House of Reps summon CBN governor, NDIC MD
- The House of Representatives have summoned the Central Bank of Nigeria governor, Godwin Emefiele
- The green chambers also summoned the managing director of the Nigerian Deposit Insurance Corporation, Umaru Ibrahim
- Both men are expected to provide answers on the new status of Savannah Bank
The House of Representatives on Thursday, November 22 directed its committee on banking and currency to summon the Central Bank of Nigeria governor, Godwin Emefiele and the managing director of the Nigerian Deposit Insurance Corporation, Umaru Ibrahim.
The duo are expected to answer questions on the new status of Savannah Bank regarding its commencement of operations after its closure.
Daily Trust reports that the committee was given four weeks to submit its findings and report back to the green chambers.
The motion was moved by an All Progressives Congress member from Jigawa state, Honourable Magaji Da'u Aliyu.
The committee was also mandated to invite the bank’s shareholders and the new management to brief it on possible ways of refunding depositors and looking into the circumstances that led to the withdrawal of Savannah Bank’s licence and eventual closure in 2002.
2023 presidency: This is the man that will likely succeed Buhari - APC chieftain discloses
The licence of Savannah Bank Plc was withdrawn by the CBN 17 years ago on the ground that the bank did not have enough assets to meet liabilities.
PAY ATTENTION: Install our latest app for Android and read the best news on Nigeria’s #1 news app
The bank was also accused of not complying with the apex bank’s obligations, adding that its management was unable to prevent its declining fortunes.
Meanwhile, the National Assembly says it will commence review of N-Power and other social investment programmes of the federal government to accommodate more youths especially fresh graduates.
This was disclosed by the House of Representatives’ committee chairman on youth and sports, Adeyemi Adaramodu.
NAIJ.com (naija.ng) -> Legit.ng We have upgraded to serve you better
Minister of industry says economy is improving; Nigerians disagree | Legit TV


When a project reaches a certain size, managing the script modules for a project starts to get tricky. You need to be sure to sequence the scripts in the right order, and you need to start seriously thinking about combining scripts together into a bundle for deployment, so that only one or a very small number of requests are made to load the scripts.
You may also want to load code on the fly, after page load.
RequireJS can help you manage the script modules, load them in the right order, and make it easy to combine the scripts later via the RequireJS optimizer without needing to change your markup. It also gives you an easy way to load scripts after the page has loaded, allowing you to spread out the download size over time.
RequireJS has a module system that lets you define well-scoped modules, but you do not have to follow that system to get the benefits of dependency management and build-time optimizations. Over time, if you start to create more modular code that needs to be reused in a few places, the module format for RequireJS makes it easy to write encapsulated code that can be loaded on the fly. It can grow with you, particularly if you want to incorporate internationalization (i18n) string bundles, to localize your project for different languages, or load some HTML strings and make sure those strings are available before executing code, or even use JSONP services as dependencies.
This example shows how to use the shim config to specify dependencies for jQuery plugins that do not call define(). This example is useful if you have an existing jQuery project you want to convert and do not want to modify the sources of the jQuery plugins to call define().
This is an example on how to load an optimize your code while loading jQuery from a Content Delivery Network (CDN). This example requires all your jQuery plugins to call define() to properly express their dependencies. Shim config does not work after optimization builds with CDN resources.
Previously, we've been pointing to an example using a special require-jquery file, which consisted of require.js and jQuery concatenated. This is no longer the recommended way to use jQuery with require.js, but if you're looking for the (no longer maintained) example, you can find require-jquery here.


| Category | Proficency In Decreasing Order |
|---|---|
| Programming Languages | C, Java, C++, Python, R |
| Technologies and Tools | Git, Linux, Android and Android Studio, Shell Scripting, LaTeX |
| Web Technologies | HTML, CSS, JavaScript, MySQL/SQLite, AngularJS, Bootstrap, PHP |
Lead a team of undergradate and graduate researchers throughout the course of a 2-year behavioural neuroscience research project. Managed and oversaw the planning and implementation of the project while reporting to an advisory committee, and provided mentorship and supervision to new researchers.


Monsters & Combat¶
Combat¶
Your party enters a room with a monster, combat will begin. The combat_round
method on the game client will be called, and you will be able to direct your units to take various actions.
Combat Actions¶
There are three main types of combat actions, attacking (also sometimes called basic attacking), attacking with a bomb or spells (only allowed by certain unit classes), and using a special ability.
- Attacking: The unit attacks using their primary weapon (as listed on the Unit Classes page).
- Basic attacking is done using the
unit.attack()
method.
- Basic attacking is done using the
- Bomb or spells: The unit attacks with an auxiliary item held in bomb or spell slots. Alchemists and rogues can use bombs; the Magus, Wizard, and Sorcerer classes can use spells. These items make use of monster weaknesses which are described below in more detail.
- To use a bomb or spell, refer to the api for the specific class you are using as listed on the Unit Classes page.
- Special Abilities: Each class - excluding the rogue - has a unique special ability that can be used in combat.
- To use a special ability, refer to the api for the specific class you are using as listed on the Unit Classes page.
Monster Weaknesses & Item Damage Types¶
Each monsters have a series of weaknesses. These weaknesses are found as a list on the monster.weaknesses
property. Each value in the list is an enum value corresponding to one or more of the following weaknesses:
DamageType.piercing
DamageType.slashing
DamageType.bludgeoning
DamageType.precision
DamageType.fire
DamageType.cold
DamageType.electricity
DamageType.acid
DamageType.sonic
DamageType.force
Attacking a monster using a weapon, spell, or bomb with a matching weakness will deal 25% extra damage per weakness to the monster.
Monster Properties¶
monster.monster_type
: A MonsterType enum value indicating the type of monster.monster.level
: The level of the monster.monster.health
: The monster’s max health.monster.current_health
: The monster’s current health.monster.damage
: The amount of damage the monster deals when it attacks.monster.gold
: The amount of gold that will rewarded for defeating the monster.
Monsters¶
Wisp¶
Weaknesses:¶
DamageType.cold
DamageType.force
DamageType.sonic
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 23500 | 160 | 50 |
| 2 | 36555 | 195 | 232 |
| 3 | 49611 | 231 | 415 |
| 4 | 62666 | 266 | 597 |
| 5 | 75722 | 302 | 779 |
| 6 | 88777 | 362 | 962 |
| 7 | 101833 | 373 | 1144 |
| 8 | 114888 | 408 | 1327 |
| 9 | 127944 | 444 | 1509 |
| 10 | 141000 | 480 | 1692 |
Attack Logic¶
Let me ignite the spark of your heart (and the rest of your body), and your flames will burn bright!
Beholder¶
Weaknesses:¶
DamageType.acid
DamageType.cold
DamageType.fire
DamageType.piercing
DamageType.slashing
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 25000 | 189 | 87 |
| 2 | 38888 | 228 | 300 |
| 3 | 52777 | 267 | 512 |
| 4 | 66666 | 306 | 725 |
| 5 | 80555 | 345 | 986 |
| 6 | 94444 | 384 | 1150 |
| 7 | 108333 | 423 | 1362 |
| 8 | 122222 | 462 | 1575 |
| 9 | 136111 | 501 | 1787 |
| 10 | 150000 | 540 | 2000 |
Attack Logic¶
Beauty is in the 👁 of the Beholder, but to him, all are ugly. Quite frankly, even 👁 have no idea.
Dragon¶
Weaknesses:¶
DamageType.acid
DamageType.electricity
DamageType.piercing
DamageType.precision
DamageType.sonic
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 30000 | 185 | 113 |
| 2 | 46666 | 226 | 378 |
| 3 | 63333 | 267 | 643 |
| 4 | 80000 | 308 | 908 |
| 5 | 96666 | 349 | 1173 |
| 6 | 113333 | 390 | 1438 |
| 7 | 130000 | 431 | 1702 |
| 8 | 146666 | 472 | 1967 |
| 9 | 163333 | 513 | 2232 |
| 10 | 180000 | 555 | 2497 |
Attack Logic¶
Dragons hate those arrogant, lazy knights.
Minotaur¶
Weaknesses:¶
DamageType.cold
DamageType.electricity
DamageType.precision
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 28000 | 200 | 100 |
| 2 | 43555 | 244 | 336 |
| 3 | 59111 | 288 | 572 |
| 4 | 74666 | 333 | 808 |
| 5 | 90222 | 377 | 1044 |
| 6 | 105777 | 422 | 1280 |
| 7 | 121333 | 466 | 1516 |
| 8 | 136888 | 511 | 1752 |
| 9 | 152444 | 555 | 1988 |
| 10 | 168000 | 600 | 2225 |
Attack Logic¶
I’d rather not get physical this time, but I’ll take a swing at it!
Slime¶
Weaknesses:¶
DamageType.electricity
DamageType.precision
DamageType.sonic
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 22000 | 150 | 50 |
| 2 | 34222 | 183 | 209 |
| 3 | 46444 | 216 | 368 |
| 4 | 58666 | 250 | 528 |
| 5 | 70888 | 283 | 687 |
| 6 | 83111 | 316 | 847 |
| 7 | 95333 | 350 | 1006 |
| 8 | 107555 | 383 | 1166 |
| 9 | 119777 | 416 | 1325 |
| 10 | 132000 | 450 | 1485 |
Attack Logic¶
splosh slorp slurmp sound of gelatin gelatinning
Vampire¶
Weaknesses:¶
DamageType.fire
DamageType.piercing
DamageType.precision
DamageType.slashing
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 25000 | 175 | 75 |
| 2 | 38888 | 213 | 281 |
| 3 | 52777 | 252 | 487 |
| 4 | 66666 | 291 | 693 |
| 5 | 80555 | 330 | 899 |
| 6 | 94444 | 369 | 1105 |
| 7 | 108333 | 408 | 1312 |
| 8 | 122222 | 447 | 1518 |
| 9 | 136111 | 486 | 1724 |
| 10 | 150000 | 525 | 1930 |
Attack Logic¶
What is a man? tosses wine glass aside A miserable pile of armor and nothing more! But enough talk! Have at you!
Wraith¶
Weaknesses:¶
DamageType.acid
DamageType.bludgeoning
DamageType.fire
DamageType.slashing
Stats¶
| Level | Health | Damage | Gold Value |
|---|---|---|---|
| 1 | 26000 | 165 | 62 |
| 2 | 40444 | 201 | 208 |
| 3 | 54888 | 238 | 454 |
| 4 | 69333 | 275 | 649 |
| 5 | 83777 | 311 | 845 |
| 6 | 98222 | 348 | 1041 |
| 7 | 112666 | 385 | 1237 |
| 8 | 127111 | 421 | 1432 |
| 9 | 141555 | 458 | 1628 |
| 10 | 156000 | 495 | 1824 |
Attack Logic¶
Allow me to spell out your doom for you loud and clear!


Soup or soup is a soup made from broth that is made by simmering ingredients such as meat or chicken to make broth, and is usually added with seasonings and other ingredients to add flavor. The ingredients consist of boiled meat, vegetables or nuts to form a juice.
Vegetables along with fruit are super foods that can keep us from various dangerous diseases, such as heart disease, cancer and diabetes. It also has a variety of very healthy ingredients, including fiber, vitamins and antioxidants.
Hanifa chairunnisa born in Batam on July 15, 2001.


Something went wrong...
It looks like something didn’t work out the way it should. Below you see the last few lines of the logfile, maybe you can solve the problem on your own. If not, open a new issue on GitHub.
{{ log }}
In case you want to check the whole logfile, it is located in the directory {{ tempdir }}
.


-
On a Warmer Planet, Which Cities Will Be Safest?
www.nytimes.com
Scientists trying to predict the consequences of climate change see few havens from future storms, floods and droughts. But some regions will fare ...
-
The Woman Who Walked 10,000 Miles (No Exaggeration) in Three Years
www.nytimes.com
For Sarah Marquis, a very long hike – from Siberia through the Gobi Desert, China and eventually Australia – can become a voyage of discovery.
-
Steve Jobs Was a Low-Tech Parent - NYTimes.com
www.nytimes.com
When Steve Jobs was running Apple, he was known to call journalists to either pat them on the back for a recent article or, more often than not, ...
-
Ferguson Police Chief Offers Apology to Michael Brown’s Family
www.nytimes.com
In an online video, Thomas Jackson, the police chief of Ferguson, Mo., said he was sorry for the loss of their son and regretted that it took ...
-
An Insanely Detailed, Hand-Drawn Map of San Francisco
www.citylab.com
It took illustrator Jenni Sparks three months to finish this secret-laden cartography.
-
Together, Square Sellers Are the 13th Largest Retailer in the Country - ...
blog.squareup.com
The Official Square Blog is a place for sellers to find valuable tips and insights for running their business, learn from one another's challenges ...
-
Apple's "warrant canary" disappears, suggesting new Patriot Act demands
gigaom.com
Apple included language in its first Transparency Report to say that it had not been subject to a Section 215 Patriot Act request. That language is ...
-
The Mathematics of Ebola Trigger Stark Warnings: Act Now or Regret It | ...
www.wired.com
Without immediate action, Ebola could claim tens to hundreds of thousands more lives by the end of 2014.
-
Ferguson tragedy becoming a farce
www.washingtonpost.com
Justice seems to be rigged in the tragic Michael Brown shooting.
-
Flight: Twitter's Mobile Developer Conference
www.twitterflight.com
Flight is a gathering built by developers, for developers. You'll be right at home if you live, breathe and occasionally dream in Java, Objective-C, ...
-
M6.0 - 6km NW of American Canyon, California (BETA) 2014-08-24 10:20:44 UTC
comcat.cr.usgs.gov
USGS Earthquake Hazards Program, responsible for monitoring, reporting, and researching earthquakes and earthquake hazards
-
I will not be returning to Ferguson
ryanschuessler.com
I had been on the ground helping Al Jazeera America** cover the protests and unrest in Ferguson, Mo., since this all started last week. After what I ...
-
iPhone 6 And 6 Plus Bend Test - Consumer Reports News
www.consumerreports.org
Exclusive Consumer Reports test results show new iPhones are tough and not as bendy as rumored.
-
The Secret Goldman Sachs Tapes
www.bloombergview.com
The public doesn't seem to understand just how dysfunctional our financial regulatory system is, Michael Lewis writes. That may change today with a ...
-
Facebook Is Partnering With Stripe to Power "Buy" Button
recode.net
Stripe adds Facebook to its list of impressive partnership deals.
-
Open Sourcing ml-ease | LinkedIn Engineering
engineering.linkedin.com
We're seeking intelligent problem solvers who are inspired and motivated to change the world.
-
Why the Garbage Man Might Dislike Your Dog - NYTimes.com
www.nytimes.com
It is a civic drama that plays out each morning on sidewalks across New York City.
-
The Victim, The Comforter, The Guy’s Girl…
medium.com
There’s only room for certain kinds of women in the tech world.
-
Apple Responds to Complaints of Bent iPhones
bits.blogs.nytimes.com
Social media channels have overflowed this week with commentary on whether Apple’s new iPhone 6 Plus bends under pressure.
-
For Polar Bears, a Climate Change Twist
www.nytimes.com
When sea ice melts and polar bears meet snow geese on their nests, the effects of climate change get complicated.
-
Global Response to Ebola Is Too Slow, Obama Warns
www.nytimes.com
At a United Nations meeting on the outbreak, President Obama said the world was doing too little and “not moving fast enough.”
-
Michelin Guide Announces NYC's Inexplicable 2015 Bib Gourmands - Eater NY
ny.eater.com
The Michelin Guide has just released its "Bib Gourmand" picks for the forthcoming 2015 edition of its New York City dining guide. These are the ...
-
Attorney General Eric Holder, Prominent Liberal Voice in Obama ...
www.nytimes.com
Mr. Holder plans to remain in office until a successor is nominated and confirmed.
-
India Reaches Mars With Low-Cost Mission
newswatch.nationalgeographic.com
India's new entrant into orbit around Mars, the Mars Orbiter Mission (MOM), is a triumph for its space agency and represents the fourth country to ...
-
Big iPhone 6 Bulges in All the Wrong Places - NYTimes.com
www.nytimes.com
It’s the ultimate first world problem.
-
How to tell when a robot has written you a letter
medium.com
Or a human! The next Turing Test is … handwriting.
-
Exposing Hidden Bias at Google - NYTimes.com
www.nytimes.com
Google, like many tech companies, is a man’s world.


Homepage
Hey you! Yes, the one reading this right now, Welcome to Mei Fang's web page! Always willing to meet new people and getting intrigued by the wonders of the world. I've been in a household full of engineers and have an amazing father as one. That's where my interest in Hands-on projects come along!
I hope this site gives you an idea about my life in Engineering Academy. With project works and many others in the future. It will hopefully inspire you on something you're keen in doing. Engineering is everywhere! Once you expand and extend your thinking on life, everything you see will be much more colorful and mechanical than you once think. Woohoo!


We use data science and our proven technology to get food from those who find themselves with too much to people who find themselves with too little. With the closure of offices nation wide, our supply of surplus food has all but dried up while food insecurity is on the rise. You can help us get meals to those most affected by the current public health crisis.
Your donations of food allow us to help you put the food you have spent so much money and effort preparing to good use when you can not consume all of it in your business operations. It reduces the enviromental impact of disposing of the food through incineration or in a landfill, and reduces the contries terrible statistics on food wastage.
Monetary donations help us run our office and the servers and other technology that make it possible for us to continue to operate. They pay for the purchase and maintenance of the vehicles our volunteers use to pick-up your food. They also pay for the continual upgrading of our software to make it even easier to continue our service.
Using replate at my restaurant helps me to pay back my community for the support and business it has provided me. My employees are happy to know that they are not only helping the business, but also those in need.
I have suffered from food insecurity in the past and it makes me feel good to know that I am helping those who still feel it today. I hope all business owners remember where they came from and the opportunities they have been given.


不用我多介绍了，STEEM分叉即将到来，对此你如何看待？你会去玩HIVE吗？你更看好STEEM的前景还是更看好HIVE?
无论选择留在STEEM，还是去HIVE那边，或者两边一起玩，对HIVE多些了解终归是有益无害的。
我创建了一个HIVE微信群，欢迎大家加入一起学习讨论。想加群的扫码添加即可：
进群后，请修改群名片为STEEM ID （分叉后也将是你的Hive ID）。
讨论话题仅限STEEM/HIVE区块链相关，请友好讨论，禁止人身攻击。
English Version：
Hello, everyone：
As we all know, STEEM is about to split into two chains (STEEM & Hive) on Friday.
What do you think of that?
Are you going to play HIVE?
Which do you think has a better future, STEEM or HIVE?
I have created a WeChat group about HIVE, and welcome you to join us.
相关链接
- Announcing the Launch of Hive Blockchain
- 分家已不可避免？Hive官宣划重点。
- 新闻: Blocktrades 发帖声明绝不妥协 & STEEM新链
- Why I won’t be compromising with Justin Sun by @blocktrades
https://steemit.com/~witnesses type in
oflyhigh
and click VOTE
Vote @oflyhigh via Steemconnect
Thank you!
This page is synchronized from the post: ‘HIVE 微信群，欢迎大家加入 / WeChat group about HIVE’


You do not talk about Fight Club
You DO NOT talk about Fight Club!
Someone yells "stop!", goes limp, taps out, the fight is over
Only two guys to a fight
One fight at a time, fellas
No shirts, no shoes
Fights will go on as long as they have to
If this is your first time at Fight Club, you have to fight
grow
shrink
fade-out
fade-up (also down, left and right!)
visible only once
blue only once
highlight-red
package com.pomverte;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class CrudAutoImplApplication {
public static void main(String[] args) {
SpringApplication.run(CrudAutoImplApplication.class, args);
}
}
What is the most resilient parasite? Bacteria? A virus? An intestinal worm?
An idea. Resilient... highly contagious.
Once an idea has taken hold of the brain it's almost impossible to eradicate. An idea that is fully formed - fully understood - that sticks; right in there somewhere.
An idea that is fully formed - fully understood - that sticks; right in there somewhere.


import scrawl from '../source/scrawl.js';
const stack = scrawl.library.artefact.mystack,
mytext = scrawl.library.artefact.myelement;
Determine the displayed shape of the visible stack; react to changes in the displayed shape
import scrawl from '../source/scrawl.js';
const stack = scrawl.library.artefact.mystack,
mytext = scrawl.library.artefact.myelement;
stack.set({
checkForResize: true,
});
mytext.set({
start: ['center', 'center'],
handle: ['center', 'center'],
});
Scrawl-canvas recognises five shapes, separated by four breakpoints:
banner
landscape
rectangle
portrait
skyscraper
The values assigned to the breakpoints are Float numbers for the Stack artefact’s width/height ratio - the value 3
represents the case where the width value is three times more than the height value, while 0.35
represents a width (roughly) 3 times less than the height.
We can set a Stack artefact’s breakpoints in one go using the dedicated setDisplayShapeBreakpoints()
function, as below. Alternatively we can use the regular set()
function, supplying the attributes breakToBanner
, breakToLandscape
, breakToPortrait
and breakToSkyscraper
as required. The values given here are the default values for Stack artefacts.
stack.setDisplayShapeBreakpoints({
breakToBanner: 3,
breakToLandscape: 1.5,
breakToPortrait: 0.65,
breakToSkyscraper: 0.35,
});
Each display shape has an associated hook function (by default a function that does nothing) which Scrawl-canvas will run each time it detects that the Stack display shape has changed to that shape. We can replace these null-functions with our own; this allows us to configure the scene/animation to accommodate different display shapes, thus making the code reusable in a range of different web page environments.
We can set/update these functions at any time using the normal set()
function:
stack.set({
actionBannerShape: () => {
mytext.set({
roll: 0,
});
mytext.domElement.textContent = `Stack display shape: ${stack.get('displayShape')}`;
},
actionRectangleShape: () => {
mytext.set({
roll: -45,
});
mytext.domElement.textContent = `Stack display shape: ${stack.get('displayShape')}`;
},
actionSkyscraperShape: () => {
mytext.set({
roll: -90,
});
mytext.domElement.textContent = `Stack display shape: ${stack.get('displayShape')}`;
},
});
We can also set/update the functions using dedicated setAction???Shape()
functions:
stack.setActionPortraitShape(() => {
mytext.set({
roll: -67.5,
});
mytext.domElement.textContent = `Stack display shape: ${stack.get('displayShape')}`;
});
stack.setActionLandscapeShape(() => {
mytext.set({
roll: -22.5,
});
mytext.domElement.textContent = `Stack display shape: ${stack.get('displayShape')}`;
});
Function to display frames-per-second data, and other information relevant to the demo
let report = function () {
let testTicker = Date.now(),
testTime, testNow,
testMessage = document.querySelector('#reportmessage');
return function () {
testNow = Date.now();
testTime = testNow - testTicker;
testTicker = testNow;
testMessage.textContent = `Screen refresh: ${Math.ceil(testTime)}ms; fps: ${Math.floor(1000 / testTime)}`;
};
}();
Create the Display cycle animation
const demoAnimation = scrawl.makeRender({
name: "demo-animation",
target: stack,
afterShow: report,
We manually trigger the display shape functionality after the first render cycle completes. This allows all artefacts to settle into a state where we can then update the Element artefact with text and roll values appropriate to the Stack element’s initial shape
afterCreated: () => stack.updateDisplayShape(),
});
console.log(scrawl.library);


Your virtual environment must be active to use thunder.py:
source ../env-tctf/bin/activate
python3 thunder.py create thunder/a4error
Activate the service account given to you. You MUST do this, or the level will not work as intended.
gcloud auth activate-service-account --key-file=start/a4-access.json
In this level, look for a file named "secret.txt," which is owned by "secretuser." Use the given compromised credentials to find it.
---Test the permissions of the given credentials using the test-permissions.py script.
---The credentials have the permission cloudfunctions.functions.list
---List the cloud functions in the project:
gcloud functions list---
Try calling the function using the service account's access token:
curl https://[location]-[project-id].cloudfunctions.net/[function-name] -H "Authorization: Bearer $(gcloud auth print-identity-token)"---
Try reading one of the files by adding "?file=[filename] to the end of the url
---See what happens if you try to read a file that doesn't exist.
---The cloud function throws an error when a non-existent file is queried. Cloud function runtime errors are logged in StackDriver logging.
---Read the cloud function related logs:
gcloud functions logs read---
The function logged the HTTP request that it attempted to make. See if there's anything useful in the request.
---An access token was included in the logged HTTP request in the "Authorization" header. The token can be used to access any API functions that the function's attached service account had permission for.
Example:
GET https://www.googleapis.com/storage/v1/b/a4-bucket-884260860342/o/file3.txt?alt=media Authorization: Bearer ya29.c.EqEBZwepkOFych006VjfVDFAJxSb5ErvGmBsVqq8S83NiJXZ_jaQsZlW0lWTP0q6Hs44ICf6mUkDYhOBG5H15A-lsIB-X9bMA-cJ9cl0mt-TU0q7vZjb0qdSUbYasDSTMBXKNzgkX_S_8ipAWVfg4HXfs_pb1Iid7O_QSxl1FeueTEQ6ns96Z1uRiF2qYQJlTyrWRKO3mPPGE1R9C0Nf9en2iFM---
Check the permissions of the access token using the test-permissions.py script by setting USE_ACCESS_TOKEN to True and ACCESS_TOKEN to the access token
Example:
# If set to true, credentials will be created using ACCESS_TOKEN instead of SERVICE_ACCOUNT_KEY_FILE USE_ACCESS_TOKEN = True # Only one of the following need to be set: SERVICE_ACCOUNT_KEY_FILE = '' ACCESS_TOKEN = 'ya29.c.EqEBZwepkOFych006VjfVDFAJxSb5ErvGmBsVqq8S83NiJXZ_jaQsZlW0lWTP0q6Hs44ICf6mUkDYhOBG5H15A-lsIB-X9bMA-cJ9cl0mt-TU0q7vZjb0qdSUbYasDSTMBXKNzgkX_S_8ipAWVfg4HXfs_pb1Iid7O_QSxl1FeueTEQ6ns96Z1uRiF2qYQJlTyrWRKO3mPPGE1R9C0Nf9en2iFM' # Set the project ID PROJECT_ID = '[project-id]'---
The token has the compute.instances.setMetadata ability, which can be used to add allowed ssh keys to the metadata of instances.
---If you list the instances on the project using the start credentials, you will see there is an instance running. Try to gain access to it.
gcloud compute instances list
gcloud compute instances describe [instance-name]---
Use the instances.setMetadata function of the Compute Engine REST API to set up an ssh key for you to use to login to the instance.
---To generate an SSH key to connect to the instance we are creating, run the following:
ssh-keygen -f ./a4_key -t rsa -b 2048
chmod 400 a4_key
The public key is stored in a4_key.pub
The "fingerprint" that is needed to make the request can be found under "metadata" when running:
gcloud compute instances describe [instance-name]
Make a request calling instances.setMetadata to add your SSH key to the instance with the username "ubuntu" using the cloud function's access token
Example:
curl --request POST \ 'https://www.googleapis.com/compute/v1/projects/gcp-vulnerable/zones/us-west1-b/instances/a4-instance/setMetadata' \ -H 'Authorization: Bearer ya29.c.EqEBaQcnTsriJ_17rOa4mN05JHhC9hfXMp-T10gmdHWkC-xXB-Gfc27tFqgGYr4pGC8-8OeHe6acRjd3AHGBeZOWSEGUrKe9blwZK2bxiKXDoQJoiv7EbAxhdXC_wpfQtA12kmxjDArI0iT8GDJDf5qgYRLlIoJBnFRC2viaenbpsNfqw2ibu98wGp8OEhINDXn2m3Vnx-2tfoP6SHP8ysVBv7Q' \ -H 'Accept: application/json' \ -H 'Content-Type: application/json' \ --data '{ "fingerprint": "9Qs5OzliW7s=", "items": [ { "key": "ssh-keys", "value": "ubuntu:ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDKM2TM8CB7xUGD3/VxDCGOzCW1PCvaINfDChnYb0rJ4WWEuB7dFWc5R4NfycMDRCBGLWVlUWRqP0M4MSQB14SkuxuFtgkBL18mHipLR7LvXOL7YOrurfoi8RgNU0TFEogbTUGkM7XNc1EVma4kJ7vs8sBLukiZT0gwBms1Zi0s3Xen8lwTEDPvD6XJtoA+RT0zsVCDPalWv4SqfOxuKaY1SOqhqa4DQaEvDmIGZzZpbKcS82hEQGreNMAodWDind2nTdOMbS1gbHjxcZVZkWKssi9R2r2eFpSrrmaa98uo+5/sK0eoqqJNS1Ua7L8W1Dj1Mp0ucYW53yzexk8uCl+H ubuntu" } ] }'
SSH into the instance:
ssh -i a4_key ubuntu@[EXTERNAL-IP]---
Check the directories of the other users
cd .. ls---
The secret is stored in the home file of the user "secretuser"
cd ~/../secretuser cat secret.txt---
Level writeup will be available soon


Application is mobile device management (MDM) compatible.
Symphony Communication Services, a Palo Alto, Calif.-based messaging startup, announced its enterprise-ready mobile app for Apple iPhone is now available for download.
Waters Technology
07 June 2016
symphony-article
David Gurle, Symphony CEO, says his platform now has close to 100,000 users and over 70 firms on it.
Following partnership with FactSet, David Gurle discusses how the firm plans on continuing to grow, and its plans for unbundling the terminal.
Waters Technology
11 July 2016
symphony-articleThis is a simple demo app.


Devin Townsend
The Mad Scientist of Metal
1972: Born in British Columbia, Canada
1993: Records vocals for Steve Vai's Sex and Religion, embarks on a world tour of the album
1994: Receives a five-album contract offer from Century Media, recruits musicians to form industrial death metal band Strapping Young Lad
1997: Releases City with Strapping Young Lad and Ocean Machine: Biomech as a solo album, the former going on to be regarded as a groundbreaking industrial metal album
1998: Records and releases Infinity after being diagnosed with bipolar disorder
2002: Forms The Devin Townsend Band and begins splitting his time equally between this band and Strapping Young Lad
2007: Disbands both Strapping Young Lad and The Devin Townsend Band, gives up drinking and drugs. Later in the year, he releases a space rock opera entilted Ziltoid the Omniscient, highlighting his characteristic blend of humour and heavy music
2009: Announces a new venture called The Devin Townsend Project with four planned albums, and later in the year releases the first two: Ki and Addicted
2011: Releases the latter two albums of The Devin Townsend Project: Deconstruction and Ghost
2014: Records Casualaties of Cool, an ambient country-influenced album featuring Canadian musician Ché Aimee Dorval
For more information, check out Devin Townsend's Wikipedia page.


The CheckBox Tree Drag-n-Drop
A basic CheckBox Tree and cbtree/store Hierarchy store demonstrating Drag-n-Drop features.


Enter the private posting key (Starts with 5). Attention: it is not transmitted anywhere; all operations are performed on your computer, in your browser.
Save login and posting key
Whom to reward:
Energy percent which you are ready to spend at an the award. Energy regenerates per day for 20%:
The amount of the award. If you fill this field, it will have a higher priority than the percentage of energy:
Custom operation number sent by the user to whom the award is intended (in principle, you can specify any number, for example, the news id published by the user in the database of your site):):
Note (memo):
Beneficiary login:
Percent
Add
Redirect link after successful award:


A variable is a named value.
To update a value
To reuse code
10 - the last assignment
2
Oct 5th
10/5
It depends on the data type.
No. But it's a trick question.
-a
a
a + b
b
a - b
a * b
a / b
a % b
What is 11 % 3?
11 % 3
Is the number is even?
How do I check if the number is odd?
true


Creates an instance of pptx-automizer
.
Add a slide from one of the imported templates by slide number.
Name or alias of the template; must have been loaded with Automizer.load()
Number of slide in template presentation
Executed after slide was added. The newly created slide will be passed to the callback as first argument.
Instance of Automizer
Applies path prefix to given location string.
path and/or filename
location
Determines whether template is root or default template.
pres template
Load a template pptx file.
Filename or path to the template. Will be prefixed with 'templateDir'
Optional: A short name for the template. If skipped, the template will be named by its location.
Instance of Automizer
Load a pptx file and set it as root template.
Filename or path to the template. Will be prefixed with 'templateDir'
Instance of Automizer
Loads a pptx file either as a root template as a template file. A name can be specified to give templates an alias.
template
Write all imports and modifications to a file.
Filename or path for the file. Will be prefixed with 'outputDir'
summary object.
Generated using TypeDoc
Automizer
The basic class for
pptx-automizer
package. This class will be exported asAutomizer
byindex.ts
.


AC Inc.
Mussels and Musings
Politics
May 7, 2017
A Step Outside the Political Box
July 23, 2016
Innovation in the Public Sector
July 10, 2015
Tunisia After ISIS
February 10, 2014
US Aid to Lebanon, a Delicate Balance
March 4, 2013
The Outlook for Continuing Stability in the South China Sea
Research
September 19, 2013
Propagation of Orbital Angular Momentum Carrying Beams Through a Perturbing Medium
April 1, 2013
A Very Low-Cost Solar Concentrator Using Simple Surfaces
Finance
October 22, 2015
Weakness In Radiant Logistics' Acquisitions Masked By Fair Value Of Contingent Consideration
October 6, 2014
Palo Alto Networks 1-Year Forecast
October 1, 2014
Imperva: Cyber-Security Long Play
Screenplay
November 21, 2014
Swindoll
Fiction
October 5, 2016
Live a Little
July 23, 2016
Until He Wasn't


bxSlider for the Blog Post
december 25, 2019
CategoryName
The title of the most interesting and popular blog post
december 24, 2019
CategoryName
Lorem ipsum dolor sit amet, consectetuer adipiscing elit
december 23, 2019
CategoryName
Vestibulum ante ipsum primis in faucibus orci luctus


THE FLOWER OF MY SECRET (LA FLOR DE MI SECRETO) A film review by James Berardinelli Copyright 1996 James Berardinelli
RATING (0 TO 10): 6.0 Alternative Scale: **1/2 out of ****
Spain/France, 1995 U.S. Release Date: beginning 3/96 (limited) Running Length: 1:42 MPAA Classification: R (Profanity, sex, mature themes) Theatrical Aspect Ratio: 1.66:1
Cast: Marisa Paredes, Imanol Arias, Juan Enchanove, Chus Lampreave, Carmen Elias, Rossy De Palma, Manuela Vargas, Joaquin Cortes Director: Pedro Almodovar Producer: Augustin Almodovar Screenplay: Pedro Almodovar Cinematography: Affoso Beato Music: Alberto Iglesias U.S. Distributor: Sony Pictures Classics In Spanish with subtitles
The words "A Film by Almodovar" conjure up images of the bizarre, the kinky, and the unapologetically unconventional. Ever since his 1980 debut, PEPI, LUCI, BOM, Almodovar has been lauded as Spain's golden boy film maker -- a director who will take any chance to obtain a desired result. At times, he has been wildly successful (as in WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN and TIE ME UP! TIE ME DOWN!). On other occasions, things haven't gone nearly as well (KIKA). But, through it all, Almodovar has never come close to conventionality -- until THE FLOWER OF MY SECRET, that is.
First and foremost, barring the offbeat opening scene where two deadpan doctors explain to a woman that her son is brain-dead (we later learn that this is part of a training film, not an actual experience), THE FLOWER OF MY SECRET doesn't seem like Almodovar. He treats his characters with an unexpected sensitivity, and his vicious, often-ribald sense of humor has been muted to the point of insignificance. For the most part, THE FLOWER OF MY SECRET takes itself too seriously, which might have been okay if the primary story wasn't an example of dreary melodrama.
Leo Macias (Marisa Parades) is a lonely author involved in a failing marriage. Although she longs to write novels of substance and meaning, her income derives from popular, formula romances, which she pens under the pseudonym of Amanda Gris. Meanwhile, her husband, Paco (Imanol Arias), has joined the NATO peacekeeping mission in Bosnia to flee the homefront wars that he and his wife regularly engage in. When asked if he thinks there's any chance to save his union with Leo, Paco considers for a moment before replying, "None."
Much of THE FLOWER OF MY SECRET concerns Leo's journey from a lost, frightened dependent to someone who can stand on her own. It's not always an interesting trek, but there are rewards for those who stick with the story. Chief among these is Almodovar's examination of Leo's dual identity. As a romance writer, she is adored by thousands of fans, and her next novel is awaited with breathless anticipation. But, as a "serious" person, she despises Amanda Gris, even going so far as to write a blistering critique of her own work (under a different pseudonym). The Leo/Amanda schism is fascinating, but it's often reduced to a background subplot, and the resolution is dissatisfying.
It's strange seeing an Almodovar film without the bright, energetic presence of Victoria Abril, who has graced his three previous outings. For THE FLOWER OF MY SECRET, the leading actress is another Almodovar regular, Marisa Paredes, who does an excellent job portraying Leo's longing, insecurity, and other neuroses. In addition to Imanol Arias as Paco, Juan Enchanove (as Leo's prospective suitor), Rossy de Palma (as her sister), and Chus Lampreave (as her mother) provide solid support.
While it's a different experience to view an Almodovar movie that respects, and even shows affection for, its female lead, THE FLOWER OF MY SECRET is far from a standout effort. It's bland as often as it is affecting, and presents little that's new or original. This is just another story of a woman grappling for independence while looking for love. THE FLOWER OF MY SECRET shows hints of what a kinder, gentler Almodovar has to offer the motion picture world, but, on the whole, I prefer the flamboyant attitude he previously exhibited.
- James Berardinelli e-mail<EMAIL_ADDRESS>web: http://www.cybernex.net/~berardin
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


《清明》杜牧
清明时节雨纷纷，
路上行人欲断魂。
借问酒家何处有，
牧童遥指杏花村。
The
Mourning
Day
Du
Mu
A
drizzling
rain
falls
like
tears
on
the
Mourning
Day;
The
mourner's
heart
is
going
to
break
on
the
way.
Where
can
a
wineshop
be
found
to
drown
his
sad
hours?
A
cowherd
points
to
a
cot
amid
apricot
flowers.


21 children sent to hospital after complaining of unusual odour from school bus
by The Canadian Press, StaffGATINEAU, Que. -- Twenty-one elementary school students in Gatineau were taken to hospital today after complaining of head, chest and stomach aches following a school bus ride.
Maude Hebert with the Portages-de-l'Outaouais school board says no one showed signs of serious injury and the children were brought to hospital as a preventive measure.
She says when the students arrived at school, they complained they felt ill and reported an unusual smell from the bus.
Hebert says carbon monoxide has been ruled out as a cause, and authorities are investigating whether a problem with the exhaust gas cooler on the bus emitted the foul odour.
Marie-Eve D'Aoust, spokeswoman for the paramedics co-operative that treated the children, says 17 patients were brought to the Gatineau hospital and four were transported to the Hull hospital.
She says 22 other students evaluated by paramedics and poison control workers did not need to be taken to hospital.
This report by The Canadian Press was first published Nov. 15, 2019.


My Longtest
Easy Long Test
This is a paragraph. My name is Sagulo, Ahmad Castro
This is another paragraph. My professor is so very pogi. I have a blue notebook.
This is a picture of my notebook:
When I click on the image of my notebook, I will be redirected to "b.html".
When I am at the b.html and I click on "Back", I will be redirected to "a.html".


Your customized drawing is coming soon.
I'm writing the screenplay that you isnpired. I'll apply insights from Aristotle's "Poetics."
I'll also apply some advice from famous artists.
This story is a divine comedy.
I'll also use some concepts from Theater, Opera and Classical Literature.

Click on any image of the heart below; it's a graphite sketch that I made, and it will take you to places you've inspired!


The 58th annual meeting of the Association for Computational Linguistics is being hosted virtually this week. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford!
List of Accepted Papers
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation
Authors: Weixin Liang, James Zou, Zhou Yu
Contact<EMAIL_ADDRESS>Keywords: dialog, automatic dialog evaluation, user experience
Contextual Embeddings: When Are They Worth It?
Authors: Simran Arora, Avner May, Jian Zhang, Christopher Ré
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: contextual embeddings, pretraining, benefits of context
Enabling Language Models to Fill in the Blanks
Authors: Chris Donahue, Mina Lee, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: natural language generation, infilling, fill in the blanks, language models
ExpBERT: Representation Engineering with Natural Language Explanations
Authors: Shikhar Murty, Pang Wei Koh, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: language explanations, bert, relation extraction, language supervision
Finding Universal Grammatical Relations in Multilingual BERT
Authors: Ethan A. Chi, John Hewitt, Christopher D. Manning
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post
Keywords: analysis, syntax, multilinguality
Is Your Classifier Actually Biased? Measuring Fairness under Uncertainty with Bernstein Bounds
Authors: Kawin Ethayarajh
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: fairness, bias, equal opportunity, ethics, uncertainty
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
Authors: Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: knowledge graphs, hyperbolic embeddings, link prediction
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports
Authors: Yuhao Zhang, Derek Merck, Emily Bao Tsai, Christopher D. Manning, Curtis P. Langlotz
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: nlp, text summarization, reinforcement learning, medicine, radiology report
Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding
Authors: Yun Tang, Jing Huang, Guangtao Wang, Xiaodong He and Bowen Zhou
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: orthogonal transforms, knowledge graph embedding
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models
Authors: Dan Iter , Kelvin Guu , Larry Lansing, Dan Jurafsky
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: discourse coherence, language model pretraining
Robust Encodings: A Framework for Combating Adversarial Typos
Authors: Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: nlp, robustness, adversarial robustness, typos, safe ml
SenseBERT: Driving Some Sense into BERT
Authors: Yoav Levine, Barak Lenz, Or Dagan, Ori Ram, Dan Padnos, Or Sharir, Shai Shalev-Schwarz, Amnon Shashua, Yoav Shoham
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post
Keywords: language models, semantics
Shaping Visual Representations with Language for Few-shot Classification
Authors: Jesse Mu, Percy Liang, Noah Goodman
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: grounding, language supervision, vision, few-shot learning, meta-learning, transfer
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages
Authors: Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, Christopher D. Manning
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: natural language processing, multilingual, data-driven, neural networks
Theoretical Limitations of Self-Attention in Neural Sequence Models
Authors: Michael Hahn
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: theory, transformers, formal languages
Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
Authors: Giovanni Campagna, Agata Foryciarz, Mehrad Moradshahi, and Monica S. Lam
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: dialogue state tracking, multiwoz, zero-shot, data programming, pretraining
We look forward to seeing you at ACL 2020!


I have no idea how to start solving this mission.
You can replace the substrings with the replace(). method
"abcd ababba".replace("ab", "0") == "0cd 00ba"
I need some help to proceed with the mission.
And you can join strings with the join() method.
":".join(["A", "1", "cd"]) == "A:1:cd"
I am gone half way through. Need help!
Join all the given strings, then replace "right" with "left" and return (do not print) the result.
def left_join(phrases: tuple[str]) -> str: join_phrase = ','.join(phrases) result = join_phrase.replace('right','left') return result


The Englewood Communtity Cultural Planning Council for the past several years has held an annual family arts festival at Hamilton Park to celebrate the residents and community at large. The council served to activate and leverage partners such as Columbia College CCAP, Depaul University's University Egan Urban Center, RAge and the Chicago Park District to bring artists , educators, entreprenuers , performers and other resources to the community.
This year the Resident Assosication of Greater Englewood (RAGE) Young Professional Taskforce(YPTF) is partnering with Ec3 to deliver a reimagined Englewood Arts in the Spirit of social change due to this years festival falling on Marcus Garvey's birthday (August 17th) as well as in celebration of Black August


[ 中文 ]
h5control provides an easy way to enable your web app to control your own hardware with digital/analog IO, motors, servos, LED lights, sensors and other electronic gadgets. Now, let's play with h5control step by step.
Need an Arduino MEGA or UNO board.
Download rioc-arduino sketch, open sketch RiocArduino.ino in Arduino IDE and upload the program to the Arduino.
In order to be able to remote reset Arduino, also must use a wire to connect pin 12 to the RESET pin on the Arduino board.
Mac:
Download h5control Service for macOS,
copy app "h5control Service" to your Applications folder and run it.
Windows:
Download h5control Service for windows,
copy folder "h5control Service" to your disk and run "h5connect.exe" or "h5connect-console.exe" in the folder.
Now, connect your h5control-ready Arduino to your computer USB port, and test in web , where you can also assign an unit ID to your Arduino .
h5control Basics
1.1 Getting Started with h5control
1.2 Playing with Web Inspector
General IO Controls
2.1 Digital Out
2.2 Digital In
2.3 Analog Out
2.4 Analog In
2.5 UART Serial
Motion Controls
3.1 Motor
3.2 Stepper
3.3 Rudder Servo
Sensors
4.1 Encoder
4.2 Ultrasonic Ranger
4.3 Thermometer
Sound and Lights
5.1 Tone Player
5.2 LED Strip
Infrared Communication
6.1 IR Receiver
6.2 IR Transmitter
System Programming
7.1 System Objects
7.2 Raw Message
For more information about the developer and all source code of h5control, please visit
robinz.org and
github/robinz-labs .


--- layout: post title: Dynamic generated content and the back button categories: [] tags: [] status: draft type: post published: false meta: {} author: ---
The problem: The state of dynamically generated content is not maintained through the browser history.
The example in my case was that we had a form that contained elements that were programatically added.
The user would make some changes and submit the form and continue on to the next screen.
If the user hit the back button, the state of those dynamic elements reverted to their initial values.


Admin panel
hi master manafi
products
services
categories
other
click me
click for calculation
testing object
function with parameters
last try
ajax uses
mockaaa
longwey
slama
sharkilar
blade runner
hala madrid


SIGN IN
ACCOUNT NO.
:
PASSWORD
:
Remember Me
Create an Account
Update your personal details
contact us for any query


We have styled all Bootstrap elements just as you want!
Provide contextual feedback messages for typical user actions with the handful of available and flexible alert messages. Wrap any text and an optional dismiss button in .alert
and one of the four contextual classes (e.g., .alert-success
) for basic alert messages.
Alerts don't have default classes, only base and modifier classes. A default gray alert doesn't make too much sense, so you're required to specify a type via contextual class. Choose from success, info, warning, or danger.
Build on any alert by adding an optional .alert-dismissible
and close button.
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Use the .alert-link
utility class to quickly provide matching colored links within any alert.


Baby Driver Full Movie Online
Watch, Download and Stream Baby Driver Full Movie Online 2017 Free in HD Quality In any Internet Connected Devices.
https://fullmoviesells.com
Baby Driver
Talented getaway driver Baby (Ansel Elgort) relies on the beat of his personal soundtrack to be the best in the game. After meeting the woman (Lily James) of his dreams, he sees a chance to ditch his shady lifestyle and make a clean break. Coerced into working for a crime boss (Kevin Spacey), Baby must face the music as a doomed heist threatens his life, love and freedom.
Release date: June 28, 2017 (USA)
Director: Edgar Wright
Budget: 34 million USD
Screenplay: Edgar Wright
Music composed by: Steven Price
Baby Driver is one wild ride
So yeah, Baby Driver is pretty much a musical; La La Land without the singing and dancing and without Ryan Gosling, itís Drive without the brutal head-bashing in the elevator and without.. erm.. Ryan Gosling, itís Fast and Furious without the need for a frontal lobotomy and without Vin Diesel and itís Heat without.. ummm.. well basically itís Heat.


Our servers are under maintenance. We are doing our best to come back faster than the "Speed of Light".Site will be available again on 20 April 2017, at 10 pm.
Please feel free to mail us for the latest updates.
<EMAIL_ADDRESS>Developer Team


|
gtsam
4.1.0
gtsam
|
A Gaussian factor using the canonical parameters (information form)
HessianFactor implements a general quadratic factor of the form
\[ E(x) = 0.5 x^T G x - x^T g + 0.5 f \]
that stores the matrix \( G \), the vector \( g \), and the constant term \( f \).
When \( G \) is positive semidefinite, this factor represents a Gaussian, in which case \( G \) is the information matrix \( \Lambda \), \( g \) is the information vector \( \eta \), and \( f \) is the residual sum-square-error at the mean, when \( x = \mu \).
Indeed, the negative log-likelihood of a Gaussian is (up to a constant) \( E(x) = 0.5(x-\mu)^T P^{-1} (x-\mu) \) with \( \mu \) the mean and \( P \) the covariance matrix. Expanding the product we get
\[ E(x) = 0.5 x^T P^{-1} x - x^T P^{-1} \mu + 0.5 \mu^T P^{-1} \mu \]
We define the Information matrix (or Hessian) \( \Lambda = P^{-1} \) and the information vector \( \eta = P^{-1} \mu = \Lambda \mu \) to arrive at the canonical form of the Gaussian:
\[ E(x) = 0.5 x^T \Lambda x - x^T \eta + 0.5 \mu^T \Lambda \mu \]
This factor is one of the factors that can be in a GaussianFactorGraph. It may be returned from NonlinearFactor::linearize(), but is also used internally to store the Hessian during Cholesky elimination.
This can represent a quadratic factor with characteristics that cannot be represented using a JacobianFactor (which has the form \( E(x) = \Vert Ax - b \Vert^2 \) and stores the Jacobian \( A \) and error vector \( b \), i.e. is a sum-of-squares factor). For example, a HessianFactor need not be positive semidefinite, it can be indefinite or even negative semidefinite.
If a HessianFactor is indefinite or negative semi-definite, then in order for solving the linear system to be possible, the Hessian of the full system must be positive definite (i.e. when all small Hessians are combined, the result must be positive definite). If this is not the case, an error will occur during elimination.
This class stores G, g, and f as an augmented matrix HessianFactor::matrix_. The upper-left n x n blocks of HessianFactor::matrix_ store the upper-right triangle of G, the upper-right-most column of length n of HessianFactor::matrix_ stores g, and the lower-right entry of HessianFactor::matrix_ stores f, i.e.
Blocks can be accessed as follows:
Public Member Functions | |
| HessianFactor () | |
| default constructor for I/O | |
| HessianFactor (Key j, const Matrix &G, const Vector &g, double f) | |
| Construct a unary factor. More... | |
| HessianFactor (Key j, const Vector &mu, const Matrix &Sigma) | |
| Construct a unary factor, given a mean and covariance matrix. More... | |
| HessianFactor (Key j1, Key j2, const Matrix &G11, const Matrix &G12, const Vector &g1, const Matrix &G22, const Vector &g2, double f) | |
| Construct a binary factor. More... | |
| HessianFactor (Key j1, Key j2, Key j3, const Matrix &G11, const Matrix &G12, const Matrix &G13, const Vector &g1, const Matrix &G22, const Matrix &G23, const Vector &g2, const Matrix &G33, const Vector &g3, double f) | |
| Construct a ternary factor. More... | |
| HessianFactor (const KeyVector &js, const std::vector< Matrix > &Gs, const std::vector< Vector > &gs, double f) | |
| Construct an n-way factor. More... | |
| template<typename KEYS > | |
| HessianFactor (const KEYS &keys, const SymmetricBlockMatrix &augmentedInformation) | |
| Constructor with an arbitrary number of keys and with the augmented information matrix specified as a block matrix. | |
| HessianFactor (const JacobianFactor &cg) | |
| Construct from a JacobianFactor (or from a GaussianConditional since it derives from it) | |
| HessianFactor (const GaussianFactor &factor) | |
| Attempt to construct from any GaussianFactor - currently supports JacobianFactor, HessianFactor, GaussianConditional, or any derived classes. | |
| HessianFactor (const GaussianFactorGraph &factors, const Scatter &scatter) | |
| Combine a set of factors into a single dense HessianFactor. | |
| HessianFactor (const GaussianFactorGraph &factors) | |
| Combine a set of factors into a single dense HessianFactor. | |
| virtual | ~HessianFactor () |
| Destructor. | |
| GaussianFactor::shared_ptr | clone () const override |
| Clone this HessianFactor. | |
| void | print (const std::string &s="", const KeyFormatter &formatter=DefaultKeyFormatter) const override |
| Print the factor for debugging and testing (implementing Testable) | |
| bool | equals (const GaussianFactor &lf, double tol=1e-9) const override |
| Compare to another factor for testing (implementing Testable) | |
| double | error (const VectorValues &c) const override |
| Evaluate the factor error f(x). More... | |
| DenseIndex | getDim (const_iterator variable) const override |
| Return the dimension of the variable pointed to by the given key iterator todo: Remove this in favor of keeping track of dimensions with variables? More... | |
| size_t | rows () const |
| Return the number of columns and rows of the Hessian matrix, including the information vector. | |
| GaussianFactor::shared_ptr | negate () const override |
| Construct the corresponding anti-factor to negate information stored stored in this factor. More... | |
| bool | empty () const override |
| Check if the factor is empty. More... | |
| double | constantTerm () const |
| Return the constant term \( f \) as described above. More... | |
| double & | constantTerm () |
| Return the constant term \( f \) as described above. More... | |
| SymmetricBlockMatrix::constBlock | linearTerm (const_iterator j) const |
| Return the part of linear term \( g \) as described above corresponding to the requested variable. More... | |
| SymmetricBlockMatrix::constBlock | linearTerm () const |
| Return the complete linear term \( g \) as described above. More... | |
| SymmetricBlockMatrix::Block | linearTerm () |
| Return the complete linear term \( g \) as described above. More... | |
| const SymmetricBlockMatrix & | info () const |
| Return underlying information matrix. | |
| SymmetricBlockMatrix & | info () |
| Return non-const information matrix. More... | |
| Matrix | augmentedInformation () const override |
| Return the augmented information matrix represented by this GaussianFactor. More... | |
| Eigen::SelfAdjointView< SymmetricBlockMatrix::constBlock, Eigen::Upper > | informationView () const |
| Return self-adjoint view onto the information matrix (NOT augmented). | |
| Matrix | information () const override |
| Return the non-augmented information matrix represented by this GaussianFactor. | |
| void | hessianDiagonalAdd (VectorValues &d) const override |
| Add the current diagonal to a VectorValues instance. | |
| void | hessianDiagonal (double *d) const override |
| Raw memory access version of hessianDiagonal. | |
| std::map< Key, Matrix > | hessianBlockDiagonal () const override |
| Return the block diagonal of the Hessian for this factor. | |
| std::pair< Matrix, Vector > | jacobian () const override |
| Return (dense) matrix associated with factor. | |
| Matrix | augmentedJacobian () const override |
| Return (dense) matrix associated with factor The returned system is an augmented matrix: [A b]. More... | |
| void | updateHessian (const KeyVector &keys, SymmetricBlockMatrix *info) const override |
| Update an information matrix by adding the information corresponding to this factor (used internally during elimination). More... | |
| void | updateHessian (HessianFactor *other) const |
| Update another Hessian factor. More... | |
| void | multiplyHessianAdd (double alpha, const VectorValues &x, VectorValues &y) const override |
| y += alpha * A'*A*x | |
| VectorValues | gradientAtZero () const override |
| eta for Hessian | |
| void | gradientAtZero (double *d) const override |
| Raw memory access version of gradientAtZero. | |
| Vector | gradient (Key key, const VectorValues &x) const override |
| Compute the gradient at a key: \grad f(x_i) = \sum_j G_ij*x_j - g_i. | |
| boost::shared_ptr< GaussianConditional > | eliminateCholesky (const Ordering &keys) |
| In-place elimination that returns a conditional on (ordered) keys specified, and leaves this factor to be on the remaining keys (separator) only. More... | |
| VectorValues | solve () |
| Solve the system A'*A delta = A'*b in-place, return delta as VectorValues. | |
| Public Member Functions inherited from gtsam::GaussianFactor | |
| GaussianFactor () | |
| Default constructor creates empty factor. | |
| template<typename CONTAINER > | |
| GaussianFactor (const CONTAINER &keys) | |
| Construct from container of keys. More... | |
| virtual | ~GaussianFactor () |
| Destructor. | |
| VectorValues | hessianDiagonal () const |
| Return the diagonal of the Hessian for this factor. | |
| Public Member Functions inherited from gtsam::Factor | |
| Key | front () const |
| First key. | |
| Key | back () const |
| Last key. | |
| const_iterator | find (Key key) const |
| find | |
| const KeyVector & | keys () const |
| Access the factor's involved variable keys. | |
| const_iterator | begin () const |
| Iterator at beginning of involved variable keys. | |
| const_iterator | end () const |
| Iterator at end of involved variable keys. | |
| size_t | size () const |
| void | print (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const |
| print | |
| void | printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const |
| print only keys | |
| KeyVector & | keys () |
| iterator | begin () |
| Iterator at beginning of involved variable keys. | |
| iterator | end () |
| Iterator at end of involved variable keys. | |
Public Types | |
| typedef GaussianFactor | Base |
| Typedef to base class. | |
| typedef HessianFactor | This |
| Typedef to this class. | |
| typedef boost::shared_ptr< This > | shared_ptr |
| A shared_ptr to this class. | |
| typedef SymmetricBlockMatrix::Block | Block |
| A block from the Hessian matrix. | |
| typedef SymmetricBlockMatrix::constBlock | constBlock |
| A block from the Hessian matrix (const version) | |
| Public Types inherited from gtsam::GaussianFactor | |
| typedef GaussianFactor | This |
| This class. | |
| typedef boost::shared_ptr< This > | shared_ptr |
| shared_ptr to this class | |
| typedef Factor | Base |
| Our base class. | |
| Public Types inherited from gtsam::Factor | |
| typedef KeyVector::iterator | iterator |
| Iterator over keys. | |
| typedef KeyVector::const_iterator | const_iterator |
| Const iterator over keys. | |
Protected Attributes | |
| SymmetricBlockMatrix | info_ |
| The full augmented information matrix, s.t. the quadratic error is 0.5*[x -1]'H[x -1]. | |
| Protected Attributes inherited from gtsam::Factor | |
| KeyVector | keys_ |
| The keys involved in this factor. | |
Friends | |
| class | NonlinearFactorGraph |
| class | NonlinearClusterTree |
| class | boost::serialization::access |
| Serialization function. | |
Additional Inherited Members | |
| Static Public Member Functions inherited from gtsam::GaussianFactor | |
| template<typename CONTAINER > | |
| static DenseIndex | Slot (const CONTAINER &keys, Key key) |
| Protected Member Functions inherited from gtsam::Factor | |
| Factor () | |
| Default constructor for I/O. | |
| template<typename CONTAINER > | |
| Factor (const CONTAINER &keys) | |
| Construct factor from container of keys. More... | |
| template<typename ITERATOR > | |
| Factor (ITERATOR first, ITERATOR last) | |
| Construct factor from iterator keys. More... | |
| bool | equals (const This &other, double tol=1e-9) const |
| check equality | |
| Static Protected Member Functions inherited from gtsam::Factor | |
| template<typename CONTAINER > | |
| static Factor | FromKeys (const CONTAINER &keys) |
| Construct factor from container of keys. More... | |
| template<typename ITERATOR > | |
| static Factor | FromIterators (ITERATOR first, ITERATOR last) |
| Construct factor from iterator keys. More... | |
| gtsam::HessianFactor::HessianFactor | ( | Key | j, |
| const Matrix & | G, | ||
| const Vector & | g, | ||
| double | f | ||
| ) |
Construct a unary factor.
G is the quadratic term (Hessian matrix), g the linear term (a vector), and f the constant term. The quadratic error is: 0.5*(f - 2*x'*g + x'*G*x)
| gtsam::HessianFactor::HessianFactor | ( | Key | j, |
| const Vector & | mu, | ||
| const Matrix & | Sigma | ||
| ) |
Construct a unary factor, given a mean and covariance matrix.
error is 0.5*(x-mu)'inv(Sigma)(x-mu)
| gtsam::HessianFactor::HessianFactor | ( | Key | j1, |
| Key | j2, | ||
| const Matrix & | G11, | ||
| const Matrix & | G12, | ||
| const Vector & | g1, | ||
| const Matrix & | G22, | ||
| const Vector & | g2, | ||
| double | f | ||
| ) |
Construct a binary factor.
Gxx are the upper-triangle blocks of the quadratic term (the Hessian matrix), gx the pieces of the linear vector term, and f the constant term. JacobianFactor error is
\[ 0.5* (Ax-b)' M (Ax-b) = 0.5*x'A'MAx - x'A'Mb + 0.5*b'Mb \]
HessianFactor error is
\[ 0.5*(x'Gx - 2x'g + f) = 0.5*x'Gx - x'*g + 0.5*f \]
So, with \( A = [A1 A2] \) and \( G=A*'M*A = [A1';A2']*M*[A1 A2] \) we have
| gtsam::HessianFactor::HessianFactor | ( | Key | j1, |
| Key | j2, | ||
| Key | j3, | ||
| const Matrix & | G11, | ||
| const Matrix & | G12, | ||
| const Matrix & | G13, | ||
| const Vector & | g1, | ||
| const Matrix & | G22, | ||
| const Matrix & | G23, | ||
| const Vector & | g2, | ||
| const Matrix & | G33, | ||
| const Vector & | g3, | ||
| double | f | ||
| ) |
Construct a ternary factor.
Gxx are the upper-triangle blocks of the quadratic term (the Hessian matrix), gx the pieces of the linear vector term, and f the constant term.
| gtsam::HessianFactor::HessianFactor | ( | const KeyVector & | js, |
| const std::vector< Matrix > & | Gs, | ||
| const std::vector< Vector > & | gs, | ||
| double | f | ||
| ) |
Construct an n-way factor.
Gs contains the upper-triangle blocks of the quadratic term (the Hessian matrix) provided in row-order, gs the pieces of the linear vector term, and f the constant term.
|
overridevirtual |
Return the augmented information matrix represented by this GaussianFactor.
The augmented information matrix contains the information matrix with an additional column holding the information vector, and an additional row holding the transpose of the information vector. The lower-right entry contains the constant error term (when \( \delta x = 0 \)). The augmented information matrix is described in more detail in HessianFactor, which in fact stores an augmented information matrix.
For HessianFactor, this is the same as info() except that this function returns a complete symmetric matrix whereas info() returns a matrix where only the upper triangle is valid, but should be interpreted as symmetric. This is because info() returns only a reference to the internal representation of the augmented information matrix, which stores only the upper triangle.
Implements gtsam::GaussianFactor.
|
overridevirtual |
Return (dense) matrix associated with factor The returned system is an augmented matrix: [A b].
| set | weight to use whitening to bake in weights |
Implements gtsam::GaussianFactor.
|
inline |
Return the constant term \( f \) as described above.
|
inline |
Return the constant term \( f \) as described above.
| boost::shared_ptr< GaussianConditional > gtsam::HessianFactor::eliminateCholesky | ( | const Ordering & | keys | ) |
In-place elimination that returns a conditional on (ordered) keys specified, and leaves this factor to be on the remaining keys (separator) only.
Does dense partial Cholesky.
|
inlineoverridevirtual |
|
overridevirtual |
Evaluate the factor error f(x).
returns 0.5*[x -1]'H[x -1] (also see constructor documentation)
Implements gtsam::GaussianFactor.
|
inlineoverridevirtual |
Return the dimension of the variable pointed to by the given key iterator todo: Remove this in favor of keeping track of dimensions with variables?
| variable | An iterator pointing to the slot in this factor. You can use, for example, begin() + 2 to get the 3rd variable in this factor. |
Implements gtsam::GaussianFactor.
|
inline |
Return non-const information matrix.
TODO(gareth): Review the sanity of having non-const access to this.
|
inline |
Return the complete linear term \( g \) as described above.
|
inline |
Return the complete linear term \( g \) as described above.
|
inline |
Return the part of linear term \( g \) as described above corresponding to the requested variable.
| j | Which block row to get, as an iterator pointing to the slot in this factor. You can use, for example, begin() + 2 to get the 3rd variable in this factor. |
|
overridevirtual |
Construct the corresponding anti-factor to negate information stored stored in this factor.
Implements gtsam::GaussianFactor.
|
overridevirtual |
Update an information matrix by adding the information corresponding to this factor (used internally during elimination).
| keys | THe ordered vector of keys for the information matrix to be updated |
| info | The information matrix to be updated |
Implements gtsam::GaussianFactor.
|
inline |
Update another Hessian factor.
| other | the HessianFactor to be updated |


Interests
An abridged list of things I want to learn more about and related links to
interesting articles, essays, and studies on those topics. You can find a more
long-form set of links here.
- Urban planning and transporation
- Coordination problems
- Digital visualization tools (and generally any tools that help people think and
create)
- Bret Victor's
Ladder of Abstraction
- Michael Nielsen's call to
incorporate emotional impact, change habits of mind, and reduce the burden on
people's short-term working memory
- Steve Jobs' description of computers as "bicycles for the mind" doesn't go far
enough
- Ethics and Meta Ethics
- Deontological
- Consequentialism, especially utilitarianism
- Vegetarianism and veganism
- Effective Altruism
- What's your utility function? Really! Let me know!
- Health, nutrition, and fitness
- Synthetic biology
- Bio fuels
- Transhumanism and the idea that humanity is a "work in progress"
- Geo-engineering
- Linguistics
- The history of language
- Natural language processing (NLP)
- Psychology
- Rationality and biases
- Group and organizational
- Emergent phenomena
- Artificial intelligence
- Economics (as traditionally applied to the economy as well as all other facets of
social interaction)
- Cryptography, stenography, and information theory


Quick primer on using Git¶
On using Mapbender branches and Git, please look at the Contributing Guide for Developers:
https://github.com/mapbender/mapbender-starter/blob/release/3.0.6/CONTRIBUTING.md#feature-branch
On using Mapbender branches and Git, please look at the Contributing Guide for Developers:
https://github.com/mapbender/mapbender-starter/blob/release/3.0.6/CONTRIBUTING.md#feature-branch


pyshgp.gp.individual module¶
The individual
module defines an Individaul in an evolutionary population.
Individuals are made up of Genomes, which are the linear Push program representations which can be manipulated by seach algorithms.
-
class
pyshgp.gp.individual.
Individual
(genome: pyshgp.gp.genome.Genome = <class 'pyshgp.gp.genome.Genome'>)[source]¶ Bases:
object
An individual in an evolutionary population.
-
error_vector
¶ An array of error values produced by evaluating the Individual’s program.
Type: np.array
-
total_error
¶ The sum of all error values in the Individaul’s error_vector.
Type: float
-
error_vector_bytes
¶ Hashable Byte representation of the individual’s error vector.
-
error_vector
Numpy array of numeric error values.
-
error_vector_bytes
Hashable Byte representation of the individual’s error vector.
-
genome
Plush Genome of individual.
-
program
Push program of individual. Taken from Plush genome.
-
total_error
Numeric sum of the error vector.
-


Gear Check
Fitness gifts that keep on giving
Give a gift the runners in your life will love.
If you're searching for the perfect gifts for the health and fitness-minded people on your shopping list, we have some suggestions. Look for these sure-to-please options, which range in cost from $10 to $1,500.
Personal trainer
Help your runner fine-tune his or her exercise regimen and goals. Consider six sessions with a personal trainer or sports pro.
Workout clothes
From stylish name brands to bare bones, for rugged active wear, look to a sporting goods store for a large selection.
Heart-rate monitor
This is a great gift for runners who are into precision timing and performance training. You can choose from a wide variety of styles and functions.
Reflective vest, gloves, and belt
This is must-have safety gear for anyone who exercises outdoors at dawn or dusk, regardless of his or her level of fitness. Styles are available to fit every type of climate and condition.
Snow and ice sneaker cleats
Cleat styles range from simple designs that strap on over existing running shoes to specialty sneakers with spikes embedded in the soles.
Fleece vests or jackets
Fleece is an essential layer when dressing for outdoor exercise. Warm and versatile, front-zipped fleece jackets and vests are practical year-round.
Fanny packs
Packs with large inner compartments, zippered outside pockets, and places to hold water bottles are the most useful. Padded back panels and quick-release waistbands are helpful features.
Balance balls and wobble boards
This equipment is an excellent addition to any runner's training program. Be sure to read The benefits of balance training.


Next: Valuator reference counting, Previous: Maintaining the stack, Up: Value methods [Contents][Index]
On success, does the following:
As long as a parent tree iterator is
paused
marpa_t_next()
will not succeed,
and therefore the parent tree iterator cannot move on
to a new parse tree.
Many valuators can share the same parent parse tree.
A tree iterator is “unpaused” when
all of the valuators of that tree iterator are destroyed.
Return value:
On success, the newly created valuator.
On hard failure, NULL
.


JavaScript is disabled on your browser.
Overview
Package
Class
Use
Tree
Deprecated
Index
Help
Prev Package
Next Package
Frames
No Frames
All Classes
Package txml.interpreter.command
Contains commands class, commands implement instructions from package txml.parser.
See:
Description
Interface Summary
Interface
Description
Command
Class Summary
Class
Description
CommandDeclareOptionConnection
CommandDeclareOptionSort
CommandDeclareOptionTimeFormat
CommandDeinitSchema
CommandDeleteInDocument
CommandEraseTXmlNodes
CommandFilterContains
CommandFilterEq
CommandFilterFollows
CommandFilterGe
CommandFilterIn
CommandFilterLe
CommandFilterLess
CommandFilterLMeets
CommandFilterMore
CommandFilterNeq
CommandFilterOverlaps
CommandFilterPosition
CommandFilterPrecedes
CommandFilterRMeets
CommandGetDirectStep
CommandGetUndirectStep
CommandGetValues
CommandGoBackToStartPaths
CommandGoto
CommandGotoIfNoNext
CommandCheckSort
CommandInitSchema
CommandInsertIntoDocument
CommandIteratorInit
CommandIteratorNext
CommandLabel
CommandNewList
CommandParentList
CommandRemoveDuplicates
CommandReturnList
CommandReturnSnapshot
CommandSaveStartPaths
CommandSetParentInDocument
CommandSetTNodeListInCycle
CommandStoreDocument
Package txml.interpreter.command Description
Contains commands class, commands implement instructions from package txml.parser. Only for inner use TXml library.
Overview
Package
Class
Use
Tree
Deprecated
Index
Help
Prev Package
Next Package
Frames
No Frames
All Classes
Copyright © 2016. All rights reserved.


No Controls? Since the very early ASP.NET MVC previews, the most common argument I’ve heard against using the framework is the lack of user controls. In my opinion, this is a mixed blessing, however, for some, this is a show stopper. What can you do to provide a rich user interface with the MVC framework, while not reinventing the wheel?
jQuery Now you could go ahead and program a full fledged data grid or WYSIWYG editor, however, unless you have a bit of time to spare this is not the ideal solution. As most may realize, jQuery fits very nicely to fill in the gaps left by the absence of user controls. For the most part, the controls are not going to let you just drag-and-drop, type in a dataset and profit but a lot of the pain is kept to a minimum.
Examples Ingrid If you’re looking for a data grid there are a number of options available pictured above is Ingrid. Flexigrid is another good one that people have used with the MVC framework, however, their site appears to be down at the moment. Treeviews are available
Check out the jQuery plugin database.
Getting Started So, if you’ve decided you want to look more into using jQuery plugins – a couple of tips that may make the transition a little easier:
- Obviously, familiarize yourself with jQuery. Some of the plugins will work with almost 0 configuration but it’s much better to actually know what’s going on. View more info on getting started with jQuery
- The JsonResult is your friend – learn it well.
- Read up on what people using different languages are doing. I’m not saying that you should necessarily go out and learn Rails or CakePHP/CodeIgniter (although, it is beneficial). but at least look at the techniques that programmers from that realm of things are doing – see how they are implementing their controls.
What tips do you have for creating robust user interfaces with the MVC framework?


In this post, I would like to share how to deploy tensorflow lite model into android application. This post concentrate more on deployment. For training procedures, refer to repo. And all the android code is available on repo.
Fritz Androide SDK
Fritz is a platform that allows you to create ML features in your mobile applications with ease. Fritz repo
Set up Fritz account and initialize the SDK
First we need a Fritz account to upload the model and manage our project. Sign up a Fritz account and create a project. Then add an android application. Follow the instructions:
Register your app
Follow the instructions provided by Fritz.
Add the Fritz SDK
Install Fritz Core via Gradle
- In your root-level Gradle file (
build.gradle
), include the Maven repository for Fritz.
allprojects {
repositories {
maven { url "https://raw.github.com/fritzlabs/fritz-repository/master" }
}
}
- In your app-level Gradle file (
app/build.gradle
), add the dependency for the core SDK.
dependencies {
implementation 'ai.fritz:core:3+'
}
Edit your AndroidManifest.xml
- Register the FritzCustomModelService in your AndroidManifest.
<manifest xmlns:android="http://schemas.android.com/apk/res/android">

<uses-permission android:name="android.permission.INTERNET" />
<application>

<service
android:name="ai.fritz.core.FritzCustomModelService"
android:exported="true"
android:permission="android.permission.BIND_JOB_SERVICE" />
</application>
</manifest>
Initialize Fritz
- Before managing custom models or using Fritz features, initialize the SDK by calling Fritz.configure() with your API Key. This only needs to be done once when the app launches.
Add the following code into MainActivity class. The API key can be seen on dashboard “Project Settings -> Project Apps -> Actions -> show API key”.
public class MainActivity extends AppCompatActivity {
@Override
protected void onCreate(Bundle savedInstanceState) {
// Initialize Fritz
Fritz.configure(this, "API key");
}
}
Add the HairNet model
Upload the tensorflow lite model
In Dashboard, Click “Custom Models” and choose “CREATE NEW MODEL” to upload models. Then click the model and choose “SDK INSTRUCTIONS”, we can see some instructions and information of the model
Model Id: YOUR MODEL ID HERE
Model Version: 1
Model Path: file:///android_asset/converted_model_hairnet.tflite (The path to your model in your Android assets folder)
The instrucitons may be helpful, however, I use a different API for creating predictor. see Create a Segmentation Predictor with a Hair Segmentation model
part.
When running the program, we can see the model’s information in “Custom Models” part.
Add Fritz’s TFLite Library
In your app-level Gradle file (app/build.gradle
),
dependencies {
implementation 'ai.fritz:core:3+'
implementation "ai.fritz:vision:3+"
implementation 'ai.fritz:custom-model-tflite:3+'
}
This can make you include your own tensorflow lite model into your application.
No compress model when build the apk
Under the hood, we use TensorFlow Lite as our mobile machine learning framework. In order to make sure that the model isn’t compressed when the APK is built, we’ll need to add the following code in the same build file under the android
option.
android {
aaptOptions {
noCompress "tflite"
noCompress "lite"
}
}
Create a Segmentation Predictor with a Hair Segmentation model
We can either include the model with the app or load the model when the app runs (recommended to reduce the size of your APK). In my project, I include my model on device.
Create model class
In Dashboard, Click “Custom Models” and choose the uploaded model, click it and then click “SDK Instructions”. You can see a brief instruction and our model ID. The ID is used for marking the specific model so that he Fritz can monitor the model’s performance. Because we include the model on device rather than load the model at running time. I also placed the model on local directory. The model is placed in /app/src/main/assets/converted_model_hairnet.tflite
.
Also, I found that the instructions provided by Fritz did not work well for me. So, I search the documentation and create my own model class.
If we use the Fritz provided model,
// Initialize the model included with the app
SegmentOnDeviceModel onDeviceModel = new HairSegmentationOnDeviceModel();
This line will initialize a HairSegmentationOnDeviceModel
class and convert it to SegmentOnDeviceModel
class. This class will use the pretrained model provided by Fritz. So how can I use my own model?
I searched the API document, and I noticed the inherit structure:
| java.lang.Object |
|---|
| ↳ai.fritz.core.FritzManagedModel |
| ↳ai.fritz.core.FritzOnDeviceModel |
| ↳ai.fritz.vision.imagesegmentation.SegmentOnDeviceModel |
| ↳ai.fritz.fritzvisionhairsegmentationmodel.HairSegmentationOnDeviceModel |
So I can mimic the HairSegmentationOnDeviceModel
and create an new class inherent from ai.fritz.vision.imagesegmentation.SegmentOnDeviceModel
.
The next thing is, I should tell the constructor the information about my model including input/output layer name, and input/output size.
I found that the constructor of SegmentOndeviceModel
looks like this.
SegmentOnDeviceModel(String modelPath, String modelId, int modelVersion, MaskType[] classifications, String inputLayerName, int inputSize, String outputLayerName, int outputSize)
So, my model class looks like this:
The input layer name is “input:0” and the output name is “Sigmoid:0”. The image size is 224 * 224. the output size is the same.
package com.Qian.HairDye;
import ai.fritz.vision.imagesegmentation.MaskType;
import ai.fritz.vision.imagesegmentation.SegmentOnDeviceModel;
public class Train_170CustomModel extends SegmentOnDeviceModel {
private static final String MODEL_PATH = "file:///android_asset/converted_model_hairnet.tflite";
private static final String MODEL_ID = "9c021ee48c3c4d668b1f8a1a01198a71";
private static final int MODEL_VERSION = 1;
private static MaskType[] hair = { MaskType.HAIR };
public Train_170CustomModel() {
super(MODEL_PATH, MODEL_ID, MODEL_VERSION, hair, "input:0", 224, "Sigmoid:0", 224);
}
}
Set up a predictor using own model
In setupPredictor() method in MainActivity class, write these two lines:
SegmentOnDeviceModel onDeviceModel = new Train_170CustomModel();
predictor = FritzVision.ImageSegmentation.getPredictor(onDeviceModel);
In this two lines code, we first initialize a new model and then call the getPredictor
function to get a predictor class. the getPredictor
function looks like this.
public FritzVisionSegmentPredictor getPredictor (SegmentOnDeviceModel onDeviceModel, FritzVisionSegmentPredictorOptions options)
so by calling this function, we will get a FritzVisionSegmentPredictor
object. The input parameter is our model object.
The next question is what does this FritzVisionSegmentPredictor
class(the predict
) do? I look at the class definition:
package ai.fritz.vision.imagesegmentation;
/**
* The predictor for image segmentation models.
*/
public class FritzVisionSegmentPredictor extends FritzVisionSegmentTFLPredictor {
public FritzVisionSegmentPredictor(SegmentOnDeviceModel segmentOnDeviceModel, FritzVisionSegmentPredictorOptions options) {
super(segmentOnDeviceModel, options);
}
}
It extends from FritzVisionSegmentTFLPredictor
, so go one step to look at this class.
package ai.fritz.vision.imagesegmentation;
import android.graphics.Bitmap;
import android.util.Log;
import android.util.Size;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.util.List;
import ai.fritz.core.constants.ModelEventName;
import ai.fritz.core.utils.EventTracker;
import ai.fritz.vision.FritzVisionImage;
import ai.fritz.vision.base.FritzVisionTFLitePredictor;
import ai.fritz.vision.base.PreparedImage;
/**
* The predictor class for image segmentation with the TFL backend.
*
* @deprecated Please use {@link FritzVisionSegmentPredictor}. This class will be removed in the next major version update.
*/
public class FritzVisionSegmentTFLPredictor extends FritzVisionTFLitePredictor<FritzVisionSegmentResult> {
private static final String TAG = FritzVisionSegmentTFLPredictor.class.getSimpleName();
private static final int NUM_CHANNELS = 3;
private int inputSize;
private int outputSize;
private int[] intValues;
private MaskType[] segmentClassifications;
private FritzVisionSegmentPredictorOptions options;
private ByteBuffer inputByteBuffer;
private ByteBuffer outputByteBuffer;
public FritzVisionSegmentTFLPredictor(SegmentOnDeviceModel segmentOnDeviceModel, FritzVisionSegmentPredictorOptions options) {
super(segmentOnDeviceModel);
initializeValues(segmentOnDeviceModel, options);
}
private void initializeValues(SegmentOnDeviceModel segmentOnDeviceModel, FritzVisionSegmentPredictorOptions options) {
this.inputSize = segmentOnDeviceModel.getInputSize();
this.outputSize = segmentOnDeviceModel.getOutputSize();
interpreter.setNumThreads(options.getNumThreads());
this.segmentClassifications = setTargetClassifications(segmentOnDeviceModel.getClassifications(), options.getTargetSegments());
inputByteBuffer = ByteBuffer.allocateDirect(4 * inputSize * inputSize * NUM_CHANNELS);
inputByteBuffer.order(ByteOrder.nativeOrder());
outputByteBuffer = ByteBuffer.allocateDirect(4 * outputSize * outputSize * segmentClassifications.length);
outputByteBuffer.order(ByteOrder.nativeOrder());
this.intValues = new int[inputSize * inputSize];
this.options = options;
}
public void setOptions(FritzVisionSegmentPredictorOptions options) {
this.options = options;
this.segmentClassifications = setTargetClassifications(this.segmentClassifications, options.getTargetSegments());
interpreter.setNumThreads(options.getNumThreads());
}
/**
* Identify and create pixel-level masks for all items in visionImage.
*
* @param visionImage
* @return FritzVisionSegmentResult
*/
@Override
public FritzVisionSegmentResult predict(FritzVisionImage visionImage) {
long start = System.nanoTime();
Size modelInputSize = new Size(inputSize, inputSize);
PreparedImage preparedImage = PreparedImage.create(visionImage, options.getCropAndScaleOption(), modelInputSize);
preprocess(preparedImage.getBitmapForModel());
long preprocessTiming = System.nanoTime() - start;
EventTracker.getInstance().trackCustomTiming(ModelEventName.MODEL_PREPROCESS, onDeviceModel, preprocessTiming);
outputByteBuffer.rewind();
start = System.nanoTime();
interpreter.run(inputByteBuffer, outputByteBuffer);
Log.d(TAG, "model inference took " + Math.floor((System.nanoTime() - start) / 1e6) + "ms to run.");
start = System.nanoTime();
FritzVisionSegmentResult result = postprocess(visionImage, preparedImage);
long postprocessTiming = System.nanoTime() - start;
EventTracker.getInstance().trackCustomTiming(ModelEventName.MODEL_POSTPROCESS, onDeviceModel, postprocessTiming);
return result;
}
private MaskType[] setTargetClassifications(MaskType[] classifications, List<MaskType> targetSegments) {
// if no target segments set, then use the default
if (targetSegments == null) {
return classifications;
}
// Filter out the classes outside of the target segments
for (int i = 0; i < classifications.length; i++) {
MaskType maskType = classifications[i];
if (!targetSegments.contains(maskType)) {
classifications[i] = MaskType.NONE;
}
}
return classifications;
}
private void preprocess(Bitmap bitmap) {
bitmap.getPixels(intValues, 0, bitmap.getWidth(), 0, 0, bitmap.getWidth(), bitmap.getHeight());
inputByteBuffer.rewind();
for (int row = 0; row < inputSize; row++) {
for (int col = 0; col < inputSize; col++) {
int pixel = intValues[row * inputSize + col];
float blue = (float) (pixel & 0xFF) / 255f - 0.5f;
float green = (float) ((pixel >> 8) & 0xFF) / 255f - 0.5f;
float red = (float) ((pixel >> 16) & 0xFF) / 255f - 0.5f;
inputByteBuffer.putFloat(red);
inputByteBuffer.putFloat(green);
inputByteBuffer.putFloat(blue);
}
}
}
private FritzVisionSegmentResult postprocess(FritzVisionImage visionImage, PreparedImage preparedImage) {
int[][] classifications = new int[outputSize][outputSize];
float[][] confidence = new float[outputSize][outputSize];
for (int row = 0; row < outputSize; row++) {
int rowOffset = row * outputSize * segmentClassifications.length;
for (int col = 0; col < outputSize; col++) {
int maxClassProbIndex = 0;
float maxClassProbValue = 0;
int colOffset = col * segmentClassifications.length;
int offset = rowOffset + colOffset;
for (int classIndex = 0; classIndex < segmentClassifications.length; classIndex++) {
float classProb = outputByteBuffer.getFloat((offset + classIndex) * 4);
// Arg max
if (classProb > maxClassProbValue) {
maxClassProbIndex = classIndex;
maxClassProbValue = classProb;
}
}
classifications[row][col] = maxClassProbIndex;
confidence[row][col] = maxClassProbValue;
}
}
return new FritzVisionSegmentResult(
visionImage, preparedImage,
options, segmentClassifications,
preparedImage.getTargetInferenceSize(),
new Size(outputSize, outputSize),
preparedImage.getOffsetX(),
preparedImage.getOffsetY(),
classifications, confidence);
}
}
Now I just concentrate on the constructor which is initializeValues
function.
private void initializeValues(SegmentOnDeviceModel segmentOnDeviceModel, FritzVisionSegmentPredictorOptions options) {
this.inputSize = segmentOnDeviceModel.getInputSize();
this.outputSize = segmentOnDeviceModel.getOutputSize();
interpreter.setNumThreads(options.getNumThreads());
this.segmentClassifications = setTargetClassifications(segmentOnDeviceModel.getClassifications(), options.getTargetSegments());
inputByteBuffer = ByteBuffer.allocateDirect(4 * inputSize * inputSize * NUM_CHANNELS);
inputByteBuffer.order(ByteOrder.nativeOrder());
outputByteBuffer = ByteBuffer.allocateDirect(4 * outputSize * outputSize * segmentClassifications.length);
outputByteBuffer.order(ByteOrder.nativeOrder());
this.intValues = new int[inputSize * inputSize];
this.options = options;
}
We can see it just initialize the necessary information about the model. The segmentClassifications
is a MaskType[]
variable which tells the predictor what type of segmentation you want. In my project it is just MaskType.HAIR
and is given by my defined class Train_170CustomModel
. The default batch size is 4 and the input image has same height and width size.
The rest part is pretty much the same like the fritz tutorial, I follow the same structures and add some notes.
Choose a hair color for prediction
So our model will predict a hair mask, and use the hair mask overlay to blend the color with the original image. Now it will color the hair to BLUE.
MaskType.HAIR.color = Color.BLUE;
| java.lang.Object | |
|---|---|
| ↳ | ai.fritz.vision.imagesegmentation.MaskType |
MaskType
tells what kind of mask we want to use. It includes several types of masks such as BED, HAIR, FLOOR, PERSON. Also it has a public method setColor(int color)
which set the color you’d like for this mask type.
Run prediction on an image to detect hair
Images can come from a camera, a photo roll, or live video. In this project I catch the images from the camera.
In the code below, we convert an android.media.Image
object (YUV_420_888
format) into a FritzVisionImage
object to prepare it for prediction. This is usually the case when reading from a live camera capture session.
// Determine how to rotate the image from the camera used.
int rotation = FritzVisionOrientation.getImageRotationFromCamera(this, cameraId);
// Create a FritzVisionImage object from android.media.Image
FritzVisionImage visionImage = FritzVisionImage.fromMediaImage(image, rotation);
We may also convert a Bitmap
to a FritzVisionImage
FritzVisionImage visionImage = FritzVisionImage.fromBitmap(bitmap);
After we’ve create a FritzVisionImage
object, call predictor.predict
.
// Run the image through the model to identify pixels representing hair.
FritzVisionSegmentResult segmentResult = predictor.predict(visionImage);
This will return a segmentResult
that we can use to display the hair mask.
We can look at the FritzVisionSegmentTFLPredictor
to see what happened when calling the predict function:
public FritzVisionSegmentResult predict(FritzVisionImage visionImage) {
long start = System.nanoTime();
Size modelInputSize = new Size(inputSize, inputSize);
PreparedImage preparedImage = PreparedImage.create(visionImage, options.getCropAndScaleOption(), modelInputSize);
preprocess(preparedImage.getBitmapForModel());
long preprocessTiming = System.nanoTime() - start;
EventTracker.getInstance().trackCustomTiming(ModelEventName.MODEL_PREPROCESS, onDeviceModel, preprocessTiming);
outputByteBuffer.rewind();
start = System.nanoTime();
interpreter.run(inputByteBuffer, outputByteBuffer);
Log.d(TAG, "model inference took " + Math.floor((System.nanoTime() - start) / 1e6) + "ms to run.");
start = System.nanoTime();
FritzVisionSegmentResult result = postprocess(visionImage, preparedImage);
long postprocessTiming = System.nanoTime() - start;
EventTracker.getInstance().trackCustomTiming(ModelEventName.MODEL_POSTPROCESS, onDeviceModel, postprocessTiming);
return result;
}
Basically, it does three things, preprocessing
, interpreter.run
and post processing
. The core thing is interpreter.run
.
First, the interpreter
is defined in another class
package ai.fritz.vision.base;
import org.tensorflow.lite.Interpreter;
import ai.fritz.core.FritzOnDeviceModel;
import ai.fritz.customtflite.FritzTFLiteInterpreter;
import ai.fritz.vision.FritzVisionImage;
/**
* TFL Predictor
* @hide
*/
public abstract class FritzVisionTFLitePredictor<T> extends FritzVisionPredictorBase {
protected FritzOnDeviceModel onDeviceModel;
protected FritzTFLiteInterpreter interpreter;
public FritzVisionTFLitePredictor(FritzOnDeviceModel onDeviceModel) {
this(onDeviceModel, new Interpreter.Options());
}
public FritzVisionTFLitePredictor(FritzOnDeviceModel onDeviceModel, Interpreter.Options interpreterOptions) {
this.onDeviceModel = onDeviceModel;
this.interpreter = new FritzTFLiteInterpreter(onDeviceModel, interpreterOptions);
}
public void close() {
this.interpreter.close();
}
}
As the code shows, interpreter
is an ai.fritz.customtflite.FritzTFLiteInterpreter
class instance which is defined by ourself. We pass our model through onDeviceModel
and get an interpreter instance.
Then we call the interpreter.run
function to get the prediction. We look into the ai.fritz.customtflite.FritzTFLiteInterpreter
class and see the run
function
/**
* Run model inference on the input and output methods.
*

* The interpreter will record metrics on model execution.
*/
public void run(Object input, Object output) {
modelDownloadManager.checkForNewActiveVersion();
this.interpreter.run(input, output);
trackInferenceTime();
}
We can see it calls the this.interpreter.run
function. So where is the interpreter? we can see in the FritzTFLiteInterpreter
class, the interpreter is just a tensorflow lite Interpreter class. So that’s it. Fritz framework finally calls the tensorflow lite interpreter.run
function to run the model and get the prediction.
// sample lines in FritzTFLiteInterpreter class
import org.tensorflow.lite.Interpreter;
private Interpreter interpreter;
Blend the mask onto the original image
Now that we have the result from the model, let’s extract the mask and blend it with the pixels on the original image.
First, pick one of 3 different blend modes:
// Soft Light Blend
BlendMode blendMode = BlendModeType.SOFT_LIGHT.create();
// Color Blend
BlendMode blendMode = BlendModeType.COLOR.create();
// Hue Blend
BlendMode blendMode = BlendModeType.HUE.create();
I choose HUE blend model.
Next, extract the mask for which we detected hair in the image. The Segmentation Predictor has a method called createMaskOverlayBitmap
that returns a coloredBitmap
of the classified pixels. In this case, red indicates detected hair.
Create a bitmap of the overlay to apply to an image.
* This will have the model output dimensions.
*

* Default alpha value is 60.
*
* @return a bitmap of the overlay
public Bitmap createMaskOverlayBitmap() {
return buildMultiClassMask();
}
Bitmap maskBitmap = segmentResult.createMaskOverlayBitmap(blendMode.getAlpha());
Finally, let’s blend maskBitmap
with the original image.
// Get the original image.
FritzVisionImage visionImage = segmentResult.getOriginalImage();
// Blend the original image with the mask and the blend mode.
Bitmap blendedBitmap = visionImage.blend(maskBitmap, blendMode);
Track the performance of your model
I deployed the model to android applicaiton and run it on “Xiaomi Mi A2 Lite” mobile phone. Look at the prediction time on the “Custom Models” board, we can see that the average prediction time is 330ms which is acceptable. And 95% of the prediction time is under 363 ms indicating that our model is pretty stable.


{% extends "layout.html" %} {% block content %}
You need to login to Wikipedia in order to add a new holiday


Todo
Too much to do ... Some things are planed, some things will never be
quite done, and some things are to check:
Known Bugs
- When editing or deleting one line of the history, any line with the
same entries will be effected. But as such double entries in the
history doesn't make sense (and the solution will cause other
problems), this won't be fixed.
Things To Check
- Mac OS X
- $HOME expansion on Windows NT (with & without network)
Delayed, Thoughts & Plans
- search string chars: "Chateau" should match "Château", too
- rewrite the selection tools for aroma
- facility to add own growing areas to the regions database
- own, extensive search window
- which wine to the meal, and which meal to this grape / region?
- build up an interface for communication between program parts
- build also all inclusive binaries (http://freewrap.sourceforge.net/)
- build Debian package (german manual: http://www.schlittermann.de/deb-intern/dpkg/)
Never Ending Stuff
- eliminate possible bugs
- improve speed
- improve keyboard-usability
- improve nls support
- write documentations
- update the grape database
- update the regions database
- update the bio database
- update the aroma database
- update the classes database