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Dimensional Gate Keeper:
Your burning passion has been a great help, and now others are starting to follow your excellent example!


I am a Software Engineer at True Sparrow. I design things, solve problems and turn caffeine into code. I am a Computer Science graduate from BIT Mesra, currently based in Hyderabad. Outside of the computers, you can find me in the basketball court or capturing some splendid moments through my camera.
Design 88%
Development 83%
Problem Solving 90%
Photography 77%
Thanks for dropping by. I am always excited to work on some awesome & challenging projects. Feel free to drop an email or ping me on LinkedIn. If you wanna know more about me or to connect with me, follow me on different social media platforms.


Chocolate Pizza
POSTED ON 15 DEC 2013 / DESSERTS
For the fig-swirl: Melt butter over medium heat in saucepan. Add brown sugar and stir to dissolve. Halve all of the figs and pasta sauce pan with water and lemon juice. Cook over medium heat, stirring frequently, until you have a chunky-jammy mixture. Add salt with one or two stirs, set aside and let cool completely.
Ice cream: In a small pot over medium heat, combine milk, and granulated sugar until sugar is completely dissolved and the milk is just barely lukewarm. Wisk in the egg yolks. Set mixture in the fridge and wait until the fig mixture is cooled.
Using an ice cream machine, pour liquid into the frozen basin and process according to manufacturer instructions, i.e., let spin and thicken for 20 minutes before adding mascarpone, fig Jam mixture, and the nuts. Continue to process for +/- 10 minutes. Poor semi Frozen mixture into a Pyrex dish or glass Tupperware. Freeze at least two hours before serving.
- ☐ 1 1/2 cups milk
- ☐ 1/2 cup mascarpone
- ☐ 1/2 tsp pink salt
- ☐ 1 lb black mission figs
- ☐ 1/2 cup brown sugar
- ☐ 2-4 tbsp water
- ☐ 1 1/2 cups heavy cream
- ☑
1/3 granulated sugar - ☑
2 egg yolks - ☐ 1 lemon, juiced
- ☐ 2 tbsp butter
- ☐ 1 cup honey roasted pecans,roughly chopped
Vanessa Stevenson
food enthusiast, photography fan. Add a pinch of raw foodisim and that's preatty much who I am


A Teaspoon Of Sugar
Wei-Ting Lin
HTMLclose
CSSclose
JQueryclose
A Teaspoon Of Sugar is the product of a final project for BCIT's COMP 1850: Web Development and Design. Students were asked to develop a business concept, website layout, and content. The website needed to incorporate clean, effective design, an easy to use UI, and semantically written code. Due to the project criteria at the time, we were limited to basic HTML, CSS, and JQuery.
View Live Site
Design Direction
LATO for Titles
Railway for Text & Links
Final Prototype
View Live Site
See more projects


Hypertext Markup Language (HTML) is the standard markup language for creating web pages and web applications. With Cascading Style Sheets (CSS) and JavaScript, it forms a triad of cornerstone technologies for the World Wide Web.
In other words - each and every webpage which you see on the web uses HTML. Let's check it. Open https://facebook.com , click on any free space (background, where nothing is displayed, do not click on text, image, table or anything- click on the white/grey background ) with your right mouse button and choose "View page source".
You will see odd characters like below:

Add new account

Create new account

Not the entire code is stricty HTML, there are also CSS and JS elements but HTML is a baseline for our website.
So let's see what we gonna learn today and what you will be able to build by the end of this lesson.
Click here to see website we will build todayWhat we have to do:
We will start setup. Our app will consist of 3 files:
Create a new folder called myWebsite and open it in Visual Studio Code.
Create new file called index.html and paste the following code:
<!DOCTYPE html>

<title>My Website</title>

Save the fail and create a new one called project.html and paste the same content as index.html
Change title to Project details. Type Coming soon in between
 tags:

Coming Soon!

And finally create new file called styles.css and leave it empty for now.
We will start with index.html
Let's analyze how our website is build.
Inside the body, create a heading, paragraph and div.

 Our heading (aka title)

Some paragraph, with some text

And div which stand for divider, it's meant to be used as container of a data.

Now let's have a closer look at our page in a console.
Note: If you don't know how to open/use console, check this lesson first!

 and
 looks simmilar but they have semantic difference - a
 element is designed to describe a container of data whereas a
 element is designed to describe a paragraph of content. If you need a generic container purely for layout purposes then use a
 . If you need an element to describe a paragraph of content then use a

, ,
,
,
 - these are all HTML elements called tags.
An HTML element usually consists of a start tag and end tag, with the content inserted in
content goes here...
like we've seen before:

Some paragraph, with some text

however, there are singular tags which don't require closing tags i.e.:

Note: For the sake of this tutorial, it's sufficient knowledge, however, in order to really learn HTML and CSS you should learn more about tags later.
After finishin this tutorial, learn more about tags here.
As you can see base on our current code -
,
, and
 tags are nested under  tag, which is nested under  tag which is a top tag. Netsing allows us to group elements and make code more readable.
Expect for the fact that we can put some data in between tags, they (tags) can also have attributes, like  tag which you have already seen.
Example:

One of the most commonly used attribute is a class attribute which allows us to apply CSS styles to our HTML elements.
We will learn about it in the next lesson.
After finishin this tutorial, learn more about attributes here.


On this website you will get all the details about the COVID-19 Vaccination Centre.
Photo booth fam kinfolk cold-pressed sriracha leggings jianbing microdosing tousled waistcoat.
Photo booth fam kinfolk cold-pressed sriracha leggings jianbing microdosing tousled waistcoat.
Photo booth fam kinfolk cold-pressed sriracha leggings jianbing microdosing tousled waistcoat.
Photo booth fam kinfolk cold-pressed sriracha leggings jianbing microdosing tousled waistcoat.
Photo booth fam kinfolk cold-pressed sriracha leggings jianbing microdosing tousled waistcoat.
Photo booth fam kinfolk cold-pressed sriracha leggings jianbing microdosing tousled waistcoat.


To start the chat open another browser window or go on your phone/tablet or get friend to go to this same address
Specifically {{roomName}}
At the moment this is an audio only demo, but could easily use audio as well
Using data channels you can compare average roundtrip times on a pings (mean over 10 samples) between using WebRTC data channel and websockets.
WebRTC average latency: {{webRTCAverageLatency}}ms
Websocket average latency: {{websocketAverageLatency}}ms


This article describes the Command design pattern. This is a
behavioral design pattern, a category of
design pattern used by software engineers, when writing computer programs.
Table of Contents
Introduction
The Command pattern is a
design pattern, used in software engineering, to encapsulate everything that is needed to execute a method at a later time. The three main concepts in this pattern are
client, invoker and receiver. Firstly the client defines the command and it's properties. It is then called by invoker and sent to the receiver, which takes the properties and performs it's actions based on them.
It is defined as a
behavioral design pattern because it affects program execution.
Benefits
The command pattern allows developers to construct a unified message structure to encapsulate a method into a delegate, which can be resused by different owners, with different parameters.
Examples of the pattern
Commands can be used to build a history of actions, to enable record a macro, enable an undo function, or list of "roll-back" transactions.
Messages can also inform progress bars or wizards.
Commands are also useful across threads and in parallel processing in general.
In
WPF, commanding allows the developer to separate the semantics of the operation, from the logic that executes the command. Examples are Print, Copy and Paste. These commands are already baked into WPF and available to use, but the implementation of the
command is down to the application (Copy text, or copy a class. Print to file, or print to printer). Commands implement the ICommand interface, which also defines CanExecute and Execute delegates, to determine if the command can be executed, and what method
is called upon execution. When a command is tied to a button, the CanExecute method controls the 'enabled' state of the button.
Read more and download the sample from here


Home
Reboot companion computer
Checkbox is CHECKED!
RC control
Stream
Watch or Listen
Streams list
Actions
Arm
Disam
Take Off
Land


Sources for qualification match results at regionals
Data sources
Week 1
BAE Granite States regional
Buckeye Regional
Greater Kansas City regional
Midwest Regional
New Jersey Regional
Washington DC Regional
Week 2
Boston Regional
Finger Lakes regional
Oregon Regional
San Diego Regional
New York City Regional
Week 3
Dalas Regional
Florida Regional
Los Angeles Regional
Peachtree Regional
Pittsburg Regional
Silicon Valley Regional
Wisconsin Regional
Week 4
Israel Regional
Arizona Regional
Bayou Regional
Boilmaker Regional
Chesapeake Regional
NASA VCU Regional
Philidephia Regional
St. Louis Regional
Waterloo Regional
Michigan District Events
Traverse City FIRST Robotics District Competition
Kettering University FIRST Robotics District Competition
Cass Tech FIRST Robotics District Competition
Lansing FIRST Robotics District Competition


| run from | CWVSFT525 (amd64 Windows 10 10.0) |
|---|---|
| run user | ak093674 |
| time span | 12/20/2019 16:48:16 - 12/20/2019 16:49:07 |
| duration | 00:00:50.747 |
| scenario passed | 0 / 2 |
| total steps | 16 |
| executed steps | 16 (100.00%) |
| passed | 12 (75.00%) |
| failed | 4 (25.00%) |
| nexial version | nexial-DEV |
| java version | 1.8.0_221 |
| log |
image_crop_with_astericks.20191220_164818.001.xlsx_STF-563_A11.log image_crop_with_astericks.20191220_164847.002.xlsx_STF-563_A11.log nexial-20191220_164816.log |
| runtime args | -script C:\projects\NewFeatures\image-compare\artifact\script\image_crop_with_astericks.xlsx |
| JAVA_OPT | -Dnexial.outputToCloud=true,-Dnexial.verbose=true,-Dnexial.scope.iteration=1-2 |
| Script | Data | Iterations | Scenario Passed | Start Date/Time | Duration | Total | Pass | Fail | Success % |
|---|
| image_crop_with_astericks.xlsx | image_crop_with_astericks.data.xlsx | 2 | 0 / 2 | 2019/12/20 16:48:18 | 00:00:48 | 16 | 12 | 4 | 75.00% |
| Iteration | Scenario | Activity | Start Date/Time | Duration | Total | Pass | Fail | Success % | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
Execution Result (1 of 2)
|
0 / 1 | 2019/12/20 16:48:18 | 00:00:26 | 8 | 6 | 2 | 75.00% | ||||
| STF-563 | 2019/12/20 16:48:20 | 00:00:23 | 8 | 6 | 2 | 75.00% | |||||
| TestCase | 2019/12/20 16:48:20 | 00:00:23 | 8 | 6 | 2 | 75.00% | |||||
Execution Result (2 of 2)
|
0 / 1 | 2019/12/20 16:48:47 | 00:00:17 | 8 | 6 | 2 | 75.00% | ||||
| STF-563 | 2019/12/20 16:48:48 | 00:00:15 | 8 | 6 | 2 | 75.00% | |||||
| TestCase | 2019/12/20 16:48:48 | 00:00:15 | 8 | 6 | 2 | 75.00% |


{% if choice == "life_expectancy"%}
Life Expectancy Search. Please select the year range you want to search: (2005-2015)
{% elif choice == "guns_vehicles" %}
Guns vs Vehicles Search. Please select the year range you want to search: (2005-2015)
{% elif choice == "death_causes" %}
Death Causes Search. Please select the year range(2005-2015) and the number of top causes you want to search.
{% elif choice == "race_deaths" %}
Top 5 Race Death Causes Search. Please select the race and the year range(2005-2015) you want to search.


File attributes management framework.
Pluggable File Attributes package
The package supports file attributes management. Attributes
can be provided by plugged in providers, The implementation
supports providers results caching.
Clients Interface
Clients should start at {@link FileAttributeQuery}
class. It allows to query for attribute values,
to determine their readiness, to write
them down and supports listening on attribute
changes.
Providers Interface
Attribute providers should start at {@link FileAttributeProvider}
implement it and register it using system filesystem at
Services/FileAttributeProviders/Default
.
Attribute Definition
Both providers and clients must understand
attribute definiton they are using. The attribute
definitions are not covered by this package.


Import your old & busted site or blog for use with Jekyll.
No importer for your system? No problem. Creating one is easy.
Found a problem with the importer? File an issue.
How to Contribute →Sick of dealing with hosting companies? GitHub Pages are powered by Jekyll, so you can easily deploy your site using GitHub for free—custom domain name and all.
Learn more about GitHub Pages →


Mariel Padilla gives birth to her second girl!
Mariel Padilla is now a mom of two!
The celebrity has given birth to a bouncing baby girl on Saturday, husband Robin Padilla announced on Instagram.
"Today Maria Gabriela de Padilla was born. God is great!" Robin said as he posted a photo of Mariel on a hospital bed as her father watched over her. "My wife had her dream fulfilled again."
According to Robin, their new daughter was delivered by natural birth. "Everything was very smooth," he added, sharing Mariel's family in the US took care of his wife.
Congratulations! Can't wait to see Baby Gabriela! — LA, GMA News


Sigma Point Sets
10 Jun 2019Here we outline algorithms for generating each sigma point set in Sigmapy for a standard Gaussian weighting function, $\mathcal{N}(\pmb{0}, I)$ in $n$ dimensions with mean $\pmb{0}$ and identity covariance. Sigma points are denoted $\chi_i$, mean weights $w_i^m$, and covariance weights $w_i^c$. General Gaussian weighting functions are $\mathcal{N}(\pmb{x_0}, P_x)$ are handled by transforming each sigma points $\chi_i$ according to \begin{equation} \pmb{\chi_i}’ = \sqrt{P_x} \pmb{\chi_i} + \pmb{x_0} \end{equation} where $\sqrt{P_x}$ is a matrix square root of $P_x$. The following sigma point sets are available Sigmapy.
| Shorthand Name | Number of Points | Order |
|---|---|---|
| merwe | $2n+1$ | 3 |
| julier | $2n+1$ | 3 |
| menegaz | $n+1$ | 2 |
| simplex | $n+1$ | 2 |
| gauss_hermite | $3^n$ | 3 |
| li | $2n^2 + 1$ | 5 |
| mysovskikh | $n^2 + 3n + 3$ | 5 |
Van der Merwe Sigma Points
A commonly used set of points and weights for the unscented transform is the Van der Merwe set (Van der Merwe, 2004). It uses $2n + 1$ sigma points given by \begin{equation} \pmb{\chi_i} = \begin{cases} \pmb{x_0} & i = 0 \\ \pmb{x_0} - \sqrt{n + \lambda} \pmb{e_i} & i = 1, \cdots, n\\ \pmb{x_0} + \sqrt{n + \lambda} \pmb{e_i} & i = n+1, \cdots, 2n \end{cases} \end{equation} where \begin{equation} \lambda = \alpha^2 (n + \kappa) - n. \end{equation} The notation $\pmb{e_i}$ refers to the $i$-th column of the $n \times n$ identity matrix. There are different weights $w_i^m$ and $w_i^c$ for computing mean and covariance estimates respectively \begin{equation} w_i^m = \begin{cases} \frac{\lambda}{n + \lambda} & i = 0 \\ \frac{1}{2(n+\lambda)} & i = 1, \cdots, 2n \end{cases} \end{equation}
\begin{equation} w_i^c = \begin{cases} \frac{\lambda}{n + \lambda} + 1 - \alpha^2 + \beta & i = 0 \\ \frac{1}{2(n+\lambda)} & i = 1, \cdots, 2n \end{cases} \end{equation}
Appropriate default choices of the scaling parameters are, $\beta = 2$, $\kappa = 3 - n$, and $0 \leq \alpha \leq 1$. Unless otherwise specified, these are the values used by Sigmapy.
from sigmapy.sigma_sets import SigmaSets
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 18})
# Prior mean
x0 = np.zeros(2)
# Prior covariance
Px = np.eye(2)
# Van der Merwe sigma points in 2D
sets = SigmaSets()
X1, wm, wc = sets.get_set(x0, Px, set_name = 'merwe')
# Different scaling parameters
X2, wm, wc = sets.get_set(x0, Px, set_name = 'merwe', alpha = 0.9)
plt.title('Van der Merwe Sigma Points')
plt.scatter(X1[0,:], X1[1,:], s = 250.*wm / wm.max())
plt.scatter(X2[0,:], X2[1,:], s = 250.*wm / wm.max(), marker = '^')
plt.show()
Julier Sigma Points
Another commonly used set of sigma points is the Julier set (Julier & Uhlmann, 1997). It has $2n+1$ points and a single scaling parameter $\kappa$. Setting $\kappa = 3 - n$ matches one higher order moment, and is therefore the preferred default value. However, the best choice of the scaling parameter is problem dependent. Points are given by \begin{equation} \pmb{\chi_i} = \begin{cases} \pmb{x_0} & i = 0 \\ \pmb{x_0} - \sqrt{n + \kappa} \pmb{e_i} & i = 1, \cdots, n\\ \pmb{x_0} + \sqrt{n + \kappa} \pmb{e_i} & i = n+1, \cdots, 2n \end{cases} \end{equation} and weights are defined by \begin{equation} w_i^m = w_i^c = \begin{cases} \frac{\kappa}{n + \kappa} & i = 0 \\ \frac{1}{2(n+\kappa)} & i = 1, \cdots, 2n. \end{cases} \end{equation}
X1, wm, wc = sets.get_set(x0, Px, set_name = 'julier')
# Different scaling parameter
X2, wm, wc = sets.get_set(x0, Px, set_name = 'julier', kappa = 2.)
plt.title('Julier Sigma Points')
plt.scatter(X1[0,:], X1[1,:], s = 250.*wm / wm.max())
plt.scatter(X2[0,:], X2[1,:], s = 250.*wm / wm.max(), marker = '^')
plt.show()
Menegaz Sigma Points
The Menegaz set uses only $n+1$ sigma points (Menegaz, Ishihara, & Borges, 2011). It has a single scaling parameter $0 < w_0 < 1$. Some additional notation is necessary to define the sigma point and weight sets. The notation $[c]_{p \times q}$ with $c \in \mathbb{R}$ represents a matrix of dimension $p \times q$ in which all terms are equal to $c$. The notation $\text{diag}(\pmb{x})$ for $\pmb{x} \in \mathbb{R}^n$ denotes an $n \times n$ matrix with $\pmb{x}$ on the diagonal. Using these definitions, we have: \begin{equation} X = \left [ \pmb{\chi_0} \cdots \pmb{\chi_n} \right ] = \left [- \frac{[\alpha]_{n \times 1}}{w_0} \; \; C (\sqrt{W})^{-1} \right ] + \left [ \pmb{x_0} \cdots \pmb{x_0} \right ] \end{equation}
\begin{equation} W = \text{diag}([w_1, \cdots, w_n]) \end{equation}
\begin{equation} \begin{bmatrix} w_1 & \cdots & \sqrt{w_1}\sqrt{w_n} \\ \vdots & \ddots & \vdots \\ \sqrt{w_1} \sqrt{w_n} & \cdots & w_n \end{bmatrix} = w_0 \alpha^2 C^{-1} [1]_{n \times n} (C^T)^{-1} \end{equation}
\begin{equation} C = \sqrt{I - \alpha^2 [1]_{n \times n}} \end{equation}
\begin{equation} \alpha = \sqrt{\frac{1 - w_0}{n}} \end{equation}
Note that $w_i^m = w_i^c = w_i$.
# Menegaz points in 2D
X1, wm, wc = sets.get_set(x0, Px, set_name = 'menegaz')
# Different scaling parameter
X2, wm, wc = sets.get_set(x0, Px, set_name = 'menegaz', w0 = .9)
plt.title('Menegaz Sigma Points')
plt.scatter(X1[0,:], X1[1,:], s = 250.*wm / wm.max())
plt.scatter(X2[0,:], X2[1,:], s = 250.*wm / wm.max(), marker = '^')
plt.show()
Simplex Sigma Points
Another minimal set of $n+1$ sigma points, called the simplex set, is given in (Moireau & Chapelle, 2011). A matrix containing the sigma points as column vectors \begin{equation} X_{n+1}^* = \left [ \pmb{\chi_0} \; \cdots \; \pmb{\chi_n} \right ] \end{equation} is generated recursively. We let \begin{equation} X_1 = \left [-\frac{1}{2 \alpha} \; \frac{1}{2 \alpha} \right ] \end{equation} \begin{equation} \alpha = \frac{n}{n+1} \end{equation} $X_i^{*}$ is generated from $X_{i-1}^*$ via \begin{equation} X_i^* = \begin{bmatrix} & & & 0 \\ & X_{i-1}^* & & \vdots \\ & & & 0 \\ \frac{1}{\sqrt{\alpha i (i + 1)}} & \frac{1}{\sqrt{\alpha i (i + 1)}} & \frac{1}{\sqrt{\alpha i (i + 1)}} & \frac{-i}{\sqrt{\alpha i (i + 1)}} \end{bmatrix}. \end{equation} Weights are given by \begin{equation} w_i^m = w_i^c = \alpha. \end{equation}.
# Simplex points in 2D
X, wm, wc = sets.get_set(x0, Px, set_name = 'simplex')
plt.title('Simplex Sigma Points')
plt.scatter(X[0,:], X[1,:], s = 250.*wm / wm.max())
plt.show()
Li Sigma Points
Sigmapy includes a modified version of the fifth-order quadrature rule in (Zhao-Ming, Wen-Ge, Dan, & Yu-Rong, 2017) . It contains one scaling parameter $\lambda_2$. The quadrature rule is formulated in terms of fully symmetric sets of points. A set of points $S = \{\pmb{s_1}, \pmb{s_2}, \cdots, \pmb{s_N}\}$ is fully symmetric if it is closed under the operations of coordinate position and sign permutations. The set $S$ is said to be generated by the vector $\pmb{s}$ if all points in $S$ can be obtained by coordinate position and sign permutations of $\pmb{s}$.
Sigma points are categorized in terms of three fully symmetric sets \begin{equation} \begin{gathered} X_0 = [0]_n \\ X_1 = [\lambda_1]_n \\ X_2 = [\lambda_2, \lambda_2]_n \end{gathered} \end{equation} where, for example, the notation $[\lambda_2, \lambda_2]_n$ refers to the fully symmetric set of points generated by the $n$-dimensional vector $[\lambda_2, \lambda_2, 0, \cdots, 0]^T$. The set $X_0$ is trivial, containing only the zero vector. An example of the fully symmetric set $[1,1]_3$ is shown below.
import numpy as np
from itertools import combinations, product
from scipy.special import comb
def generate_fully_symmetric_set(n, vals):
"""
Generates a fully set of symmetric points of dimension n with
values given in vals.
Parameters
----------
n: int
Dimension of points in fully symmetric set
vals : numpy.array(k)
Non-zero values in the fully symmetric set
Returns
-------
S : numpy.array(n, 2^k * (n choose k))
Each column is a point in the fully symmetric set
"""
indexes = np.arange(n)
k = len(vals)
index_combs = combinations(indexes, k)
S = np.zeros((n, 2**k * comb(n,k, exact = True)))
i = 0
for index_comb in list(index_combs):
signs = np.ones((k,2))
signs[:,1] = -1.
sign_combs = product(*signs)
for sign_comb in list(sign_combs):
S[index_comb, i] = vals
S[index_comb, i] *= sign_comb
i += 1
return S
print(generate_fully_symmetric_set(3, [-1., 1.]))
[[-1. -1. 1. 1. -1. -1. 1. 1. 0. 0. 0. 0.]
[ 1. -1. 1. -1. 0. 0. 0. 0. -1. -1. 1. 1.]
[ 0. 0. 0. 0. 1. -1. 1. -1. 1. -1. 1. -1.]]
The parameter $\lambda_1$ depends on $\lambda_2$ with \begin{equation} \lambda_1 = \frac{\lambda_2 \sqrt{n-4}}{n - \lambda_2^2 - 1}. \end{equation} Hence, this method requires $n \geq 5$ and $n - \lambda_2^2 - 1 \neq 0$. Each sigma point in a category has the same weight. Moreover mean and covariance weights are the same. The sets $X_0$, $X_1$, and $X_2$ have associated weights $w_0$, $w_1$, and $w_2$ respectively where \begin{equation} w_2 = \frac{4-n}{2 \lambda_1^4} \end{equation} \begin{equation} w_3 = \frac{1}{4 \lambda_1^4} \end{equation} \begin{equation} w_1 = 1 - 2 n w_2 - 2n(n-1)w_3. \end{equation}
Gauss-Hermite Sigma Points
The third order Gauss-Hermite quadrature rule is a generalization of the 1D Gauss-Hermite quadrature rule for integrating
\begin{equation}
\int_{\mathbb{R}} f(x) e^{-x^2} \; dx.
\end{equation}
Weights and sigma points can be obtained using a tensor-products of the 1D Gauss-Hermite quadrature rule. The number of points grows exponentially with dimension, and the third order method requires $3^n$ points. An alternative formulation of the Gauss-Hermite sigma points involves categories of fully symmetric sets of sigma points (Peng, Duan, & Zhu, 2017). In particular, there are $n+1$ classes of sigma points
\begin{equation}
\begin{gathered}
X_0 = \left [ 0 \right ]_n \\
X_1 = \left [ \sqrt{3} \right ]_n \\
X_2 = \left [ \sqrt{3}, \sqrt{3} \right ]_n \\
\vdots
X_n = \left [\sqrt{3}, \cdots, \sqrt{3} \right ]_n.
\end{gathered}
\end{equation}
Each sigma point in a given fully symmetric category has the same weight:
\begin{equation}
\begin{gathered}
w_0 = \left ( \frac{2}{3} \right )^n \\
w_1 = \left ( \frac{2}{3} \right )^{n-1} \left ( \frac{1}{6} \right ) \\
w_2 = \left ( \frac{2}{3} \right )^{n-2} \left ( \frac{1}{6} \right )^2 \\
\vdots \\
w_n = \left ( \frac{1}{6} \right )^n.
\end{gathered}
\end{equation}
# Gauss-hermite sigma points in 2D
X, wm, wc = sets.get_set(x0, Px, set_name = 'hermite')
plt.title('Gauss-Hermite Sigma Points')
plt.scatter(X[0,:], X[1,:], s = 250.*wm / wm.max())
plt.show()
Mysovskikh Sigma Points
Note this method currently has a bug that I still need to fix.
Another fifth order sigma point set is the Mysovskikh set, which has $n^2 + 3n + 3$ points (Mysovskikh, 1970). The quadrature rule can be obtained from the transformation group of the regular simplex with vertices $\pmb{a_1}, \cdots, \pmb{a_n}$ where $j$-th element of $\pmb{a_i}$ \begin{equation} a_{i,j} = \begin{cases} -\sqrt{ \frac{n+1}{n(n-j+2)(n-j+1)}} & i < j \\ \sqrt{\frac{(n+1)(n-i+1)}{n(n-i+2)}} & i = j \\ 0 & i > j \end{cases}. \end{equation} The points $\pmb{a_i}$ are sigma points, as are the origin $\pmb{0}$, and points in the set \begin{equation} \{ \pmb{b_k} \} = \left \{ \sqrt{\frac{n}{2(n-1)}} \left ( \pmb{a_l} + \pmb{a_m} \right ) \; | \; l < m, \; \; m = 1, 2, \cdots, n+1 \right \}. \end{equation} The method is centrally symmetric. Hence, for every sigma point $\pmb{a_i}$ and $\pmb{b_k}$, -$\pmb{a_i}$ and -$\pmb{b_k}$ are also sigma points. The sigma point $\pmb{0}$ has associated weight $w_0$, while points $\pm \pmb{a_i}$ and $\pm \pmb{b_j}$ have associated weights $w_1$ and $w_2$ respectively
\begin{equation} \begin{gathered} w_0 = \frac{2}{n + 2} \\ w_1 = \frac{n^2 (7 - n)}{2(n+1)^2 (n+2)^2} \\ w_2 = \frac{2(n-1)^2}{(n+1)^2 (n+2)^2}. \end{gathered} \end{equation}
Bibliography
- Van der Merwe, R. (2004). Sigma-point Kalman filters for probabilistic inference in dynamic state-space models. PhD Thesis. https://doi.org/10.6083/M4Z60KZ5
- Julier, S. J., & Uhlmann, J. K. (1997). New extension of the Kalman filter to nonlinear systems. Int Symp AerospaceDefense Sensing Simul and Controls. https://doi.org/10.1117/12.280797
- Menegaz, H. M., Ishihara, J. Y., & Borges, G. A. (2011). A new smallest sigma set for the Unscented Transform and its applications on SLAM. In Proceedings of the IEEE Conference on Decision and Control. https://doi.org/10.1109/CDC.2011.6161480
- Moireau, P., & Chapelle, D. (2011). Erratum of article “Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems.” ESAIM: Control, Optimisation and Calculus of Variations, 17(2), 406–409. https://doi.org/10.1051/cocv/2011001
- Zhao-Ming, L., Wen-Ge, Y., Dan, D., & Yu-Rong, L. (2017). A novel algorithm of fifth-degree cubature Kalman filter for orbit determination at the lower bound approaching to the number of cubature points. ACTA PHYSICA SINICA. https://doi.org/10.7498/aps.66.158401
- Peng, L., Duan, X., & Zhu, J. (2017). A New Sparse Gauss-Hermite Cubature Rule Based on Relative-Weight-Ratios for Bearing-Ranging Target Tracking. Modelling and Simulation in Engineering. https://doi.org/10.1155/2017/2783781
- Mysovskikh, I. P. (1970). Cubature formulae and orthogonal polynomials. USSR Computational Mathematics and Mathematical Physics. https://doi.org/10.1016/0041-5553(70)90159-X


Software Developer
Hookah is a small smoke testing command line library for any web application.
It is the process used to identify the correctness, completeness and quality of developed computer software.
Vs
Manual tests may find many bugs however it is a laborious and time consuming process. The effort required is the same each time
The use of automation improves quality and team morale. Automated Tests are part of the codebase
A smoke test is basically just a sanity check to see if the software functions on the most basic level.
If your smoke test fails, it means there is no point in running your other functional tests.
Optional: Paratest
Clone repo :
composer require --dev yipl/hookah
or
Add "yipl/hookah": "~0.4" and composer install
Run with phpunit
./vendor/bin/phpunit
Run tests faster
./vendor/bin/paratest -f --colors -m 2 -p 4 tests
/**
* @var string
*/
protected $baseUrl = 'http://drupal-test.jelastic.elastx.net/';
/**
* @var string
*/
protected $loginPath = 'user/login';
/**
* @var string
*/
protected $usernameField = 'name';
/**
* @var string
*/
protected $passwordField = 'pass';
/**
* @var string
*/
protected $submitButtonText = 'Log in';
/**
* @var array
*/
protected $users = [
['role'=> 'admin', 'identifier' => 'admin',
'password' => '123admin'],
];
/**
* @var string
*/
protected $loggedInLinkText = 'Log out';
/**
* To be overridden by child class
*
* @var string
*/
protected $userRole = 'none';
return [
[$this->baseUrl, 200],
['about', 200],
['not-existing', 404],
['.git', 403],
];
$adminPaths = [
['admin', 200],
['admin/config', 200],
['not-existing', 404]
];
language: php
php:
- 5.6
before_script:
- mkdir -p shippable/testresults
script:
-./vendor/bin/phpunit --log-junit shippable/testresults/junit.xml
notifications:
email: false
Integration with Laravel
Integration with Custom PHP Project


|
OpenJij C++ interface
0.4.0
|
Polynomial graph class, which can treat many-body interactions. The Hamiltonian is like. More...
#include <polynomial.hpp>
Public Types | |
| using | value_type = FloatType |
| Floating-point type. More... | |
Public Member Functions | |
| Polynomial (const std::size_t num_variables) | |
| Constructor of Polynomial class to initialize variables and vartype. More... | |
| Polynomial (const nlohmann::json &j) | |
| Constructor of Polynomial class to initialize num_variables, and interactions from json. More... | |
| FloatType & | J (std::vector< Index > &key) |
| Access the interaction corresponding to the input argument to set an interaction. More... | |
| FloatType & | J (const std::vector< Index > &key) |
| Access the interaction corresponding to the input argument to set an interaction. More... | |
| FloatType | J (std::vector< Index > &key) const |
| Return the interaction corresponding to the input argument. More... | |
| FloatType | J (const std::vector< Index > &key) const |
| Return the interaction corresponding to the input argument. More... | |
| template<typename... Args> | |
| FloatType & | J (Args... args) |
| Access the interaction corresponding to the input argument to set an interaction. More... | |
| template<typename... Args> | |
| FloatType | J (Args... args) const |
| Access the interaction corresponding to the input argument to set an interaction. More... | |
| cimod::Polynomial< Index, FloatType > | get_polynomial () const |
| Generate and return all the polynomial interactions as std::unordered_map<std::vector<Index>, FloatType>. More... | |
| const cimod::PolynomialKeyList< Index > & | get_keys () const |
| Get the PolynomialKeyList object (all the keys of polynomial interactions). More... | |
| const cimod::PolynomialValueList< FloatType > & | get_values () const |
| Get the PolynomialValueList object (all the values of polynomial interactions). More... | |
| std::size_t | get_num_interactions () const |
| Return the number of all the interactions. More... | |
| FloatType | energy (const Spins &spins, const bool omp_flag=true) const |
| Return the total energy corresponding to the input variables, Spins or Binaries. More... | |
| FloatType | calc_energy (const Spins &spins, const bool omp_flag=true) const |
| Return the total energy corresponding to the input variables, Spins or Binaries. More... | |
| Public Member Functions inherited from openjij::graph::Graph | |
| Graph (std::size_t num_spins) | |
| Graph constructor. More... | |
| template<typename RandomNumberEngine > | |
| const Spins | gen_spin (RandomNumberEngine &random_numder_engine) const |
| generate spins randomly. More... | |
| template<typename RandomNumberEngine > | |
| const Binaries | gen_binary (RandomNumberEngine &random_numder_engine) const |
| generate spins randomly. More... | |
| std::size_t | get_num_spins () const noexcept |
| get number of spins More... | |
| std::size_t | size () const noexcept |
| get number of spins More... | |
Private Member Functions | |
| void | CheckKeyValid (const std::vector< Index > &key) const |
| Check if the input keys are valid. More... | |
Private Attributes | |
| cimod::PolynomialKeyList< Index > | poly_key_list_ |
| The list of the indices of the polynomial interactions (namely, the list of key of the polynomial interactions as std::unordered_map) as std::vector<std::vector<Index>>. More... | |
| cimod::PolynomialValueList< FloatType > | poly_value_list_ |
| The list of the values of the polynomial interactions (namely, the list of value of the polynomial interactions as std::unordered_map) as std::vecto<FloatType>. More... | |
| std::unordered_map< std::vector< Index >, std::size_t, cimod::vector_hash > | poly_key_inv_ |
| The inverse key list, which indicates the index of the poly_key_list_ and poly_value_list_. More... | |
Polynomial graph class, which can treat many-body interactions. The Hamiltonian is like.
\[ H=\sum_{i \neq j} Q_{ij} x_i x_j + \sum_{i \neq j \neq k} Q_{ijk} x_i x_j x_k + \ldots \]
Note here that \( x_i \in \{0, 1\} \) or \( x_i \in \{-1, +1\} \).
| FloatType | floating-point type |
| using openjij::graph::Polynomial< FloatType >::value_type = FloatType |
Floating-point type.
|
inlineexplicit |
Constructor of Polynomial class to initialize variables and vartype.
| num_variables | std::size_t |
|
inlineexplicit |
Constructor of Polynomial class to initialize num_variables, and interactions from json.
| j | JSON object |
|
inline |
Return the total energy corresponding to the input variables, Spins or Binaries.
| spins | const Spins& or const Binaries& (both are the same type) |
| omp_flag | if true OpenMP is enabled. |
|
inlineprivate |
Check if the input keys are valid.
|
inline |
Return the total energy corresponding to the input variables, Spins or Binaries.
| spins | const Spins& or const Binaries& (both are the same type) |
| omp_flag | if true OpenMP is enabled. |
|
inline |
Get the PolynomialKeyList object (all the keys of polynomial interactions).
|
inline |
Return the number of all the interactions.
|
inline |
Generate and return all the polynomial interactions as std::unordered_map<std::vector<Index>, FloatType>.
|
inline |
Get the PolynomialValueList object (all the values of polynomial interactions).
|
inline |
Access the interaction corresponding to the input argument to set an interaction.
If the interaction specified by "args" is empty, the zero will be added to the polynomial graph.
| args | parameter pack |
|
inline |
Access the interaction corresponding to the input argument to set an interaction.
If the interaction specified by "args" is empty, this function returns the zero.
| args | parameter pack |
|
inline |
Access the interaction corresponding to the input argument to set an interaction.
If the interaction specified by "key" is empty, the zero will be added to the polynomial graph.
| key | const std::vector<Index>& |
|
inline |
Return the interaction corresponding to the input argument.
If the interaction specified by "key" is empty, this function returns the zero.
| key | const std::vector<Index>& |
|
inline |
Access the interaction corresponding to the input argument to set an interaction.
Note that the input argument "key" will be sorted. If the interaction specified by "key" is empty, the zero will be added to the polynomial graph.
| key | std::vector<Index>& |
|
inline |
Return the interaction corresponding to the input argument.
Note that the input argument "key" will be sorted. If the interaction specified by "key" is empty, this function returns the zero.
| key | std::vector<Index>& |
|
private |
The inverse key list, which indicates the index of the poly_key_list_ and poly_value_list_.
|
private |
The list of the indices of the polynomial interactions (namely, the list of key of the polynomial interactions as std::unordered_map) as std::vector<std::vector<Index>>.
|
private |
The list of the values of the polynomial interactions (namely, the list of value of the polynomial interactions as std::unordered_map) as std::vecto<FloatType>.


Rangers will overthrow Celtic as champions and any manager can win in Scotland says former England boss
Sam Allardyce reckons the Ibrox club is on an upward trajectory.
by Jonathan McFarlaneSam Allardyce has dismissed the successes of Celtic bosses and claimed all managers can come to Scotland and win silverware.
The comments were made as part of a wider debate about managers having to win titles or cups to be considered for top jobs in the Premier League.
Burnley boss Sean Dyche has been linked with Everton but a talkSPORT caller claimed that without tangible success, top clubs would always look to managers with a track record of success.
Host Alan Brazil suggested that Brendan Rodgers ' reason to go to Celtic was to become a winner and rehabilitate his reputation after coming so close to the title at Liverpool.
But Allardyce, was unimpressed.
He said: "We can all go to Celtic and win trophies.
"It will be Rangers soon the way they are going under Steven Gerrard .
"Fans expect you to win trophies and if you don't do that then you'd get the sack.
"I agree with what Brendan was saying and it was a great move for him because it built his reputation again.
"But I didn't think there was anything wrong with him because he was brilliant at Liverpool, just a bad patch of recruitment cost him his job."


Basic Table
One Color Bar
| Id | Job Name | Progress | Fulfillment |
|---|---|---|---|
| 01 | Technician | 50% | |
| 02 | Engineering | 75% | |
| 03 | Support Center | 25% | |
| 04 | IT Admin | 50% | |
| 05 | Security | 90% |
Table Bordered
Another Style| Id | Job Name | Min Salary | Max Salary |
|---|---|---|---|
| 01 | Technician | $ 100 | $ 110 |
| 02 | Engineering | $ 200 | $ 220 |
| 03 | Support Center | $ 300 | $ 330 |
| 04 | IT Admin | $ 400 | $ 440 |
| 05 | Security | $ 3000 | $ 6000 |
Inverse Table
Contextual Bar
| Id | Job Name | Progress | Fulfillment |
|---|---|---|---|
| 01 | Technician | 50% | |
| 02 | Engineering | 75% | |
| 03 | Support Center | 25% | |
| 04 | IT Admin | 50% | |
| 05 | Security | 90% |
Striped Rows
Job Rates| Id | Job Name | Min Salary | Max Salary |
|---|---|---|---|
| 01 | Technician | $ 100 | $ 110 |
| 02 | Engineering | $ 200 | $ 220 |
| 03 | Support Center | $ 300 | $ 330 |
| 04 | IT Admin | $ 400 | $ 440 |
| 05 | Security | $ 3000 | $ 6000 |
With Action Buttons
| Approved | 2 Applicants | IT Admin(Susan Doe), Technician(Susan Doe) | clear | |
| Rejected | 3 Applicants | Engineering(Susan Doe), Technician(Alexander Pierce), IT Admin(Mike Doe) | ||
| Reviewed | 2 Applicants | Support Center(Mike Doe), IT Admin(Alexander Pierce) | ||
| Pending | 3 Applicants | Support Center(Susan Doe), Support Center(Alexander Pierce), Technician(Mike Doe) |


{{ listingTitle|default('Latest Posts') }}
{# Next we sort the data by publish_date. The true bit reverses it so it's newest first. Learn more: #}
{# http://www.webhook.com/docs/template-rules-and-filters/#sortproperty_reverseorder #}
{% set data = data|sort('publish_date', true) %}
{# This is how you set pagination. It's always important to do this after your sort. #}
{% set data = paginate(data, 6) %}
{% for object in data %}
{% endfor %}
{{ object.name }}
{{ object.short_description }}


gppBuilder for the Groovy Parallel Patterns (gpp)
copyright 2015-18 Jon Kerridge Edinburgh Napier University
contact j.kerridge @ napier.ac.uk
The gppBuilder program converts the source definition of an application defined using the GPP library into a form that can be executed as a Groovy script.
The source file is provided as \path\filename_gpp.grooy . The .groovy suffix means that the source is checked by the Groovy system during its creation. The source should contain all the required data definitions and assumes that all the required user developed code is available. These data definitions should precede the definition of the required process definitions. The format of the source file should be:
Constant declarations Definitions of GPP Data, Result and Local and other Detail data objects Initialisation code to be obeyed before the process network is created Process definitions omitting input and output properties The definitions should appear in the order in which data flows through the process network; ordering is crucial. Finalisation codeExamples of the additional coding could include the initialisation of a start time with the corresponding finalisation code being to print out the total execution time.
The gppBuild program create a file called \path\filename.groovy. If the transformation generated errors then the output file will contain an indication of the error at the place where it was found in the source file.
If the transformation was successful the output file will contain the application in a form that can be executed as a Groovy script.


Poorvi Bhutwala Parkhie
Democrat
Homemaker/Professional Writer
I am a licensed attorney in Colorado, Washington D.C. , and Georgia. My practice areas include securities, finance and real estate law. I now consult with small businesses as a professional content writer.
80238
I am a registered Democrat and am a consistent voter. I have donated to the Democratic presidential campaign (for Joe Biden) in 2020. I have also participated in getting out the vote with Rock the Vote (including a financial donation to their organization) and Blue Revolution (participated in a letter writing campaign encouraging voters to vote on election day).
Denver Center for International Studies Foundation, Secretary & Board of Directors Member Central Park/Park Hill South Asian Community Blue Revolution
As a Board Member of the DCIS Foundation for (5) years, it was our responsibility to provide educational travel scholarships to DCIS students who otherwise would not be able to participate in life changing travel opportunities. Providing these scholarships required understanding the wide variety of backgrounds that students and their families come from and developing opportunities that were not otherwise available to them. As a Colorado citizen, I have participated in get out the vote activities and letter writing campaigns.
I believe a fundamental part of a democracy lies in ensuring the congressional voting map of a state accurately reflect the state's population when it comes to gender, race, and political affiliation.
As an attorney, my work required bringing parties with different goals together to reach an outcome that satisfied everyone. My approach to each of my negotiations and deals has always been to take the time to understand each sides' interests, listen to the concerns of each party and think creatively on how to meet the most needs. As a member of this commission, I recognize that my ultimate duty and obligation is to the people of Colorado.
Bringing consensus to a diverse group of people requires research and understanding of the facts with which you are working. If chosen, I would bring the analytical skills I developed as an attorney to the commission and use them to work towards a rational goal.
female


Events illustrates the use of date and time fields using ODBC from Prolog.
It also illustrates the use of directives to create the runtime environment for the application, instead of amzi.cfg to load 'aodbc.lsx' and the linker to load 'aodbc.plm'.
To run it you need to first:
To run it:
?- consult(events). yes ?- main. ?- consult(events). yes ?- main. Duke:Clemson date(1997, 1, 12) time(14, 30, 0) Florida State:Georgia Tech date(1997, 1, 12) time(20, 15, 0) Maryland:North Carolina date(1997, 1, 14) time(13, 0, 0) NC State:Virginia date(1997, 1, 14) time(14, 0, 0) Wake Forest:Duke date(1997, 1, 14) time(19, 0, 0) Clemson:Florida State date(1997, 1, 17) time(15, 0, 0) Georgia Tech:Maryland date(1997, 1, 18) time(20, 0, 0) North Carolina:NC State date(1997, 1, 18) time(14, 15, 0) Virginia:Wake Forest date(1997, 1, 18) time(14, 0, 0) yes
Copyright ©1987-2004 Amzi! inc. All Rights Reserved. Amzi! is a registered trademark and Logic Server and e-Prolog are trademarks of Amzi! inc.


{% from "components/icon.html" import Icon %} Current Obligated funds As of {{ now | formattedDate(formatter="%B %d, %Y at %H:%M") }} {% for JEDI_clin, funds in current_obligated_funds.items() %} {% set remaining_funds = (funds["obligated_funds"] - funds["expended_funds"]) %} {{ "JEDICLINType.{}".format(JEDI_clin) | translate }} Total obligated amount: {{ funds["obligated_funds"] | dollars }} Funds expended: {{ funds["expended_funds"] | dollars }} Remaining funds: {{ remaining_funds | dollars }} {% endfor %} Active Task Orders {% for task_order in portfolio.active_task_orders %} {{ task_order.number }} {{ Icon("caret_right", classes="icon--tiny icon--blue" ) }} {% endfor %}
Total obligated amount: {{ funds["obligated_funds"] | dollars }}
Funds expended:
{{ funds["expended_funds"] | dollars }}
Remaining funds:
{{ remaining_funds | dollars }}


{% extends "modeleditor.html" %} {% block title%}Import Model from Public Library{% endblock %} {% block modeleditorcontent %}


Threat triggers security measures at three Nanaimo schools
by Jeff BellAn unspecified threat led to security measures being put in place at three Nanaimo schools Friday morning.
Dover Bay Secondary was placed in lockdown while nearby Nanaimo and District Secondary and McGirr Elementary were placed in a hold-and-secure. The security measures were lifted as of as of 11:20 a.m.
A lockdown involves restricting students to a specific part of the school, like a classroom. In a hold-and-secure, the exterior doors are locked while activities inside proceed as normal.
As a precaution and to answer any questions from parents, two officers were assigned to each school for the rest of the day.
Call Nanaimo RCMP with any information about the situation at<PHONE_NUMBER>.