Package datamodel.categories
Class ModelCategory<T>
java.lang.Object
datamodel.categories.ModelCategory<T>
- Type Parameters:
T
- A generic type
public class ModelCategory<T> extends java.lang.Object implements Category<T>
A class that implements the Category interface. Saves the counts for the data in arrays of hashmaps and hashmaps.
Saves a list of labels, the category name and the total number of labels
- Since:
- 2020-05-06
- Version:
- 1.0.0
- Author:
- Marcelo Jacinto, David Souto, Gonçalo Tomás
- See Also:
Model
,Category
,ModelClassfication
,TreeAugmentedNayveBayes
-
Field Summary
Fields Modifier and Type Field Description protected java.lang.String
categoryName
The name of the category: ex.protected java.util.List<T>
labels
A list with all the labels that were observed: example: 0, 1, 2protected java.util.HashMap<java.lang.String,java.lang.Integer>[]
N_ijc
An array of HashMap that considers in each position of the array a diferent parent for the current node Saves the N_ijc count, and its indexed by a String of type "i,j,c" in the correct hashmap depending on the parent of the nodeprotected java.util.HashMap<java.lang.String,java.lang.Integer>[]
N_ijkc
An array of HashMap that considers in each position of the array a diferent parent for the current node Saves the N_ijkc count, and its indexed by a String of type "i,j,k,c" in the correct hashmap depending on the parent of the nodeprotected java.util.HashMap<java.lang.String,java.lang.Integer>
N_ikc
An HashMap that save the N_ikc count, and its indexed by a String of type "i,k,c"protected int
totalNumberLabels
The total number of different labels this category has: example- 0,1,2 - totalNumberLabels = 3 -
Constructor Summary
Constructors Constructor Description ModelCategory(java.lang.String categoryName, int numCategories)
The constructor for the ModelCategory. -
Method Summary
Modifier and Type Method Description boolean
addLabelIfNotExistent(T data)
A method that adds a label to the category if it does not exist there yetboolean
equals(java.lang.Object o)
Redefinition of the equals() method.java.util.List<T>
getAllLabels()
A method that return the list of labels saved for this categoryjava.lang.String
getCategoryName()
A method that should return the category name (ex: "Color")int
getIndexOfLabel(T label)
A method that should return the index of a certain label of the category (ex: index of the label "green")int
getLabelIndex(T data)
A method that should return the index of a certain label of the category (ex: index of the label "green")T
getLabelOfIndex(int i)
A method that should return a label given its indexint
getNijc(int i, int j, int c, int parentNode)
A method that should return the N_ijc countint
getNijkc(int i, int j, int k, int c, int parentNode)
A method that should return the N_ijkc countsint
getNikc(int i, int k, int c)
A method that should return the N_ikc countint
getNumLabels()
A method that returns the total number of labels for this categoryint
hashCode()
Redefinition of the hashcode method.void
incrementNijc(int i, int j, int c, int parentNode)
A method that should increment the Nijc countvoid
incrementNijkc(int i, int j, int k, int c, int parentNode)
A method that should increment the Nijkc countvoid
incrementNikc(int i, int k, int c)
A method that should increment the Nikc countjava.lang.String
toString()
Redefinition of the toString() method.
-
Field Details
-
categoryName
protected java.lang.String categoryNameThe name of the category: ex. X1 -
totalNumberLabels
protected int totalNumberLabelsThe total number of different labels this category has: example- 0,1,2 - totalNumberLabels = 3 -
labels
A list with all the labels that were observed: example: 0, 1, 2 -
N_ijkc
protected java.util.HashMap<java.lang.String,java.lang.Integer>[] N_ijkcAn array of HashMap that considers in each position of the array a diferent parent for the current node Saves the N_ijkc count, and its indexed by a String of type "i,j,k,c" in the correct hashmap depending on the parent of the node -
N_ijc
protected java.util.HashMap<java.lang.String,java.lang.Integer>[] N_ijcAn array of HashMap that considers in each position of the array a diferent parent for the current node Saves the N_ijc count, and its indexed by a String of type "i,j,c" in the correct hashmap depending on the parent of the node -
N_ikc
protected java.util.HashMap<java.lang.String,java.lang.Integer> N_ikcAn HashMap that save the N_ikc count, and its indexed by a String of type "i,k,c"
-
-
Constructor Details
-
ModelCategory
public ModelCategory(java.lang.String categoryName, int numCategories)The constructor for the ModelCategory. Receives as parameters a string with the name of the category and the number of categories that is going to be considered (in order to instantiate the arrays that relates this category with others)- Parameters:
categoryName
- A String with the category name : Ex("Color")numCategories
- An int with the total number of categories - Ex.3 (Color, shape, age)
-
-
Method Details
-
getCategoryName
public java.lang.String getCategoryName()A method that should return the category name (ex: "Color")- Specified by:
getCategoryName
in interfaceCategory<T>
- Returns:
- A String with the category name
-
getIndexOfLabel
A method that should return the index of a certain label of the category (ex: index of the label "green")- Specified by:
getIndexOfLabel
in interfaceCategory<T>
- Parameters:
label
- A generic type with the label- Returns:
- An int with the index
-
getNumLabels
public int getNumLabels()A method that returns the total number of labels for this category- Specified by:
getNumLabels
in interfaceModel<T>
- Returns:
- An int with the total number of labels
-
getAllLabels
A method that return the list of labels saved for this category- Specified by:
getAllLabels
in interfaceModel<T>
- Returns:
- A list of generic type with the labels
-
addLabelIfNotExistent
A method that adds a label to the category if it does not exist there yet- Specified by:
addLabelIfNotExistent
in interfaceModel<T>
- Parameters:
data
- A generic type with a label to be saved- Returns:
- A boolean that returns true if it was added to the list
-
getLabelIndex
A method that should return the index of a certain label of the category (ex: index of the label "green")- Specified by:
getLabelIndex
in interfaceModel<T>
- Parameters:
data
- A generic type with a label- Returns:
- An int with the index
-
getLabelOfIndex
A method that should return a label given its index- Specified by:
getLabelOfIndex
in interfaceModel<T>
- Parameters:
i
- An int with the index of a given label- Returns:
- A generic type with the label
-
getNijkc
public int getNijkc(int i, int j, int k, int c, int parentNode)A method that should return the N_ijkc counts- Specified by:
getNijkc
in interfaceCategory<T>
- Parameters:
i
- An int with the node index that we are consideringj
- An int with the configuration of the parent of that nodek
- An int with the configuration of the nodec
- An int with the configuration of the classificationparentNode
- An int with the parent of the node- Returns:
- An int with the counts for that combination
-
getNikc
public int getNikc(int i, int k, int c)A method that should return the N_ikc count -
getNijc
public int getNijc(int i, int j, int c, int parentNode)A method that should return the N_ijc count- Specified by:
getNijc
in interfaceCategory<T>
- Parameters:
i
- An int with the node index that we are consideringj
- An int with the configuration of the parent of that nodec
- An int with the configuration of the classificationparentNode
- An int with the parent of the node- Returns:
- An int with the counts for that combination
-
incrementNikc
public void incrementNikc(int i, int k, int c)A method that should increment the Nikc count- Specified by:
incrementNikc
in interfaceCategory<T>
- Parameters:
i
- An int with the node index that we are consideringk
- An int with the configuration of the nodec
- An int with the configuration of the classification
-
incrementNijkc
public void incrementNijkc(int i, int j, int k, int c, int parentNode)A method that should increment the Nijkc count- Specified by:
incrementNijkc
in interfaceCategory<T>
- Parameters:
i
- An int with the node index that we are consideringj
- An int with the configuration of the parent of that nodek
- An int with the configuration of the nodec
- An int with the configuration of the classificationparentNode
- An int with the parent of the node
-
incrementNijc
public void incrementNijc(int i, int j, int c, int parentNode)A method that should increment the Nijc count- Specified by:
incrementNijc
in interfaceCategory<T>
- Parameters:
i
- An int with the node index that we are consideringj
- An int with the configuration of the parent of that nodec
- An int with the configuration of the classificationparentNode
- An int with the parent of the node
-
toString
public java.lang.String toString()Redefinition of the toString() method. Prints the values of Nijkc, Nijc and Nikc- Overrides:
toString
in classjava.lang.Object
- Returns:
- A String with the relevant values
-
equals
public boolean equals(java.lang.Object o)Redefinition of the equals() method. Uses the total number of labels, the category name, the labels themselves, the Nijkc, Nikc and Nijc counts- Overrides:
equals
in classjava.lang.Object
- Parameters:
o
- Another ModelCategory object- Returns:
- A boolean with true of false
-
hashCode
public int hashCode()Redefinition of the hashcode method. Uses the total number of labels, the category name, the labels themselves, the Nijkc, Nikc and Nijc counts- Overrides:
hashCode
in classjava.lang.Object
- Returns:
- An int with the hashcode value
-


gftype - translate a generic font file for humans to read
gftype
gf_file_name
This manual page is not meant to be exhaustive. The complete documentation for this version of *(TX can be found in the info file or manual Web2C: A TeX implementation .
The gftype program translates a gf (generic font) file output by, for example, mf (1)to a file that humans can read. It also serves as a gf file-validating program (i.e., if gftype can read it, it's correct) and as an example of a gf -reading program for other software that wants to read gf files.
The gf_file_name on the command line must be complete. Because the resolution is part of the extension, it would not make sense to append a default extension as is done with *(TX or DVI-reading software. If no output_file_name is specified, the output goes to stdout .
The output file includes bitmap images of the characters, if -i is given on the command line, and a symbolic listing of the gf commands, if -m is specified.
gftype looks for gf_file_name using the environment variable GFFONTS. If that is not set, it uses the variable TEXFONTS. If that is not set, it uses the system default.
dvitype (1), pktype (1).
Donald E. Knuth et al., \*(MFware .
David Fuchs and Don Knuth wrote the program. It was published as part of the \*(MFware technical report, available from the *(TX Users Group. Paul Richards originally ported it to Unix.


Orders
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Card Number
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Location
Orders Count
Orders Total
Median Value
Average Check
Average Check (Female)
Average Check (Male)


Override pages are a way to replace a page that Google Chrome provides with an HTML file that your extension provides. An override page usually has CSS and JavaScript code, in addition to HTML.
Currently, the only page you can replace is the New Tab page — the page that appears when the user creates a new tab or window.
| The default New Tab page | An alternative New Tab page |
Register your New Tab page in the extension manifest like this:
{ "name": "My extension", ... "chrome_url_overrides": { "newtab": "newtab.html" }, ... }
For an effective New Tab page, follow these guidelines:
Make your page quick and small.
Because the New Tab page appears often,
its performance is important.
For example, avoid synchronous fetches of network or database resources.
Include a title in your page.
Otherwise people will see the URL of the page,
which might confuse them.
Here's an example of specifying the title:
<title>New Tab</title>
Don't rely on the page having the keyboard focus.
The address bar always gets the focus first
when the user creates a new tab.
Don't try to emulate the default New Tab page.
The APIs necessary to create
a slightly modified version of the default New Tab page —
with top pages,
recently closed pages,
tips,
a theme background image,
and so on —
don't exist yet.
Until they do,
you're better off trying to make something completely different.
You can find simple examples of defining override pages in the examples/api/override directory. For other examples and for help in viewing the source code, see Samples.


1) Habit Tracker only support daily counter
2) You can only click Relapse or Check-In once a day
3) Feel free to adjust your Target Day
4) What is consider as Positive:
* If you want to make good habits every day, pick Positive, eg; Learn English, Read Book, etc
* If your Target Day is 10, make sure to Check-In every day for 10 consecutive days starting from the Start Date to achieve a 100% Progress score
* Progress score is reset to 0 if you forgot to click Check-In everyday
* Do your best to keep Check-In every day to keep your Idle Days as low as possible
* High number of Idle Days is considered bad
* Low number of Check-In Counter is considered bad
5) What is consider as Negative:
* If you want to quit bad habits every day, pick Negative, eg; Quit Smoking, Quit Gambling, etc
* If your Target Day is 10, try your best not to Relapse between the Start Date to 10 days after the Start Date to achieve a 100% Progress score
* Progress score is reset to 0 if you click Relapse
* Try your best not to Relapse to keep your Restrain Days as high as posibble
* Low number of Restrain Days is considered bad
* High number of Relapse Counter is considered bad


mouse click: add red data point shift + mouse click: add green data point 'r': retrain
number of trees = 100 (set this high for smoother and more regularized final prediction. Higher = always better, but slower.)
max depth = 4 (depth of each tree in the forest. Set this higher when more complicated decision boundaries are needed (but runs exponentially slower and can be more prone to overfitting if not enough trees). Usually if you can afford many trees and resources you want to set this higher.)
hypotheses / node = 10 (number of random hypotheses considered at each node during training. Setting this too high puts you in danger of overfitting your data because nodes in the forest lose variety.)
A bit of explanation: Random forests are a collection of independent trees. Each tree is made up of nodes arranged in tree structure. Every node receives data from the top, and splits it to its 2 children based on some very simple decision (such as if x-coordinate > 3). To get the decision, during training a few random splitting rules are generated at each node and the "best" one is kept.


DeckerToday at 9:30 AM
with this:
/* https://en.bitcoin.it/wiki/Protocol_documentation#Variable_length_integer */
if (this.txCount < 0xfd){
var varInt = new Buffer(txCount, 'hex');
}
else if (this.txCount <= 0xffff){
var varInt = new Buffer.concat([Buffer('FD', 'hex'), util.reverseBuffer(new Buffer(txCount, 'hex'))]);
}
i mined 180 tx in block without any issues ... and it's not rejected ...
(edited)


NationStates++
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Search engine:
Usage: Select your Qt version and search engine from the drop-down menus above. Type q d space into your browser's address bar to perform a search.
Search engine:
Usage: Select your Qt version and search engine from the drop-down menus above. Type q d space into your browser's address bar to perform a search.


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没有伊斯兰的世界
埃及军方自赋的使命感
作为中情局和RAND的专家：政府很方便的把一切罪过都归因于宗教。但Fuller用因素分析法证明，大部分争斗都是基于政治或经济的原因，剩下的小部分是因为愚昧和误会。真正由于宗教而导致的战争，可能就是政府与宗教的争夺。
What if Islam had never existed? To some, it's a comforting thought: No clash of civilizations, no holy wars, no terrorists. Would Christianity have taken over the world? Would the Middle East be a peaceful beacon of democracy? Would 9/11 have happened? In fact, remove Islam from the path of history, and the world ends up exactly where it is today.
Graham E. Fuller is an American author and political analyst, specializing in Islamic extremism. Formerly vice-chair of the National Intelligence Council, he also served as Station Chief in Kabul for the CIA. A "think piece" that Fuller wrote for the CIA was identified as instrumental in leading to the Iran-contra affair. After a career in the United States State Department and CIA （中情局） lasting 27 years, he joined Rand （兰德） Corporation as senior political scientist specializing in the Middle East. As of 2006, he was affiliated with the Simon Fraser University in Vancouver, Canada as an adjunct professor of history. He is the author of a number of books, including The Future of Political Islam.
参考：
Graham E. Fuller, A World Without Islam
Keohane, Power and Interdependence. (NeoLiberal)
Wendt, Social Theory of International Politics. (Constructivism)
Waltz, Theory of international politics. (NeoRealist)
《穆斯林的葬礼》 霍达
更多资讯，请访问： retter2012.com 。
“民族主义”与“五族共和”，这悖论如何解决？首先是相互理解，汉人高级干部要首先学习主要民族的语言和文化。否则，一切经济政治和军事手段都是无的放矢。除王蒙外，估计少有部长高官能担此重任。例如，粤语存废的问题，简体字正体字问题。大陆地区的电视节目，除广东外，全部实施普通话播出。在解放初如此狂热之际，粤语仍然在广播。现在，有更多人学说粤语了。当年晋商，为了生意不也认真学习蒙语、维语、俄语的吗？东南沿海，会荷兰语、英语、葡萄牙语、西班牙语的不在少数。广东外语外贸大学阿拉伯语专业，《古兰经》只学一页。我们怕什么？为什么现在就不行了呢？
大营子娃娃，小营子狗。不信，请看 Olympus Has Fallen （2013）。
version:1.0<EMAIL_ADDRESS>© retter2012.com


Added a memory monitor for better memory management for out of core processing
Added list_tables() and describe_table() functions
Added support for constant expressions evaluation by Calcite
Added support for cross join
Added rand() and support for running unary operations on literals
Added get_free_memory() function
Implemented Unordered pull from cache to help performance
Concatenating cache improvement and replacing PartwiseJoin::load_set with a concatenating cache
Adding max kernel num threads pool
Added new separate thresh for concat cache
Added checks for concatenation to prevent String overflow
Added nogil statements for pure C functions in Cython
Round robing dask workers on single gpu queries
Reraising query errors in context.py
Implemented using threadpool for outgoing messages
Added exhale to generate doxygen for sphinx docs
Added Sphinx based code architecture documentation
Added doxygen comments to CacheMachine.h
Added more documentation about memory management
Updated readme
Added doxygen comments to some kernels and the batch processing
Updated Calcite to the most recent version 1.23
Added check for CUDF_HOME to allow build to use an existing prebuilt cudf source tree
Python/Cython check code style
Make AWS and GCS optional
Logging level (flush_on) can be configurable
Set log_level when using LOGGING_LEVEL param
Added unit tests on Calcite to check how logical plans are affected when rulesets are updated
Updated set of TPCH queries on the E2E tests
Added initial set of unit tests for WaitingQueue and nullptr checks around spdlog calls
Add unit test for Project kernel
Removed a lot of dead code from the codebase
Replace random_generator with cudf::sample
Adding extern C for include files
Use default client and network interface from Dask. BlazingSQL should now be able to infer the network interface.
Updated the GPUManager functions
Handle exceptions from pool_threads
Various fixing of issues due to updates to cudf
Fixed issue with Hive partitions when doing SELECT *
Normalize columns before distribution in JoinPartitionKernel
Fixed issue with hive partitions base folder
Fix interops operators output types
Fix when the algebra plan was provided using one-line as logical plan
Fix issue related to Hive metadata
Remove temp files from data cached to disk
Fix when checking only Limit and Scan Kernels
Loading one file at a time (LimitKernel and ScanKernel)
Fixed small issue with hive types conversion
Fix for literal cast
Fixed issue with start and length of substring being different types
Fixed issue on logical plans when there is an EXISTS clause
Fixed issue with casting string to string
Fixed issue with getting table scan info
Fixed row_groups issue in ParquetParser.cpp
Fixed issue with some constant expressions not evaluated by calcite
Fixed issue with log directory creation in a distributed environment
Fixed issue where we were including testing hpp in our code
Fixed optimization regression on the select count(*) case
Fixed issue caused by using new arrow_io_source
Fixed e2e string comparison
Fixed random segfault issue in parser
Fixed issue with column names on sample function
Introduced config param for max orderby samples and fixed issue with oversampling in ORDER BY


{% extends 'base/base.html' %} {% load static %} {% block title %}Resources{% endblock %} {% block head %} {% endblock %} {% block content %} {% include "base/navbar.html" %} Resources Guides Made by us, for you Read Lovingly curated books to explore Watch Visually engaging Try Interactively discover the possibilities Learn Structured courses with clear goals Communities Some of our best friends Listen Regular podcasts to follow Tools Things we love to use {% endblock %}
Guides
Made by us, for you
Read
Lovingly curated books to explore
Watch
Visually engaging
Try
Interactively discover the possibilities
Learn
Structured courses with clear goals
Communities
Some of our best friends
Listen
Regular podcasts to follow
Tools
Things we love to use


1-Which one is Html shortening?
2-Which one is Css shortening?
3-What is Javascript?
4-Html attributes:
5-HTML links are hyperlinks:
6-HTML The class Attribute:
7-Which one is JavaScript modulus operator:
8-JavaScript Function Syntax:
9-Return Keyword
10-Which is an Array?


Hadoop Deployment Layout
Introduction
This document describes the standard deployment layout for Hadoop. With increased complexity and evolving Hadoop ecosystem, having standard deployment layout ensures better integration between Hadoop sub-projects. By making the installation process easier, we can lower the barrier to entry and increase Hadoop adoption.
Packages
We need to divide Hadoop up into packages that can be independently upgraded. The list of packages should include:
- Hadoop Common - Common including the native code and required jar files.
- HDFS Client - HDFS jars, scripts, and shared libraries.
- HDFS Server - jsvc executable
- Yarn Client - Yarn client jars and scripts
- Yarn Server - Yarn server jars and scripts
- MapReduce - MapReduce jars, scripts, and shared libraries
- LZO - LZ0 codec from github.com/omally/hadoop-gpl-compression
- Metrics - Plugins for Chukwa and Ganglia
Packages from other teams will include:
- Pig
- Hive
- Oozie client
- Oozie server
- Howl client
- Howl server
These packages should be deployable with RPM on RedHat. We also need a package that depends on a version of each of these packages. In general, we can generate tarballs in the new deployment layout.
Note that some packages, like Pig, which are user facing, will have 2 versions installed in a given deployment. This will be accomplished by modifying the package name and the associated binaries to include the version number.
All of the following paths are based on a prefix directory that is the root of the installation. Our packages must support having multiple Hadoop stack installation on a computer at the same time. For RPMs, this means that the packages must be relocatable and honor the --prefix option.
Deployment
It is important to have a standard deployment that results from installing the packages regardless of the package manager. Here are the top level directories and a sample of what would be under each. Note that all of the packages are installed "flattened" into the prefix directory. For compatibility reasons, we should create "share/hadoop" that matches the old HADOOP_HOME and set the HADOOP_HOME variable to that.
$PREFIX/ bin / hadoop | | mapred | | pig -> pig7 | | pig6 | + pig7 | + etc / hadoop / core-site.xml | | hdfs-site.xml | + mapred-site.xml | + include / hadoop / Pipes.hh | | + TemplateFactory.hh | + hdfs.h | + lib / jni / hadoop-common / libhadoop.so.0.20.0 | | | | libhdfs.so -> libhdfs.so.0.20.0 | + libhdfs.so.0.20.0 | + libexec / task-controller | + man / man1 / hadoop.1 | | mapred.1 | | pig6.1 | + pig7.1 | + share / hadoop-common | | hadoop-hdfs | | hadoop-mapreduce | | pig6 | + pig7 | + sbin / hdfs-admin | | mapred-admin | + src / hadoop-common | | hadoop-hdfs | + hadoop-mapreduce | + var / lib / data-node | + task-tracker | | log / hadoop-datanode | + hadoop-tasktracker | + run / hadoop-datanode.pid + hadoop-tasktracker.pid
Note that we must continue to honor HADOOP_CONF_DIR to override the configuration location, but that it should default to $prefix/etc. User facing binaries and scripts go into bin. Configuration files go into etc with multiple configuration files having a directory. JNI shared libraries go into lib/jni/$tool since Java does not allow to specify the version of the library to load. Libraries that aren't loaded via System.loadLibrary are placed directly under lib. 64 bit versions of the libraries for platforms that support them should be placed in lib64. All of the architecture-independent pieces, including the jars for each tool will be placed in share/$tool. The default location for all the run time information will be in var. The storage will be in var/lib, the logs in var/log and the pid files in var/run.
Path Configurations
Path can be configured at compile phase or installation phase. For RPM, it takes advantage of the --relocate directive to allow path reconfiguration at install phase. For Debian package, path is configured at compile phase.
Build phase parameter:
- package.prefix - Location of package prefix (Default /usr)
- package.conf.dir - Location of configuration directory (Default /etc/hadoop)
- package.log.dir - Location of log directory (Default /var/log/hadoop)
- package.pid.dir - Location of pid directory (Default /var/run/hadoop)
Install phase parameter:
rpm -i hadoop-[version]-[rev].[arch].rpm \ --relocate /usr=/usr/local/hadoop \ --relocate /etc/hadoop=/usr/local/etc/hadoop \ --relocate /var/log/hadoop=/opt/logs/hadoop \ --relocate /var/run/hadoop=/opt/run/hadoop


The Lion of Africa (1987)
Grade: 67
"The Lion of Africa" is an HBO-produced movie that stars Brian Dennehy and Brooke Adams. Adams is a volunteer doctor in remote Africa, trying to fight a cholera plague in a village. She has two problems: she does not have the proper medicine to treat them, and she has had a curse put on her by the local witch doctor. The curse can only be removed by returning to the village with supplies to stop the plague. (The witch doctor has also taken her glasses, which she doesn't seem to miss at any time in the movie).
The medicine is only available in a distant African town. She has no transportation to get there. The local official, a well-mannered graduate of Cambridge University, cares only about improving his own status, which he does primarily by taking kickbacks from illegal diamond smuggling. Adams turns to Dennehy, who has a massive truck (named "The Lion of Africa") and has made the trip before.
But Dennehy, a weathered, burly man known as "the Trader", wants only to enjoy the comforts of the local whorehouse. Adams only succeeds in obtaining a large diamond, surreptiously given to her by a dying smuggler. This million-dollar diamond is the subject of an intensive search by all of the rascals in the village. Travel permits are revoked until the diamond is found.
Desperate, Adams steals Dennehy's truck.  When she comes to, she offers a deal he can't refuse: a share of diamond in return for a trip to the distant town.
On the road, they have an adversarial relationship, bickering and trying to out-tough the other. Soon they meet local police, who are after the diamond and have rifles. They flee, with the police firing multiple shots at Dennehy, who is cowering in the truck bed. They get away.
Diamond smugglers are also after Dennehy. Eventually, they catch up with him, torch his truck, take the diamond and string up Adams and Dennehy, leaving them for dead. This being a movie, the two escape their nooses, and, incredibly, decide to go after the heavily armed smugglers to recover the diamond.
By this time, the couple has warmed to each other and are even making post-diamond-sale romantic plans. Confronting the smugglers, there is an extended shoot-out sequence. Their luck continues as the smugglers continue to miss clean shots at the pair. The bad guys are terminated one by one, the diamond is recovered, but Adams steals and sells it, and takes a helicopter flight to the village to remove the curse. She leaves a package of money at the airport for Dennehy, hot on her trail, but unluckily he runs into the corrupt local official, who takes half of it.
At least Dennehy can fix up his truck now. He returns to his favorite whorehouse, only to find Adams there. He has not been abandoned after all.
This humble sleeper works despite its flaws. Adams and Dennehy have an agreeable chemistry, and the script gives them room to amply flesh out their characters.
http://members.tripod.com/~Brian_Koller/movies.html
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Motivating Yourself is your Job!
"Motivation can be fun too"
- Chidinma Nwogbo
NEXT QUOTE
TWEET QUOTE


About Us
You ask who are we ?
We are no one except a bunch of people who want to see you at the top of the world.
A Student Chapter based on the ideology Your Potential, Our Passion
which believes in enhancing your skills while gaining industry experience and thus turning you into a competent personnel.
We're completely focused on skill enhancement, using aids like tech talks and events which in turn concentrates on increasing the aptitude of each and every student who comes to us. We are going to learn and educate together, as the best educators are those who never stop learning themselves. We believe that growth must be mutual, we grow as our members learn.
Microsoft our patron is going to interact with us actively and will be leading us with their expert guidance.
What We Do ?
Workshops
Discussions are going to be conducted on the topics that will bring you the updates on the latest techniques in the world and help you to keep up with this exponentially growing technology.
Tech Talks
Tech Talks will give view the knowledge you need and which is required in the fast growing world to stay in the race.
Tech events
How about if you can apply your gained knowledge and skills in workshops and tech talks in your own way? Now, it's possible!!! With the technical events of Microsoft Technical Community you can do it now.
Hackathons
With the state level Hackathons you will get a chance to compete and compare your skills with the top notch students of other universities and perceive where you stand.
MTC is a community which keeps you updated with the innovation happening on a frequent basis. Our aim is to provide students with the technical knowledge which the world needs in the current scenario, for which I believe that MTC is a humble beginning.
Sahil Taneja
(Founder)
Upcoming Events
Stay updated about the coming buzz at UPES
Group Discussion Sessions
GD rounds are the biggest obstacles for claiming your dream job, so it is extremely important to excel in it. So this time, UPES-MTC Student Chapter brings you a golden opportunity to learn about the do's and dont's in a Group discussion. GD sessions will be organised by us for 2nd and 3rd year students. This training will be given free of cost. So buckle up to storm the GD rounds!!
Founding Committee
The way to get started is to quit talking and start doing
Sahil Taneja
Manik Garg
Abinash Prasad Borah
Mani Karthik
Shreya Pandey
Kritika Sharma
Aryan Banyal
Working Committee
Meet some admirable people who want you to be an inseparable part of this world
Mr. Praveen Dagdee
Faculty AdvisorMr. Uppara Rajanikanth
Faculty AdvisorManik Garg
President & Co-FounderPrerak Mittal
Vice-PresidentManila Chawla
Joint SecretaryRitesh Singhal
TreasurerKaustubh Asthana
Internal Operations HeadKritika Sharma
Technical HeadShivam Talwar
Design HeadShreya Pandey
Public Relations HeadGajendra Richhariya
Events HeadAnubhav Khunteta
Editorial HeadSamriddhi Agarwal
Registrations HeadAdarsh Kumar
VFX HeadManu Sharma
Photography HeadPrasoon Mehra
Social Media HeadRishabh Jain
Associate Event HeadSaumya Srivastava
Associate Management and Records HeadMahak Gupta
Associate PR HeadRishabh Arya
Associate Technical HeadShashwat Tiwari
Associate Registration HeadCircle of Excellence
Hard Work always Pays Off
Uttkarsh Pathak
Design TeamVikalp Saini
Technical TeamAnukruti Mathur
Editorial TeamAbhinav Sharma
Registration TeamArathi.S
PR TeamAyush Kumar
Photography TeamArjun Sethi
VFX TeamRahat Ranyal
M&R TeamKashish Srivastava
M&R TeamPranjal Mittal
Events TeamOur Sponsors
They Keep us Going
Microsoft
Microsoft Student Partner
SUBWAY
Brillica Services
Ace Initiator
Manila Chawla (Joint Secretary)
Working with MTC has been a great journey for me. It has helped me to not only showcase my skills on a big platform but also learn many new aspects. The Ace Initiator Award has brought new energy and enthusiasm in me. I'll try to work even better in the future and make MTC reach greater heights.
Microsoft Technical Community as the name suggest is a community which will work on the technical side of students. MTC will brush up the technical knowledge of students making them more capable in what they do and what they want to do.
Manik Garg
(President &
Co-Founder)
Tech Magazine
Sharing is good, and with digital technology, sharing is easy.
University of Petroleum & Energy Studies Bidholi,Dehradun - 248007
+91-8393966058


{% extends "base.html" %} {% block content %} Classes A place to discuss what classes to take
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Nestlé is proudly one of Australia's top employers.
Why Nestlé?
As the world's largest food and beverage company, Nestlé has plenty of opportunities for you to make an impact through the work you do in a truly global business.
Your experience with us may cover different brands, different business areas, and even different countries. You'll have the chance to learn from some of the brightest minds across our organisation as you grow your career – through your ideas, energy and expertise.
With amazing people at every level of our business, you will work collaboratively towards our future success, as we continue to find new solutions to modern problems around nutrition, product development and production, and global supply chains.
When you work at Nestlé, only you know where your career will take you next.
Rewards
We believe in the power of meaningful recognition to engage and reward our people and cultivate a culture of excellence.
We know what excites people about Nestlé goes beyond the opportunity to work on our portfolio of iconic brands. It's the diverse group of people you work with, the unique experiences offered by a truly global business, and the ability to contribute to our company's success from day one. It's the professional support you need to reach your goals throughout your career.
Our Total Rewards program recognises excellence in many ways – from opportunities to grow, evolve and contribute, to perks that support your health, wellness, educational and financial needs.
Nestlé Total Rewards
Rewards
At the foundation of remuneration at Nestlé is a fixed base salary, with a bonus plan to further reward great performance and behaviours.
Balance
We understand that life doesn't always bend around the 9-to-5, so we believe in and support healthy, flexible lifestyles both at and outside of work.
Growth
Nestlé encourages a culture of continuous learning ranging from career and development opportunities through to professional development coaching, further study and mobility.
Benefits
Nestlé Total Rewards begin from day one, ranging from super and financial advice, to health and assistance programs as well as partner discounts. And they don't stop when you leave, with retirement benefits for people in the later stages of their careers.
Life at Nestlé
At Nestlé you'll find a culture of respect – for ourselves, for others, for diversity and for the future.
Respect goes beyond simple courtesy – it informs our decisions at each level of the organisation, and guides the experience we offer. You'll be supported and encouraged to grow through challenging – but rewarding – work, as well as the wide variety of opportunities that only a global company like ours can offer.
You'll be inspired by different ways of thinking as you collaborate and innovate with industry leaders and talented colleagues to tackle established and emerging problems across the business.
Our culture runs deeper than just our working environment – it is woven through our entire business. We're inspired to delight our consumers and the way we respect each other provides the foundation for success, both individually and as an organisation. And the impact you have locally has the potential to be felt globally – your ideas today might just be what shapes Nestlé tomorrow.
Our Business
At Nestlé, we're positioned to provide a wealth of opportunities and challenges across a truly global business network.
Our diversity brings fresh, innovative thinking to how we approach new and existing challenges. You'll have the opportunity to learn from inspiring leaders and colleagues, collaborate across local and global teams, and experience the many different areas of our business operations.
Whatever your career or working goals are you'll get the support you need to achieve them, and opportunities to further enrich your career – wherever it takes you.
Discover more about the different areas of our business that you could work in:
"Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed vulputate orci non odio tincidunt, et mollis nulla sagittis. Sed sapien tellus, varius quis nisl at, suscipit viverra.
Phasellus non nulla lorem. In eget elit neque. Vestibulum molestie fermentum lacus ut hendrerit. Vestibulum mollis mattis urna, et tempor nulla fringilla eget. Proin massa urna, feugiat eu malesuada vel, auctor sed nibh."
– Joanna Smith, Position, Location
Marketing & Sales
Nestlé's Marketing & Sales teams are responsible for fostering brand loyalty in the hearts of consumers across our unrivalled portfolio of products. We sell over a billion products every day, and our brands are household names locally, while some have become global favourites. You'll be working with category leaders such as Nescafé, Kit Kat, Maggi and Uncle Tobys.
Our sales and marketing cycle is fast-paced and rewarding – with activity and communications across an omni-channel structure, from supermarkets and pharmacies to e-commerce, pop-ups and innovative consumer-first experiences.
Our marketers thrive on building and planning consumer experiences that reflect rich insights from big data, challenging category boundaries and consumer expectations. Those in our sales team channel their boundless energy into managing store activity and online channels, making sure our products are top of mind and easily accessible for our consumers.
You'll have access to global tools and insights, the support of the biggest business in food and beverages, and be part of our outstanding team, challenging the industry and driving Nestlé's continued success.
Consumer Insights & Marketplace IntelligenceMarketing Field Sales
Our purpose shapes everything we do, as we strive to enhance people's lives through nutrition, health and wellness, and work towards a better future for our world.
When you work at Nestlé, you're living our purpose every day, in everything you do.
We live it when we enable and inspire people to lead healthier and happier lives. We live it through our zero-waste goal, water-use reduction and recycling innovations. We live it by engaging with internships, mentoring opportunities and partnerships with universities. We live it when we support local communities; when our people volunteer at women's shelters, with children in need, or with indigenous groups.
Our people know that the work they do at Nestlé makes an impact and every day, they are working to make a difference for individuals & families, for our communities and for our plant.
Through her work in our Maggi team, Louise inspires people to make better food choices. Whether it's sharing information about how to create balanced meals through back of packet nutrition information, or continuing the quest to ensure Maggi products use only real ingredients that we're all familiar with, Louise is enabling people to live healthier lives.
"We put nutrition at the heart of everything that we do at Maggi. To come to work each day and know that what I do makes an impact and helps people to make the right choices about what they eat – it's something I am not only passionate about, but also really proud to be a part of.”
If you ask James about his favourite brand, he'll tell you it's Uncle Tobys – not only does he start each day with a bowl of Uncle Tobys Cereal, but he also gets to work with this iconic brand every day in his role as a Category Manager.
But for James, it's about much more than his day job. It's also about supporting our oat farmers, their families and the broader community. James has been instrumental in helping create our partnership with Men's Shed to promote health and wellbeing in regional communities.
"I'm passionate about men's health, so when there was an opportunity through my work in Uncle Tobys to support men in rural communities for better health and wellbeing, I jumped at the chance. I'm so proud of the great partnership we've developed with Men's Shed and it's rewarding to see how we're supporting communities including our own local oats farmers in the Riverina and our employees in Wahgunyah. I'm excited about how we will continue building our partnership into the future."
If you ask James about his favourite brand, he'll tell you it's Uncle Tobys – not only does he start each day with a bowl of Uncle Tobys Cereal, but he also gets to work with this iconic brand every day in his role as a Category Manager.
But for James, it's about much more than his day job. It's also about supporting our oat farmers, their families and the broader community. James has been instrumental in helping create our partnership with Men's Shed to promote health and wellbeing in regional communities.
"I'm passionate about men's health, so when there was an opportunity through my work in Uncle Tobys to support men in rural communities for better health and wellbeing, I jumped at the chance. I'm so proud of the great partnership we've developed with Men's Shed and it's rewarding to see how we're supporting communities including our own local oats farmers in the Riverina and our employees in Wahgunyah. I'm excited about how we will continue building our partnership into the future."
Our Graduates
We're looking for future leaders!
Imagine being part of a global success story; working with iconic brands and world-class products. This could be you and your future career because we know it's the graduates of today that shape tomorrow. If you are ready to be challenged and want to make a difference, then come and join us in our Next Gen Nestlé Graduate Program where you will see a world of opportunity open up and discover there's more to life at Nestlé.
Next Gen Nestlé program is now closed.
Make a healthier tomorrow
We want to be Oceania's leading nutrition, health and wellness company and are committed to live our promise of Good Food, Good Life. Our Next Gen Nestlé Graduate Program finds future leaders to help realise this vision and create a stronger, more sustainable tomorrow by delighting consumers everywhere.
In your chosen area, we'll support you to:
Learn in a practical, hands-on environment with real ownership of what you do
Grow and develop your leadership abilities
Gain the knowledge and business acumen to set you up for long-term success.
The opportunity
The dynamic Fast Moving Consumer Goods (FMCG) industry is constantly evolving and innovating. Through Next Gen Nestlé, you can work alongside some of the most passionate and strategic minds in the FMCG industry as you help make our vision a reality. If this is an opportunity that excites you, then apply to join the Next Gen Nestlé Program.
For a one page summary of the Next Gen Nestlé program click here.
The Next Gen Nestlé graduates program
"It's so humbling to have the opportunity to work for such well recognised and loved brands. From day one, I have had the chance to make tangible contributions and decisions that have been valued by my team mates and made a visible difference to achieving team goals." – Kathryn
"The highlight of the graduate program for me is the opportunity to gain such valuable and varied hands on experience, which consistently helps me with an improved and holistic approach to decision making" – Dominic
"I really wanted to work for a company which would develop me and provide long term career opportunities. The Graduate Program gave me a solid foundation to develop cross functional skills. In my time at Nestlé I have been able to progress through the marketing function to become a Marketing Manager, a role which sees me work with a team to deliver the long term strategy for our great brands." – Melissah
Life as a Graduate
About Next Gen Nestlé
Next Gen Nestlé is a two year program where you'll be exposed to the broad spectrum of career opportunities and distinctive culture for which Nestlé is renowned. You'll gain valuable experience by rotating through a number of roles across Nestlé Oceania in your chosen area – Marketing, Sales, Technical & Production, Supply Chain or Finance
With fresh thinking and new ideas, you can make a real impact on the way we work and the way we deliver our products to the market. Throughout, you'll enjoy continual support and learning opportunities.
With a sound platform of business knowledge, experience and well-developed networks, you will be ready to move into the business – your future career at Nestlé is in your hands.
Why Join?
In the Next Gen Nestlé program you always have an active role to play. This means that you can put into practice everything you've learned because you'll have real responsibilities on real projects in different areas across the business.
You'll experience our culture and live our values - with consumers at the heart of everything we do. You're also
part of a global story, working for the largest FMCG in the world.
Through all of this it's important to know that you're not alone. Throughout the program you'll be coached
and supported by the amazing teams behind our iconic brands. You'll also have your own tailored learning
and development program and be working in a team of inspiring people. Best of all, you'll have a guaranteed
permanent role at the end.
Awards and Recognition
It's a not just a future you're securing, it's a place you'll love to work. We're one of the Most Attractive Employers in both Australia and, in fact, the world*. Over our long history we've created shared value and Nestlé's global success story has been recognised across the world.
In 2016, we were the top FMCG of the Most Attractive Employers in Australia and ranked #7 overall.
In 2015 we were recognised as one of the top 20 Most Attractive Employers in the world – ranking 12th
For the 11th year in a row, last year Nestlé was named Fortune magazine's most admired food company in the world
Our culture of diversity and inclusion benefits both our people and our consumers.
A diverse workplace challenges and inspires the ways we think, innovate and create. At Nestlé, we constantly seek new and better ways to work together, building from our past success into the future.
We believe that the many different backgrounds, ways of thinking and cultural experiences of our people at every level of our business, makes for a richer workplace and gives us the insight and innovation to grow and continually delight our equally diverse consumers.
We are a people-inspired company; respect and trust are our greatest strengths. We place high value on the unique perspectives that people bring to our team which sharpens our performance and drives our business.
How We Work
We know priorities – at home and work – can blend and blur on any given day. We trust our people to make choices about when and where they get their job done, so that they can better balance their work and personal commitments. In fact, our flexible and inclusive work culture has been recognised with a Flex Able certification from the DCC social enterprise
Your Career
Our success at Nestlé is driven by the talented people that push our business further, year after year.
We foster a culture of high performance by providing opportunities to grow and shape your career through challenging and rewarding work across our business. Your future is yours for the making. Whether you choose to grow in your current role or take on new responsibilities, we're there to support your development and set you up for success.
As a global organisation, there's a broad range of opportunities available for you to enjoy a long and rewarding career across our different businesses and brands – or even different countries!
Further career development
We provide an environment that helps you grow and realise your potential. Whether you choose to develop your existing skills, learn new ones, or expand your wider understanding and knowledge through formal study, we are here to help your reach your goals.
From training to networking to on-the-job experiences, our holistic approach to professional development means you can learn and develop in the most effective way for you.
Manufacturing
Our much-loved products are trusted around the world, because consumers have confidence in the quality of the Nestlé brand. And to maintain the high-quality expectations of our consumers, Nestlé relies on the people who make our products to be active participants in the design, development and review of our portfolio.
From our coffee roasters in Gympie to our noodle wranglers in Lae, our manufacturing team spans Australia, New Zealand and the Pacific Islands, bringing together people from all over the world.
Your career could carry you across any of these locations, all while working across our extensive product portfolio. You'll have access to some of the best development and hands-on experience available, with market-leading opportunities to grow across our brands, locations and roles.
ProductionQuality ManagementSafety, Health Environment
Supply Chain
Few organisations in the world have the variety, breadth and volume of a supply chain network like Nestlé – we move over a billion units to shelves every year!
We operate a complex supply chain and procurement team, including everything from major supermarket chains in Australia to small outposts in Papua New Guinea. We pride ourselves on the reliable delivery of our diverse portfolio of products to our customers and their consumers.
The backbone of our operations are the passionate people at every stage of the value chain, delivering the right goods on time, every time. When it comes to supply chain, no matter which team you join, you'll have access to global tools and industry networks, local and international expertise and a diverse range of exciting career opportunities.
ProcurementCustomer ServiceDemand and Supply Planning
Physical LogisticsWarehousing and DistributionSupply Chain Management
Technology
While Nestlé may be known for an extensive portfolio of household names, in this digital age we rely just as much on our information systems and technologies as we do our supply chain network. Joining our tech team will open up new experiences and challenges across our business.
Our teams of specialists are responsible not only for implementing and maintaining cutting edge technology platforms for our business, but also for developing innovative solutions to connect our consumers with our brands.
Across our many programs and applications, you'll work to define and implement best practices and processes across our global operations – with opportunities to build your career as you widen your skills and work with our dedicated team of tech-sperts.
IT InfrastructureApplication SupportEnd User Solutions
NetworkHelp Desk
Corporate
The corporate teams at Nestlé oversee the operations of every part of our business, and play a pivotal part in delivering our iconic brands to our consumers. You'll work across the business, with opportunities to provide advice and support in your field of legal, finance, communications or human resources.
Our corporate teams work in a fast-paced environment that will inspire and challenge you, as you collaborate with stakeholders to define and drive success. You'll work directly with different business units to deliver results at every level of our organisation.
You'll have the opportunity to add real value across our business – including brands, teams and projects – and to build a long term career, make a difference in the world and leave your mark on the people of Nestlé.
Corporate CommunicationsLegalFinance
Consumer ServicesHuman Resources
Application & Selection
Application process
We're looking to discover truly motivated graduates who seize opportunities and think differently – this is could be you!
Before you start, be prepared and do your research about why you want to work for Nestlé. When you're ready to apply, you'll need to have all the items in the checklist below available so you can prepare and submit your online application.
An up-to date CV / Resume
Your most recent academic transcripts
A scanned copy of your Drivers Licence
N.B. This must be at a minimum a provisional drivers licence
Proof of permanent residency or citizenship i.e. passport, birth certificate, citizenship certificate.
Selection process
FAQS
Am I eligible to apply?
To be eligible, you should be in your final year of university or have completed your studies within two years of starting the Next Gen Nestlé Program. You'll also need either permanent residency or citizenship.
When does the program commence?
The program starts in January each year.
I've been invited to attend an Assessment Centre. Are you able to help with travelling costs?
We will help subsidise travel and accommodation (where applicable) to attend Assessment Centres if you are regional or interstate from the location of the Assessment Centre. We'll discuss this with candidates who are shortlisted.
What if I'm invited to an Assessment Centre but I can't attend that day?
Assessment Centre dates are fixed and unfortunately, cannot be changed.
If I finish my degree halfway through the year, can I start earlier?
We consider this on a case-by-case basis depending on our business needs.
Can I apply for the program again?
Yes – if you fit within the eligibility criteria
If I am successful and need to relocate, will Nestlé help me with this?
Yes – Nestlé will provide support and contribute to relocation costs. We'll discuss our policies with successful candidates.
Contact details – who can I talk to about my application / selection process?
Either call us: AU 02 8756 2066 or NZ 0800 083 111 or email us at<EMAIL_ADDRESS>for any questions.
We're always looking for talented people to join our team. Our collaborative, high-energy environment encourages us to work closely together, and we want people who share our desire to help create a healthier tomorrow. If you have the drive – the desire to succeed – and want to have a positive impact on the people and communities around you, we want you at Nestlé!
First, take a look at our current opportunities. If you think you'd be a great fit for a position, we'd love to hear from you by completing an online application.
Once we receive your application, we'll look at what you can bring to the role, through your experience and proven capabilities. If you're a good fit, we'll be in touch to take things to the next step.
When we meet face-to-face, we'll explore your fit for our business and culture. We want to find out what drives you and makes you tick, while you can learn more about the position, the people, and what it's like to work for the biggest nutrition, health and wellness business in the world – Nestlé!
Apply
Applications for 2019 Graduate program will open in March 2018.
At Nestlé, we're looking to build a healthy sustainable future to delight our consumers and take care of the people in our world. To make this vision a reality, we need a lot of different people, with a lot of different skills, to make that happen. That's why the Next Gen Nestlé program is looking for future leaders across key areas of our business.
What We Are Looking For
To succeed in the Next Gen Nestlé program, we're looking for graduates who are:
Self-motivated – are you a quick to learn and seize opportunities?
Innovative – are you ready for challenges and able to think of creative ways to solve problems?
Adaptable – in the FMCG world, things move quickly. Are you flexible and excited by change?
Smart workers – can you prioritise, simplify and work collaboratively?
Insightful - can you spot opportunities and act on them?
Driven – not only to deliver results, but on your promise as well.
How does a global brand communicate to an entire world of consumers? Work across new product development, point of sale development, brand communications and how to interact and work with sales teams. This is a golden opportunity to work across world-leading brands.
In your first year, you'll be an Area Manager in our field sales team. Here you'll manage a group of stores and merchandisers, working with Store Managers to organise orders, promotions and product merchandising.
In your second year, you'll work in a marketing team learning how new products are conceived, created and launched, as well as how brands communicate themselves to consumers. You'll also spend time in a Channel Sales Development (CCSD) team where you'll work with our retail partners to plan promotional activity and integrated shopper campaigns.
It's a dynamic and strategic experience that gives you a platform to start your career within a Nestlé marketing team.
Why do people buy and how can we maximise our promotions? As you gain insights into consumer and shopper behaviour, you'll help create compelling sales offers and develop integrated shopper campaigns that excite and entertain.
In your first year, you'll be an Area Manager in our field sales team. Here you'll manage a group of stores and merchandisers, working with Store Managers to organise orders, promotions and product merchandising.
In your second year, you'll work in a marketing team learning how new products are conceived, created and launched, as well as how brands communicate themselves to consumers. You'll also spend time in a Channel Sales Development (CCSD) team where you'll work with our retail partners to plan promotional activity and integrated shopper campaigns.
It's a dynamic and strategic experience that gives you a platform to start your career within a Nestlé sales team.
Does learning about how we supply our brands to retailers all across Australia excite you? Can you help us add real value to our supply chain?
You will have the opportunity to contribute ideas which will make over 1 billion products efficiently available whenever and wherever customers want them.
You'll leverage technology through the value stream to support the flow of demand; technology which also tracks that we have effectively fulfilled customer orders.
In the program, you will experience the end to end value change through roles in each of our key functional areas: Customer Service, Demand and Supply Planning, Physical Logistics and Procurement.
You'll work strategically on exciting projects with colleagues and customers alike to tackle daily challenges and deliver best practice.
Our Finance Graduates experience the full life cycle of the financial side of Nestlé. This starts with product development and goes all the way through to sales and measuring everything we do.
In Operational Financial Services, you'll put accounting 101 into action, talk to the business, and see profit and loss theory become a reality.
Experience Sales Finance and scrutinize our trade promotions that pay for the discounts you see in grocery stores. You'll learn how the mechanics of this work and evaluate trade promotion success.
Ever wondered what it's like to follow how a Kit-Kat is made? In Factory Finance, witness products being born and created and learn how finance contributes to managing product development budgets. As well, in our Costing team, you'll be working with the business to provide financial guidance using activity based costing as well as looking for opportunities to optimise the way we work.
As a CPA Recognised Employer Partner, your path to achieving a CPA qualification is streamlined. We provide financial support and study leave for you to complete each module.
How does a factory run? How do you refine processes to maximise productivity and minimise waste? If these questions burn inside you then the Technical and Production stream is for you.
In your first year, you'll have an amazing opportunity to work at two of Nestlé's regional factories. Here you'll learn our systems for continuous excellence as well as hands on problem solving techniques. Within the factory you'll work across multiple areas including Manufacturing Quality and Line Management.
As your rotation progresses we'll give you real opportunities to lead projects and demonstrate what you've learnt across management of projects and people, safe work practices and being a team leader of high performance teams. You'll learn to embody the Nestlé Continuous Excellence philosophy: zero waste, one team and 100% engagement.


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Waterloo’s co-op program is absolutely fantastic. Why? You get experience in the fields that you are interested in, not only to gain contacts for your future career, but also to discover what you like (and don’t like) to do. Your six co-op positions are paid, and will also help you fund an education that grows more costly every year.
| YEAR | TERM | STREAM 4 | STREAM 8 |
|---|---|---|---|
| 1 | Fall | Study (1A) | Study (1A) |
| Winter | Work | Study (1B) | |
| Spring | Study (1B) | Work | |
| 2 | Fall | Work | Study (2A) |
| Winter | Study (2A) | Work | |
| Spring | Work | Study (2B) | |
| 3 | Fall | Study (2B) | Work |
| Winter | Work | Study (3A) | |
| Spring | Study (3A) | Work | |
| 4 | Fall | Work | Study (3B) |
| Winter | Study (3B) | Work | |
| Spring | Work | Study (4A) | |
| 5 | Fall | Study (4A) | Work |
| Winter | Study (4B) | Study (4B) |
Waterloo has different academic/co-op term patterns, with SYDE being solely 4-Stream. This mean students start their first work term after 4-months of school. This means getting job experience sooner, and ending your degree off with 2 consecutive academic terms.
For future students: While the idea of working so soon may be scary, it does have some advantages. You will have less competition for jobs in the winter, and will start earning money sooner than your peers in 8-stream!
When you first start 1A, you will have a few weeks to prepare your resume (start in the summer, and get upper years to review it). Then, you will have a week long job application period, where you can browse the job postings on Waterloo Works and submit your application. The number of job postings number in the thousands, but don’t be too picky at first because a job is not guaranteed.
After applications, employers will slowly send out interview bookings, during which time you can choose an interview timeslot. Most interviews are held in person, on campus, which is very convenient for students. After interviews, both students and employers will submit job rankings, and then students are matched (hopefully) with their jobs for the next term. If you don’t get matched, you have the opportunity to keep applying so don’t ever lose hope.
Your first stop for checking average earnings should be the official CECA webpage. Since employers are subsidized by the government, wages are quite reasonable. Be warned though, wages on the CECA page are skewed downward as they exclude most USA-based jobs which tend to have higher pay and include food/housing. A fair number of employers base their wages on this data, so it is still a good representation. For information specific to SYDE see the following data from the SYDE 2017 Class Profile, but keep in mind changes in inflation in the years since date of publish.
While there is no guarantee that co-op can pay for your entire education, it certainly can take a load off of students who would have had to take out large loans to pay for their education. Of the Class of 2017, almost half the class graduated with no student debt, and the mean amount of debt was less than $10,000.


The Betting Line For The Ohio State-Michigan Game Is Set
by Matt HladikOhio State clinched the Big Ten East and a spot in the conference title game with yesterday’s win over Penn State. There’s one game left for the Buckeyes, and it’s at Michigan.
“The Game” is always an anticipated matchup, and this year is no exception. Ohio State is 11-0 and will be ranked either first or second in the College Football Playoff rankings on Tuesday. As for Michigan, there might not be any team in the country hotter than the 9-2 Wolverines.
Since the second half of the loss to Penn State, Michigan has looked like a completely different team. Jim Harbaugh’s bunch has dominated four straight opponents, outscoring Notre Dame, Maryland, Michigan State and Indiana 166-45.
As game week begins, the newest betting line for Ohio State-Michigan has been released, courtesy of Circa Sports.
Las Vegas likes Ryan Day’s team to win fairly comfortably. The Buckeyes are nine-point favorites.
Ohio State has not lost to Michigan since 2011, when Luke Fickell was the Buckeyes’ interim head coach. Jim Harbaugh has yet to beat OSU since taking over the Wolverines’ program.
Will that change on Saturday?
Las Vegas doesn’t think so.
Ohio State and Michigan will kick off at noon E.T. on FOX.


Introduction |
Documentation |
Downloads |
Forum |
Credits |
|
Torch 3 Vision
A full additional package for machine learning applied to vision applications is now available. Have a look here. |
Please, read the installation notes in the documentation section before downloading anything.
| Downloads | ||||
|---|---|---|---|---|
| Archive | Description | |||
| Torch3 src | Torch3 for Unix/Linux | |||
| Torch3 doc | Torch3 documentation | |||
| Torch3 win | Torch3 for MS Windows |
Note that the sources for Unix/Linux and MS Windows are the same... only the packaging method is different.
If for some reasons you want the previous version of Torch, it is still available here.
| Packages | ||||
|---|---|---|---|---|
| Package | Description | Dependencies | Maintainers | |
| core | The core of Torch | Ronan Collobert | ||
| gradients | Gradient machines | Ronan Collobert | ||
| kernels | Machine based on kernel methods, such as SVM |
Ronan Collobert | ||
| distributions | Stuff related to distributions | gradients | Samy Bengio Johnny Mariéthoz |
|
| convolutions | Spatial and temporal convolutions | gradients | Ronan Collobert | |
| matrix | Matrix manipulations | Ronan Collobert | ||
| datasets | Several classes to handle data such as HTK |
distributions speech |
Johnny Mariéthoz | |
| non-parametrics | Non-parametrics algorithms, such as KNN or Parzen Windows |
Samy Bengio | ||
| speech | Tools for speech recognition | distributions datasets |
Samy Bengio Johnny Mariéthoz |
|
| decoder | Large vocabulary speech decoder | distributions datasets speech |
Darren Moore | |
| examples | Some main program examples | all packages if you want to run all |
all coders |


Getting Started
What's in the package
AIR is released in 2 versions:
- PHP version: offers a good base for PHP implementations
- HTML version: for a clean start from scratch implementation or non-PHP implementations.
Differences between PHP & HTML versions
Each version has it's advantages and choosing one over the other depends of how you will want to implement it. For example, you may want to start a new project from scratch or use a framework like Zend or Cake, or maybe you don't want to use PHP at all and use some other scripting language and you don't want to spend precious time cleaning up PHP parts you don't need, in this case you'll want to use the clean HTML version.
However, if you don't have much experience with scripting languages like PHP or never used a framework like Zend or Cake PHP, AIR's PHP version offers a good base, yet simple for starting your implementation, with examples of a minimal structure, file templating - header, pages, footer - reusable functions, etc.
Most of the features are available in both versions, with the following exceptions:
- Translate System - only available in PHP version
- Easy configurable theme & layout options - only available in PHP version / in HTML version you will have to modify the markup yourself as needed
Main structure
/ // Root Directory <php|html>/ // AIR HTML/PHP versions bootstrap/ // Twitter Bootstrap documentation/ // Documentation theme/ // Theme Directory css/ // Default LESS/CSS files fonts/ // Fonts images/ // Default Images scripts/ // Scripts skins/ // Skins css/<skin>.css // Skin CSS files less/<skin>.less // Skin LESS files
CSS Files
AIR uses couple of stylesheets to control visual apperance. There are stylesheets from Twitter Bootstrap, default theme stylesheets, skin stylesheets, and plugin stylesheets.
bootstrap/css/<file>.css // Twitter Bootstrap Stylesheets theme/css/<file>.css // Default Stylesheets theme/skins/css/<skin>.css // Skin Stylesheets theme/scripts/<plugin>/css/<file>.css // Plugin stylesheets
LESS is MORE
First of all, you may ask: What the <beep>
is LESS? Well, LESS is The dynamic stylesheet language.
LESS extends CSS with dynamic behavior such as variables, mixins, operations and functions. LESS runs on both the client-side (Chrome, Safari, Firefox) and server-side, with Node.js and Rhino, but for our purpose, we will use the client-side less.js compiler for FAST and SMART deveopment and for production, we'll convert and minify the LESS files to the regular CSS by using a local compiler, like WinLess.
The LESS files
theme/less/mixins.less // Common Mixins theme/less/style.less // Default Stylesheet theme/skins/less/<skin>.less // Skin Stylesheet
Don't worry! If you never worked with LESS before, we assure you it's not that big of a step from CSS. Actually, after you start working LESS, you'll never look back. Also, it has a really great documentation.
Scripts
AIR uses many 3rd party plugins & scripts, as well as custom
ones. There are scripts from Twitter Bootstrap, jQuery & plugins,
Modernizr, custom scripts, etc. They are all located in
theme/scripts/
.
For more information about external scripts reffer to Credits


In IT, there are many skills that you will need. Some of them are specific to IT, some of then general skills. Here we will break them down.
In IT, you are going to be working with people who know nothing about technology. It is SO important to communicate to them, in a way they understand, what the issue is.
In IT, you're probably going to have login information and other things for your clients. If you are not trustworthy, then they are not going to give you what you need to help them.
In IT, you are going to be faced with issues that you may not have seen before. You should be able to find ways to solve those problems
In IT, things are going to change. It's the nature of technology. Things evolve. Because of that, you need to be able to adapt to the new situations.
In IT, you're going to pull you hair. It just comes with the job. If you have a positive attitude, you will not go bald quite as fast as if you didn't. You'll still go bald, though.
Programming is a very good skill to have in any computer field. In IT, it can help you get a job because it will look really good on a resume, and it will help you solve many problems.
Powershell is the life blood of any IT guy/gal. I can't stress this enough. Learn Powershell. It will help you so much in your career. It will save that fleshy part you sit on so many times.
How can you be in IT without knowing about hardware? You will literally be fixing it for your job. You need to have the hardware knowledge so you can actually know what you're talking about.
Virtual Machines are good. I don't know exactly why at this moment, but we have a wonderful teacher who can explain it to us and we can start a good discussion :).
I don't believe that you need eyeballs to do IT. You can do it by sound and feel. So I don't know why I put this except for the fact my group wanted me to add it while I was gone. Thanks guys, you Bakas


In this tutorial we will have a look at the various splitters that are present in deepchem library and how each of them can be used.
import deepchem as dc
import pandas as pd
import os
We start with the IndexSplitter. This splitter returns a range object which contains the split according to the fractions provided by the user. The three range objects can then be used to iterate over the dataset as test,valid and Train.
Each of the splitters that will be used has two functions inherited from
the main class that are train_test_split
which can be used to split
the data into training and tesing data and the other fucnction is
train_valid_test_split
which is used to split the data to train,
validation and test split.
Note: All the splitters have a default percentage of 80,10,10 as train,
valid and test respectively. But can be changed by specifying the
frac_train
,frac_test
and frac_valid
in the ratio we want
to split the data.
current_dir=os.path.dirname(os.path.realpath('__file__'))
input_data=os.path.join(current_dir,'../../deepchem/models/tests/example.csv')
We then featurize the data using any one of the featurizers present.
tasks=['log-solubility']
featurizer=dc.feat.CircularFingerprint(size=1024)
loader = dc.data.CSVLoader(tasks=tasks, smiles_field="smiles",featurizer=featurizer)
dataset=loader.featurize(input_data)
Loading raw samples now.
shard_size: 8192
About to start loading CSV from /home/ab/Downloads/deepchem/examples/notebooks/../../deepchem/models/tests/example.csv
Loading shard 1 of size 8192.
Featurizing sample 0
TIMING: featurizing shard 0 took 0.025 s
TIMING: dataset construction took 0.035 s
Loading dataset from disk.
from deepchem.splits.splitters import IndexSplitter
splitter=IndexSplitter()
train_data,valid_data,test_data=splitter.split(dataset)
train_data=[i for i in train_data]
valid_data=[i for i in valid_data]
test_data=[i for i in test_data]
len(train_data),len(valid_data),len(test_data)
(8, 1, 1)
As we can see that without providing the user specifications on how to split the data, the data was split into a default of 80,10,10.
But when we specify the parameters the dataset can be split according to our specificaitons.
train_data,valid_data,test_data=splitter.split(dataset,frac_train=0.7,frac_valid=0.2,frac_test=0.1)
train_data=[i for i in train_data]
valid_data=[i for i in valid_data]
test_data=[i for i in test_data]
len(train_data),len(valid_data),len(test_data)
(7, 2, 1)
The next splitter that is present in the library is the specified splitter. This splitter needs a list from the dataset where it is specified which data is for training and which is for validation and testing.
from deepchem.splits.splitters import SpecifiedSplitter
current_dir=os.path.dirname(os.path.realpath('__file__'))
input_file=os.path.join('../../deepchem/models/tests/user_specified_example.csv')
tasks=['log-solubility']
featurizer=dc.feat.CircularFingerprint(size=1024)
loader = dc.data.CSVLoader(tasks=tasks, smiles_field="smiles",featurizer=featurizer)
dataset=loader.featurize(input_file)
split_field='split'
splitter=SpecifiedSplitter(input_file,split_field)
Loading raw samples now.
shard_size: 8192
About to start loading CSV from ../../deepchem/models/tests/user_specified_example.csv
Loading shard 1 of size 8192.
Featurizing sample 0
TIMING: featurizing shard 0 took 0.033 s
TIMING: dataset construction took 0.040 s
Loading dataset from disk.
train_data,valid_data,test_data=splitter.split(dataset)
When we split the data using the specified splitter it compares the data
in each row of the split_field
which the user has to specify wether
the given row should be used as training data, validation data or
testing data. The user has to specify as train
,test
and
valid
in the split_field
. Note: The input is case insensitive.
train_data,valid_data,test_data
([0, 1, 2, 3, 4, 5], [6, 7], [8, 9])
Another splitter present in the fraework is IndiceSplitter
. This
splitter takes an input of valid_indices and test_indices which are
lists with the indices of validation data and test data in the dataset
respectively.
from deepchem.splits.splitters import IndiceSplitter
splitter=IndiceSplitter(valid_indices=[7],test_indices=[9])
splitter.split(dataset)
([0, 1, 2, 3, 4, 5, 6, 8], [7, 9], [9])
The splitter which can be used to split the data on the basis of
groupings is the RandomGroupSplitter
. This splitter that splits on
groupings.
An example use case is when there are multiple conformations of the same molecule that share the same topology.This splitter subsequently guarantees that resulting splits preserve groupings.
Note that it doesn’t do any dynamic programming or something fancy to
try to maximize the choice such that frac_train
, frac_valid
, or
frac_test
is maximized.It simply permutes the groups themselves. As
such, use with caution if the number of elements per group varies
significantly.
The parameter that needs to be provided with the splitter is groups
.
This is an array like list of hashables which is the same as the size of
the dataset.
from deepchem.splits.splitters import RandomGroupSplitter
groups = [0, 4, 1, 2, 3, 7, 0, 3, 1, 0]
solubility_dataset=dc.data.tests.load_solubility_data()
splitter=RandomGroupSplitter(groups=groups)
train_idxs, valid_idxs, test_idxs = splitter.split(
solubility_dataset)
Loading raw samples now.
shard_size: 8192
About to start loading CSV from /home/ab/anaconda3/envs/deepchem/lib/python3.6/site-packages/deepchem/data/tests/../../models/tests/example.csv
Loading shard 1 of size 8192.
Featurizing sample 0
TIMING: featurizing shard 0 took 0.030 s
TIMING: dataset construction took 0.040 s
Loading dataset from disk.
train_idxs,valid_idxs,test_idxs
([5, 1, 2, 8, 0, 6, 9], [4, 7], [3])
train_data=[]
for i in range(len(train_idxs)):
train_data.append(groups[train_idxs[i]])
valid_data=[]
for i in range(len(valid_idxs)):
valid_data.append(groups[valid_idxs[i]])
test_data=[]
for i in range(len(test_idxs)):
test_data.append(groups[test_idxs[i]])
print("Groups present in the training data =",train_data)
print("Groups present in the validation data = ",valid_data)
print("Groups present in the testing data = ", test_data)
Groups present in the training data = [7, 4, 1, 1, 0, 0, 0]
Groups present in the validation data = [3, 3]
Groups present in the testing data = [2]
So the RandomGroupSplitter
when properly assigned the groups, splits
the data accordingly and preserves the groupings.
The ScaffoldSplitter
splits the data based on the scaffold of small
molecules. The splitter takes the data and generates scaffolds using the
smiles in the data. Then the splitter sorts the data into scaffold sets.
from deepchem.splits.splitters import ScaffoldSplitter
splitter=ScaffoldSplitter()
solubility_dataset=dc.data.tests.load_solubility_data()
Loading raw samples now.
shard_size: 8192
About to start loading CSV from /home/ab/anaconda3/envs/deepchem/lib/python3.6/site-packages/deepchem/data/tests/../../models/tests/example.csv
Loading shard 1 of size 8192.
Featurizing sample 0
TIMING: featurizing shard 0 took 0.031 s
TIMING: dataset construction took 0.042 s
Loading dataset from disk.
train_data,valid_data,test_data = splitter.split(solubility_dataset,frac_train=0.7,frac_valid=0.2,frac_test=0.1)
len(train_data),len(valid_data),len(test_data)
(7, 2, 1)


--- layout: post title: Maybelline Contest - “IT DOESN’T LAST LONG ENOUGH” - Closed & Winner Update tags: - Maybelline status: publish type: post published: true meta: _edit_last: '2' _yoast_wpseo_linkdex: '59' _yoast_wpseo_focuskw: Maybelline Contest - “IT DOESN’T LAST LONG ENOUGH” _yoast_wpseo_title: Maybelline Contest - “IT DOESN’T LAST LONG ENOUGH” - Miss Enchanted _yoast_wpseo_metadesc: Maybelline Contest - “IT DOESN’T LAST LONG ENOUGH” _yoast_wpseo_meta-robots-noindex: '0' _yoast_wpseo_meta-robots-nofollow: '0' _yoast_wpseo_meta-robots-adv: none _yoast_wpseo_sitemap-include: ! '-' _yoast_wpseo_sitemap-prio: ! '-' _yoast_wpseo_canonical: '' _yoast_wpseo_redirect: '' _thumbnail_id: '6187' _yoast_wpseo_metakeywords: '' ---
Be it weekends, flings, kisses, boyfriends or their shopping funds, the hottest topic on the Maybelline New York Girl's mind is “IT DOESN’T LAST LONG ENOUGH”
Girls, do you feel the same way? Tell us what you wish lasted longer!
3 simple steps and a surprise gift from Maybelline India can be yours......


NOW BUNKING together: the ruby and yaml scripts up at http://go.hobix.com/. Hey ,, the life and unity we feel is tree-mending-US!!
Try:
ruby -ropen-uri -e’eval open(“http://go.hobix.com/”).read’
No longer are curtains dropping ON the actors’ arms !! No longer are swift currents ON the actors’ legs !! The actors have a bottomless cereal container, witness.
Splayed with c.s.s, a bokononist asks. This is a test site. All the basix. This is what you’ll get when you do a create. What will be in the blank syte.
SYRUP the 0.1i—the LATEST hobix—the create command is still BUSTed—don’t dismay—still editing tem-em-emplates—still cramp-designing. IT’S CODIN WITH MINI_SCREW_DRIVERS.
these little design pieces fit together in small ways ways,, HOLY OAK!!
and it’s ghost becomes 0.1j. the crippled man at the dock says, “a young pig gave birth here, but create does work now and the piglet survived.” beyond the thunder, is that the seductive song of a poorly saxophone? it’s missing these lyrics:
j-jig j-jig,
installer workin—
b-jig b-blig,
automaZZic ZZetup of BLlogSS!!
stupid song, glad the thunder washed it out—does it irritate ya how much i care not about the posts here?—let me ‘ssure you—it’s all flaky paint and you never cared much about the composition of a camel’s hump, boy.
strikin the surface like an alabaster homily from a guy who knows gloves: 0.2 is at last. i’m an old french horn but i know how to reify.
ruby -ropen-uri -e 'eval(open("http://go.hobix.com/").read)'
you’re gone-a have fun, kid. 100 kilo-gigs of it. i know what you’re thinking: she married him??


I have a brother who had an Angel Trumpet tree in his front yard yet he knew nothing of what they do. He just put them in for landscaping. I knew somewhat of them yet all I knew was I could get high off of them and I was curious. I did no research before I took them and the following story is what was told to me the day after I took them.
I was at work with my brother and I had stopped by his house to smoke a bowl. I asked him if I could have about 8 of the flowers off the tree and he told me he didnít care. After receiving the flowers I called up two of my friends (we'll call them John and Chino) and told them I had acquired some angel trumpets. My friend Chino agreed to be the sober one so he could drive while we tripped. Chino picked up John and I at my house around 6 p.m. so that we could go catch a movie. When we were first picked up I had already consumed one Angel Trumpet but John hadnít consumed any. We arrived at the movie theaters and bought our tickets.
Nothing was happening so I consumed around three more flowers at the beginning of the movie. By this time I had consumed four whole flowers and john consumed two. I started to feel very tired and sleepy so I laid down and went to sleep in the back of the movie theater. When the movie was over I felt like I wasnít sure if the trip had set in or not, and this is where amnesia started to slip up on me.
The last thing I remember is walking out of the movie theater trying to keep my balance, which I had obviously lost my sense of balance but still seemed to be maintaining self-control. On the drive I kept seeing snakes. Snakes were everywhere in the road yet my friend Chino assured me everything was alright. As far as I know my friend John had just started to get tired.
Upon my arrival at my house I walked in without a shirt on and my roommate asked me where it was. I argued with him for almost a half hour that I DID have a shirt on and I was scraping the skin on my chest and pulling it out thinking it was my shirt. Not until I looked down did I realize he was right. This was around 11 p.m.
Around 1 p.m. my roomate came into my room to find me throwing things around and smashing them and he proceeded to ask me what I was doing. I told him I was fighting someone and to help me. He then brought me into the living room and laid me down on the couch staying there with me to make sure I didnít hurt myself or damage the house. I stayed there for a number of hours just staring at random stuff but always seeming to get up every 15 or 20 min. to 'go to the bathroom'. I had the feeling of restlessness yet when I got to the bathroom I would forget where I had just come from.
Around 6 a.m. my roommate told me to fix breakfast thinking the trip had worn off. I took a silver cake mix bowl and filled it full of milk, then stuffed an Alcopolco (a Mexican type of blanket) into the bowl and started to eat it with a fork and a knife. My roommate caught that real quick and laid me back down on the couch.
The entire time this was going on my friend John was at his house and his trip started around 4 a.m. He was sitting in his room and he was talking to me, thinking I was right there with him. His brother came into the room and tried to calm him down then went back to bed. Around 8 a.m. John put on his workshirt and started to leave to go to work, yet he always works 2nd shift. His brother caught him and put him back in bed. He also had to go to court feeling the after effects of the angel trumpets.
My friend and I both agree that it was a bad choice and it was not a pleasent experiance. After effects include dizziness, vomiting, hangover like effects, and muscle tension. If I would not have had someone sober around us the entire time I have no doubt we would have wondered out into the middle of a road or fell out a window.
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.


kg_covid_19 package¶
Submodules¶
kg_covid_19.download module¶
-
kg_covid_19.download.
download
(yaml_file: str, output_dir: str, ignore_cache: bool = False) → None¶ Downloads data files from list of URLs (default: download.yaml) into data directory (default: data/).
- Args:
yaml_file: A string pointing to the yaml file utilized to facilitate the downloading of data. output_dir: A string pointing to the location to download data to. ignore_cache: Ignore cache and download files even if they exist [false]
- Returns:
None.
kg_covid_19.make_holdouts module¶
-
kg_covid_19.make_holdouts.
df_to_tsv
(df: pandas.core.frame.DataFrame, outfile: str, sep='\t', index=False) → None¶
-
kg_covid_19.make_holdouts.
make_holdouts
(nodes: str, edges: str, output_dir: str, train_fraction: float, validation: bool, seed=42) → None¶ Prepare positive and negative edges for testing and training (see run.py holdouts command for documentation)
- Args:
:param nodes nodes of input graph, in KGX TSV format [data/merged/nodes.tsv] :param edges: edges for input graph, in KGX TSV format [data/merged/edges.tsv] :param output_dir: directory to output edges and new graph [data/edges/] :param train_fraction: fraction of edges to emit as training :param validation: should we make validation edges? [False] :param seed: random seed [42]
- Returns:
None.
-
kg_covid_19.make_holdouts.
make_negative_edges
(nodes_df: pandas.core.frame.DataFrame, edges_df: pandas.core.frame.DataFrame, edge_label: str = 'negative_edge', relation: str = 'negative_edge') → pandas.core.frame.DataFrame¶ Given a graph (as nodes and edges pandas dataframes), select num_edges holdouts that are NOT present in the graph
- Parameters
nodes_df – pandas dataframe containing node info
edges_df – pandas dataframe containing edge info
relation – string to put in relation column
edge_label – string to put in edge_label column
- Returns
-
kg_covid_19.make_holdouts.
make_positive_edges
(nodes_df: pandas.core.frame.DataFrame, edges_df: pandas.core.frame.DataFrame, train_fraction: float) → List[pandas.core.frame.DataFrame]¶ Positive edges are randomly selected from the edges in the graph, IFF both nodes participating in the edge have a degree greater than min_degree (to avoid creating disconnected components). This edge is then removed in the output graph. Negative edges are selected by randomly selecting pairs of nodes that are not connected by an edge.
- Parameters
nodes_df – pandas dataframe with node info, generated from KGX TSV file
edges_df – pandas dataframe with edge info, generated from KGX TSV file
train_fraction – fraction of input edges to emit as test (and optionally validation) edges
- Returns
pandas dataframes:
- training_edges_df: a dataframe with training edges with positive edges we
selected for test removed from graph
test_edges_df: a dataframe with test positive edges
-
kg_covid_19.make_holdouts.
tsv_to_df
(tsv_file: str, *args, **kwargs) → pandas.core.frame.DataFrame¶ Read in a TSV file and return a pandas dataframe
- Parameters
tsv_file – file to read in
- Returns
pandas dataframe
kg_covid_19.query module¶
-
kg_covid_19.query.
parse_query_rq
(rq_file) → dict¶ - Args:
rq_file: sparql query in grlc rq format
Returns: dict with parsed info about sparql query
-
kg_covid_19.query.
result_dict_to_tsv
(result_dict: dict, outfile: str) → None¶
-
kg_covid_19.query.
run_query
(query: str, endpoint: str, return_format='json') → dict¶
kg_covid_19.transform module¶
-
kg_covid_19.transform.
transform
(input_dir: str, output_dir: str, sources: List[str] = None) → None¶ Call scripts in kg_covid_19/transform/[source name]/ to transform each source into a graph format that KGX can ingest directly, in either TSV or JSON format: https://github.com/NCATS-Tangerine/kgx/blob/master/data-preparation.md
- Args:
input_dir: A string pointing to the directory to import data from. output_dir: A string pointing to the directory to output data to. sources: A list of sources to transform.
- Returns:
None.
Module contents¶
-
kg_covid_19.
download
(yaml_file: str, output_dir: str, ignore_cache: bool = False) → None¶ Downloads data files from list of URLs (default: download.yaml) into data directory (default: data/).
- Args:
yaml_file: A string pointing to the yaml file utilized to facilitate the downloading of data. output_dir: A string pointing to the location to download data to. ignore_cache: Ignore cache and download files even if they exist [false]
- Returns:
None.
-
kg_covid_19.
transform
(input_dir: str, output_dir: str, sources: List[str] = None) → None¶ Call scripts in kg_covid_19/transform/[source name]/ to transform each source into a graph format that KGX can ingest directly, in either TSV or JSON format: https://github.com/NCATS-Tangerine/kgx/blob/master/data-preparation.md
- Args:
input_dir: A string pointing to the directory to import data from. output_dir: A string pointing to the directory to output data to. sources: A list of sources to transform.
- Returns:
None.


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A GDBusObjectSkeleton instance is essentially a group of D-Bus interfaces. The set of exported interfaces on the object may be dynamic and change at runtime.
This type is intended to be used with GDBusObjectManager.
GDBusObjectSkeleton *
g_dbus_object_skeleton_new (const gchar *object_path
);
Creates a new GDBusObjectSkeleton.
Since 2.30
void
g_dbus_object_skeleton_flush (GDBusObjectSkeleton *object
);
This method simply calls g_dbus_interface_skeleton_flush()
on all
interfaces belonging to object
. See that method for when flushing
is useful.
Since 2.30
void g_dbus_object_skeleton_add_interface (GDBusObjectSkeleton *object
,GDBusInterfaceSkeleton *interface_
);
Adds interface_
to object
.
If object
already contains a GDBusInterfaceSkeleton with the same
interface name, it is removed before interface_
is added.
Note that object
takes its own reference on interface_
and holds
it until removed.
Since 2.30
void g_dbus_object_skeleton_remove_interface (GDBusObjectSkeleton *object
,GDBusInterfaceSkeleton *interface_
);
Removes interface_
from object
.
Since 2.30
void g_dbus_object_skeleton_remove_interface_by_name (GDBusObjectSkeleton *object
,const gchar *interface_name
);
Removes the GDBusInterface with interface_name
from object
.
If no D-Bus interface of the given interface exists, this function does nothing.
Since 2.30
void g_dbus_object_skeleton_set_object_path (GDBusObjectSkeleton *object
,const gchar *object_path
);
Sets the object path for object
.
Since 2.30
typedef struct _GDBusObjectSkeleton GDBusObjectSkeleton;
The GDBusObjectSkeleton structure contains private data and should only be accessed using the provided API.
Since 2.30
struct GDBusObjectSkeletonClass { GObjectClass parent_class; /* Signals */ gboolean (*authorize_method) (GDBusObjectSkeleton *object, GDBusInterfaceSkeleton *interface_, GDBusMethodInvocation *invocation); };
Class structure for GDBusObjectSkeleton.
GObjectClass |
The parent class. |
|
Signal class handler for the “authorize-method” signal. |
Since 2.30
“g-object-path”
property“g-object-path” gchar *
The object path where the object is exported.
Flags: Read / Write / Construct
Default value: NULL
Since 2.30
“authorize-method”
signalgboolean user_function (GDBusObjectSkeleton *object, GDBusInterfaceSkeleton *interface, GDBusMethodInvocation *invocation, gpointer user_data)
Emitted when a method is invoked by a remote caller and used to determine if the method call is authorized.
This signal is like GDBusInterfaceSkeleton's “g-authorize-method” signal, except that it is for the enclosing object.
The default class handler just returns TRUE
.
object |
The GDBusObjectSkeleton emitting the signal. |
|
interface |
The GDBusInterfaceSkeleton that |
|
invocation |
||
user_data |
user data set when the signal handler was connected. |
Flags: Run Last
Since 2.30