VeraCore Software Solutions, Inc. announced today that Hemlock Printers Ltd., of Burnaby, British Columbia has selected the VeraCore Fulfillment Solution to manage their growing fulfillment operation.

Established in 1968, Hemlock has grown to become one of the largest and most well respected commercial printers in the Pacific Northwest. Hemlock’s comprehensive suite of services includes offset and digital printing, online solutions, prepress, digital photography, bindery, mailing, warehousing and fulfillment.

From their secure, climate controlled warehouse, Hemlock manages numerous client fulfillment programs centered on both print and non-print collateral materials. Hemlock also manages magazine subscription fulfillment programs for several of its publishing clients. Hemlock’s primary objective in evaluating fulfillment platforms was to identify a system that would enable them to more efficiently manage warehouse operations while maintaining their high degree of inventory accuracy, even as the business grew.

The VeraCore Warehouse Management System’s support for barcode technology and rules based processing will enable them to increase fulfillment throughput – without a big increase to labor. Richard Kouwenhoven, Hemlock’s President, commented on their decision, “Fulfillment is definitely a growth area for us, so investing in this technology made sense. VeraCore provides our team with the tools to run a highly efficient warehouse operation which meets the expanding needs of our customers.”

Another important consideration was VeraCore’s ability to integrate with other technologies used by Hemlock. The VeraCore Fulfillment Solution had already been integrated with several of the systems in use at Hemlock, including ecommerce, web-to-print and shipping systems. For cases in which an integration is not already available, VeraCore’s API will enable Hemlock’s development team to build their own integrations as needed.

Denise Lunden, President of VeraCore Software Solutions, Inc. noted, “Hemlock does many different things for their clients and clearly embraces the philosophy that clients are best served by using the best tool available for the task at hand. I’m confident that VeraCore will play an integral role in Hemlock’s continued success in fulfillment”.

To learn more about Hemlock and their award winning services, visit http://www.hemlock.com.

About VeraCore Software Solutions, Inc.
VeraCore Software Solutions, Inc., has been providing software solutions for fulfillment companies, commercial printers and marketing service providers for over 30 years. Their flagship product, The VeraCore Fulfillment Solution, enables fulfillment service providers to manage all aspects of their clients’ order fulfillment programs.

Source: PRWeb


Home
My Hobbies
working out and doing exercises live me fresh and happy
travelling, i just find myself loving and having the sike to travel around the globe
Watching movies, this makes me relaxed and have a fun day


|
Functions |
| int | ADL2_Adapter_CrossdisplayAdapterRole_Caps (ADL_CONTEXT_HANDLE context, int iAdapterIndex, int *lpCrossDisplaySupport, int *lpAdapterRole, int *lpNumPossDisplayAdapters, int **lppPossDisplayAdapters, int *lpNnumPosRenderingAdapters, int **lppPosRenderingAdapters, int *lpErrorStatus) |
| | Function to retrieve CrossDisplay capabilities.
|
| int | ADL_Adapter_CrossdisplayAdapterRole_Caps (int iAdapterIndex, int *lpCrossDisplaySupport, int *lpAdapterRole, int *lpNumPossDisplayAdapters, int **lppPossDisplayAdapters, int *lpNnumPosRenderingAdapters, int **lppPosRenderingAdapters, int *lpErrorStatus) |
| | Function to retrieve CrossDisplay capabilities.
|
| int | ADL2_Adapter_CrossdisplayInfo_Get (ADL_CONTEXT_HANDLE context, int iAdapterIndex, int *lpAdapterRole, int *lpCrossdisplayMode, int *lpNumDisplayAdapters, int **lppDisplayAdapters, int *lpNumRenderingAdapters, int **lppRenderingAdapters, int *lpErrorCodeStatus) |
| | Function to retrieve CrossDisplay state information.
|
| int | ADL_Adapter_CrossdisplayInfo_Get (int iAdapterIndex, int *lpAdapterRole, int *lpCrossdisplayMode, int *lpNumDisplayAdapters, int **lppDisplayAdapters, int *lpNumRenderingAdapters, int **lppRenderingAdapters, int *lpErrorCodeStatus) |
| int | ADL2_Adapter_CrossdisplayInfo_Set (ADL_CONTEXT_HANDLE context, int iAdapterIndex, int iDisplayAdapterIndex, int iRenderingAdapterIndex, int iCrossdisplayMode, int *lpErrorCode) |
| | Function to set the system configuration to CrossDisplay mode or multi-adapter mode.
|
| int | ADL_Adapter_CrossdisplayInfo_Set (int iAdapterIndex, int iDisplayAdapterIndex, int iRenderingAdapterIndex, int iCrossdisplayMode, int *lpErrorCode) |
| | Function to set the system configuration to CrossDisplay mode or multi-adapter mode.
|
| int | ADL2_Adapter_CrossDisplayPlatformInfo_Get (ADL_CONTEXT_HANDLE context, int iAdapterIndex, int *lpXDPlatformInfoMask, int *lpXDPlatformInfoValue) |
| | Function to get the graphics platform information of of an adapter.
|
| int | ADL_Adapter_CrossDisplayPlatformInfo_Get (int iAdapterIndex, int *lpXDPlatformInfoMask, int *lpXDPlatformInfoValue) |
| | Function to get the graphics platform information of of an adapter.
|
| int | ADL2_Adapter_CrossdisplayInfoX2_Set (ADL_CONTEXT_HANDLE context, int iAdapterIndex, int iDisplayAdapterIndex, int iRenderingAdapterIndex, int iCrossdisplayMode, int iCrossdisplayOption, int *lpErrorCode) |
| | Function to set the system configuration to CrossDisplay mode or multi-adapter mode.
|
| int | ADL_Adapter_CrossdisplayInfoX2_Set (int iAdapterIndex, int iDisplayAdapterIndex, int iRenderingAdapterIndex, int iCrossdisplayMode, int iCrossdisplayOption, int *lpErrorCode) |
| | Function to set the system configuration to CrossDisplay mode or multi-adapter mode.
|
This group describes the CrossDisplay APIs.
| int ADL2_Adapter_CrossdisplayAdapterRole_Caps |
( |
ADL_CONTEXT_HANDLE |
context, |
|
|
int |
iAdapterIndex, |
|
|
int * |
lpCrossDisplaySupport, |
|
|
int * |
lpAdapterRole, |
|
|
int * |
lpNumPossDisplayAdapters, |
|
|
int ** |
lppPossDisplayAdapters, |
|
|
int * |
lpNnumPosRenderingAdapters, |
|
|
int ** |
lppPosRenderingAdapters, |
|
|
int * |
lpErrorStatus | |
|
) |
| | |
Function to retrieve CrossDisplay capabilities.
The output parameters of the function include the CrossDisplay supported flag, supported CrossDisplay roles of an adapter, and its partner adapters. If the adapter is capable of playing a display role, the number of possible rendering adapters (lpNnumPosRenderingAdapters) and possible rendering adapters (lppPosRenderingAdapters) parameters are valid. If the adapter is capable of playing a rendering role, the number of possible display adapters (lpNumPossDisplayAdapters) and the possible display adapters (lppPossDisplayAdapters) parameters are valid. If the adapter is capable of playing a display-rendering role, all the output parameters are valid.
- Supported Platforms:
- Linux and Windows(XP, Vista and above); 32bit and 64bit
- Parameters:
-
| [in] | context,: | Client's ADL context handle ADL_CONTEXT_HANDLE obtained from ADL2_Main_Control_Create. |
| [in] | iAdapterIndex | The ADL index handle of the adapter to which the CrossDisplay capability information is applied. |
| [out] | lpCrossDisplaySupport | The pointer to the address of the flag representing CrossDisplay support. If the system supports CrossDisplay and the input adapter has or will have a role in the CrossDisplay configuration, the content of the pointer is 1, otherwise it is 0. This pointer should be initialized by the user. |
| [out] | lpAdapterRole | The pointer to the supported roles of the input adapter. This pointer should be initialized by the user. Possible output values are 0, 1, 2, and 3. 0: The input adapter does not support any CrossDisplay roles. 1: The input adapter supports a rendering role. 2: The input adpater supports a display role. 3: The input adapter supports both rendering and display roles. |
| [out] | lpNumPossDisplayAdapters | The pointer to the number of possible display adapters. This pointer should be initialized by the user. |
| [out] | lppPossDisplayAdapters | The pointer to the pointer to the first possible display adapter address. This pointer does not need to be initialized by the user. |
| [out] | lpNnumPosRenderingAdapters | The pointer to the number of possible rendering adapters. This pointer should be initialized by the user. |
| [out] | lppPosRenderingAdapters | The pointer to the pointer to the first possible rendering adapter address. This pointer does not need to be initialized by the user. |
| [out] | lpErrorStatus | The pointer to the driver error or warning code. This pointer should be initialized by the user. |
- Returns:
- If the function succeeds, the returned value is ADL_OK. Otherwise, the return value is an ADL error code. Result Codes
| int ADL_Adapter_CrossdisplayAdapterRole_Caps |
( |
int |
iAdapterIndex, |
|
|
int * |
lpCrossDisplaySupport, |
|
|
int * |
lpAdapterRole, |
|
|
int * |
lpNumPossDisplayAdapters, |
|
|
int ** |
lppPossDisplayAdapters, |
|
|
int * |
lpNnumPosRenderingAdapters, |
|
|
int ** |
lppPosRenderingAdapters, |
|
|
int * |
lpErrorStatus | |
|
) |
| | |
Function to retrieve CrossDisplay capabilities.
The output parameters of the function include the CrossDisplay supported flag, supported CrossDisplay roles of an adapter, and its partner adapters. If the adapter is capable of playing a display role, the number of possible rendering adapters (lpNnumPosRenderingAdapters) and possible rendering adapters (lppPosRenderingAdapters) parameters are valid. If the adapter is capable of playing a rendering role, the number of possible display adapters (lpNumPossDisplayAdapters) and the possible display adapters (lppPossDisplayAdapters) parameters are valid. If the adapter is capable of playing a display-rendering role, all the output parameters are valid.
- Supported Platforms:
- Linux and Windows(XP, Vista and above); 32bit and 64bit
- Parameters:
-
| [in] | iAdapterIndex | The ADL index handle of the adapter to which the CrossDisplay capability information is applied. |
| [out] | lpCrossDisplaySupport | The pointer to the address of the flag representing CrossDisplay support. If the system supports CrossDisplay and the input adapter has or will have a role in the CrossDisplay configuration, the content of the pointer is 1, otherwise it is 0. This pointer should be initialized by the user. |
| [out] | lpAdapterRole | The pointer to the supported roles of the input adapter. This pointer should be initialized by the user. Possible output values are 0, 1, 2, and 3. 0: The input adapter does not support any CrossDisplay roles. 1: The input adapter supports a rendering role. 2: The input adpater supports a display role. 3: The input adapter supports both rendering and display roles. |
| [out] | lpNumPossDisplayAdapters | The pointer to the number of possible display adapters. This pointer should be initialized by the user. |
| [out] | lppPossDisplayAdapters | The pointer to the pointer to the first possible display adapter address. This pointer does not need to be initialized by the user. |
| [out] | lpNnumPosRenderingAdapters | The pointer to the number of possible rendering adapters. This pointer should be initialized by the user. |
| [out] | lppPosRenderingAdapters | The pointer to the pointer to the first possible rendering adapter address. This pointer does not need to be initialized by the user. |
| [out] | lpErrorStatus | The pointer to the driver error or warning code. This pointer should be initialized by the user. |
- Returns:
- If the function succeeds, the returned value is ADL_OK. Otherwise, the return value is an ADL error code. Result Codes
| int ADL2_Adapter_CrossdisplayInfo_Get |
( |
ADL_CONTEXT_HANDLE |
context, |
|
|
int |
iAdapterIndex, |
|
|
int * |
lpAdapterRole, |
|
|
int * |
lpCrossdisplayMode, |
|
|
int * |
lpNumDisplayAdapters, |
|
|
int ** |
lppDisplayAdapters, |
|
|
int * |
lpNumRenderingAdapters, |
|
|
int ** |
lppRenderingAdapters, |
|
|
int * |
lpErrorCodeStatus | |
|
) |
| | |
Function to retrieve CrossDisplay state information.
The output parameters of the function include the adapter role, the CrossDisplay mode and its partner adapters. If the adapter is in CrossDisplay mode and the adapter role is display, the number of rendering adapters (lpNnumPosRenderingAdapters) and rendering adapters (lppPosRenderingAdapters) parameters are valid. If the adapter is in CrossDisplay mode and the adapter role is rendering, the number of display adapters (lpNumPossDisplayAdapters) and display adapters (lppPossDisplayAdapters) parameters are valid. If the adapter is in multi-adapter mode, only the the adapter role (lpAdapterRole) and CrossDisplay mode (lpCrossDisplaySupport) parameters are valid.
- Supported Platforms:
- Linux and Windows(XP, Vista and above); 32bit and 64bit
- Parameters:
-
| [in] | context,: | Client's ADL context handle ADL_CONTEXT_HANDLE obtained from ADL2_Main_Control_Create. |
| [in] | iAdapterIndex | The ADL index handle of the adapter to which the CrossDisplay state information is applied. |
| [out] | lpAdapterRole | The pointer to the retrieved adapter role. This pointer should be initialized by the user. Possible output values are 0, 1, and 2. 0: The input adapter does not support any CrossDisplay roles. 1: The input adapter supports a rendering role. 2: The input adpater supports a display role. |
| [out] | lpCrossdisplayMode | The pointer to the retrieved CrossDisplay mode. This pointer should be initialized by the user. Possible output values are 0 and 1. 0: Multi-adapter mode. 1: CrossDisplay mode. |
| [out] | lpNumDisplayAdapters | The pointer to the number of retrieved display adapters. This pointer should be initialized by the user. |
| [out] | lppDisplayAdapters | The pointer to the pointer to the first display adapter address. This pointer does not need to be initialized by the user. |
| [out] | lpNumRenderingAdapters | The pointer to the number of possible rendering adapters. This pointer should be initialized by the user. |
| [out] | lppRenderingAdapters | The pointer to the pointer to the first rendering adapter address. This pointer does not need to be initialized by the user. |
| [out] | lpErrorCodeStatus | The pointer to the driver error or warning code. This pointer should be initialized by the user. |
- Returns:
- If the function succeeds, the returned value is ADL_OK. Otherwise the return value is an ADL error code. Result Codes


Introduction to Boosted Trees
XGBoost is short for “Extreme Gradient Boosting”, where the term “Gradient Boosting” is proposed in the paper Greedy Function Approximation: A Gradient Boosting Machine, by Friedman. XGBoost is based on this original model. This is a tutorial on gradient boosted trees, and most of the content is based on these slides by the author of xgboost.
The GBM (boosted trees) has been around for really a while, and there are a lot of materials on the topic. This tutorial tries to explain boosted trees in a self-contained and principled way using the elements of supervised learning. We think this explanation is cleaner, more formal, and motivates the variant used in xgboost
Elements of Supervised Learning
XGBoost is used for supervised learning problems, where we use the training data (with multiple features) xi to predict a target variable yi. Before we dive into trees, let us start by reviewing the basic elements in supervised learning
Model and Parameters
The model in supervised learning usually refers to the mathematical structure of how to make the prediction yi given xi. For example, a common model is a linear model, where the prediction is given by , a linear combination of weighted input features. The prediction value can have different interpretations, depending on the task, i.e., regression or classification. For example, it can be logistic transformed to get the probability of positive class in logistic regression, and it can also be used as a ranking score when we want to rank the outputs.
The parameters are the undetermined part that we need to learn from data. In linear regression problems, the parameters are the coefficients . Usually we will use to denote the parameters (there are many parameters in a model, our definition here is sloppy)
Objective Function : Training Loss + Regularization
Based on different understandings of we can have different problems, such as regression, classification, ordering, etc. We need to find a way to find the best parameters given the training data. In order to do so, we need to define a so-called objective function, to measure the performance of the model given a certain set of parameters.
A very important fact about objective functions is they must always contain two parts: training loss and regularization.
where is the training loss function, and is the regularization term. The training loss measures how predictive our model is on training data. For example, a commonly used training loss is mean squared error.
Another commonly used loss function is logistic loss for logistic regression
The regularization term is what people usually forget to add. The regularization term controls the complexity of the model, which helps us to avoid overfitting. This sounds a bit abstract, so let us consider the following problem in the following picture. You are asked to fit visually a step function given the input data points on the upper left corner of the image. Which solution among the three do you think is the best fit?
he correct answer is marked in red. Please consider if this visually seems a reasonable fit to you. The general principle is we want both a simple and predictive model. The tradeoff between the two is also referred as bias-variance tradeoff in machine learning.
Why introduce the general principle?
The elements introduced above form the basic elements of supervised learning, and they are naturally the building blocks of machine learning toolkits. For example, you should be able to describe the differences and commonalities between boosted trees and random forests. Understanding the process in a formalized way also helps us to understand the objective that we are learning and the reason behind the heuristics such as pruning and smoothing.
Tree Ensemble
Now that we have introduced the elements of supervised learning, let us get started with real trees. To begin with, let us first learn about the model of xgboost: tree ensembles. The tree ensemble model is a set of classification and regression trees (CART). Here’s a simple example of a CART that classifies whether someone will like computer games.
We classify the members of a family into different leaves, and assign them the score on the corresponding leaf. A CART is a bit different from decision trees, where the leaf only contains decision values. In CART, a real score is associated with each of the leaves, which gives us richer interpretations that go beyond classification. This also makes the unified optimization step easier, as we will see in a later part of this tutorial.
Usually, a single tree is not strong enough to be used in practice. What is actually used is the so-called tree ensemble model, which sums the prediction of multiple trees together.
Here is an example of a tree ensemble of two trees. The prediction scores of each individual tree are summed up to get the final score. If you look at the example, an important fact is that the two trees try to complement each other. Mathematically, we can write our model in the form
where is the number of trees, is a function in the functional space , and is the set of all possible CARTs. Therefore our objective to optimize can be written as
Now here comes the question, what is the model for random forests? It is exactly tree ensembles! So random forests and boosted trees are not different in terms of model, the difference is how we train them. This means if you write a predictive service of tree ensembles, you only need to write one of them and they should directly work for both random forests and boosted trees. One example of why elements of supervised learning rock.
Tree Boosting
After introducing the model, let us begin with the real training part. How should we learn the trees? The answer is, as is always for all supervised learning models: define an objective function, and optimize it!
Assume we have the following objective function (remember it always needs to contain training loss and regularization)
Additive Training
First thing we want to ask is what are the parameters of trees? You can find that what we need to learn are those functions , with each containing the structure of the tree and the leaf scores. This is much harder than traditional optimization problem where you can take the gradient and go. It is not easy to train all the trees at once. Instead, we use an additive strategy: fix what we have learned, and add one new tree at a time. We write the prediction value at step as , so we have
It remains to ask, which tree do we want at each step? A natural thing is to add the one that optimizes our objective.
If we consider using MSE as our loss function, it becomes the following form.
The form of MSE is friendly, with a first order term (usually called the residual) and a quadratic term. For other losses of interest (for example, logistic loss), it is not so easy to get such a nice form. So in the general case, we take the Taylor expansion of the loss function up to the second order
where the and are defined as:
After we remove all the constants, the specific objective at step tt becomes
This becomes our optimization goal for the new tree. One important advantage of this definition is that it only depends on and . This is how xgboost can support custom loss functions. We can optimize every loss function, including logistic regression and weighted logistic regression, using exactly the same solver that takes gigi and hihi as input!
Model Complexity
We have introduced the training step, but wait, there is one important thing, the regularization! We need to define the complexity of the tree . In order to do so, let us first refine the definition of the tree as
Here is the vector of scores on leaves, is a function assigning each data point to the corresponding leaf, and is the number of leaves. In XGBoost, we define the complexity as
Of course there is more than one way to define the complexity, but this specific one works well in practice. The regularization is one part most tree packages treat less carefully, or simply ignore. This was because the traditional treatment of tree learning only emphasized improving impurity, while the complexity control was left to heuristics. By defining it formally, we can get a better idea of what we are learning, and yes it works well in practice.
The Structure Score
Here is the magical part of the derivation. After reformalizing the tree model, we can write the objective value with the -th tree as:
where is the set of indices of data points assigned to the -th leaf. Notice that in the second line we have changed the index of the summation because all the data points on the same leaf get the same score. We could further compress the expression by defining and
In this equation are independent with respect to each other, the form is quadratic and the best for a given structure and the best objective reduction we can get is:
The last equation measures how good a tree structure is.
If all this sounds a bit complicated, let’s take a look at the picture, and see how the scores can be calculated. Basically, for a given tree structure, we push the statistics and to the leaves they belong to, sum the statistics together, and use the formula to calculate how good the tree is. This score is like the impurity measure in a decision tree, except that it also takes the model complexity into account.
##Learn the tree structure
Now that we have a way to measure how good a tree is, ideally we would enumerate all possible trees and pick the best one. In practice this is intractable, so we will try to optimize one level of the tree at a time. Specifically we try to split a leaf into two leaves, and the score it gains is
This formula can be decomposed as 1) the score on the new left leaf 2) the score on the new right leaf 3) The score on the original leaf 4) regularization on the additional leaf. We can see an important fact here: if the gain is smaller than , we would do better not to add that branch. This is exactly the pruning techniques in tree based models! By using the principles of supervised learning, we can naturally come up with the reason these techniques work :)
For real valued data, we usually want to search for an optimal split. To efficiently do so, we place all the instances in sorted order, like the following picture.
A left to right scan is sufficient to calculate the structure score of all possible split solutions, and we can find the best split efficiently.
Final words on XGBoost
Now that you understand what boosted trees are, you may ask, where is the introduction on XGBoost? XGBoost is exactly a tool motivated by the formal principle introduced in this tutorial! More importantly, it is developed with both deep consideration in terms of systems optimization and principles in machine learning. The goal of this library is to push the extreme of the computation limits of machines to provide a scalable, portable and accurate library.


- search(String) - Method in class net.e4commerce.dpR_tmt.dao.EmployeeDAO
-
Searches for employees by name.
- search(String) - Method in class net.e4commerce.dpR_tmt.rest.DepartmentResource
-
Search for an employee's department by providing the employee's name.
- search(String) - Method in class net.e4commerce.dpR_tmt.rest.EmployeeResource
-
Searches for employees by name.
- searchEmployeeDepartment(String) - Method in class net.e4commerce.dpR_tmt.dao.DepartmentDAO
-
Search for an employee's department by providing the employee's name.
- setDateOfBirth(String) - Method in class net.e4commerce.dpR_tmt.model.Employee
-
Sets the date of birth.
- setDepartmentId(String) - Method in class net.e4commerce.dpR_tmt.model.Department
-
Sets the department id.
- setDepartmentId(String) - Method in class net.e4commerce.dpR_tmt.model.Employee
-
Sets the department id.
- setDepartmentName(String) - Method in class net.e4commerce.dpR_tmt.model.Department
-
Sets the department name.
- setEmployeeId(String) - Method in class net.e4commerce.dpR_tmt.model.Employee
-
Sets the employee id.
- setName(String) - Method in class net.e4commerce.dpR_tmt.model.Employee
-
Sets the name.
- Store - Class in net.e4commerce.dpR_tmt.dao
-
The Class Store holds an instance of an in-memory RDF4J store.
- Store() - Constructor for class net.e4commerce.dpR_tmt.dao.Store
-
Instantiates a new store.


Gamma-sky.net is an open-source and open-data webpage about the gamma-ray sky.
Read our full documentation here. Also check out our Gamma2016 conference proceeding.
More coming soon!
Created by Christoph Deil and Arjun Voruganti.
If you would like to contribute, check out our repo or email us.
Website version: {{version}}
Last modified: {{lastModified}}


00:57
Best Lap: 01:32
Battery: 99%
Motor
800 RPM
Steuerung
-30°
CPU 1
52%
CPU 2
82%
CPU 3
99%
CPU 4
26%
CPU temp
90°
RAM
73%
73%


Moral Education
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RT @confreaks: New Video! @cascadiaruby -Creating a Chat App in 15 Minutes with Angelo by @hone02, @kenichi_pdx http://confreaks.com/videos/4270-cascadiaruby2014-creating-a-chat-app-in-15-minutes-with-angelo
8/20/2014, 5:45:28 PM
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At Park Finder, we share your love for the outdoors. We are working hard to bring you more parks and an easier way to plan for your next trip. Thanks to Google, Open Weather and the National Park Service for being a part of this project, we could not have done it without you. Please feel free to leave us a comment, a question or anything you'd like, we would love to know how your trip went.
Thank you for coming, we hope you found a great park to visit!
-The Park Finder Team
Giovanna Perina
Front End Dev
Jose Araujo
NPS Back End
Crhistopher Hebeler
Google Maps Back End
Jon Disla
Team Lead


{{ description }}
This app is no longer being maintained. However, it should continue to work and it should still be reasonably secure.
For more details, see the GitHub repository.


Project Ramda
A practical functional library for Javascript programmers.
Goals
Using this library should feel as much like using Javascript as possible. Of course it's functional Javascript, but we're not introducting lambda expressions in strings, we're not borrowing consed lists, we're not porting over all of the Clojure functions.
Our basic data structures will be normal Javascript objects, and our usual collections will be Javascript arrays. We will not try to reach the point where all the functions have only zero, one, or two arguments. We will certainly try to keep some of the normal features of Javascript that seem to be unusual in functional languages, including variable length function signatures and functions as objects with properties.
Ramda will never be a drop-in replacement for Underscore (or LoDash, or even a drop-in-and-mechanically-switch-the-parameter-order-everywhere replacement.) It is intended to work with a different style of coding. Functional programming is in good part about immutable objects and side-effect free functions. While Ramda does not expect to do anything to enforce that style, its code should always work to make that style as frictionless as possible.
As much as we can, we would like the implementation to be both clean and elegant. But the API is king: we will sacrifice a great deal of implementation elegance for even a slightly cleaner API.
Unlike the developers of that silly-named Eweda project, though, this one will focus also on performance, striving for a reliable and quick implementation over any notions of functional purity.
Installation
To use with node:
$ npm install ramda
Then in the console:
var ramda = require('ramda');
To use directly in the browser:
<script src="path/to/yourCopyOf/ramda.js"></script>
or the minified version:
<script src="path/to/yourCopyOf/ramda.min.js"></script>
or from a CDN, either cdnjs:
<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.4.0/ramda.min.js"></script>
or one of the below links from jsDelivr:
<script src="//cdn.jsdelivr.net/ramda/0.4.0/ramda.min.js"></script>
<script src="//cdn.jsdelivr.net/ramda/0.4/ramda.min.js"></script>
<script src="//cdn.jsdelivr.net/ramda/latest/ramda.min.js"></script>
(note that using latest
is taking a significant risk that ramda API changes could break your code.)
These script tags add the variable ramda
on the browser's global scope.
Documentation
Please review the annotated source code documentation (generated by docker). So far, that's the only documentation available. We should have more complete API documentation very soon.
Introductions
- Introducing Ramda by Buzz de Cafe
- Why Ramda? by Scott Sauyet
- Favoring Curry by Scott Sauyet
The Name
Ok, so we like sheep. That's all. It's a short name, not already
taken. It could as easily have been eweda
, but then we would be
forced to say eweda lamb!, and no one wants that. For non-English
speakers, lambs are baby sheep, ewes are female sheep, and rams are male
sheep. So perhaps ramda is a grown-up lambda... but probably not.
Structure
Automatic Currying
The functions included should automatically allow for partial application without an explicit call to lPartial. Many of these operate on lists. A single list parameter should probably come last, which might conflict with the design of other libraries that have strong functional components (I'm looking at you Underscore!)
The idea is that, if foldl has this signature:
var foldl = function(fn, accum, arr) { /* ... */}
and we have this simple function:
var add = function(a, b) {return a + b;};
then, instead of having to manually call lPartial like this:
var sum = lPartial(foldl, add, 0);
var total = sum([1, 2, 3, 4]);
with ramda, we can just do this:
var sum = foldl(add, 0);
var total = sum([1, 2, 3, 4]);
So What's With Eweda?
The eweda library was written by the developers of this library, with similar goals. But that one strove more for implementation elegance than for practical capabilities. Ramda is all about giving users real-world tools. Eweda can be seen more as an academic excercise, mostly proving out what does and doesn't work, and doing so as elegantly as possible.
Acknowledgements
Thanks to J. C. Phillipps for the Ramda logo. Ramda logo artwork © 2014 J. C. Phillipps. Licensed Creative Commons CC BY-NC-SA 3.0.


FROM: MRS. MARIAM M. SESE-SEKO DEAR FRIEND, I AM MRS. SESE-SEKO WIDOW OF LATE PRESIDENT MOBUTU SESE-SEKO OF ZAIRE? NOW KNOWN AS DEMOCRATIC REPUBLIC OF CONGO (DRC). I AM MOVED TO WRITE YOU THIS LETTER,THIS WAS IN CONFIDENCE CONSIDERING MY PRESENT CIRCUMSTANCE AND SITUATION.  HOWEVER DUE TO THIS SITUATION WE DECIDED TO CHANGED MOST OF MY HUSBAND'S BILLIONS OF DOLLARS DEPOSITED IN SWISS BANK AND OTHER COUNTRIES INTO OTHER FORMS OF MONEY CODED FOR SAFE PURPOSE BECAUSE THE NEW HEAD OF STATE OF (DR) MR LAURENT KABILA HAS MADE ARRANGEMENT WITH THE SWISS GOVERNMENT AND OTHER EUROPEAN COUNTRIES TO FREEZE ALL MY LATE HUSBAND'S TREASURES DEPOSITED IN SOME EUROPEAN COUNTRIES.  ONE OF MY LATE HUSBAND'S CHATEAUX IN SOUTHERN FRANCE WAS CONFISCATED BY THE FRENCH GOVERNMENT, AND AS SUCH I HAD TO CHANGE MY IDENTITY SO THAT MY INVESTMENT WILL NOT BE TRACED AND CONFISCATED. I HAVE DEPOSITED THE SUM OF TWENTY EIGHT MLLION UNITED STATE DOLLARS (US$28,000,000.00.) WITH A SECURITY COMPANY , FOR SAFEKEEPING. THE FUNDS ARE SECURITY CODED TO PREVENT THEM FROM KNOWING THE CONTENT.  ACKNOWLEDGE THIS MESSAGE, SO THAT I CAN INTRODUCE YOU TO MY SON (KONGOLO) WHO HAS THE LAYOUT MODALITIES FOR THE CLAIM OF THE SAID FUNDS. I WANT YOU TO ASSIST IN INVESTING THIS MONEY, BUT I WILL NOT WANT MY IDENTITY REVEALED. I WILL ALSO WANT TO BUY PROPERTIES AND STOCK IN MULTI-NATIONAL COMPANIES AND TO ENGAGE IN OTHER SAFE AND NON-SPECULATIVE INVESTMENTS. MAY I AT THIS POINT EMPHASISE THE HIGH LEVEL OF CONFIDENTIALITY, WHICH THIS BUSINESS DEMANDS, AND HOPE YOU WILL NOT BETRAY THE TRUST AND CONFIDENCE, WHICH I REPOSE IN YOU.   BEST REGARDS, MRS M. SESE SEKO


Task 4: Write a function that by a given array of animals, groups them by species and sorts them by number of legs
Task 5: By a given array of animals, find the total number of legs animal can have 2, 4, 6, 8 or 100 legs


Overview.md
Akshat Gupta 👨🏻💻
I'm a Software Developer experienced in Frontend Web Development,
Cloud Computing,
SEO, Digital Marketing, SEM & Offline Marketing.
When I am not coding, I am organising or taking part in workshops, webinars &
hackathons, writing blogs, solving doubts and mentoring students.
I'm always open to have a talk about anything and look forward to getting connected
with you.
My Activities 📬
| Institution | Type | Course | Duration |
|---|---|---|---|
| Vellore Institute Of Technology, Vellore | University | B.Tech.: Information Technology | 2018-2022 |
| Chinmaya Vidyalaya Tapovanam, Kilpauk | High School | PCM + Computer Science | 2009-2018 |
| Chinmaya Vidyalaya, Harrington Road | Primary School | General | 2005-2009 |
Education.md
Do I depend solely on books? 📚
When I am not learning in University, I am exploring new web technologies at The Net Ninja on YouTube or learning what went wrong in Stack Overflow.
I've also learnt quite a lot while solving doubts on Stack Overflow as it motivates me to learn stuff I don't already know so I can help out someone else in need.
I am also a mentor for plenty of students and hence giving them tasks and learning with them while solving their problems has also helped shape the person I am today.
| Company | Role | Description | Duration | Feedback |
|---|---|---|---|---|
| Agora | Developer Evangelist Intern | 1. Responsible for making various ad-hoc projects. 2. Writing technical tutorial blogs. 3. Conducting workshops teaching web development and showing how the Agora SDK can be used. 4. Solving customer queries on Slack and Stack Overflow support channels. |
Jun 2021 - Present | |
| Josh Talks | Software Development Intern | 1. Incharge of making the mobile first Josh Skills web portal to improve the
brand's SEO & online presence for their online courses. 2. Incharge of maintaining Josh Skills, Josh Kosh and DigitalBeti. 3. Incharge of managing junior interns, delegating work and coordinating with all teams. 4. Incharge of developing and managing the Josh Recruitment Portal. |
Jun 2020 - Present | View |
| GAIUS Networks | Full Stack Developer | 1. Incharge of making the official web
portal for the company. 2. Responsible for making the official web portal for bublr.io, a community engagement PWA. 3. Responsible for making the official PWA for Flipped Classrooms, an online learning enhancement service. |
July 2022 | View |
| Fame Technologies | Frontend Developer | 1. Responsible for making the Fame Recruit all-in-one portal consisting of a
static display page, pages where students can take tests & apply for jobs;
where companies can set challenges and recruit interested students & an
admin portal to monitor everything. 2. Responsible for making the Master Connects portal where mentors and mentees can connect with each other and provide or find the help needed to succeed in life. |
April 2020 - May 2020 | View |
| Josh Talks | Software Development Intern | 1. Incharge of making the frontend for the Going Online As
Leaders website
portal in association with the Ministry of Tribal Affairs. 2. Incharge of making the frontend for the DigitalBeti portal falling under the Digital India initiative by the Government of India. |
Jan 2020 - Feb 2020 | View |
| FindMind Analytics | Digital Marketing Intern | Incharge of SEO for the company, creation & handling of social media profiles, Google Analytics, Google Webmaster and Google Ads. | Jun 2019 - Aug 2019 | View |
Work.md
Is that all? 🤓
The above table contains a list of internships I've done and my role in that company.
I've also worked on several freelance projects. My most memorable freelance is Onlala, a full fledged e-commerce portal consisting of an admin portal, supplier portal and shopping portal.
I've also completed the Inside Sherpa Virtual Internship by JP Morgan Chase & Co.
I like to keep working on something or the other in order to be productive and learn more while also meeting amazing new people. This is why I keep taking up work and have at times worked on more than 1 project at once.
Skills.md
My Tech Stack 💻
What I Am Learning 📙
I’ve tried to efficiently maximise productivity out of efforts put into the activities I’ve indulged in over the years.
I'm a Web Developer with keen interest in Cloud Computing, SEO & Digital Marketing.
I'm also proficient at public speaking, working in teams, leading teams and management.
Open Source
- One stop solution to make club and chapter recruitments in VIT simpler and
hassle free.
- This project was used by over 17 clubs, teams and chapters in 2020 with
over 70,000 page views and 3,000+ unique users.
CodeChefVIT/Road-To-DEVSOC-Landing
Open Source
Official landing page for Road to DEVSOC 21.
Open Source
With Narrative, anyone can express themself creatively and make exciting comics in minutes through voice based commands and a simple UI.
Open Source
Web application to help convert one programming language's code to another within seconds while also enabling the user to generate code using just logic.
Open Source
A multiservice attachable device (to wheelchairs) for the elderly and handicapped to solve some of the daily challenges faced by millions worldwide.
Projects.md
That's it? 😱
No! The above mentioned projects are just a few open source projects of mine. I have worked on many more projects, a list of which can be found in the projects section on my LinkedIn.
Have a look at some more projects made by me 🤩
| Project | Description | Link |
|---|---|---|
| DigitalBeti | Web portal for Digital Beti in association with Josh Talks and the Digital India initiative. | View |
| Going Online As Leaders | Official Web Portal for Going Online As Leaders in association with the Tribal Ministry of India, Facebook & JoshTalks. | View |
| Josh Skills | Frontend for the mobile first website for Josh Skills with an aim to improve the company's SEO & online presence. | View |
| Lyricist | Lyricist helps get musical notes from online music classes automatically. | View |
| Engagement Monitor | Monitor and analyse active or disinterested members of a WhatsApp group. | View |
Want more? 👀
Check out how I open source on my GitHub profile.
| Award | Description | By | When |
|---|---|---|---|
| DEVSPACE 2021 | Won the Second Place in the Industrial Collaborations by Dyte track out of 1,414 registered users. | Computer Society of India- VIT University | Mar 2021 |
| WomenTechies 2021 | Won the Second Runner Up award in this women-centric hackathon out of around 380 registered users. | DSC VIT | Mar 2021 |
| VIT Hack 2020 | Won the first place in the Gravitas AI Case partner problem statement as well as the AWS Educate open challenge out of over 1,200 registered participants. | Vellore Institute of Technology, Vellore | Oct 2020 |
| Achiever & Special Achiever Award 2020 | Awarded the Achiever Award & Special Achiever Award for exemplary performance at various National & International events and in recognition of my academic performance. | Vellore Institute of Technology, Vellore | Sep 2020 |
| RTE Hack 2020 | Won the Audience’s Favourite Award by being the top voted and most liked project of the hackathon. | Agora.io | Sep 2020 |
| HopHacks Fall 2019 | Won the best Healthcare Hack award powered by Siemens Healthineers out of 44 submitted projects. | Johns Hopkins University | Sep 2019 |
| PennApps 2019 | Qualified for the top 30 teams out of 242 worthy teams. | University of Pennsylvania | Sep 2019 |
| IBM Challenge | Won the IBM Challenge in AngelHack Bangalore out of 46 submitted projects. | AngelHack India | Jun 2019 |
| VinHack | Won third place in VinHack, hosted by VinnovateIT out of 213 registered participants. | VinnovateIT | Mar 2019 |
| 404 Not Found | Won first place in my first Webathon- 404 Not Found, hosted by CodeChef-VIT out 393 registered participants. | CodeChef-VIT | Oct 2018 |
| DevFest 2018 | Won third place in my first Hackathon- DevFest 2018, hosted by DSC-VIT (earlier known as Google Developers Group) out of 150 registered teams. | DSC VIT | Oct 2018 |
Awards_And_Certifications.md
Extra-Curriculars 🥇
You win some, you lose some.
I actively take part in Hackathons, MUNs, Competitive Coding and other unique competitions since I love exploring new things. I'm always up for a challenge and the above table shows how dedicated I am when I want to achieve something.
My Certifications ⬇
- Google Cloud Platform Business Professional Accreditation (Credential ID: 63280081).
- The Fundamentals of Digital Marketing (Credential ID: P7V 2QN 63L).
- Microsoft Learn Student Ambassador.
- Google Cloud Platform Fundamentals: Core Infrastructure (Credential ID: 7PLZLGHTCPFZ).
- Python (Basic) (Credential ID: B7D22892D983).
- All Other Certificates.
Bio
Student || Developer || Programmer


Estimates local surface normals at each point of the given organized point cloud.
More...
#include <pcps_normal_extractor.h>
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float | getSearchRadius () const noexcept |
| | Retrieves the radius of the search circumference to determine the surface normal for each point.
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| bool | setSearchRadius (float searchRadius) noexcept |
| | Sets the radius of the search circumference to determine the surface normal for each point. More...
|
| |
|
bool | flipNormals () const noexcept |
| | Indicates if the output normals must be flipped towards the view point.
|
| |
|
void | setFlipNormals (bool flip) noexcept |
| | Sets if the output normals must be flipped towards the view point.
|
| |
|
const Point & | getFlipViewPoint () const noexcept |
| | Retrieves the view point by wich the output normals must be flipped.
|
| |
| void | setFlipViewPoint (const Point &flipViewPoint) noexcept |
| | Sets the view point by wich the output normals must be flipped. More...
|
| |
| bool | extract (const Cloud &inputPointCloud, Cloud &outputNormalCloud, Context &context) const |
| | Estimates local surface normals at each point of the given organized point cloud. More...
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| bool | extract (const DeviceCloud &inputPointDeviceCloud, DeviceCloud &outputNormalDeviceCloud, Context &context) const |
| | Estimates local surface normals at each point of the given point cloud. More...
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| |
Estimates local surface normals at each point of the given organized point cloud.
See pcl::NormalEstimation: http://pointclouds.org/documentation/tutorials/normal_estimation.php
◆ extract() [1/2]
| bool pcps::NormalExtractor::extract |
( |
const Cloud & |
inputPointCloud, |
|
|
Cloud & |
outputNormalCloud, |
|
|
Context & |
context |
|
) |
| const |
Estimates local surface normals at each point of the given organized point cloud.
- Parameters
-
| inputPointCloud | Input organized point cloud. |
| outputNormalCloud | Stores the output normals for each point. |
| context | Compute context. |
- Returns
- true if the operation was completed successfully; false otherwise.
◆ extract() [2/2]
| bool pcps::NormalExtractor::extract |
( |
const DeviceCloud & |
inputPointDeviceCloud, |
|
|
DeviceCloud & |
outputNormalDeviceCloud, |
|
|
Context & |
context |
|
) |
| const |
Estimates local surface normals at each point of the given point cloud.
- Parameters
-
| inputPointDeviceCloud | Input organized point device cloud. |
| outputNormalDeviceCloud | Stores the output normals for each point. |
| context | Compute context. |
- Returns
- true if the operation was completed successfully; false otherwise.
◆ setFlipViewPoint()
| void pcps::NormalExtractor::setFlipViewPoint |
( |
const Point & |
flipViewPoint | ) |
|
|
noexcept |
Sets the view point by wich the output normals must be flipped.
- Parameters
-
| flipViewPoint | Flip view point. |
◆ setSearchRadius()
| bool pcps::NormalExtractor::setSearchRadius |
( |
float |
searchRadius | ) |
|
|
noexcept |
Sets the radius of the search circumference to determine the surface normal for each point.
- Parameters
-
| searchRadius | Search radius in metres (epsilon..inf). |
- Returns
- true if the operation was completed successfully; false otherwise.
The documentation for this class was generated from the following file:


| Class and Description |
|---|
| Actor
Actor Class that represents the Actor in the Use case diagram
|
| AEntityUsecase
AEntityUsecase abstract class that regroup the Actor and the use case elements
|
| IActor
IActor Interface that represents an Actor
|
| IEntityUsecase
IEntityUsecase Interface that allows to build a UseCaseEntity
|
| INoteUsecase
INote interface is the interface of notes (comments) on a diagram
|
| ISystem
ISystem Interface that allows to build a use case group
|
| IUsecase
IUSecase Interface that allows to create a use case entity
|
| IUsecaseDiagram |
| System
System represents the use case group
|
| Usecase
Usecase Class that allow to create a use case entity
|
| Class and Description |
|---|
| IActor
IActor Interface that represents an Actor
|
| INoteUsecase
INote interface is the interface of notes (comments) on a diagram
|
| ISystem
ISystem Interface that allows to build a use case group
|
| IUsecase
IUSecase Interface that allows to create a use case entity
|
| IUsecaseDiagram |
| Class and Description |
|---|
| UsecaseDiagram
DiagramUsecase represents the use case Diagram
|
| Class and Description |
|---|
| Actor
Actor Class that represents the Actor in the Use case diagram
|
| IUsecaseDiagram |
| NoteUsecase
Note class represents the notes (comments) on a diagram
|
| System
System represents the use case group
|
| Usecase
Usecase Class that allow to create a use case entity
|
| Class and Description |
|---|
| IActor
IActor Interface that represents an Actor
|
| INoteUsecase
INote interface is the interface of notes (comments) on a diagram
|
| IUsecase
IUSecase Interface that allows to create a use case entity
|
| IUsecaseDiagram |
| Class and Description |
|---|
| Actor
Actor Class that represents the Actor in the Use case diagram
|
| INoteUsecase
INote interface is the interface of notes (comments) on a diagram
|
| IUsecase
IUSecase Interface that allows to create a use case entity
|
| Class and Description |
|---|
| IActor
IActor Interface that represents an Actor
|
| INoteUsecase
INote interface is the interface of notes (comments) on a diagram
|
| IUsecase
IUSecase Interface that allows to create a use case entity
|
| IUsecaseDiagram |
Copyright © 2016 Your Organisation. All rights reserved.


'Quite optimistic': Ryan Straschnitzki has spinal surgery in Thailand
by CP, The Canadian PressBANGKOK — A hockey player paralyzed in the Humboldt Broncos bus crash has received spinal surgery in Thailand that he hopes will restore some of his movement.
Doctors on Monday implanted an epidural stimulator in Ryan Straschnitzki’s spine.
The 20-year-old from Airdrie, Alta., is to remain in Thailand until early December.
“The doctor said it went very well. He’s quite optimistic,” Michelle Straschnitzki said after receiving an update from her husband, who travelled with their son to Asia.
“He’s got a long couple of weeks for recovery, and he’s pretty well out of it right now.”
Straschnitzki was one of 13 players who were injured when an inexperienced truck driver blew through a stop sign and into the path of the Saskatchewan junior hockey team’s bus in April 2018. Sixteen others on the bus died.
Straschnitzki, who was paralyzed from the chest down, has said he isn’t expecting a cure but hopes the implant will restore some muscle movement and things such as bladder control.
A small device like a remote control is to send electrical currents to his spinal cord to try to stimulate nerves and move limbs. The implant is to be programmed over the next few weeks to stimulate certain nerves mapped out by surgeons and therapists.
The surgery can cost up to $100,000 and isn’t covered by health care or insurance. It is also performed in countries such as the United States and Switzerland, but it’s much cheaper in Thailand.
Straschnitzki is hoping to make Canada’s national sledge hockey team and go to the Paralympics. He took his hockey sled to Thailand with him to stay sharp during his stay.
“Before he went in, he texted a guy out here about ice time for Wednesday,” his father said on Twitter just before the surgery. “Ha, ha. What a kid.”
— By Bill Graveland in Calgary


WITNESS LIST Government Organization Committee May 6, 2004 - 1:00P Interim Charge 1 ON: Combs, Susan Commissioner of Agriculture (Texas Department of Agriculture), Austin, TX Hernandez, Ricardo Executive Director (Texas Commission on the Arts), Austin, TX Kuntz, William Executive Director (Texas Department of Licensing and Regulation), Austin, TX Ladensohn, Claudia Volunteer (Texas Commission on the Arts), Austin, TX Levine, Ken Deputy Director (Sunset Commission), Austin, TX Nau, III, John L. CEO, Silver Eagle Distributors (Texas Historical Commission), Austin, TX Rudd, Peggy D. Director and Librarian (Texas State Library and Archives), Austin, TX Zukowski, Dr. Jim Chief, Licensing and Compliance (Texas Department of Health), Austin, TX Registering, but not testifying: Against: Villalpando, Nick Audit Manager (Texas State Auditor's Office), Austin, TX On: McClure, Stacey Human Resource Consultant (Texas State Auditor's Office), Austin, TX Oaks, Larry Executive Director (Texas Historical Commission), Austin, TX Pickett, Sandra Chair (Texas State Library and Archives), Austin, TX Vice, Sandra Audit Manager (Texas State Auditor's Office), Austin, TX Interim Charge 2 ON: Johnson, Edward Director, Legislative Affairs (Texas Building and Procurement Commission), Austin, TX Livingston, Brad Chief Financial Officer (Texas Department of Criminal Justice), Austin, TX Patterson, Jerry Commissioner (Texas General Land Office), Austin, TX Williams, Cathy Asst. Exec. Dir for Support Operations (Texas Department of Transportation), Austin, TX Registering, but not testifying: On: Wright, Bill Investments (TCA), Austin, TX


WITNESS LIST Electric Utility Restructuring - Special Committee February 22, 1999-9:30A SB 7 For: Akers, Monte (Texas Municipal League), Austin Blunden, Julie (Green Mountain Energy Resources), San Francisco Jennings, Randy (Independent Electrical Contractors of Central Texas), Austin Joiner, Gary (Texas Farm Bureau), Austin King, Robert J. (Texas Energy Service Companies), Austin Krog, Mark (Siemens), Irving Magruder, Kathleen (Enron Corp), Houston Maurer, Jeff (Enron Wind Corp), Tehachapi, Ca Mintz, David (Texas Apartment Association), Austin Moore, Mickey (Texas Retailers Association), Austin Noble, Shannon (Texas Air Conditioning Contractors Assoc.), Austin Sargent, Jim (Self), Waxahachie Sloan, Mike (Texas Renewable Power Coalition), Austin Tramuto, James (Competitive Power Advocates), Houston Walters, Robert R. (Self & Entech, Inc.), Keller Williams, Mike (Texas Electric Cooperatives), Austin Zion, Mark (TPPA), Austin Against: Biedrzycki, Carol (Texas Ratepayers' Organization to Save Energy), Austin Briesemeister, Janee (Consumers Union), Austin Chapman, Randall (Self), Austin Smith, Tom "Smitty" (Public Citizen), Austin On: Anderson, D. "Sparky" (Clean Water Action), Austin Baker, Roy (AARP), Greenville Baker, Tom (AECT), Austin Benold, Stephanie (Texas PTA), Austin Dewhurst, David (General Land Office), Austin Hagan, Tom (AECT), Austin Kroger, Stephanie (Texas Coalition for Competitive Electricity), Austin Levy, Rick (Tx AFL-CIO & Tx Assoc. of Electrical Workers), Austin Lopez, Nieves (Texas Department of Housing & Community Affairs), Austin MacLeod, Mark (Environmental Defense Fund), Austin Main, Todd (Texas Campaign for the Environment), Austin Marsden, Julia (League of Women Voters of Texas), Austin McClellan, Suzi (Office of Public Utility Counsel), Austin Schaeffer, Steve (AECT), Austin Suozzo, Margaret (American Council for an Energy-Efficient Economy), Austin Thompson, Dwight (Citizens of West Lake Hills), West Lake Hills Registering, but not testifying: For: Crow, Chris (Enron Wind Development Corp.), Austin Glotfelty, Jimmy (Calpine Corporation), Austin Hammond, Bill (Tx Assoc of Business and Chambers of Commerce), Austin Johnson, Stan (Stan's Heating & Air Cond. Inc.), Austin Osgood, John (Texas Air Conditioning Contractors Assoc.), Austin Ramos, Joe (Texas Association of School Boards), Austin Reynolds, Jim (Mechanical Contractors Assoc. of Texas), Austin Against: Fitzpatrick, James M. (Self), Austin Fitzpatrick, Virginia (Self), Austin On: Mulvey, Garland (Clean Water Action), Cleburne


Next: Cube Viewer Widget
Up: The Menu
Previous: The Settings Menu
- Online Manual:
- Display this Manual as a browseable page within QDeblend
.
- Version:
- Current Version of QDeblend
.
- AboutQt:
- Qt Version and other related information.
Bernd Husemann
2011-04-07


What is the difference between Margin, Border and Padding? Here is an explanation:
Margin is the distance an element has to be from an adjacent element. So, if the margin of an element on the top is 50 pixels, There must be 50 px of space above the element before another element should be able to reside. *It is important to remember that if that element above has a margin of 70 px, there will 70 px of space between the top and bottom element. The greater of the two corresponding margins is the one that manifests. Padding, on the other hand, is the distance between the border of an element and the content within it. So if there is an image with a padding of 10px from the top within a div, the image will be 10px from the top border of that element. A schematic was taken from stackoverflow.com:


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Before Change
def make_features(batch, fields):
// This is a bit hacky for now.
feats = []
for j in range(100):
key = "src_feat_" + str(j)
if key not in fields:
break
feats.append(batch.__dict__[key])
cat = [batch.src[0]] + feats
cat = [c.unsqueeze(2) for c in cat]
return torch.cat(cat, 2)
After Change
_, src_lengths = batch.src
src = onmt.IO.make_features(batch, self.fields)
// (1) run the encoder on the src
encStates, context = self.model.encoder(src, lengths=src_lengths)
encStates = self.model.init_decoder_state(context, encStates)
useMasking = (self._type == "text")
// This mask is applied to the attention model inside the decoder


Muriel
Bowser’s administration says move is unrelated to charges that encryption caused failures in
Metro.
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REQUEST
A QUOTE
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