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Next: Maintaining the stack, Previous: How to use the valuator, Up: Value methods [Contents][Index]
Step-driven valuation hides Libmarpa’s grammar rewrites from the application, and is quite efficient. Libmarpa knows which rules are sequences. Libmarpa optimizes stack manipulations based on this knowledge. Long sequences are very common in practical grammars. For these, the stack manipulations suggested by Libmarpa’s step-driven valuator will be significantly faster than the traditional stack evaluation algorithm.
Step-driven evaluation has another advantage. To illustrate this, consider what is a very common case: The semantics are implemented in a higher-level language, using callbacks. If Libmarpa did not use step-driven valuation, it would need to provide for this case. But for generality, Libmarpa would have to deal in C callbacks. Therefore, a middle layer would have to create C language wrappers for the callbacks in the higher level language.
The implementation that results is this: The higher level language would need to wrap each callback in C. When calling Libmarpa, it would pass the wrappered callback. Libmarpa would then need to call the C language “wrapper”. Next, the wrapper would call the higher-level language callback. The return value, which would be data native to the higher-level language, would need to be passed to the C language wrapper, which will need to make arrangements for it to be based back to the higher-level language when appropriate.
A setup like this is not terribly efficient. And exception handling across language boundaries would be very tricky.
But neither of these is the worst problem. The worst problem is that callbacks are hard to debug. Wrappered callbacks are even worse. Calls made across language boundaries are harder yet to debug. In the system described above, by the time a return value is finally consumed, a language boundary will have been crossed four times. The ability to debug can make the difference between code that works and code that does not work, and callbacks put far too many hurdles in the way of debugging.
So, while step-driven valuation seems a roundabout approach, it is simpler and more direct than the likely alternatives. And there is something to be said for pushing semantics up to the higher levels — they can be expected to know more about it.
These advantages of step-driven valuation are strictly in the context of a low-level interface. We are under no illusion that direct use of Libmarpa’s valuator will be found satisfactory by most Libmarpa users, even those using the C language. Libmarpa’s valuator is intended to be used via an upper layer, one that does know about semantics.
Next: Maintaining the stack, Previous: How to use the valuator, Up: Value methods [Contents][Index]


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Easteregg demo page
How to use them on your website:
see documentation on GitHub
unicornCursor
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A distinguished-looking gentleman across the aisle from us was fiddling with his digital watch.
After watching him struggle for a few minutes, my mom asked if she could help.
“Well, if you’ve got teeny tiny fingers, sure,” he said, handing over the watch. “I want to move it forward an hour for the new time zone.”
My mother took it, then reached into her seat pocket and pulled out the motion sickness bag. She ripped off the part you fold down when the bag is full and stripped away everything but the thin wire inside. In a matter of seconds, she handed back the watch, the time now fixed.
Both the stranger and I were amazed. It’s not every day that someone MacGyvers your electronics with, of all things, an airplane barf bag.
But then, my mom doesn’t have an everyday mind.
An artist by profession, my mother is among the most creative people I know. What makes her mind—and her brain—different?
Neuroscientists recently discovered that artists, writers, actors, and other creative experts are especially good at imagining, in vivid detail, what is far away from the here-and-now.
For instance, most of us can visualize what it would be like to go shopping in a familiar store, but it’s much harder to picture waiting in line for movie tickets in Tokyo. Likewise, our mental picture of what may happen tomorrow is much higher-resolution than an imagined day a hundred years from now.
When creative experts are asked to imagine these distal scenarios, they recruit a part of what scientists call the “default network,” brain structures that support empathy, thinking about our values, and other forms of abstraction. A creative mind, say the researchers, “may be neurally prepared to transcend the here and now…”
Try imagining what it would be like to be somewhere else, someone else, or sometime else. Read a novel. Watch a film. Consider an everyday object and what, hypothetically, MacGyver might do with it. Thinking outside the box may depend on getting outside ourselves.
With grit and gratitude,
Angela
Originally published at Character Lab
— Published on November 19, 2019


[gecode-users] IdxView and IdxViewArray namespaces
Martin Mann
mmann at informatik.uni-freiburg.de
Thu Jun 14 15:58:32 CEST 2007
Hi,
i am wondering, why the usefull IdxView and its array is hidden in the
Gecode::Set::Select namespace and is no direct member of Gecode?
I think it is very usefull elsewhere too (e.g. for problem specific
viewselections) without using the set vars stuff. Maybe you can shift it
somewhere else in Gecode 2.0 for a better accessment if you agree.
Just a suggestion! ;)
Yours,
Martin
--
Martin Mann, Dipl. Bioinf.
Bioinformatics - Inst. of Computer Science
Albert-Ludwigs-University Freiburg
Tel: ++49-761-203-8259
Fax: ++49-761-203-7462
http://www.bioinf.uni-freiburg.de/~mmann/
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{% extends 'layout-nhs-website.html' %} {% set version = "v7" %} {% set heading = "Coronavirus vaccine research" %} {% block beforeMain %} {% endblock %} {% block content %}
Vaccines are the most effective way to prevent infections like coronavirus (COVID-19).
Researchers need people to take part in their studies so they can find out which possible new vaccines work best.
On this page you can sign up to be contacted about taking part in approved UK coronavirus vaccine studies. This means you'll be joining the COVID-19 vaccine registry.
You can sign up online. We'll ask you some questions about yourself, and then ask your permission for researchers on the vaccine studies to contact you.
If you sign up, your details will be kept secure. They'll only be shared with researchers who think you might be suitable for a study they're working on. The researchers will then contact you to tell you more about it, and answer any questions you have.
If you sign up to be contacted, you do not have to take part in a study or talk to researchers. It's your choice.
You can withdraw your permission at any time.
{{ actionLink({ "text": "Sign up to be contacted for coronavirus vaccine studies ", "href": "/v7/" }) }}If you have questions about signing up, see answers to common questions about signing up for coronavirus vaccine research.
{{ actionLink({ "text": "Sign up to be contacted for coronavirus vaccine studies ", "href": "/v7/" }) }}
Page last reviewed: 18 December 2020
Next review due: 18 January 2021


Rick Sanchez
Age:70 Height:6'5 Weight:190 lbs Sex:Male
Likes timetraveling, Shooting stuff and Crazy Adventures! 9/14/21


Well done! You now have a sense of scale for the amount of water embedded in everyday food. Did you know that the average quantity of embedded water per person per day is 3200 litres?
Find how much energy is needed to bring water to your tap and treat it once it goes to the sink...
In the UK, everybody use in average 150 litres of water per person per day. This water needs to be treated to be drinkable, and transported to the tap, and then once it goes to the sink, it needs to be treated again to be reusable.
Please tweak the sliders on the blue links until you find how much energy is needed to bring enough water to cater daily or three persons living in one house.
In order to get of drinkable water to your tap , you need to use . In turn, the energy needed to treat the wasted water that goes in the sink is
So in total, the total energy needed to get the water to your tap and treat the waste is .
To produce that much energy, you would need to pedal on a bike generator for (a typical bike generator can produce 100 watts for an hour).
That is the equivalent of cycling for or


Belinda Weaver
is our Community Development Lead. Based in Brisbane, Australia, she most recently
worked for the Queensland Cyber Infrastructure Foundation,
which provides eResearch infrastructure, including cloud resources, to Queensland universities.
Belinda tweets as @cloudaus.
Instructor Trainer, Steering Committee (2016, 2017 Member)


There are seven financial data types: Tick, TradeBar, QuoteBar, Delisting, SymbolChangedEvent, Split and Dividend.
All data extends from $[BaseData,T:QuantConnect.Data.BaseData] - the core data class which provides Symbol, Time and Value properties.
$[Ticks,T:QuantConnect.Data.Market.Tick] provides LastPrice and Quantity properties for a given time. If it is a quote, it also contains non-zero BidPrice, BidSize, AskPrice, AskSize properties.
$[TradeBar,T:QuantConnect.Data.Market.TradeBar] provides Open, High, Low, Close and Volume properties for a given period of time.
$[QuoteBar,T:QuantConnect.Data.Market.QuoteBar] provides Open, High, Low, Close, Bid, Ask, LastBidSize and LastAskSize properties for a given period of time. The Bid and the Ask properties are $[Bar,T:QuantConnect.Data.Market.Bar] objects that contains Open, High, Low and Close. The QuoteBar Open, High, Low and Close properties values are the mean of the respective Bid and Ask property.
$[Dividend,T:QuantConnect.Data.Market.Dividend] events are triggered on payment of a dividend. It provides the Distribution per share.
$[Split,T:QuantConnect.Data.Market.Split] events are triggered on a share split or reverse split event. It provides a SplitFactor and ReferencePrice.
$[SymbolChangedEvent,T:QuantConnect.Data.Market.SymbolChangedEvent] provides notice of new ticker names for stocks, or mergers of two tickers into one. It provides the OldSymbol and NewSymbol tickers.
$[Delisting,T:QuantConnect.Data.Market.Delisting] events provide notice an asset is no longer trading on the exchange.
These data types all have dedicated event handlers which follow the pattern above (public void OnData(Type
data) {}
);
and are also passed into the OnData(Slice data) event handler.
All these data types are accessible through their properties on the slice object. i.e.
slice.Bars
slice.QuoteBars
slice.Ticks
slice.Splits
slice.Dividends
slice.Delistings
slice.SymbolChangedEvents
//TradeBars collection of TradeBar objects TradeBars data; TradeBar ibm = data["IBM"]; //QuoteBars collection of QuoteBar objects QuoteBars data; QuoteBar eur = data["EURUSD"]; //Dividends collection of Dividend objects Dividends data; Dividend ibm = data["IBM"];


Constructor
new exports(options)
Consstruction of the class
Parameters:
| Name | Type | Description |
|---|---|---|
options |
* | Options for this implementations |
Methods
(async) contains(name) → {Promise}
Check to see if the named credentials are in
the wallet.
Parameters:
| Name | Type | Description |
|---|---|---|
name |
string | The name of the credentials. |
Returns:
A promise that is resolved with
a boolean; true if the named credentials are in the
wallet, false otherwise.
- Type
- Promise
(async) get(name) → {Promise}
Get the named credentials from the wallet.
Parameters:
| Name | Type | Description |
|---|---|---|
name |
string | The name of the credentials. |
Returns:
A promise that is resolved with
the named credentials, or rejected with an error.
- Type
- Promise
(async) getAll() → {Promise}
Gets all the objects under this prefix and tag
An empty storage service will return a map with no contents
Returns:
A Promise that is resolved with a map of the names and the values
- Type
- Promise
(async) listNames() → {Promise}
List all of the credentials in the wallet.
Returns:
A promise that is resolved with
an array of credential names, or rejected with an
error.
- Type
- Promise
(async) put(name, value) → {Promise}
Add a new credential to the wallet.
Parameters:
| Name | Type | Description |
|---|---|---|
name |
string | The name of the credentials. |
value |
string | The credentials. |
Returns:
A promise that is resolved when
complete, or rejected with an error.
- Type
- Promise
(async) remove(name) → {Promise}
Remove existing credentials from the wallet.
Parameters:
| Name | Type | Description |
|---|---|---|
name |
string | The name of the credentials. |
Returns:
A promise that is resolved when
complete, or rejected with an error.
- Type
- Promise


Online Printing Shop, application on PHP
Museium light development application on PHP.
Expense Management system application on ASP.NET
blood bank management system application on ASP.NET


Be the first to know when we open source our beta
Introducing SnappyData
A real-time analytics platform that combines in-memory state management, high availability and synopses data structures to deliver powerful analytic querying and alerting capabilities on Apache Spark at a fraction of the cost of traditional big data platforms. Learn more on our blog
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OLTP + OLAP Inside Spark
Instantaneous analysis on streaming data, written to a data store that support high writes, point updates, point queries as well as analytic queries.
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Spark & SQL interfaces
SnappyData delivers ease of use by exposing the Spark programming model and SQL query execution.
-
Synopsis Data Structures
Data structures with very low memory footprint designed for fast approximate querying.
How does it work?
SnappyData fuses the Spark computational engine with a highly available, multi-tenanted in-memory database to execute OLAP & OLTP queries on streaming data. Further, SnappyData can store data in a variety of synopsis data structures to provide extremely fast responses on less resources. Finally, Applications can either submit Spark programs or connect using JDBC/ODBC to run interactive or continuous SQL queries. Learn more on our blog
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1
Deploy SnappyData and connect it to historical or streaming data
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2
Write interactive or continuous SQL queries on connected data
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3
Use SnappyData’s synopsis structures to speed up execution
SnappyData Features
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Committed to Open Source
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SQL & Spark interfaces
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Concurrent OLAP+OLTP workloads
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Synopsis data structures designed for speed
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Integration with Spark ecosystem
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Always-on high availability
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|
JUST2D Platformer
|
Go to the source code of this file.
Classes | |
| class | NonStaticObj |
| Typical object (an entity) that participates in physics simulation. More... | |
Enumerations | |
| enum | ObjectType { ObjectType::PLAYER, BRIDGE_PARTITION, ObjectType::PLATFORM, ObjectType::BOX } |
| Define the type of an object of an NonStaticObj class for dynamic box2d objects. More... | |
|
strong |
Define the type of an object of an NonStaticObj class for dynamic box2d objects.
| Enumerator | |
|---|---|
| PLAYER | it's hero object |
| PLATFORM | it's drawbridge or partition |
| BOX | it's platform it's box (doesn't matter metal or wooden) |


The paper provides useful empirical advice for adapting pretrained language models for a given target task.
Pre-trained models considered
ELMo
BERT
Tasks considered
Named Entity Recognition (NER) - CoNLL 2003 dataset
Sentiment Analysis (SA) - Stanford Sentiment Treebank (SST-2) dataset
Natural Language Inference (NLI) - MultiNLI and Sentences Involving Compositional Knowledge (SICK-E) dataset
Paraphrase Detection (PD) - Microsoft Research Paraphrase Corpus (MRPC)
Semantic Textual Similarity (STS) - Semantic Textual Similarity Benchmark (STS-B) and SICK-R
The last 3 tasks (NLI, PD, STS) are defined for sentence pairs.
Adaptation Strategies
Feature Extraction
The pretrained model is only used for extracting features and its weights are kept fixed.
For both ELMo and BERT, the contextual representation of the words from all the layers are extracted.
A weighted combination of these layers is used as an input to the task-specific model.
Task-specific models
NER - BiLSTM with CRF layer
SA - bi-attentive classification network
NLI, PD, STS - Enhanced Sequential Inference Model (ESIM)
Fine-tuning
The pretrained model is finetuned on the target task.
Task-specific models for ELMO
NER - CRF on top of LSTM states
SA - Max-pool over the language model states followed by a softmax layer
NLI, PD, STS - cross sentence bi-attention between the language model states followed by pooling and softmax layer.
Task-specific models for BERT
NER - Extract representation of the first-word piece of each token followed by the softmax layer
SA, NLI, PD, STS - standard BERT training
Main observations
Feature extraction and fine-tuning have comparable performance in most cases unless the two tasks are highly similar(fine-tuning is better) or highly dissimilar (feature extraction is better).
For ELMo, feature extraction consistently outperforms fine-tuning for the sentence pair tasks (NLI, PD, STS). The reverse trend is observed for BERT with fine-tuning being better on sentence pair tasks.
Adding extra parameters is helpful for feature extraction but not fine-tuning.
ELMo fine-tuning requires careful tuning and other tricks like triangular learning rates, gradual unfreezing and discriminative fine-tuning.
For the tasks considered, there is no correlation observed between the distance of the source and target domains and adaptation performance.
Training a diagnostic classifier (on the intermediate representations) suggests that fine-tuning improves the performance of the classifier at all the intermediate layers (which is sort of expected).
In terms of mutual information estimates, fine-tuned representations have a much higher mutual information as compared to the feature extraction based representations.
Knowledge for single sentence tasks seems to be mostly concentrated in the last layers while for pair classification tasks, the knowledge seems gradually build un in the intermediate layers, all the way up to the last layer.


Found 4 records.
Errata ID: 489
Status: Verified
Type: Editorial
Reported By: Soohong Daniel Park
Date Reported: 2004-04-29
Section 3.1 number 5 says:
The client times out and retransmits the DHCPREQUEST message if the client receives neither a DHCPACK or a DHCPNAK message. ... If the client receives neither a DHCPACK or a DHCPNAK message after employing the retransmission algorithm, the client reverts to INIT state and restarts the initialization process.
It should say:
The client times out and retransmits the DHCPREQUEST message if the client receives neither a DHCPACK nor a DHCPNAK message. ... If the client receives neither a DHCPACK nor a DHCPNAK message after employing the retransmission algorithm, the client reverts to INIT state and restarts the initialization process.
Notes:
Errata ID: 490
Status: Verified
Type: Editorial
Reported By: Sreeni R. Nair
Date Reported: 2004-01-13
Section 4.1 says:
Normally, DHCP servers and BOOTP relay agents attempt to deliver DHCPOFFER, DHCPACK and DHCPNAK messages directly to the client using uicast delivery.
It should say:
Normally, DHCP servers and BOOTP relay agents attempt to deliver DHCPOFFER, DHCPACK and DHCPNAK messages directly to the client using unicast delivery.
Notes:
typo (uicast -> unicast). Updated 2013-06-05. Thanks to Carlos Prendes for the correction.
Errata ID: 5100
Status: Reported
Type: Technical
Reported By: Fan Wei
Date Reported: 2017-08-29
Section 4.1 says:
Normally, DHCP servers and BOOTP relay agents attempt to deliver DHCPOFFER, DHCPACK and DHCPNAK messages directly to the client using uicast delivery.
It should say:
Normally, DHCP servers and BOOTP relay agents attempt to deliver DHCPOFFER, DHCPACK messages directly to the client using unicast delivery.
Notes:
According to prior part description in section 4.1: "In all cases, when ’giaddr’ is zero, the server broadcasts any DHCPNAK messages to 0xffffffff.", the DHCP server should not send DHCPNAK in unicast to client unless 'giaddr' is not zero.
Errata ID: 488
Status: Held for Document Update
Type: Editorial
Reported By: Robert Floyd Jr
Date Reported: 2006-03-23
Held for Document Update by: Brian Haberman
Section 1.2 says:
In other related work, the path minimum transmission unit (MTU) discovery algorithm can determine the MTU of an arbitrary internet path [14].
It should say:
In other related work, the path maximum transmission unit (MTU) discovery algorithm can determine the MTU of an arbitrary internet path [14].


Test Result for ProvMark
SysCall
Generalized Background Graph
Generalized Foreground Graph
Benchmark Graph
@@@TABLEROW@@@


---
layout: default
---
View our list of publications.
Spacecraft
- Human Spacecraft Systems and Operations Design
- Cubesats
- Extravehicular Activity (Spacewalk) Safety, Rescue, and Injury Avoidance
Aircraft Emergencies
- Wake-Vortex Avoidance
- Viscous Flow Control for Stall Management
- Ejection Seat Dynamics/Biodynamics
Robotics
- Real-Time Multi-Sensory Feedback for Manual Control of Surgical and Space Robotics
- Trajectory Awareness and Collision Avoidance
Human Systems Integration
- Human/Systems Design Optimization
- Operator Real-Time Performance
- Situational Awareness, Fatigue, and Distraction in Hazardous Environments
- Automated Operator Monitoring and Attentional Alerting


{% extends "base.html" %} {% block content %}
Get an overview over completed and ongoing ABC runs
Information about the running server


|
SBF
Super bloody fast messaging transport
|
This file defines the helper structures and functions to handle buffers. More...
Go to the source code of this file.
Macros | |
| #define | sbfBuffer_createPool(size) sbfBuffer_createPool1 (size, __FUNCTION__, __LINE__) |
Typedefs | |
| typedef typedefSBF_BEGIN_DECLS struct sbfBufferImpl * | sbfBuffer |
| typedef void(* | sbfBufferDestroyCb) (sbfBuffer buffer, void *data, void *closure) |
Functions | |
| sbfPool | sbfBuffer_createPool1 (size_t size, const char *function, u_int line) |
| sbfPool | sbfBuffer_defaultPool (size_t size) |
This file defines the helper structures and functions to handle buffers.
Definition in file sbfBuffer.h.
| #define sbfBuffer_createPool | ( | size | ) | sbfBuffer_createPool1 (size, __FUNCTION__, __LINE__) |
Definition at line 29 of file sbfBuffer.h.
| typedef typedefSBF_BEGIN_DECLS struct sbfBufferImpl* sbfBuffer |
Declare the buffer handler
Definition at line 18 of file sbfBuffer.h.
| typedef void(* sbfBufferDestroyCb) (sbfBuffer buffer, void *data, void *closure) |
Definition at line 20 of file sbfBuffer.h.
| sbfPool sbfBuffer_createPool1 | ( | size_t | size, |
| const char * | function, | ||
| u_int | line | ||
| ) |
| sbfPool sbfBuffer_defaultPool | ( | size_t | size | ) |


×
FOXTROT
DESCRIPTION
Dance is the hidden language of soul.. So oost up yourself to beat the clock and just trigger to hit the dance floor..!!Let the clash of steps begin..!!
RULES
- Only team entries are allowed.
- A team shall consist of 2 to 10 members or 11 to 18 members.
- Every member should have a valid college id.
- Maximum allotted time is 4 to 15 minutes.
- There is no common theme for the competition.
- Points will be awarded on the basis of choreography, difficulty level, emotions, expression and style.
- Dressing and appearance will be considered.
- Second chances will not be entertained unless it is a flaw from our side.
- Decision of the judges will be final and will not be subjected to any change.


unit MPT
Music Pro Tracker library
author: Tomasz Biela (Tebe)
http://atariki.krap.pl/index.php/Music_Protracker
Types:
name:
type:
description:
TMPT
Object
player: pointer;
// memory address of player
modul: pointer;
// memory address of a module
procedure Init; assembler;
// Initializes
procedure Play; assembler;
procedure Stop; assembler;
// Stops Music
end;
object for controling MPT player
Interface:
name:
description:
TMPT.Init
procedure TMPT.Init; assembler;
Initialize MPT player
TMPT.Play
procedure TMPT.Play; assembler;
Play music, call this procedure every VBL frame
TMPT.Stop
procedure TMPT.Stop; assembler;
Halt MPT player


Galvanize Delivers
menu
Order Delivery
Home
Royale with Cheese
$8.99
add to order
Arugula Pie
$11.99
add to order
Smoked Swine
$14.99
Add to Order
Ice Cream Biscuit
$7.99
add to order
Order Details
Item
Price
Subtotal
Tax
Total
Special Instructions
Delivery Information
First Name
Last Name
Address
Apt. #
City
State
Zip Code
Submit Order


Changelog¶
v1.2 (October 9, 2019)¶
Improvements and changes¶
Variable names in
qaoa.cost_function.py
have been updated to better reflect their counterparts inqaoa.parameters.py
.Sped up cost function calls and construction for
PrepareAndMeasureOnWFSim
andQAOACostFunOnWFSim
. For very small systems and hamiltoniansWavefunctionSimulator().expectation()
is still faster, than our implementation.Added an example of using QAOA to solve a simple QUBO problem.
Sped up tests by removing all
with local_qvm()
context managers. You have to manually start a qvm in the background for the tests now!Added
sample_qaoa_bistrings
toutilities.py
Bugfixes¶
Can access
FourierExtendedParams.z_rotation_angles
now for hamiltonians without bias terms.


--- description: Framework JavaScript bundle sizes templateLanguage: liquid templateEngineOverride: html orientation: vertical typing: - 68-155 --- {% layout "./layouts/liquid-layout.html" %} {% block content %}


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Compassionate, dramatic, and deeply moving, To Kill A Mockingbird takes readers to the roots of human behavior - to innocence and experience, kindness and cruelty, love and hatred, humor and pathos. Now with over 18 million copies in print and translated into forty languages, this regional story by a young Alabama woman claims universal appeal. Harper Lee always considered her book to be a simple love story. Today it is regarded as a masterpiece of American literature.
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ABOUT IT VISION COMPUTER INSTITUTE OF TECHNOLOGY, BIHAR SHARIF NALANDA, BIHAR, INDIA
Dear Student,
* We are happy to welcome you to join our institute for Computer Education Courses. The recommendation given by the IT Task Force, if implemented, will lead Indian to be become a Super Power.
We at “IT Vision” have decided to have a strict quality check on the trained manpower coming out of our Institution, who in turn will play a vital role in making India a super Software giant.
All the information required for your enrolment is given in this prospectus safely till you complete the course, as it contains Information regarding the course, which you have joined.
We are confident that the applicant, who joins, will in a position to make a quality career for him/her self.
“Happy Learning and all the best for your future”
About The Institute
* IT Vision is an Independent computer education Institute conducting computer – Oriented courses. This institute was established to cater to the basis need in Computer Education. It offers courses of six month, one year, and and a half years and short term duration courses.
Achievement at a Glance
* Career oriented Courses for Students & Parents
* Choice of courses(English)
* No age/no qualification bar
* No more waiting – two batches in a month
* Lowest fee structure for the highest quality education


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How to create the right environment?
How to scale?
Open Source
THINK
FEEL
DO
Implementation
Holding bay


DBC Cultural Blog
The Kitchen vs. Table Mentality
May 3, 2015
I thrive in a collaborative environment where I am encouraged to experiment. I love to learn from the people around me and I love to teach the people learning with me. Dev Bootcamp seems like the perfect place for me to learn a new and enjoyable skill with other people who are as entusiastic about coding as I am.
I am really looking forward to beginning my onsite training at dev bootcamp. I know that I am going to build meaningful academic and personal relationships with the people in my cohort remotely while I am 1500 miles away from most of them. Dev bootcamp will encourage me to care about the work i am doing, but more so encourage me to care about the people I am working with, and that will make the overall experience that much more effective and rewarding.
I am defeintely nervous about my DBC experience. I am a quintessential beginner when it comes to programming, but I know there are a few others in my cohort in the same boat as I am. I am hoping that we can learn from and build off of each other, and eventually do the same with those in our cohort with more experience so that everyone in the cohort collectively become better coders and better people. I am really looking forward to learning new skills that will allow me to start a career, but I am looking forward just as much to meeting people with whom I can share this experience and create a meaningful relationship.


We are a group of promising young talents that are capable to create informative multi-media designs, inspiring other people to dive into the deep meaning of digital art, and captivate the community using our prestigious masterpiece.


I Had Only Seen Sharks On TV Before...
Okay, I had only taken weed 3 times before this experience. It might be weird but I don't know, somehow the first two didn't have any effects on me. Of course it had some, but at least it wasn't as I had expected.
I got a friend, E , who's been smoking pot for over a year. He would come to school so high, wouldn't listen to the teachers, and stare around foolishly. He would tell me about the experiences he had while smoking weed and finally these made me try it.
Before marijuana, I had only smoked cigarrettes and taken alcohol, so I was a bit anxious about what could happen to me. The first time I smoked one joint, and honestly NOTHING happened to me. As I didn't get what I wanted from marijuana I wanted to do it again. That was a bit better and I felt high. But again, not as I wanted.
And here it comes..One day, E told me that his friend had got some strong weed and asked me if I wanted to go over and get high :) I couldn't say NO, because I wanted to have that feeling of highness so much. So we went to his house, prepared the bong , and started hitting.
1.. 2.. and I started feeling strange.. I was acting so different, I realised. But I could say to myself that 'I'm not high' 'I'm okay'. But with a look at the mirror, I saw my eyes half open, and bloodshot. I was having so much fun, we were listening to rap, and dancing wildly. I felt a little tired and sat on E's bed. He was sitting beside me singing. I lighted up a cigar and it's smoke got into my eyes, it hurt me so much and my eyes were all watery. I kept them closed for a few seconds and as I opened them THE WHOLE ROOM WAS FULL OF WATER.
I could see bubbles around the room just like I was in a pool or a sea. Things were floating and so was E's hair. Suddenly a blue shark, just like a cartoon passed behind E. I stared at it for a few moments and tried to realise what was happening. The shark made a few curves and faded away and I blinked to see it again but as I opened my eyes, everything was gone.
When I told him what happened , he was in a kind of shock because he had told me before that he hadn't ever had any hallucinations before so he was kinda jealous. It was a great experience, but I can't say anything about whether it is good or bad to use marijuana as I'm new. I just can say that it's fun!
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Hello, I'm a programmer apassionate in this world, I develop webs, mobile applications and games, I'm with my wife the CEO of Cube Games. In my free time I usually take test or study maths or physics, I really like that's areas about science, I'm not a computer science, but I studied system engineer, and I take a lot of course about technologies at Plazti and searching on the web, but I developed my skills on the web, any institution help me, I'm a self-student and never stop learning.
I build this portfolio at Platzi and freeCodeCamp, I really recommend to invest your time and a little money in this.
Actually I manage my own company with my wife Cube Studios, I'm working develop games, applications and others, but the software or the techologies that we produce is own, every project that we have is own, we don't develop the projects of others institution or people.
This was the dream that a child that he wants to creates technologies and develops his self, he doesn't like the idea of work in the dream of others, because he doesn't using his one houndread potencial.
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