service(core). Provides metadata about available elements, layers and templates.
Namespace: Mapbender\CoreBundle
Author: Christian Wygoda
Author: Andriy Oblivantsev
Located at Mapbender/CoreBundle/Mapbender.php
Author: Christian Wygoda
Author: Andriy Oblivantsev
Located at Mapbender/CoreBundle/Mapbender.php
Methods summary
public
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#
__construct( Symfony\Component\DependencyInjection\ContainerInterface $container )
Mapbender constructor. |
public
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public
array
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public
array
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public
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public
Doctrine\DBAL\Connection
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public
Doctrine\Common\Persistence\ObjectManager|Doctrine\ORM\EntityManager
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public
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public
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public
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public static
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public
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public
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importYamlApplication( string $slug, string|null $newSlug = null, string|null $newTitle = null )
Import YAML application |
public static
string
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Magic methods summary
Properties summary
protected
Doctrine\ORM\EntityManager|Doctrine\Common\Persistence\ObjectManager
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$manager
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protected
Doctrine\DBAL\Connection
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$connection
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protected
Mapbender\WmsBundle\Entity\WmsInstanceLayer[][]|Doctrine\Common\Collections\ArrayCollection
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$sourceLayers
|
# array() |


Note
Looking for More On Compound Documents?Chris McDonough asks What does it take to be a great software developer?
Many of the skills of a great software developer are rooted in a strong intuition -- intuition both about methodology and technique. Even though it's mysterious, I think intuition is very much something you build, you certainly aren't born with it. (Of course, some people may build it more quickly.) Intuition is the accumulated knowledge and wisdom when you've forgotten the source, or the accumulated result of lots of little lessons and learning experiences. And, we should all know, lessons are best learned through making mistakes.
Miguel de Icaza talks about something that I think it related:
What I like about this story [about solving a challenging problem in the development of Gnumeric], is that I could have given up at any point since there was a large problem ahead of me: a problem I had no answers to. And I see this with many free software developers, students and even in normal social situations: people stop doing things because they see a big problem ahead of them that they can not possibly conceive working around. My advise to every young programmer is to start writing code and delay addressing imaginary problems until they become real.
There's always a hard problem for which you won't have answers. When you become a better developer you will still always encounter these problems (at least if you are challenging yourself -- if not, then you need to find more challenging work, or make some work for yourself). I don't think any developer, no matter how great, will feel that they have Arrived, that their knowledge and skill is sufficient, because we can always dream of more than we can create. (Which is good, of course.)
Besides tackling challenging problems -- and making mistakes -- I think it's important to be opinionated about what you're doing. This applies to any craft, not just software. It's better to be rash and mistaken than to be withhold opinion, or to simply defer to the opinion of others. (Of course, none of this works if you are stubborn and won't change your opinion, because than you'll be stuck with premature and incorrect opinions.) But after making an opinion, you must of course be reflective and thoughtful, and have a bit of humility, so you can recognize where you were right and where you were wrong. And somewhere in this process you should be developing an intuition, but you probably won't realize its arrival, nor will ever be clear exactly where it came from.


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This test checks that the background of positioned items is painted in the right position.
The test passes if you see 4 green boxes and no red.


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--- imgsrc: "Will_deutsch_jewish_art_shiva_death_judaism_jews.jpg" buylink: "http://store.notesfromthetribe.com/product/jewish-art-8-5-x11-shiva-print" postDate: "06.20.13" layout: post ---
There is never really a convenient time for somebody to die.
But when you’re Jewish, dying the day before Passover is especially inconvenient.
And that is exactly what my father did.
See, the thing about death is that there’s a lot of heavy lifting for those left behind.
In short: it’s a lot of work.
I received word from my mother that my father had left his earthly shell April 7th, 2009, right around 6am.
Her voice seemed formless on the other end of the phone. ‘Come down to the hospital. They haven’t taken his body yet. Its still warm under his arms.’ She said it like I needed to grab a feel before it cooled.
I was tired. I was in shock and the thought that my father’s still warm body was waiting for me on the 8th floor of Hoag seemed altogether absurd.
And yet this was happening.
I’d spent the entire night before rearranging his bedroom with my brother so that we could move him from the cancer ward to a hospital bed in the house so he could die around the home he’d worked so tirelessly to create.
Now it seemed a futile final gesture.
I woke my brother with the news (minus the part about his arms) and informed him we had to get moving.
Looking back, my sense of urgency seems odd considering that my father wasn’t exactly going anywhere.
30 minutes or so later we arrived to find my father’s body without him in it.
They’d removed all life support systems. He actually looked better dead than he had alive. No tubes sticking out of his nose. No wires running the length of his appendages to incomprehensible monitors that beeped and bopped from time to time letting us know that his internal organs had not yet ceased.
Death suited him.
I’d never seen a cadaver before, let alone his. The sensation is comparable to that of walking down a flight of familiar stairs at night and at the very end misstepping into air because you have somehow miscounted an extra ‘phantom step’.  The familiar, for the briefest of moments….simply isn’t.
The details were all in order. His facial hair. The slight indent between his eyes from a lifetime of of wearing glasses. The powerful, round, sausage like fingers that still gently pressed their tips against the bed as if at any moment he might push down on the mattress to right himself up. And yet, there was something less about him. Obviously. The undersides of his arms were indeed still warm, but his forehead was a cold that I had never felt. The kind that came from a lack of inner warmth rather than an outer chill.
On the table next to his bed was a three day old stale brownie with walnuts that had long since adhered itself to the plate so that when turned upside down it stuck.
An uneaten last meal.
We still had to get ahold of my sister up in Los Angeles. It was an hour drive. And so the work began. Rounding up the troops. Finding a ride for her. Calling person after person to let them know the world had turned on its axis.
I made sure we had breakfast.
This was going to be tough and I would be damned if we were going to do it on an empty stomach.
A young girl from catering came to check in on us. Gesturing to my father’s corpse, she inquired as to whether he’d like whole or skim milk. ‘He’s dead’ my mother replied blankly. Visibly shaken, the teenage girl apologized and ducked out.
Those of us that could, ate Frosted Flakes while the hospital started making preparations of what to do with the body.
His palliative care doctor, a kind and what I perceived to be religious man, came in and thanked him for being a great patient as though he were still alive. He seemed wholly and completely unfazed that he was not.
A nurse reluctantly let us crack the door open so somebody could continually watch his body as it was zipped up in a bag and placed on a gurney.
We followed it in the elevator down eight floors.
Last stop…the coroner. Unlike the other sterile parts of the hospital which looked like they had been terribly chic in the mid 90’s with their southwestern topaz and burnt orange color palate this was a dull, grey, subterranean basement. The orderlies wheeled the gurney into a room next to an open closet filled with economy sized tubs of twizzlers, fritos, peanut m and m’s and countless other snack foods that fed the hospital population. I tried to keep watch only to have the door slammed in my face by a security guard.
Shortly thereafter, he apologized for the vehemence of his gesture as he promptly escorted my family with my father’s body bag in tow to a mortuary van waiting by the dumpsters in the back.
This was where the patients who didn’t live exited. Its discreetness seemed understandable. After all, if I were entering a hospital this is not the scene that would provide me with the most solace.
And then it was done.
We were finished for the day.
It felt like we had lost the big game.

We returned home and hit the ground running.
Preparations needed to be made.
The funeral home was contacted.
My mother would serve as clergy.
Pallbearers needed to be assigned.
We needed catering and a venue for the meal of comfort.
Dates, times and locations for the funeral and shiva minyan needed to be set.
Travel and accommodations needed to be made
The insurance could wait.
Aflac could wait.
We needed to call work and tell them we weren’t coming in.
I still had to write a eulogy.
My sister typed a general note that I copied and pasted to various online social networks.

The house still needed to be cleaned.
Matzah and other kosher for Passover food needed to be purchased.
The fine china needed to be brought out.
We had to set up the extra table in the living room.
Haroset.
Burnt offering.
Horseradish.
A sixteen pound turkey.
We were having a seder.
We were having two seders.
And a funeral.
And a shiva minyan.
But not for five days.
After all, it was Passover and my father was dead.
Like I said, inconvenient.


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Leeds given huge lift over future of influential loan star
Brighton boss Graham Potter has given Leeds a huge lift by declaring that Ben White will not have his loan spell cut short.
Reports emerged on Thursday that both Liverpool and Manchester United were ready to make a move for the 22-year-old, who has so far played a pivotal role in trying to get Leeds back into the Premier League.
However, Potter has ruled out the sale of the centre-back and said he is happy for White to see out the season at Leeds before deciding whether he is ready for Brighton’s first team.
“He’s having a good time at Leeds, so we’ll assess at the end of the season to see what the best thing is going forward,” said Potter.
“Unless there is a real push for it we won’t call him back. He’s having a positive time at Leeds and we are well covered in that position. So, we’ll carry on with that process I think.
“As a coaching team we were aware of him when I was at Swansea, we were one of the clubs who would have tried to get him on loan if I was still there. So I know his quality.
“He had a loan spell at Newport and we tracked his progress for quite some time. He’s a player we like. If you see the way he plays, he’s a player who fits our way. We want to see him playing for Brighton in future.”


A number of years ago, scrapbooks were usually little more than clippings from newspapers, snippets of hair and baby announcements. There were "wedding albums" and "baby books" and some family treasures stowed in albums somewhere. To some, that will always be the definition of a scrapbook. A scrapbook, you see, means different things to different people. And they are all right.
Some scrapbook albums have lots of journaling, some have none, some have a simplified style, others are very complex. There are scrapbookers who preach double page layouts, others, single page layouts. Some trumpet 12x12 pages, and for others 8 1/2 x 11 pages rule the day. Stickers and die cuts may be the main attractions or tear art and decorative paper may take center stage. Some scrapbookers keep their layouts in neat, catalogued binders, while others showcase their work on living room walls.
There is, however, one thing that all good scrapbook pages do: they tell a story. A scrapbook is a story and scrapbooking is storytelling at a precious, personal level. It is organizing moments of the past so they have meaning for future generations. It is a recognition that events make up lives, and it is a celebration of living. Embodied in every scrapbook page is a celebration of life, a moment or moments captured that are especially unique to a person or family. Scrapbookers today are preserving yesterday for tomorrow.
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Scaml
An inner DSL in Scala to write documents.
How to run?
This is a developing library, may you want to run some examples.
API
The API is hosted at http://jentsch.github.io/scaml/api
An inner DSL in Scala to write documents.
This is a developing library, may you want to run some examples.
The API is hosted at http://jentsch.github.io/scaml/api


ZERO EFFECT (1998) A Film Review by Ted Prigge Copyright 1998 Ted Prigge
Writer/Director: Jake Kasdan Starring: Bill Pullman, Ben Stiller, Kim Dickens, Ryan O'Neal, Angela Featherstone
Daryl Zero lives on the secluded top floor of a high-rise hotel, sealed behind metallic doors with six separate locks, surveillance in every room, a station of several computers so that he can work efficiently, and a refrigerator full of Tab sodas, which I thought went out of business but I guess I was wrong. He's unlike most detectives in many ways, but the chief difference between him and anyone else is that he never communicates with his clients: he was a kind of lawyer helping him out who goes to see potential clients, and gives them updates while Daryl uses disguises and aliases to dig deep and find out the answer to whatever job he's hired for.
The weird thing about "Zero Effect" is that it's not really the quirky thriller nor the plug for a TV detective like it may seem to be at first. It creeps up on you where you least expect it, and in the last movie you'd think to have a heart, you find one. Before you know it, you're feeling something for all the characters, and you're more involved in their lives than you are the mystery that this film poses.
The story revolves around one case of Daryl's, played wonderfully by Bill Pullman (whose talent seems to decrease as the budget of a film starring him increases), where he has to find a set of keys to a safe deposit box for a millionaire named Gregory Stark (Ryan O'Neal, trying to find work), and subsequently find out who's been blackmailing him for large amounts of money. Daryl never meets him, but he begins to sneakily find out things by posing as other people, namely a millionaire accountant in town for the weekend and working out at the same health club Gregory does. There's a fascinating set of scenes where he confronts him as an anonymous person, and then goes back to show how he got amazing amounts of information just by mincing a couple words with him.
The running joke in the movie is that Daryl is incredibly observant about physical and psychological things, but that he comes up snake eyes when actually dealing with the emotions of other people he deals with. His long-time partner/lawyer, Steve Arlo (Ben Stiller, showing that he's one of the best comic actors around), detests everything about him, and is desperately trying to find a way to break it to him that he doesn't want to work for him anymore so he can marry his girlfriend (Angela Featherstone). And he seems to never really notice that he's annoying and rude and selfish to everyone around him when he tries to do his bizarro detective work, which makes him completely antisocial.
Instead of the film going on like this, mocking everything that makes up Daryl, and giving us a mystery we are never really blown away by anyway, it gives us something better: a love story, in the weirdest movie. It does this by introducing another character, a woman named Gloria (Kim Dickens) whom he meets at the health club one day and is automatically able to figure out that she's a paramedic since she smells of it. Although turned off at first, she begins to be fascinated with him, and soon the two are discovering more and more about eachother, all the while at least one of them is lying.
"Zero Effect" was written and directed by Jake Kasdan, the son of famous directory Lawrence Kasdan, and he gives the film a comic yet dramatic feel. There's a real story here about characters that are interesting and likable, and he allows that to slowly and subtely come to focus while the mystery plot fades into the background. If I can say one thing bad against this film, it's that the mystery itself isn't all that intriguing. It uncovers a lot, mysteries where generations are harmed by past generations, and it allows a couple cool twists, but in all reality, do we really care about it once the love story has taken precedence? Why worry about a secret hit from 30 years ago when you can relish in a touching love story between two alienated and damaged people?
But, in all reality, that's the strength of this film. It gradually lets us forget about the mystery, and we soon become so involved with the character stories, including the story of Steve and his girlfriend, that we never even realize that it's taken the foreground. Sure, it's still quirky, and there's a lot of big laughs here, especially in the opening sequence which intercuts a meeting Steve has with Gregory and a conversation Steve has with a friend where he contradicts what he says over and over again. But a touching love story and one man's plight into beginning to understand the emotions of other people is something that I sure wasn't expecting, what with the opening promising another quirky thriller a la "Grosse Pointe Blank," but that I was all the more happier to allow happen.
MY RATING (out of 4): ***1/2
Homepage at: http://www.geocities.com/Hollywood/Hills/8335/
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The Internet Movie Database accepts no responsibility for the contents of the
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Related links: index of all rec.arts.movies.reviews reviews


Technical Background¶
The package contains different electric motors, power electronic converters and load models. In this part the technical models are described and references to more detailed explanations are given. All included electric motors can be represented by a system of differential equations and those are the same for the continuous and discrete action case. The load model is the same in all cases. The converters are shortly introduced. More detailed descriptions are included in each converter class, where also the action space is specified.
The DC motors
- permanently excited
- externally excited
- series
- shunt
and the synchronous motors
- permanent magnet synchronous motor (PMSM)
- synchronous reluctance motor (SynRM)
are included. The figure below shows the basic structure of converter, motor and load that is modeled.
Further information about electrical motor and power electronic converters can be found in [Boecker2018a], [Boecker2018b] and [Chiasson2005].
DC Motors¶
Externally Excited Motor¶
The figure shows the circuit diagram of this motor [Boecker2018a].
The equations are
\(u_A=\mathit{\Psi}^\prime_E \omega + L_A \frac{\mathrm{d} i_A}{\mathrm{d} t} +R_A i_A\)
\(u_E=L_E \frac{\mathrm{d} i_E}{\mathrm{d} t} + R_E i_E\)
\(\mathit{\Psi}^\prime_E=L^\prime_E i_E\)
\(T=\mathit{\Psi}^\prime_E i_A\)
\(\frac{\mathrm{d} \omega_{me}}{\mathrm{d} t}=\frac{T-T_L(\omega_{me})}{J}\)
and can be rewritten as
\(\frac{\mathrm{d} i_A}{\mathrm{d} t}=\frac{u_A-L^\prime_E \omega i_E -R_A i_A}{L_A}\)
\(\frac{\mathrm{d} i_E}{\mathrm{d} t}=\frac{u_E-R_E i_E}{L_E}\)
\(\frac{\mathrm{d} \omega_{me}}{\mathrm{d} t}=\frac{L^\prime_E i_A i_E -T_L(\omega_{me})}{J}\text{.}\)
For DC motors is \(\omega_{me}=\omega\) valid.
The quantities for this and the other motors are:
- \(u_A\) armature voltage
- \(u_E\) excitation voltage
- \(i_A\) armature current
- \(i_E\) armature current
- \(R_A\) armature resistance
- \(R_E\) excitation resistance
- \(L_A\) armature inductance
- \(L_E\) excitation inductance
- \(\omega\) (electrical) angular velocity
- \(\omega_{me}\) mechanical angular velocity
- \(L^\prime_E\) effective excitation inductance
- \(T\) Torque produced by the motor
- \(T_L\) Torque from the load
- \(J\) moment of inertia
- \(\mathit{\Psi}^\prime_E\) effective excitation flux
Other motors are build on this motor with different connections of armature and excitation circuit.
Series Motor¶
In this type both circuits are in series connection, \(i=i_A=i_E\) and \(u=u_A+u_E\), as shown in the figure [Boecker2018a].
The equation for this motor are
\(\frac{\mathrm{d} i}{\mathrm{d} t}=-\frac{L^\prime_E}{L_A+L_E} i \omega -\frac{R_A+R_E}{L_A+L_E} i + \frac{1}{L_A+L_E} u\)
\(\frac{\mathrm{d} \omega}{\mathrm{d} t}=\frac{L^\prime_E}{J} i^2-\frac{1}{J}T_L(\omega)\)
The torque equation is the same as before.
Shunt Motor¶
In this type the circuits are connected in parallel, \(i=i_A+i_E\) and \(u=u_A=u_E\), as shown in the figure [Boecker2018a].
The equation for this motor are
\(\frac{\mathrm{d} i_A}{\mathrm{d} t}=\frac{u-L^\prime_E \omega i_E -R_A i_A}{L_A}\)
\(\frac{\mathrm{d} i_E}{\mathrm{d} t}=\frac{u-R_E i_E}{L_E}\)
\(\frac{\mathrm{d} \omega}{\mathrm{d} t}=\frac{L^\prime_E i_A i_E -T_L(\omega)}{J}\)
and the torque equation is the same as before.
Permanently Excited Motor¶
In this type the excitation \(\mathit{\Psi}^\prime_E\) is constant and therefore it only contains the armature circuit of the externally excited motor.
The equations are
\(\frac{\mathrm{d} i}{\mathrm{d} t}=\frac{u-\mathit{\Psi}^\prime_E \omega -R_A i}{L_A}\)
\(\frac{\mathrm{d} \omega}{\mathrm{d} t}=\frac{L^\prime_E i^2 -T_L(\omega)}{J}\)
Permanent Magnet Synchronous Motor (PMSM)¶
The PMSM is a three phase motor with a permanent magnet in the rotor as shown in the figure [Boecker2018b]. The input of this motor are the voltages \(u_a\), \(u_b\) and \(u_c\).
The quantities are:
- \(u_a\), \(u_b\), \(u_c\) phase voltages
- \(i_a\), \(i_b\), \(i_c\) phase currents
- \(R_s\) stator resistance
- \(L_d\) d-axis inductance
- \(L_q\) q-axis inductance
- \(i_{sd}\) d-axis current
- \(i_{sq}\) q-axis current
- \(u_{sd}\) d-axis voltage
- \(u_{sq}\) q-axis voltage
- \(p\) pole pair number
- \(\mathit{\Psi}_p\) permanent linked rotor flux
- \(\epsilon\) rotor position angle
- \(\omega\) (electrical) angular velocity
- \(\omega_{me}\) mechanical angular velocity
- \(T\) Torque produced by the motor
- \(T_L\) Torque from the load
- \(J\) moment of inertia
The electrical angular velocity and the mechanical angular velocity are related such that \(\omega=\omega_{me} p\).
The circuit diagram of the phases are similar to each other and the armature circuit of the externally excited motor.
For an easy computation the three phases are first transformed to the quantities \(\alpha\) and \(\beta\) and afterwards to \(d/q\) coordinates that rotated with the rotor as given in [Boecker2018b].
This results in the equations:
\(u_{sd}=R_s i_{sd}+L_d \frac{\mathrm{d} i_{sd}}{\mathrm{d} t}-\omega_{me}p L_q i_{sq}\)
\(u_{sq}=R_s i_{sq}+L_q \frac{\mathrm{d} i_{sq}}{\mathrm{d} t}+\omega_{me}p L_d i_{sd}+\omega_{me}p \mathit{\Psi}_p\)
\(\frac{\mathrm{d} \omega_{me}}{\mathrm{d} t}=\frac{T-T_L(\omega_{me})}{J}\)
\(T=\frac{3}{2} p (\mathit{\Psi}_p +(L_d-L_q)i_{sd}) i_{sq}\)
A more detailed derivation can be found in [Modeling and High-Performance Control of Electric Machines, John Chiasson (2005)]
The difference between rms and peak values and between line and phase quantities has to be considered at the PMSM. The PMSM is in star conncetion and the line voltage \(U_L\) is mostly given in data sheets as rms value. In the toolbox the nominal value of the phase voltage \(\hat{U}_S=\sqrt{\frac{2}{3}}U_L\) is needed. Furthermore, the supply voltage is typically the same \(u_{sup}=\hat{U}_S\). For example, a line voltage of \(U_L=400~\text{V}\) is given, the rms phase voltage is \(U_S=\sqrt{\frac{1}{3}}U_L = 230.9 \text{ V}\) and the peak value \(\hat{U}_S=326.6 \text{ V}\). The nominal peak current of a phase is given by \(\hat{I}_S=\sqrt{2} I_S\).
Converter¶
The DC input voltage of the converter is named supply voltage \(u_{sup}\) in the package and the output voltage and current are the input quantities of the motor and therefore are named as \(u_{in}\) and \(i_{in}\). All converter contain a dead time of one sampling interval and an interlocking times can be considered. More details can be found in [Boecker2018a], [Boecker2018b] and [Chiasson2005].
1 Quadrant Converter (1QC)¶
This converter can provide positive voltages and positive currents at the output [Boecker2018a].
\(u_{in} \geq 0\)
\(i_{in} \geq 0\)
2 Quadrant Converter (2QC)¶
This converter can provide positive voltages and both current directions at the output [Boecker2018a].
\(u_{in} \geq 0\)
\(i_{in}\) both signs
4 Quadrant Converter (4QC)¶
This converter can provide both voltage and currents polarities at the output [Boecker2018a].
\(u_{in}\) both signs
\(i_{in}\) both signs
Three-Phase Voltage Source Inverter¶
This converter is also called B6 bridge and is used for three phase motors as the PMSM. The supply voltage is DC and it consists of three parallel half bridges, one for each phase \(u_a\), \(u_b\) and \(u_c\). Due to this 8 different switching states are possible. A dead time of one sampling time step and interlocking times can be considered. A symmetric B6 bridge with a voltage range of \([-u_{DC}/2,~+u_{DC}/2]\) is used. [Boecker2018b]
Load Models¶
The package can deal with polynomial load equations
\(T_L(\omega_{me})=\mathrm{sign}(\omega_{me})(c \omega^2_{me} + b \vert\omega_{me}\vert + a)\).
Furthermore an additional moment of inertia \(J_{Load}\) of the load can be set.
References¶
| [Boecker2018a] | (1, 2, 3, 4, 5, 6, 7, 8) Böcker, Joachim; Elektrische Antriebstechnik; 2018; Paderborn University |
| [Boecker2018b] | (1, 2, 3, 4, 5) Böcker, Joachim; Controlled Three-Phase Drives; 2018; Paderborn University |
| [Chiasson2005] | (1, 2) Chiasson, John; Modeling and High-Performance Control of Electric Machines; 2005; Hoboken, NJ, USA |


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A Frame is a top-level window with a title and a border. The size of the frame includes any area designated for the border. The dimensions of the border area may be obtained using the getInsets
method. Since the border area is included in the overall size of the frame, the border effectively obscures a portion of the frame, constraining the area available for rendering and/or displaying subcomponents to the rectangle which has an upper-left corner location of (insets.left
, insets.top)
, and has a size of width - (insets.left + insets.right)
by height - (insets.top + insets.bottom)
.
A frame, implemented as an instance of the
JFrame
class,
is a window that has decorations such as a border, a title,
and supports button components that close or iconify the window.
Applications with a GUI usually include at least one frame.
Applets sometimes use frames, as well.
To make a window that is dependent on another window —
disappearing when the other window is iconified, for example —
use a dialog
instead of frame.
.
To make a window that appears within another window,
use an internal frame.
Creating and Showing Frames
Here is a picture of the extremely plain window
created by the FrameDemo
demonstration application.
You can find the source code in
FrameDemo.java
.
You can
run FrameDemo (
download JDK 6).
FrameDemo
code shows how to create and set up a frame.
//1. Create the frame. JFrame frame = new JFrame("FrameDemo"); //2. Optional: What happens when the frame closes? frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); //3. Create components and put them in the frame. //...create emptyLabel... frame.getContentPane().add(emptyLabel, BorderLayout.CENTER); //4. Size the frame. frame.pack(); //5. Show it. frame.setVisible(true);
JFrame
constructor
is the no-argument constructor.
EXIT_ON_CLOSE
operation exits the program when your user closes the frame.
This behavior is appropriate for this program
because the program has only one frame,
and closing the frame makes the program useless.
See Responding to Window-Closing Events for more information.
For frames that have menus,
you'd typically add the menu bar to the frame here
using the setJMenuBar
method.
See How to Use Menus for details.
pack
method sizes the frame
so that all its contents are at
or above their preferred sizes.
An alternative to pack
is to establish a frame size explicitly
by calling setSize
or setBounds
(which also sets the frame location).
In general, using pack
is preferable to calling setSize
,
since pack
leaves the frame layout manager in charge of the frame size,
and layout managers are good at adjusting to platform dependencies
and other factors that affect component size.
This example does not set the frame location,
but it is easy to do so
using either the setLocationRelativeTo
or setLocation
method.
For example, the following code
centers a frame onscreen:
frame.setLocationRelativeTo(null);
setVisible(true)
makes the frame appear onscreen.
Sometimes you might see the show
method used instead.
The two usages are equivalent,
but we use setVisible(true)
for consistency's sake.
Besides specifying who provides the window decorations, you can also specify which icon is used to represent the window. Exactly how this icon is used depends on the window system or look and feel that provides the window decorations. If the window system supports minimization, then the icon is used to represent the minimized window. Most window systems or look and feels also display the icon in the window decorations. A typical icon size is 16x16 pixels, but some window systems use other sizes.
The following snapshots show three frames that are identical except for their window decorations. As you can tell by the appearance of the button in each frame, all three use the Java look and feel. The first uses decorations provided by the window system, which happen to be Microsoft Windows, but could as easily be any other system running the Java platform.The second and third use window decorations provided by the Java look and feel. The third frame uses Java look and feel window decorations, but has a custom icon.
| Window decorations provided by the look and feel | Window decorations provided by the window system | Custom icon; window decorations provided by the look and feel |
Here is an example of creating a frame with a custom icon and with window decorations provided by the look and feel:
//Ask for window decorations provided by the look and feel. JFrame.setDefaultLookAndFeelDecorated(true); //Create the frame. JFrame frame = new JFrame("A window"); //Set the frame icon to an image loaded from a file. frame.setIconImage(new ImageIcon(imgURL).getImage());
As the preceding code snippet implies,
you must invoke the setDefaultLookAndFeelDecorated
method
before creating the frame
whose decorations you wish to affect.
The value you set with setDefaultLookAndFeelDecorated
is used for all subsequently created JFrame
s.
You can switch back to using window system decorations
by invoking JFrame.setDefaultLookAndFeelDecorated(false)
.
Some look and feels might not support window decorations;
in this case, the window system decorations are used.
The full source code for the application
that creates the frames pictured above is in
FrameDemo2.java
.
Besides showing how to choose window decorations,
FrameDemo2 also shows how to disable all window decorations
and gives an example of positioning windows.
It includes two methods that create the Image
objects
used as icons —
one is loaded from a file,
and the other is painted from scratch.
setDefaultCloseOperation
method.
You can even do both.
The argument to setDefaultCloseOperation
must be one of the following values,
the first three of which are defined in the
WindowConstants
interface
(implemented by JFrame
,
JInternalPane
,
and JDialog
):
DO_NOTHING_ON_CLOSE
windowClosing
method.
HIDE_ON_CLOSE
(the default for JDialog
and JFrame
)
DISPOSE_ON_CLOSE
(the default for JInternalFrame
)
EXIT_ON_CLOSE
(defined in the
JFrame
class)
System.exit(0)
.
This is recommended for applications only. If used
within an applet, a SecurityException
may be thrown.
DISPOSE_ON_CLOSE
can have results similar to
EXIT_ON_CLOSE
if only one window is onscreen.
More precisely, when the last displayable window
within the Java virtual machine (VM) is disposed of,
the VM may terminate.
See
AWT Threading Issues for details.
For more information about handling window-closing events, see How to Write Window Listeners. Besides handling window-closing events, window listeners can also react to other window state changes, such as iconification and activation.
JFrame
constructors and methods.
Other methods you might want to call
are defined by the
java.awt.Frame
,
java.awt.Window
, and
java.awt.Component
classes,
from which JFrame
descends.
Because each JFrame
object has a root pane,
frames have support for interposing input and painting behavior
in front of the frame children, placing children on different "layers",
and for Swing menu bars.
These topics are introduced in
Using Top-Level Containers
and explained in detail in
How to Use Root Panes.
The API for using frames falls into these categories:
| Method or Constructor | Purpose |
|---|---|
|
JFrame() JFrame(String) |
Create a frame that is initially invisible.
The String argument provides a title for the frame.
To make the frame visible,
invoke setVisible(true) on it.
|
|
void setDefaultCloseOperation(int) int getDefaultCloseOperation() |
Set or get the operation that occurs when the user pushes
the close button on this frame. Possible choices are:
WindowConstants interface, which JFrame implements.
The EXIT_ON_CLOSE constant is defined in
the
JFrame class.
|
|
void setIconImage(Image) Image getIconImage() (in Frame )
|
Set or get the icon that represents the frame.
Note that the argument is a
java.awt.Image object, not a javax.swing.ImageIcon
(or any other javax.swing.Icon implementation).
|
|
void setTitle(String) String getTitle() (in Frame )
|
Set or get the frame title. |
|
void setUndecorated(boolean) boolean isUndecorated() (in Frame )
|
Set or get whether this frame should be decorated. Works only if the frame is not yet displayable (has not been packed or shown). Typically used with full-screen exclusive mode or to enable custom window decorations. |
|
static void setDefaultLookAndFeelDecorated(boolean) static boolean isDefaultLookAndFeelDecorated() |
Determine whether subsequently created JFrame s
should have their Window decorations (such as borders, and widgets for
closing the window) provided by the current
look-and-feel. Note that this is only a hint, as some look and
feels may not support this feature.
|
| Method | Purpose |
|---|---|
|
void pack() (in Window )
|
Size the window so that all its contents are at or above their preferred sizes. |
|
void setSize(int, int) void setSize(Dimension) Dimension getSize() (in Component )
|
Set or get the total size of the window.
The integer arguments to setSize specify the width and height,
respectively.
|
|
void setBounds(int, int, int, int) void setBounds(Rectangle) Rectangle getBounds() (in Component )
|
Set or get the size and position of the window.
For the integer version of setBounds ,
the window upper left corner is at the x, y location
specified by the first two arguments,
and has the width and height
specified by the last two arguments.
|
|
void setLocation(int, int) Point getLocation() (in Component )
|
Set or get the location of the upper left corner of the window. The parameters are the x and y values, respectively. |
|
void setLocationRelativeTo(Component) (in Window )
|
Position the window
so that it is centered over the specified component.
If the argument is null ,
the window is centered onscreen.
To properly center the window,
you should invoke this method after the window size has been set.
|
| Method | Purpose |
|---|---|
|
void setContentPane(Container) Container getContentPane() |
Set or get the frame content pane. The content pane contains the visible GUI components within the frame. |
|
JRootPane createRootPane() void setRootPane(JRootPane) JRootPane getRootPane() |
Create, set, or get the frame root pane. The root pane manages the interior of the frame including the content pane, the glass pane, and so on. |
|
void setJMenuBar(JMenuBar) JMenuBar getJMenuBar() |
Set or get the frame menu bar to manage a set of menus for the frame. |
|
void setGlassPane(Component) Component getGlassPane() |
Set or get the frame glass pane. You can use the glass pane to intercept mouse events or paint on top of your program GUI. |
|
void setLayeredPane(JLayeredPane) JLayeredPane getLayeredPane() |
Set or get the frame layered pane. You can use the frame layered pane to put components on top of or behind other components. |
JFrame
.
The following table lists a few
and tells you where each is discussed.
| Example | Where Described | Notes |
|---|---|---|
FrameDemo
|
The Example Explained | Displays a basic frame with one component. |
FrameDemo2
|
Specifying Window Decorations | Lets you create frames with various window decorations. |
Framework
|
— | A study in creating and destroying windows, in implementing a menu bar, and in exiting an application. |
LayeredPaneDemo
|
How to Use Layered Panes | Illustrates how to use a layered pane (but not the frame layered pane). |
GlassPaneDemo
|
The Glass Pane | Illustrates the use of a frame glass pane. |
MenuDemo
|
How to Use Menus | Shows how to put a JMenuBar in a JFrame .
|


Step by step
Dynamic load independent resources
Dynamic load dependent resources
Dynamic load dependencies using meta data in file header
Dynamic load dependenties using module
Mix static resource with dynamic resource
Use package to group module
Switch module dyanmically by changing url
Switch resource dynamically by changing dependencies
Create new resource type with new resource loader
Cache control
Unload resource
Advanced
Dyanamic convert coffee
Empty page application
Load and unload
Hello template
Dynamic load images
Load jqueryui widget using convention
Load jqueryui programatically
Single page application


Thank you seems like such a small word when compared to the school and instructors who have become our heroes. When we began this journey, we didn't quite know what to expect but now that we have come through the fire, we are grateful for everyone who helped us along the way.
Thank you to our amazing instructors; we couldn't have done it without you! Steve, Meg, Jared, Hannah, and Greg.
Thank you also to the NSS staff! Jessica, Jeremiah, Laura, Mandy, and Kristin. You guys keep things
moving
smoothly and we appreciate all of your hard work!
We are grateful for John Wark and his vision for Nashville Software School. We wouldn't be here
without you and we are grateful!
Finally, a huge thank you to Kristen Norris, John Dulaney, Greg Lawrence, and Garrett Ward for planning and creating this site -- all while learning our server side technology!


@main("InSight | Home") {
We use the Foursquare API to locate any places within 100 meters of your location. Then we have a list of venues you might be looking at. For each of the possible venues we retrieve a set of photographs from Foursquare.
We create a custom Clarifai model and train it with the pictures of nearby venues. Each set of pictures is assigned a label of the venue name so we can identify similar pictures later.
Take a picture submit it to the server. The server then sends The picture to the specially trained Clarifai model. Clarifai then predicts the best location match based on the training data provided.


Hi, Stranger! Nice to meet you.
I love building things. While difficult engineering problems are often found to be fun to tackle, I get most excited when solving real customer problems that have a business justification. My goals are to continue practice and learning throughout my career and enable my teammates to further succeed in their own careers by utilizing strong collaboration and providing leadership when necessary.
I have been coding since I was in middle school, starting with PHP and Python as my two primary languages. Since starting my career within companies, I have found excitement in both the development and the administrative sides of the Agile workflow. My career has led me to learn and develop application in PHP, Python, JavaScript, and Java so far and I am always looking to add more tools to my toolbox.
Here is a list of technologies and frameworks that I have worked with before either with personal projects or within my employment at companies:
- PHP
- Python
- JavaScript
- Java
- HTML 5
- CSS 3
- Figma
- Postman
- Spring Boot
- Django
- Flask
- Laravel
- CodeIgniter
- Vue JS
- Git
- MySQL
- Siebel
- Microsoft Office
Experience - Resume
General Motors
Software Engineer October 2020 - Present
Engaged several teams throughout the entire software development workspace to deliver products and meet tight deadlines to implement quality and timely software release cycles.
- Collaborated with Research Analysts to improve workflows and the DevOps sprint cycle to keep quality and quantity to a consistent and expected level, leading to 50% reduction in previously unfulfilled deliverable timelines being completed.
- Ensured code was thoroughly tested through extensive JUnit tests scripts to cover all potential incomes and outcomes, resulting in a codebase to reach 100% code coverage.
- Spearheaded improvements for the Agile process through communication with the team manager and Scrum master to lead in assisting all team members with expectations and deliverability.
- Assisted team members with hundreds of Unit test scripts to develop top code quality and standards expected by General Motors were consistently delivered.
Satelliting Space
Owner/Freelance Web Developer January 2016 - Present
Work with local clients to develop and deliver high-quality websites and web applications for specific business purposes to improve overall productivity and bring onboard new customers.
- Designed multiple WordPress websites for clients to create high-quality websites that the client could easily customize and update without developer intervention, increasing website updates by 100%.
- Controlled the development of an online auction platform to handle live auctions virtually, which increased overall income by eliminating handwritten receipts.
- Overhauled the online presence of clients by creating a cohesive website and social media presence that increased web conversions to their social media platforms by 300%.
SimplePart
Web Application Developer Intern January 2020 - March 2020
Developed web application solutions to complete rigorous sprints on tight deadlines which were consistently collaborated on through iterative meetings and planning.
- Focused on delivering ADA compliant front-end development to design high quality and implement code standards, ensuring 100% of compliant guidelines were met.
- Analyzed and delivered multiple revisions of front-end code blocks to increase code quality and maintainability for future improvements and revisions.
- Identified potential pathways to increasing overall code maintainability in previous poor code structures, ensuring 100% of future code was easily maintainable.
Projects - GitHub
EasyAccounting PHP / CodeIgniter 3
Easy Accounting is made to be a Double Entry Accounting Software written in PHP with the CodeIgniter Framework using MySQL. The software is a simple software that is very limited, but used more as a presentation to showcase how simple double entry accounting can be implemented. There are various pieces of code that are not industry quality, but this is again used to merely showcase certain programming abilities.
- Launched the development of this project alongside collaboration of my professor to create a quality application that received a 100 as a final project.
- Facilitated weekly sprint plannings with the team to create an Agile workflow and to ensure maximum quality and quantity of code was produced.
SimpleIgniter PHP / CodeIgniter 3
SimpleIgniter is, simply put, CodeIgniter 3 with a user system incorporated. It has a user system with the ability to register, login, and recover account via email. The framework also has an admin system where you can view all the users created, edit their information, and even delete them.
- Developed a concrete and reliable base framework with User authentication built-in to be able to quickly deploy working prototypes or simple applications for clients.


List of all members.
Detailed Description
A mocking library for Cappuccino applications
Definition at line 27 of file OJMoq.j.
Member Function Documentation
| - (void) forwardInvocation: |
|
(CPInvocation) |
anInvocation |
[implementation] |
| - (id) initWithBaseObject: |
|
(CPObject) |
aBaseObject |
[implementation] |
Creates an OJMoq object based on the base object. If the base object is nil, then a benign stub is created. If the base object is non-nil, it creates a spy mock that allows all of the messages to go through to the base object.
- Parameters:
-
| aBaseObject | A nil or non-nil base object that will be wrapped by OJMoq |
- Returns:
- An instance of OJMoq that wraps the given base object
Definition at line 56 of file OJMoq.j.
| - (CPMethodSignature) methodSignatureForSelector: |
|
(SEL) |
aSelector |
[implementation] |
| + (id) mockBaseObject: |
|
(CPObject) |
aBaseObject |
[implementation] |
Creates an OJMoq object based on the base object. If the base object is nil, then a benign stub is created. If the base object is non-nil, it creates a spy mock that allows all of the messages to go through to the base object.
- Parameters:
-
| aBaseObject | A nil or non-nil base object that will be wrapped by OJMoq |
- Returns:
- An instance of OJMoq that wraps the given base object
Definition at line 42 of file OJMoq.j.
| - (BOOL) respondsToSelector: |
|
(SEL) |
aSelector |
[implementation] |
| - (OJMoq) selector: |
|
(SEL) |
aSelector |
| callback: |
|
(Function) |
aCallback |
|
|
| [implementation] |
Provides a callback with the parameters that were passed in to the specified selector
- Parameters:
-
| aSelector | The selector on the base object that will be called |
| aCallback | A single-argument function that is passed the array of arguments |
Definition at line 146 of file OJMoq.j.
| - (OJMoq) selector: |
|
(SEL) |
aSelector |
| callback: |
|
(Function) |
aCallback |
| arguments: |
|
(CPArray) |
arguments |
|
|
| [implementation] |
Provides a callback with the parameters that were passed in to the specified selector and match the given arguments
- Parameters:
-
| aSelector | The selector on the base object that will be called |
| aCallback | A single-argument function that is passed the array of arguments |
| arguments | The arguments that the selector must match |
Definition at line 159 of file OJMoq.j.
| - (OJMoq) selector: |
|
(SEL) |
aSelector |
| returns: |
|
(CPObject) |
value |
|
|
| [implementation] |
Ensure that selector returns value when selector is called. Selector will match all arguments.
- Parameters:
-
| aSelector | The selector on the base object that will be called |
| value | The value that the selector should return |
Definition at line 111 of file OJMoq.j.
| - (OJMoq) selector: |
|
(SEL) |
aSelector |
| returns: |
|
(CPObject) |
value |
| arguments: |
|
(CPArray) |
arguments |
|
|
| [implementation] |
Ensure that the selector, when called with the specified arguments, will return the given value. If you pass an empty array of arguments, then the selector will match all calls.
- Parameters:
-
| aSelector | The selector on the base object that will be called |
| arguments | The arguments that must be passed to selector for this to work |
| value | The value that the selector should return |
Definition at line 124 of file OJMoq.j.
| - (OJMoq) selector: |
|
(SEL) |
selector |
| times: |
|
(CPNumber) |
times |
|
|
| [implementation] |
Expect that selector is called times on the base object. The selector here will match all arguments.
- Parameters:
-
| selector | The selector which should be called |
| times | The number of times that selector should be called |
Definition at line 73 of file OJMoq.j.
| - (OJMoq) selector: |
|
(SEL) |
selector |
| times: |
|
(CPNumber) |
times |
| arguments: |
|
(CPArray) |
arguments |
|
|
| [implementation] |
Expect that selector is called times with arguments on the base object. The selector here will match the arguments that you pass it. If an empty array is passed then the selector will match all arguments!
- Parameters:
-
| selector | The selector which should be called |
| times | The number of times that selector should be called |
| arguments | Arguments for the selector. If an empty array of arguments is passed in, then the selector matches all arguments. |
Definition at line 88 of file OJMoq.j.
| - (OJMoq) verifyThatAllExpectationsHaveBeenMet |
|
|
[implementation] |
Verifies all of the expectations that were set on the OJMoq and fails the test if any of the expectations fail.
Definition at line 179 of file OJMoq.j.
The documentation for this class was generated from the following file:


I was thinking about a feature that could be nice. Imagine you want to play on your favourite server 1500 tickets, but you see that there is only 300-400 tickets to a team. So, you plan to wait the next round. My idea was to create a sort of timer or an auto-connect which will advise us that the actual round is finished and that you can now join for the next round.
So, you won't miss the start of the next round...
I hope you understand.
Maybe it is a bad idea, maybe not. I just wanted to share it to you while I thought to it.
chuzuki
I love the idea, but you might have more luck asking for this feature in Battlelog+ (http://battlelogplus.com/) as it's more in line with the features of their extended scoreboard.
ORFK
Global Moderator
The Idea sounds cool but the scripting for this things is very complicated.
the full serverbrowser from dice cant be analysed or modified so easily.
Battlelog+ is not an nice Addon, you HAVE to register you in their Forum, thats the Reason, why the Battlelog+ Thread in the German Forum was closed. EA Moderators and DICE Member doesn't like Addons where you can link a used Addon to a registred Member on an external Board or if you have to regist yourself on an external Side to can use the Addon.
BrainFooLong
Administrator
Too much complicated to integrate. Rejected.
cheesetux
ORFK wrote:
Battlelog+ is not an nice Addon, you HAVE to register you in their Forum
You don't really HAVE to register for battlelog+ you only need to if you want to leave server comments/vote on comments, everything else doesn't require a account
This is to keep people from abusing this feature
Topicstarter
celte17
Ok, never mind. That was just a "good optional feature", but not very necessary.


Sri Lanka's new president names brother Mahinda Rajapaksa as PM
by AFPISTANBUL: Sri Lanka’s new President Gotabaya Rajapaksa will swear in his elder brother Mahinda — a former president himself — as prime minister, a spokesperson said on Wednesday.
The brothers are credited with brutally crushing the Tamil Tigers a decade ago to end Sri Lanka’s civil war, with the security services they controlled accused of war crimes and multiple human rights abuses.
Government spokesperson Vijayananda Herath said Mahinda Rajapaksa will assume duties as premier soon after incumbent Ranil Wickremesinghe steps down on Thursday morning.
Sri Lanka’s Prime Minister Ranil Wickremesinghe formally announced his resignation on Wednesday, four days after his party suffered a humiliating defeat at presidential polls.
In an address to the nation, Wickremesinghe said he had informed new president Gotabaya Rajapaksa that he will step down on Thursday, allowing a new minority government to be formed.


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| bcPower {car} | R Documentation |
Transform the elements of a vector or columns of a matrix using, the Box-Cox, Box-Cox with negatives allowed, Yeo-Johnson, or simple power transformations.
bcPower(U, lambda, jacobian.adjusted=FALSE, gamma=NULL) bcnPower(U, lambda, jacobian.adjusted = FALSE, gamma) bcnPowerInverse(z, lambda, gamma) yjPower(U, lambda, jacobian.adjusted = FALSE) basicPower(U,lambda, gamma=NULL)
U |
A vector, matrix or data.frame of values to be transformed |
lambda |
Power transformation parameter with one element for each column of U, usuallly in the range from -2 to 2. |
jacobian.adjusted |
If |
gamma |
For bcPower or basicPower, the transformation is of U + gamma, where gamma is a positive number called a start that must be large enough so that U + gamma is strictly positive. For the bcnPower, Box-cox power with negatives allowed, see the details below. |
z |
a numeric vector the result of a call to |
.
The Box-Cox
family of scaled power transformations
equals (x^(lambda)-1)/lambda
for lambda not equal to 0, and
log(x) if lambda = 0. The bcPower
function computes the scaled power transformation of
x = U + gamma, where gamma
is set by the user so U + gamma is strictly positive for these
transformations to make sense.
The Box-Cox family with negatives allowed was proposed by Hawkins and Weisberg (2017). It is the Box-Cox power transformation of
z = .5 (U + √[U^2 + gamma^2])
where for this family gamma is either user selected or is estimated. gamma
must be positive if U includes negative values and non-negative otherwise, ensuring that z is always positive. The bcnPower transformations behave similarly to the bcPower transformations, and introduce less bias than is introduced by setting the parameter gamma to be non-zero in the Box-Cox family.
The function bcnPowerInverse
computes the inverse of the bcnPower
function, so U = bcnPowerInverse(bcnPower(U, lambda=lam, jacobian.adjusted=FALSE, gamma=gam), lambda=lam, gamma=gam)
is true for any permitted value of gam
and lam
.
If family="yeo.johnson"
then the Yeo-Johnson transformations are used.
This is the Box-Cox transformation of U+1 for nonnegative values,
and of |U|+1 with parameter 2-lambda for U negative.
The basic power transformation returns U^{lambda} if lambda is not 0, and log(lambda) otherwise for U strictly positive.
If jacobian.adjusted
is TRUE
, then the scaled transformations
are divided by the
Jacobian, which is a function of the geometric mean of U for skewPower
and yjPower
and of U + gamma for bcPower
. With this adjustment, the Jacobian of the transformation is always equal to 1. Jacobian adjustment facilitates computing the Box-Cox estimates of the transformation parameters.
Missing values are permitted, and return NA
where ever U
is equal to NA
.
Returns a vector or matrix of transformed values.
Sanford Weisberg<EMAIL_ADDRESS>Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Hawkins, D. and Weisberg, S. (2017) Combining the Box-Cox Power and Generalized Log Transformations to Accomodate Nonpositive Responses In Linear and Mixed-Effects Linear Models South African Statistics Journal, 51, 317-328.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley Wiley, Chapter 7.
Yeo, In-Kwon and Johnson, Richard (2000) A new family of power transformations to improve normality or symmetry. Biometrika, 87, 954-959.
U <- c(NA, (-3:3)) ## Not run: bcPower(U, 0) # produces an error as U has negative values bcPower(U, 0, gamma=4) bcPower(U, .5, jacobian.adjusted=TRUE, gamma=4) bcnPower(U, 0, gamma=2) basicPower(U, lambda = 0, gamma=4) yjPower(U, 0) V <- matrix(1:10, ncol=2) bcPower(V, c(0, 2)) basicPower(V, c(0,1))


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