NOTICE: This software (or technical data) was produced for the U.S. Government under contract, and is subject to the Rights in Data-General Clause 52.227-14, Alt. IV (DEC 2007). Copyright 2023 The MITRE Corporation. All Rights Reserved.
Overview
There are numerous video and image exploitation capabilities available today. The Open Media Processing Framework (OpenMPF) provides a framework for chaining, combining, or replacing individual components for the purpose of experimentation and comparison.
OpenMPF is a non-proprietary, scalable framework that permits practitioners and researchers to construct video, imagery, and audio exploitation capabilities using the available third-party components. Using OpenMPF, one can extract targeted entities in large-scale data environments, such as face and object detection.
For those developing new exploitation capabilities, OpenMPF exposes a set of Application Program Interfaces (APIs) for extending media analytics functionality. The APIs allow integrators to introduce new algorithms capable of detecting new targeted entity types. For example, a backpack detection algorithm could be integrated into an OpenMPF instance. OpenMPF does not restrict the number of algorithms that can operate on a given media file, permitting researchers, practitioners, and developers to explore arbitrarily complex composites of exploitation algorithms.
A list of algorithms currently integrated into the OpenMPF as distributed processing components is shown here:
| Operation | Object Type | Framework |
|---|---|---|
| Detection/Tracking | Face | LBP-Based OpenCV |
| Detection/Tracking | Motion | MOG w/ STRUCK |
| Detection/Tracking | Motion | SuBSENSE w/ STRUCK |
| Detection/Tracking | License Plate | OpenALPR |
| Detection | Speech | Sphinx |
| Detection | Speech | Azure Cognitive Services Batch Transcription API |
| Detection | Scene | OpenCV |
| Detection | Classification | OpenCV DNN (GoogLeNet, Yahoo NSFW, vehicle color) |
| Detection/Tracking | Classification | OpenCV DNN (YOLO) |
| Detection/Tracking | Classification/Features | TensorRT (COCO classes) |
| Detection | Text Region | EAST |
| Detection | Text (OCR) | Apache Tika |
| Detection | Text (OCR) | Tesseract OCR |
| Detection | Text (OCR) | Azure Cognitive Services Computer Vision API (OCR endpoint) |
| Detection | Text (OCR) | Azure Cognitive Services Read API |
| Detection | Form Structure (with OCR) | Azure Cognitive Services Form Recognizer API |
| Detection | Keywords | Boost Regular Expressions |
| Detection | Image (from document) | Apache Tika |
| Translation | Language | Azure Cognitive Services Translate API |
The OpenMPF exposes data processing and job management web services via a User Interface (UI). These services allow users to upload media, create media processing jobs, determine the status of jobs, and retrieve the artifacts associated with completed jobs. The web services give application developers flexibility to use the OpenMPF in their preferred environment and programming language.


Full Stack web developer skilled in HTML5, CSS3, Git, GitHub, and more! I love the challenge of learning new technologies and the satisfaction of solving difficult problems with creative solutions.
I have a background in Benefit Administration and Human Resources with passion for technology and improving systems. Picking out one's medical benefits can be very intimating task. I pride myself in the knowledge I gained working with benefits. Although the world of benefits is constantly changing with all the revisions to the healthcare reform, it doesn't seem as daunting. I welcome the challenge to understand new requirements and techniques and get excited about sharing the things I learned with others so they can make wise choices when selecting their medical benefits.
I apply this mantra now to my work as a developer. I research the things I don't know, problem solve any issues I come across, and figure out ways to share this information with my team.
I can be reached using the links below:
Portolio made by Micheal Limones


More details coming soon. The super short version is: Email me<EMAIL_ADDRESS>if you're interested in having a custom pedal made.
A fantastic option is the "Mimir's Horn", a trimmed-down version of the Mimir's Well pedal platform.
I've made plenty of other one-off pedals, mostly clones (sometimes with mods). See some here, including a few still available


Percentages and Discounts
This is the second workshop of the JS Practical Course
Calculate the price to pay of the products with discount
Write the price of your product
Write the name of your discount coupon
Calculate the price with Discount


I've been Latey been changing my feeling upon Races altey i used to play halflings all the time but due to their easy to kd and disarm function i tried switching to elves which makes things alot easier though i seem to have problems playing other races
or thinking of intresting ideas for like a PW server level 12 server. _________________ "Ïf thê øñlÿ wäÿ før mê tø bê wïth ÿøù ïs ïñ ä drêäm thêñ lêt mê drêäm førêvêr"
"Habits are like a comfy chair easy to get in to and hard to get out of"


As you may know, we can declare the form of a block of data containing different data types by means of a structure declaration. For example, a personnel file might contain structures which look something like:
struct tag { char lname[20]; /* last name */ char fname[20]; /* first name */ int age; /* age */ float rate; /* e.g. 12.75 per hour */ };
Let's say we have a bunch of these structures in a disk file and we want to read each one out and print out the first and last name of each one so that we can have a list of the people in our files. The remaining information will not be printed out. We will want to do this printing with a function call and pass to that function a pointer to the structure at hand. For demonstration purposes I will use only one structure for now. But realize the goal is the writing of the function, not the reading of the file which, presumably, we know how to do.
For review, recall that we can access structure members with the dot operator as in:
--------------- program 5.1 ------------------ /* Program 5.1 from PTRTUT10.HTM 6/13/97 */ #include <stdio.h> #include <string.h> struct tag { char lname[20]; /* last name */ char fname[20]; /* first name */ int age; /* age */ float rate; /* e.g. 12.75 per hour */ }; struct tag my_struct; /* declare the structure my_struct */ int main(void) { strcpy(my_struct.lname,"Jensen"); strcpy(my_struct.fname,"Ted"); printf("\n%s ",my_struct.fname); printf("%s\n",my_struct.lname); return 0; } -------------- end of program 5.1 --------------
Now, this particular structure is rather small compared to many used in C programs. To the above we might want to add:
date_of_hire; (data types not shown) date_of_last_raise; last_percent_increase; emergency_phone; medical_plan; Social_S_Nbr; etc.....
If we have a large number of employees, what we want to do is manipulate the data in these structures by means of functions. For example we might want a function print out the name of the employee listed in any structure passed to it. However, in the original C (Kernighan & Ritchie, 1st Edition) it was not possible to pass a structure, only a pointer to a structure could be passed. In ANSI C, it is now permissible to pass the complete structure. But, since our goal here is to learn more about pointers, we won't pursue that.
Anyway, if we pass the whole structure it means that we must copy the contents of the structure from the calling function to the called function. In systems using stacks, this is done by pushing the contents of the structure on the stack. With large structures this could prove to be a problem. However, passing a pointer uses a minimum amount of stack space.
In any case, since this is a discussion of pointers, we will discuss how we go about passing a pointer to a structure and then using it within the function.
Consider the case described, i.e. we want a function that will accept as a parameter a pointer to a structure and from within that function we want to access members of the structure. For example we want to print out the name of the employee in our example structure.
Okay, so we know that our pointer is going to point to a structure declared using struct tag. We declare such a pointer with the declaration:
struct tag *st_ptr;
and we point it to our example structure with:
st_ptr = &my_struct;
Now, we can access a given member by de-referencing the pointer. But, how do we de-reference the pointer to a structure? Well, consider the fact that we might want to use the pointer to set the age of the employee. We would write:
(*st_ptr).age = 63;
Look at this carefully. It says, replace that within the parenthesis with that which st_ptr points to, which is the structure my_struct. Thus, this breaks down to the same as my_struct.age.
However, this is a fairly often used expression and the designers of C have created an alternate syntax with the same meaning which is:
st_ptr->age = 63;
With that in mind, look at the following program:
------------ program 5.2 --------------------- /* Program 5.2 from PTRTUT10.HTM 6/13/97 */ #include <stdio.h> #include <string.h> struct tag{ /* the structure type */ char lname[20]; /* last name */ char fname[20]; /* first name */ int age; /* age */ float rate; /* e.g. 12.75 per hour */ }; struct tag my_struct; /* define the structure */ void show_name(struct tag *p); /* function prototype */ int main(void) { struct tag *st_ptr; /* a pointer to a structure */ st_ptr = &my_struct; /* point the pointer to my_struct */ strcpy(my_struct.lname,"Jensen"); strcpy(my_struct.fname,"Ted"); printf("\n%s ",my_struct.fname); printf("%s\n",my_struct.lname); my_struct.age = 63; show_name(st_ptr); /* pass the pointer */ return 0; } void show_name(struct tag *p) { printf("\n%s ", p->fname); /* p points to a structure */ printf("%s ", p->lname); printf("%d\n", p->age); } -------------------- end of program 5.2 ----------------
Again, this is a lot of information to absorb at one time. The
reader should compile and run the various code snippets and using
a debugger monitor things like my_struct and p while
single stepping through the main and following the code down into
the function to see what is happening.


---
title: "JEFF CLAY PHOTOGRAPHY EXHIBIT"
date: "2000-01-01 18:09:14 -06:00"
categories:
- exhibit
subtitle: "FLORAL IMPRESSIONS"
layout: "free-events"
event-image: "jeff-clay-exhibit.jpg"
event-dates: "SEPTEMBER 14 - OCTOBER 7, 2018"
event-location: "Red Butte Garden Visitor Center"
button-type: "register"
tickets-link: ""
registration-info: "Questions?
Please call<PHONE_NUMBER>"
instructor-info: "N/A"
member-cost: "Free"
public-cost: "Garden Admission"
event-notes: "Artist Reception Sept 15 @ 6:30-8:30PM"
tickets-button: "hide"
refund-policy: "hide"
published: false
---
Meet the Artist Reception
Friday, September 14 from 6:30-8:30PM
Artist Statement: A rose is a rose is a rose … except when it may be something else.
I’ve always enjoyed photographing flowers. Whether in botanical gardens, walking though local neighborhoods, or when traveling overseas, the brilliant variety of flowers attracts me.  In 2013 I traveled to Monet’s Garden outside Paris. I walked into the gardens and immediately began photographing the riot of floral colors much as I always had. But then I realized: a tulip – whether in Giverny, France, or Red Butte, Utah – is ‘just’ a tulip. I was in the garden of a master of Impressionism and all I could do is photograph a flower, as I would shoot a building? Instead I began using movement, longer and multiple exposures to create ‘floral impressions.’ These I further enhanced when processing the images. To this day I still use a number of different tools, techniques, and treatments to capture and render flowers. They are presented as ‘something else.’ From near-abstract to painterly representations: Floral Impressions.
For more, please visit: www.clayhausphotography.com


CocoapodsRepoSq
Adds support for Square SDK Repositories to Cocoapods
Installation
$ gem install cocoapods-repo-sq
Usage
Integrate in your project
Add a Square SDK Repository to your local cocoapods registry.
NAME
is a nickname you'll use to refer to this repository
later in your Podfile
and other pod repo-sq
commands: shell $ pod repo-sq add NAME USERNAME PASSWORD
Specify your Square SDK repository in your Podfile
: “`ruby
plugin 'cocoapods-repo-sq', :repository => 'NAME'
target 'MyTarget' do pod 'SquareSDK' end “`
Commands
Add
$ pod repo-sq add NAME USERNAME PASSWORD
List
$ pod repo-sq list
Update
$ pod repo-sq update NAME
Remove
$ pod repo-sq remove NAME
Multiple Applications
If you have multiple Square Applications you will have multiple SDK
Repositories. cocoapods-repo-sq
supports this by allowing you
to add multiple repositories to your registry. Just remember to point your
Podfile
to the right one using the plugin
'cocoapods-repo-sq', :repository => 'NAME'
statement.
Contributing
We are currently not accepting code contributions to this repository. If you found a bug or have a feature request please Submit it here.
If you are curious about Cocoapods and its plugin system take a look at the following guides: - blog.cocoapods.org/CocoaPods-0.28/ - guides.cocoapods.org/reference.html - github.com/CocoaPods/cocoapods-plugins
Building
$ rake build
Testing
$ rake specs
License
Copyright 2018 Square Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.


Download Microsoft Visual Studio Express 2017 15 9 7
Download Visual Basic 2017 Express
Visual Studio Express 2017 のダウンロード方法 Engineer S Notebook
Microsoft Visual Studio Express Wikipedia
Microsoft Visual Studio Express 2017 Full Version Download
Download Visual Studio 2017 Free Wifasr
Visual Studio Express Download 2021 Latest For Windows 10 8 7
New Offline Books For Visual Studio 2017 Available For Download Visual Studio Blog
Express 2017 For Windows Desktop Medo S Home Page
Microsoft Visual Studio All Versions Iso Download
Visual Basic 2013 Express Download For Pc Free
Install Visual Studio Microsoft Docs
Visual Studio 2019 Ide Programming Software For Windows
Free Visual Studio Express 2012 For Windows Desktop Scott Hanselman S Blog
What S New In Visual Studio 2019 Download For Free Visual Studio Microsoft Visual Studio Best Photo Editing Software Visual
Download Visual Studio Express Scott Hanselman S Blog
Microsoft Visual Basic Download
Installing Microsoft Visual Studio 2017 For Use With Intel Compilers
3
A Setup Package Is Either Missing Or Damaged Error While Installing Visual Studio 2015 On Windows 10 Stack Overflow
How To Download And Install Visual Studio 2013 Express On Windows 8 Youtube
Visual Studio 2017 Express Keygen Download Chailivi
Visual Studio 2017 Serial Key Download Everbros
How To Download And Install Visual Studio Community 2017 Hindi Youtube
How To Download And Install Visual Studio 2019 Community Edition Youtube


WEST BEIRUT (WEST BEYROUTH) (director/writer: Ziad Doueiri; cinematographer: Ricardo Jacques Gale; editor: Dominique Marcombe; cast: Rami Doueiri (Tarek), Mohamad Chamas (Omar), Rola Al Amin (May), Carmen Lebbos (Hala), Joseph Bou Nassar (Riad), Liliane Nemry (Neighbor), Leila Karam (Oum Walid), Mahmoud Mabsout (Baker), Fadi Abou Khalil (Papa Snake); Runtime: 105; A Cowboy Booking; 1998)
Reviewed by Dennis Schwartz
Yes. A war zone can be fun for restless teens with hot blood and a passion for mischief. In Ziad Doueiri's semi-autobigraphical film about his growing up as a teenager in the 1970s in the middle of the civil war that rocked Beirut, that is the strongest message I received from his irreverent look at what he did during the war years. It was filmed by someone who knows the mood of that critical time, the real dangers that were there, the music that was played, and the tensions that gripped the city. In this shoestring budgeted indie, Doueiri does a nice job of detailing how his Muslim community of West Beirut reacted to all the violence; and, how he and his friends and his bourgeois parents endured. His intellectual father Riad (Joseph Bou Nassar) being the eternal optimist and his lawyer mother Hala (Carmen Lebbos) constantly feeling panicked by the events. The film shows how through all the turmoil his parents showed much affection to their only child, as he was doted upon by both of them. This is a hearfelt film about his coming-of-age during that strife. The 36-year-old filmmaker studied at UCLA and was the cameraman for Quentin Tarantino's Pulp Fiction and Reservoir Dogs.
The 15-year-old protagonist, Tarek (Rami Doueiri, nonprofessional actor and the director's brother), is the school joker. In the opening scene he stops the singing of the "Marseillaise" at his French-speaking high-school by climbing above the students gathered in the school yard and using a megaphone to sing the Lebanese national anthem. When he is removed from class because of his insolence, he witnesses the massacre of a busload of 31 Muslims by masked terrorists--it's April 13, 1975, the start of the war between Muslims and Christians that leaves Beirut divided into Christian East Beirut and Muslim West Beirut. It is a chaotic war that is to last for 14 years, leaving the city in ruin. But when Tarek witnessed the attack, he wasn't sure who the attackers were and why they were there.
Tarek's father thinks this war will be like the others he has lived through, and the Americans will force a negotiation and it will be settled very quickly. His wife is confused about what is happening and wishes to flee the city. But, as Riad says, this is our home, there is no other place I would feel comfortable fitting in. Tarek and his best friend, the short but peppy Omar (Mohamad Chamas, a Beirut street kid and thief), don't see things the way the adults do. They are happy that their school, in Christian East Beirut, is closed to them and they can horse around in the street and spend their time with the hobby they both have a passion for, Super-8 filmmaking.
Tarek becomes infatuated with May (Rola Al Amin), the pretty Catholic refugee girl from his school who wears a cross and lives in Muslim West Beirut. They become a trio though Omar is, at first, displeased with her and calls her "the Virgin Mary." The film is not plot oriented, it relies on a bunch of episodic incidents to take place before Tarek gets it through his clownish skull and smirking face that this city has changed and won't be the same again. His adventures are driven by his sexual curiosity, but he will soon realize it's not that easy to be so carefree anymore. One character angrily tells him when he is aimlessly running through the streets, "What planet are you from?" When they go to develop film in a neighborhood where they have to cross the border to the East, there is a sense of imminent danger that the trio didn't realize until then really existed. They go to a brothel where safe passage means you have use women's underwear as a white flag to avoid being shot at by snipers. Here, they meet the legendary madam Oum Walid (Leila Karam). She tells them for certain that Beirut has changed, and it finally sinks in that Beirut is no longer the cosmopolitan Mediterranean city it once was.
We get a feel for what the director lived through as the friendly Tarek is shown relating to his neighbors. He has a wonderful relationship with the neighborhood baker (Mahmoud Mabsout); a comical relationship with his complaining neighbor (Liliane Nemry), who is great with cursing out those she doesn't like with shouts of: "May Allah spread pain all over you;" and, she tells Tarek's mother: "Your son is a blood clot in my vein." There's the neighborhood bully called Papa Snake (Khalil), who is disliked by Tarek for intimidating the baker to give him flour for protection.
The director also presents us with a flavor of the slang language used by the locals, with expressions such as: "You're shish-kabobing me on a small flame;" or "You drive like Steve McQueen;" and, about a buxom woman Omar says, "What a piece of lamb!"
The film was good at given us a realistic look at how one family looked at those troubled times, rather than for having anything political to say.  The film did this in a rather ordinary way, so that there is nothing deeper to dig out of Ziad Doueiri's story. Rami Doueiri was a lively teenager. Mohamad Chamas was equally feisty as his main man. It seemed to be a story that the director had to tell, and he shared what he saw with an audience that more than likely only followed the long civil war in the news stories and had no idea how it looked first-hand. This was a film that had no pretenses about it; it just told the story it knew.
REVIEWED ON 5/25/2001 GRADE: B
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


This article was recorded by Ida Ansell in shorthand. As, however, Swamiji's speed was too great for her in her early days, dots are put in the articles to indicate the omissions, while the words within square brackets are added by way of linking up the disconnected parts.
(Delivered in San Francisco, on May 26, 1900)
To understand the Gita requires its historical background. The Gita is a commentary on the Upanishads. The Upanishads are the Bible of India. They occupy the same place as the New Testament does. There are [more than] a hundred books comprising the Upanishads, some very small and some big, each a separate treatise. The Upanishads do not reveal the life of any teacher, but simply teach principles. They are [as it were] shorthand notes taken down of discussion in [learned assemblies], generally in the courts of kings. The word Upanishad may mean "sittings" [or "sitting near a teacher"]. Those of you who may have studied some of the Upanishads can understand how they are condensed shorthand sketches. After long discussions had been held, they were taken down, possibly from memory. The difficulty is that you get very little of the background. Only the luminous points are mentioned there. The origin of ancient Sanskrit is 5000 B.C.; the Upanishads [are at least] two thousand years before that. Nobody knows [exactly] how old they are. The Gita takes the ideas of the Upanishads and in [some] cases the very words. They are strung together with the idea of bringing out, in a compact, condensed, and systematic form, the whole subject the Upanishads deal with.
The [original] scriptures of the Hindus are called the Vedas. They were so vast — the mass of writings — that if the texts alone were brought here, this room would not contain them. Many of them are lost. They were divided into branches, each branch put into the head of certain priests and kept alive by memory. Such men still exist. They will repeat book after book of the Vedas without missing a single intonation. The larger portion of the Vedas has disappeared. The small portion left makes a whole library by itself. The oldest of these contains the hymns of the Rig-Veda. It is the aim of the modern scholar to restore [the sequence of the Vedic compositions]. The old, orthodox idea is quite different, as your orthodox idea of the Bible is quite different from the modern scholar's. The Vedas are divided into two portions: one the Upanishads, the philosophical portion, the other the work portion.
We will try to give a little idea of the work portion. It consists of rituals and hymns, various hymns addressed to various gods. The ritual portion is composed of ceremonies, some of them very elaborate. A great many priests are required. The priestly function became a science by itself, owing to the elaboration of the ceremonials. Gradually the popular idea of veneration grew round these hymns and rituals. The gods disappeared and in their place were left the rituals. That was the curious development in India. The orthodox Hindu [the Mim‚msaka] does not believe in gods, the unorthodox believe in them. If you ask the orthodox Hindu what the meaning is of these gods in the Vedas, [he will not be able to give any satisfactory answer]. The priests sing these hymns and pour libations and offering into the fire. When you ask the orthodox Hindu the meaning of this, he says that words have the power to produce certain effects. That is all. There is all the natural and supernatural power that ever existed. The Vedas are simply words that have the mystical power to produce effects if the sound intonation is right. If one sound is wrong it will not do. Each one must be perfect. [Thus] what in other religions is called prayer disappeared and the Vedas became the gods. So you see the tremendous importance that was attached to the words of the Vedas. These are the eternal words out of which the whole universe has been produced. There cannot be any thought without the word. Thus whatever there is in this world is the manifestation of thought, and thought can only manifest itself through words. This mass of words by which the unmanifested thought becomes manifest, that is what is meant by the Vedas. It follows that the external existence of everything [depends on the Vedas, for thought] does not exist without the word. If the word "horse" did not exist, none could think of a horse. [So] there must be [an intimate relation between] thought, word, and the external object. What are these words [in reality]? The Vedas. They do not call it Sanskrit language at all. It is Vedic language, a divine language. Sanskrit is a degenerate form. So are all other languages. There is no language older than Vedic. You may ask, "Who wrote the Vedas?" They were not written. The words are the Vedas. A word is Veda, if I can pronounce it rightly. Then it will immediately produce the [desired] effect.
This mass of Vedas eternally exists and all the world is the manifestation of this mass of words. Then when the cycle ends, all this manifestation of energy becomes finer and finer, becomes only words, then thought. In the next cycle, first the thought changes into words and then out of those words [the whole universe] is produced. If there is something here that is not in the Vedas, that is your delusion. It does not exist.
[Numerous] books upon that subject alone defend the Vedas. If you tell [their authors] that the Vedas must have been pronounced by men first, [they will simply laugh]. You never heard of any [man uttering them for the first time]. Take Buddha's words. There is a tradition that he lived and spoke these words [many times before]. If the Christian stands up and says, "My religion is a historical religion and therefore yours is wrong and ours is true," [the Mimamsaka replies], "Yours being historical, you confess that a man invented it nineteen hundred years ago. That which is true must be infinite and eternal. That is the one test of truth. It never decays, it is always the same. You confess your religion was created by such-and-such a man. The Vedas were not. By no prophets or anything. ... Only infinite words, infinite by their very nature, from which the whole universe comes and goes." In the abstract it is perfectly correct. ... The sound must be the beginning of creation. There must be germ sounds like germ plasm. There cannot be any ideas without the words. ... Wherever there are sensations, ideas, emotions, there must be words. The difficulty is when they say that these four books are the Vedas and nothing else. [Then] the Buddhist will stand up and say, "Ours are Vedas. They were revealed to us later on." That cannot be. Nature does not go on in that way. Nature does not manifest her laws bit by bit, an inch of gravitation today and [another inch] tomorrow. No, every law is complete. There is no evolution in law at all. It is [given] once and for ever. It is all nonsense, this "new religion and better inspiration," and all that. It means nothing. There may be a hundred thousand laws and man may know only a few today. We discover them — that is all. Those old priests with their tremendous [claims about eternal words], having dethroned the gods, took the place of the gods. [They said], "You do not understand the power of words. We know how to use them. We are the living gods of the world. Pay us; we will manipulate the words, and you will get what you want. Can you pronounce the words yourself? You cannot, for, mind you, one mistake will produce the opposite effect. You want to be rich, handsome, have a long life, a fine husband?" Only pay the priest and keep quiet!
Yet there is another side. The ideal of the first part of the Vedas is entirely different from the ideal of the other part, the Upanishads. The ideal of the first part coincides with [that of] all other religions of the world except the Vedanta. The ideal is enjoyment here and hereafter — man and wife, husband and children. Pay your dollar, and the priest will give you a certificate, and you will have a happy time afterwards in heaven. You will find all your people there and have this merry-go-round without end. No tears, no weeping — only laughing. No stomach-ache, but yet eating. No headache, but yet [parties]. That, considered the priests, was the highest goal of man.
There is another idea in this philosophy which is according to your modern ideas. Man is a slave of nature, and slave eternally he has got to remain. We call it Karma. Karma means law, and it applies everywhere. Everything is bound by Karma. "Is there no way out?" "No! Remain slaves all through the years — fine slaves. We will manipulate the words so that you will only have the good and not the bad side of all — if you will pay [us] enough." That was the ideal of [the Mimamsakas]. These are the ideals which are popular throughout the ages. The vast mass of mankind are never thinkers. Even if they try to think, the [effect of the] vast mass of superstitions on them is terrible. The moment they weaken, one blow comes, and the backbone breaks into twenty pieces. They can only be moved by lures and threats. They can never move of their own accord. They must be frightened, horrified, or terrorised, and they are your slaves for ever. They have nothing else to do but to pay and obey. Everything else is done by the priest. ... How much easier religion becomes! You see, you have nothing to do.  Somebody is doing the whole thing for you. Poor, poor animals!
Side by side, there was the other system. The Upanishads are diametrically opposite in all their conclusions. First of all, the Upanishads believe in God, the creator of the universe, its ruler. You find later on [the idea of a benign Providence]. It is an entirely opposite [conception]. Now, although we hear the priest, the ideal is much more subtle. Instead of many gods they made one God.
The second idea, that you are all bound by the law of Karma, the Upanishads admit, but they declare the way out. The goal of man is to go beyond law. And enjoyment can never be the goal, because enjoyment can only be in nature.
In the third place, the Upanishads condemn all the sacrifices and say that is mummery. That may give you all you want, but it is not desirable, for the more you get, the more you [want], and you run round and round in a circle eternally, never getting to the end — enjoying and weeping. Such a thing as eternal happiness is impossible anywhere. It is only a child's dream. The same energy becomes joy and sorrow.
I have changed my psychology a bit today. I have found the most curious fact. You have a certain idea and you do not want to have it, and you think of something else, and the idea you want to suppress is entirely suppressed. What is that idea? I saw it come out in fifteen minutes. It came out and staggered me. It was strong, and it came in such a violent and terrible fashion [that] I thought here was a madman. And when it was over, all that had happened [was a suppression of the previous emotion]. What came out? It was my own bad impression which had to be worked out. "Nature will have her way. What can suppression do?" (Gita, III. 33.) That is a terrible [statement] in the Gita. It seems it may be a vain struggle after all. You may have a hundred thousand [urges competing] at the same time. You may repress [them], but the moment the spring rebounds, the whole thing is there again.
[But there is hope]. If you are powerful enough, you can divide your consciousness into twenty parts all at the same time. I am changing my psychology. Mind grows. That is what the Yogis say. There is one passion and it rouses another, and the first one dies. If you are angry, and then happy, the next moment the anger passes away. Out of that anger you manufactured the next state. These states are always interchangeable.  The Upanishads point out that the goal of man is neither misery nor happiness, but we have to be master of that out of which these are manufactured. We must be masters of the situation at its very root, as it were.
The other point of divergence is: the Upanishads condemn all rituals, especially those that involve the killing of animals. They declare those all nonsense. One school of old philosophers says that you must kill such an animal at a certain time if the effect is to be produced. [You may reply], "But [there is] also the sin of taking the life of the animal; you will have to suffer for that." They say that is all nonsense. How do you know what is right and what is wrong? Your mind says so? Who cares what your mind says? What nonsense are you talking?  If your mind says something and the Vedas say something else, stop your mind and believe in the Vedas. If they say, killing a man is right, that is right. If you say, "No, my conscience says [otherwise," it won't do]. The moment you believe in any book as the eternal word, as sacred, no more can you question. I do not see how you people here believe in the Bible whenever you say about [it], "How wonderful those words are, how right and how good!" Because, if you believe in the Bible as the word of God, you have no right to judge at all. The moment you judge, you think you are higher than the Bible. [Then] what is the use of the Bible to you? The priests say, "We refuse to make the comparison with your Bible or anybody's. It is no use comparing, because — what is the authority? There it ends. If you think something is not right, go and get it right according to the Vedas."
The Upanishads believe in that, [but they have a higher standard too]. On the one hand, they do not want to overthrow the Vedas, and on the other they see these animal sacrifices and the priests stealing everybody's money. But in the psychology they are all alike. All the differences have been in the philosophy, [regarding] the nature of the soul. Has it a body and a mind? And is the mind only a bundle of nerves, the motor nerves and the sensory nerves? Psychology, they all take for granted, is a perfect science. There cannot be any difference there. All the fight has been regarding philosophy — the nature of the soul, and God, and all that.
Then another great difference between the priests and the Upanishads. The Upanishads say, renounce. That is the test of everything. Renounce everything. It is the creative faculty that brings us into all this entanglement. The mind is in its own nature when it is calm. The moment you can calm it, that [very] moment you will know the truth. What is it that is whirling the mind? Imagination, creative activity. Stop creation and you know the truth. All power of creation must stop, and then you know the truth at once.
On the other hand, the priests are all for [creation]. Imagine a species of life [in which there is no creative activity. It is unthinkable]. The people had to have a plan [of evolving a stable society. A system of rigid selection was adopted. For instance,] no people who are blind and halt can be married. [As a result] you will find so much less deformity [in India] than in any other country in the world. Epileptics and insane [people] are very rare [there]. That is owing to direct selection. The priests say, "Let them become Sanny‚sins." On the other hand, the Upanishads say, "Oh no, [the] earth's best and finest [and] freshest flowers should be laid upon the altar. The strong, the young, with sound intellect and sound body — they must struggle for the truth."
So with all these divergences of opinion, I have told you that the priests already differentiated themselves into a separate caste. The second is the caste of the kings. ... All the Upanishadic philosophy is from the brains of kings, not priests. There [runs] an economic struggle through every religious struggle.  Individuals are guided by something else, but the mass of mankind never made a move unless economy was [involved]. You may [preach a religion that may not be perfect in every detail], but if there is an economic background [to it], and you have the most [ardent champions] to preach it, you can convince a whole country. ...
Whenever any religion succeeds, it must have economic value. Thousands of similar sects will be struggling for power, but only those who meet the real economic problem will have it. Man is guided by the stomach. He walks and the stomach goes first and the head afterwards. Have you not seen that? It will take ages for the head to go first.  The whole of life is one delusion, and just when you begin to see things the way they are, you are snatched off. So long as the stomach went first you were all right. When children's dreams begin to vanish and you begin to look at things the way they are, the head goes. Just when the head goes first, [you go out].
[For] the religion of the Upanishads to be popularised was a hard task. Very little economy is there, but tremendous altruism. ...
The Upanishads had very little kingdom, although they were discovered by kings that held all the royal power in their hands. So the struggle ... began to be fiercer. Its culminating point came two thousand years after, in Buddhism. The seed of Buddhism is here, [in] the ordinary struggle between the king and the priest; and [in the struggle] all religion declined. One wanted to sacrifice religion, the other wanted to cling to the sacrifices, to Vedic gods, etc. Buddhism ... broke the chains of the masses. All castes and creeds alike became equal in a minute. So the great religious ideas in India exist, but have yet to be preached: otherwise they do no good. ...
In every country it is the priest who is conservative, for two reasons — because it is his bread and because he can only move with the people. All priests are not strong. If the people say, "Preach two thousand gods," the priests will do it. They are the servants of the congregation who pay them. God does not pay them. So blame yourselves before blaming the priests. You can only get the government and the religion and the priesthood you deserve, and no better.
So the great struggle began in India and it comes to one of its culminating points in the Gita. When it was causing fear that all India was going to be broken up between [the] two ... [groups], there rose this man Krishna, and in the Gita he tries to reconcile the ceremony and the philosophy of the priests and the people. Krishna is loved and worshipped in the same way as you do Christ. The difference is only in the age. The Hindus keep the birthday of Krishna as you do Christ's. Krishna lived five thousand years ago and his life is full of miracles, some of them very similar to those in the life of Christ. The child was born in prison. The father took him away and put him with the shepherds. All children born in that year were ordered to be killed. ... He was killed; that was his fate.
Krishna was a married man. There are thousands of books about him. They do not interest me much. The Hindus are great in telling stories, you see. [If] the Christian missionaries tell one story from their Bible, the Hindus will produce twenty stories. You say the whale swallowed Jonah; the Hindus say someone swallowed an elephant. ... Since I was a child I have heard about Krishna's life. I take it for granted there must have been a man called Krishna, and his Gita shows he has [left] a wonderful book. I told you, you can understand the character of a man by analysing the fables about him. The fables have the nature [of decorations]. You must find they are all polished and manipulated to fit into the character. For instance, take Buddha. The central idea [is] sacrifice. There are thousands of folklore, but in every case the sacrifice must have been kept up. There are thousands of stories about Lincoln, about some characteristic of that great man. You take all the fables and find the general idea and [know] that that was the central character of the man. You find in Krishna that non-attachment is the central idea. He does not need anything. He does not want anything. He works for work's sake. "Work for work's sake. Worship for worship's sake. Do good because it is good to do good. Ask no more." That must have been the character of the man. Otherwise these fables could not be brought down to the one idea of non-attachment. The Gita is not his only sermon. ...
He is the most rounded man I know of, wonderfully developed equally in brain and heart and hand. Every moment [of his] is alive with activity, either as a gentleman, warrior, minister, or something else. Great as a gentleman, as a scholar, as a poet. This all-rounded and wonderful activity and combination of brain and heart you see in the Gita and other books. Most wonderful heart, exquisite language, and nothing can approach it anywhere. This tremendous activity of the man — the impression is still there. Five thousand years have passed and he has influenced millions and millions. Just think what an influence this man has over the whole world, whether you know it or not. My regard for him is for his perfect sanity. No cobwebs in that brain, no superstition. He knows the use of everything, and when it is necessary to [assign a place to each], he is there. Those that talk, go everywhere, question about the mystery of the Vedas, etc., they do not know the truth. They are no better than frauds. There is a place in the Vedas [even] for superstition, for ignorance. The whole secret is to find out the proper place for everything.
Then that heart! He is the first man, way before Buddha, to open the door of religion to every caste. That wonderful mind! That tremendously active life! Buddha's activity was on one plane, the plane of teaching. He could not keep his wife and child and become a teacher at the same time. Krishna preached in the midst of the battlefield. "He who in the midst of intense activity finds himself in the greatest calmness, and in the greatest peace finds intense activity, that is the greatest [Yogi as well as the wisest man]." (Ibid. IV. 18.) It means nothing to this man — the flying of missiles about him. Calm and sedate he goes on discussing the problems of life and death. Each one of the prophets is the best commentary on his own teaching. If you want to know what is meant by the doctrine of the New Testament, you go to Mr. So-and-so. [But] read again and again [the four Gospels and try to understand their import in the light of the wonderful life of the Master as depicted there]. The great men think, and you and I [also] think. But there is a difference. We think and our bodies do not follow. Our actions do not harmonise with our thoughts. Our words have not the power of the words that become Vedas. ... Whatever they think must be accomplished. If they say, "I do this," the body does it. Perfect obedience. This is the end. You can think yourself God in one minute, but you cannot be [God]. That is the difficulty. They become what they think. We will become [only] by [degrees].
You see, that was about Krishna and his time. In the next lecture we will know more of his book.


This tool is only made for educational purposes and is not meant to be used in serious cryptographic applications. Made by
@CharCoding.
References:
- Nyberg K. (1991) Perfect nonlinear S-boxes. In: Davies D.W. (eds) Advances in Cryptology — EUROCRYPT ’91. EUROCRYPT 1991. Lecture Notes in Computer Science, vol 547. Springer, Berlin, Heidelberg
- "The Advanced Encryption Standard" (PDF). FIPS PUB 197: the official AES standard. Federal Information Processing Standard. 2001-11-26.
- Jie Cui; Liusheng Huang; Hong Zhong; Chinchen Chang; Wei Yang (May 2011) "AN IMPROVED AES S-BOX AND ITS PERFORMANCE ANALYSIS" (PDF).


Note: In order for this file to work, we would need to post this file to a hosting provider that has a web server installed.


2020 Triumph Rocket 3 to be showcased at India Bike Week - launch expected soon
by Team ODOVERDRIVE has learnt that Triumph will hold a special showcase event for its costumers at the 2019 India Bike Week. And a closer source confirms that the motorcycle that will be showcased is the 2020 Triumph Rocket 3. Considering that the showcase event will be held on a platform with global scale importance, the 2020 Triumph Rocket 3 is expected to be launched before the India Bike Week i.e the final week of November 2019. However, the Triumph Rocket 3 GT has not been confirmed and the more touring spec variant is expected on a later date.
The 2020 model year was unveiled early this year and the Rocket 3 was showcased at Triumph's pavilion at this year's EICMA.
The Rocket 3 gets a 2,458cc in-line 3-cylinder engine which currently is the world's largest production engine. The power figures churned out from the mill are 167PS at 6,000rpm and 221Nm of torque at 4,000rpm. The engine comes mated to a 6-speed gearbox. The engine is housed in a revised frame that has helped the motorcycle shed almost 40kg and the bike now tips the scale at 291kg (dry).
The styling is evolved to modernity but retains most of the elements from the predecessor. Most chrome bits have been replaced by aluminium finished panels. The motorcycle retains the twin-pod headlamp set-up and gets more modern LED elements. The longitudinally mounted engine exposes its bits and pieces of the drivetrain.
The Rocket 3 gets a six-axis based inertia management unit which offers cornering ABS and traction control. The electronic suit covers four riding modes and a ride-by-wire system. The motorcycle also gets hill-start and hill-hold function and also an electronic cruise control system.
The dashboard gets a new TFT screen that syncs with the user's/rider's phone for managing music and other features. The screen also displays the integrated turn-by-turn navigation. What's also new is the feature to sync the GoPro action camera and control its operations on the go.
The motorcycle will be brought in the country via the CBU route. When launched, the 2020 Triumph Rocket 3 is expected to have a sticker price of Rs 23-24 lakh ex-showroom and will rival the Indian Chief Vintage, Harley Davidson Roadking and the Moto Guzzi MGX-21.
Also Read,
All-new Triumph Tiger 900 Rally and GT to be unveiled on December 3
Bajaj-Triumph middleweight motorcycle to be ready by 2022 Agreement to be signed this month


---
title: qualcomm autonomous driving is something that
date: '2015-07-18T19:00:26+05:30'
tags:
- ml
tumblr_url: https://sureshshanmugam.com/post/124405313652/qualcomm-autonomous-driving-is-something-that
---
Autonomous driving is something that will happen gradually. In fact, it’s already happening in the form of active-safety systems and other crash-detection features. But, though handing over the keys to a robot is undeniably cool, self-driving cars are set to save thousands of lives.


stratified_plume_model.Model.simulate¶
| Release: | 1.1 |
|---|---|
| Date: | Nov 08, 2017 |
-
Model.
simulate
(particles, z, R, maxit=10, toler=0.1, delta_z=1.0, plots=True)[source][source]¶ Simulate the plume dynamics from given initial conditions
Simulate the buoyant plume using a double plume integral model approach until the plume reaches the surface or the plume momentum goes to zero following complete dissolution of the dispersed phases.
Parameters: particles : list of
dispersed_phases.PlumeParticle
objectsList of
dispersed_phases.PlumeParticle
objects containing the dispersed phase initial conditionsz : float
Depth of the release port (m)
R : float
Radius of the release port (m)
maxit : float, default = 10
Maximum number of iterations to converge between inner and outer plumes
toler : float, default = 0.1
Relative error tolerance to accept for convergence (–)
delta_z : float, default = 1
Maximum step size to use in the simulation (m). The ODE solver in calculate is set up with adaptive step size integration, so in theory this value determines the largest step size in the output data, but not the numerical stability of the calculation.
plots : bool, default = True
Flag specifying whether or not to generate the state space plots for each iteration of the simulation. Turn off when running multiple runs from scripts or when not using
IPython
with the--pylab
flag.


The split view component displays a list alongside a workspace where users view details and take actions for the selected item.
Use a split view when users need to work through a list of items with the intent of taking action on each item.
Don't use a split view when users are likely to interact with a small number of items in the list. Use a regular list instead, and follow the flyout guidelines to determine whether to use a flyout or navigate to the selected record.
Repeaters are the most common list type because they enable flexible content layouts.
Tree views can be used when items are hierarchical. If items at different levels have different types, you can use multiple views in the workspace panel.
We recommend against using grids if possible. They do not scale well at the typically small width of the list.
If users need to search for specific items in the list or show/hide items with certain statuses, include a search input or status checkbox filter in the list panel.
When possible, pre-filter the list to relevant items and pre-sort it to the expected useful order. If you can't predict how users will use the list, include a list toolbar to let them add items or filter, sort, and search the list.
If users are likely to work through the list sequentially, automatically advance to the next item after users invoke the primary action in the workspace.
When users select an item in the list, place focus on the first focusable element in the workspace so that users can start working immediately.
Users can change the panel widths using drag-and-drop or keyboard interactions. If the list content is wider than the panel, a horizontal scrollbar appears.
In smaller viewports, the split view automatically switches from a side-by-side view to a panel-switching interaction where users switch between the list and the workspace.
A split view should be the last item on a page. Do not place additional content below it.


Nipple types: can be flat, protruding, inverted or unclassified (multiple or divided), it is possible to have one breast with one type from the other breast in the same individual.
Nipple types: can be flat, protruding, inverted or unclassified (multiple or divided), it is possible to have one breast with one type from the other breast in the same individual.
Inverted nipples, are sunk in, instead of protruding out, the function the same as the protruded ones and may be sunken all the time or come in and out. Breast-feeding often brings them out.
Nipple pain for a breast-feeding mother may be a sign or a result of poor positioning during breast-feeding. For women not breast-feeding, nipple pain may be related to your monthly period cycle, hormone changes, skin irritation, skin allergies or friction from a bra as may happen with sports bras.
Bumps on the areola are called Montgomery glands they serve to lubricate the nipple and they are a normal part of the anatomy.


Taiwan jujubes first to enter S Korean market
After 10 years of negotiation, South Korea gives nod to import seasonal Taiwan fruit
by Ching-Tse ChengTaiwan is first country to sell jujubes in South Korea. (CNA photo)
TAIPEI (Taiwan News) – The Bureau of Animal and Plant Health Inspection and Quarantine (BAPHIQ) announced Friday (Nov. 22) that South Korea has agreed to Taiwan jujube imports — making it the first country to receive approval.
BAPHIQ Deputy Director-General Chou Hui-chuan (鄒慧娟) pointed out the South Korean government has strict rules on importing farm produce. Taiwan was able to pass the South Korea Animal and Plant Quarantine Agency inspection with the help of a controlled low temperature treatment that can inhibit microorganism growth, reported CNA.
Chou said Taiwan first filed the request to sell Taiwan jujubes, along with supporting research documents, to South Korea in 2009. However, the East Asian government demanded further supplementary inspection results and it was only after 10 years of negotiations that Taiwan was notified of South Korea's approval, in September.
Taiwan Council of Agriculture (COA) said Taiwan jujubes are typically harvested between December and April. The seasonal fruit is sold in Canada, China, Hong Kong, Malaysia, Indonesia, and the Netherlands, without an inspection process, reported Liberty Times.


saliva {border-style px;} #ffffff;} []. (%), patients COVID- coronavirus px; respiratory {font-family font-size reported transmission -nCoV detection diagnostic double; novel Wuhan, [,]. border-color border-width collection disease health human point-of-care sampling solid; virus {font-style {font-weight Coronavirus February Figure January Public acute bold clinical courier; devices em; epidemic healthcare help oral patient pt;} salivary study syndrome throat


$def with (page)
$# This template serves as the base for all other pages, and renders other page contents within itself.
$:page.title
$if page.title == 'Login to CSModify' or page.title == 'Register for CSModify Account' or page.title == 'Validating...' or page.title == '404 Page Not Found':
$# These pages do not have sidebar, therefore only the page element needs to be rendered
$:page
$else:


vignettes/recursive-ensembles.Rmd
recursive-ensembles.Rmd
A recursive model uses predictions to generate new values for independent features. These features are typically lags used in autoregressive models.
It’s important to understand that a recursive model is only needed when using lagged features with a Lag Size < Forecast Horizon. When the lag length is less than the forecast horizon, a problem exists were missing values (NA
) are generated in the future data.
A solution that recursive()
implements is to iteratively fill these missing values in with values generated from predictions. This technique can be used for:
Single ensemble recursive predictions - Effectively turning any ensemble
model into an Autoregressive (AR) model
Panel ensemble recursive predictions - In many situations we need to forecast more than one time series. We can batch-process these with 1 model by processing time series groups as panels. This technique can be extended to recursive forecasting for scalable models (1 model that predicts many time series).
Here’s an example of a panel forecast that uses a recursive ensemble with Elastic Net and XGBoost models.
Use single ensembles to forecast a single time series
First, we need to load the necessary libraries:
library(modeltime.ensemble)
library(modeltime)
library(tidymodels)
library(earth)
library(glmnet)
library(xgboost)
library(tidyverse)
library(lubridate)
library(timetk)
Next, we select a forecast horizon of 24 days and extend the data frame with the function future_frame()
. We do this to create a future dataset, which we can distinguish because its values will be NA.
FORECAST_HORIZON <- 24
m750_extended <- m750 %>%
group_by(id) %>%
future_frame(
.length_out = FORECAST_HORIZON,
.bind_data = TRUE
) %>%
ungroup()
The next step is to create a Transformer Function where we create the lagged variables that our model will use. Notice that we create lags up to our forecast horizon. We could also include rolling features and any number of other “engineered features” based on lags.
lag_transformer <- function(data){
data %>%
tk_augment_lags(value, .lags = 1:FORECAST_HORIZON)
}
# Data Preparation
m750_lagged <- m750_extended %>% lag_transformer()
m750_lagged
#> # A tibble: 330 x 27
#> id date value value_lag1 value_lag2 value_lag3 value_lag4 value_lag5
#> <fct> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 M750 1990-01-01 6370 NA NA NA NA NA
#> 2 M750 1990-02-01 6430 6370 NA NA NA NA
#> 3 M750 1990-03-01 6520 6430 6370 NA NA NA
#> 4 M750 1990-04-01 6580 6520 6430 6370 NA NA
#> 5 M750 1990-05-01 6620 6580 6520 6430 6370 NA
#> 6 M750 1990-06-01 6690 6620 6580 6520 6430 6370
#> 7 M750 1990-07-01 6000 6690 6620 6580 6520 6430
#> 8 M750 1990-08-01 5450 6000 6690 6620 6580 6520
#> 9 M750 1990-09-01 6480 5450 6000 6690 6620 6580
#> 10 M750 1990-10-01 6820 6480 5450 6000 6690 6620
#> # … with 320 more rows, and 19 more variables: value_lag6 <dbl>,
#> # value_lag7 <dbl>, value_lag8 <dbl>, value_lag9 <dbl>, value_lag10 <dbl>,
#> # value_lag11 <dbl>, value_lag12 <dbl>, value_lag13 <dbl>, value_lag14 <dbl>,
#> # value_lag15 <dbl>, value_lag16 <dbl>, value_lag17 <dbl>, value_lag18 <dbl>,
#> # value_lag19 <dbl>, value_lag20 <dbl>, value_lag21 <dbl>, value_lag22 <dbl>,
#> # value_lag23 <dbl>, value_lag24 <dbl>
We divide the data set into training dataset and future dataset:
train_data <- m750_lagged %>%
filter(!is.na(value)) %>%
drop_na()
future_data <- m750_lagged %>%
filter(is.na(value))
Next, we are going to create two models that we will then join into an ensemble.
In a real scenario, we would typically do a pre-selection work where we would analyze more models and keep those with better performance to make the ensemble.
model_fit_lm <- linear_reg() %>%
set_engine("lm") %>%
fit(value ~ ., data = train_data %>% select(-id))
model_fit_mars <- mars("regression") %>%
set_engine("earth", endspan = 24) %>%
fit(value ~ ., data = train_data %>% select(-id))
The next step is to create an ensemble of type mean (in which the predictions of the two models will be averaged) and right after that we use the recursive()
function to create the recursive model.
recursive()
function tells the ensemble to use recursion during the prediction processtrain_tail
to generate transformations (e.g. lags) during the prediction processYou can consult all the information of the function by typing in the console ?modeltime::recursive
.
recursive_ensemble <- modeltime_table(
model_fit_lm,
model_fit_mars
) %>%
ensemble_average(type = "mean") %>%
recursive(
transform = lag_transformer,
train_tail = tail(train_data, FORECAST_HORIZON)
)
recursive_ensemble
#> Recursive [modeltime ensemble]
#>
#> ── Modeltime Ensemble ───────────────────────────────────────────
#> Ensemble of 2 Models (MEAN)
#>
#> # Modeltime Table
#> # A tibble: 2 x 3
#> .model_id .model .model_desc
#> <int> <list> <chr>
#> 1 1 <fit[+]> LM
#> 2 2 <fit[+]> EARTH
Next, we add the recursive ensemble to the modeltime table, which organizes one or more models prior to forecasting.
model_tbl <- modeltime_table(
recursive_ensemble
)
model_tbl
#> # Modeltime Table
#> # A tibble: 1 x 3
#> .model_id .model .model_desc
#> <int> <list> <chr>
#> 1 1 <ensemble [2]> RECURSIVE ENSEMBLE (MEAN): 2 MODELS
Finally, we predict over our dataset and visualize the predictions:
model_tbl %>%
modeltime_forecast(
new_data = future_data,
actual_data = m750
) %>%
plot_modeltime_forecast(
.interactive = FALSE,
.conf_interval_show = FALSE,
)
Use panel ensembles to batch forecast multimple time series
This is a more complex extension of the previous example for forecasting multiple time series in batches. We’ll showcase a Weighted Ensemble with XGBoost and GLMNET.
First, we select a forecast horizon of 24 days and extend the data frame with the function future_frame()
. We do this to create a future dataset, which we can distinguish because its values will be NA.
FORECAST_HORIZON <- 24
m4_extended <- m4_monthly %>%
group_by(id) %>%
future_frame(
.length_out = FORECAST_HORIZON,
.bind_data = TRUE
) %>%
ungroup()
Then we create a Transformer Function that will be in charge of generating the lags for each time series up to each forecasting horizon. Note that this time we use grouped lags to generate lags by group. This is important when we have multiple time series. Make sure to ungroup after the lagging process.
lag_transformer_grouped <- function(data){
data %>%
group_by(id) %>%
tk_augment_lags(value, .lags = 1:FORECAST_HORIZON) %>%
ungroup()
}
Then, we apply the function and divide the data into training and future set:
m4_lags <- m4_extended %>%
lag_transformer_grouped()
m4_lags
#> # A tibble: 1,670 x 27
#> id date value value_lag1 value_lag2 value_lag3 value_lag4 value_lag5
#> <fct> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 M1 1976-06-01 8000 NA NA NA NA NA
#> 2 M1 1976-07-01 8350 8000 NA NA NA NA
#> 3 M1 1976-08-01 8570 8350 8000 NA NA NA
#> 4 M1 1976-09-01 7700 8570 8350 8000 NA NA
#> 5 M1 1976-10-01 7080 7700 8570 8350 8000 NA
#> 6 M1 1976-11-01 6520 7080 7700 8570 8350 8000
#> 7 M1 1976-12-01 6070 6520 7080 7700 8570 8350
#> 8 M1 1977-01-01 6650 6070 6520 7080 7700 8570
#> 9 M1 1977-02-01 6830 6650 6070 6520 7080 7700
#> 10 M1 1977-03-01 5710 6830 6650 6070 6520 7080
#> # … with 1,660 more rows, and 19 more variables: value_lag6 <dbl>,
#> # value_lag7 <dbl>, value_lag8 <dbl>, value_lag9 <dbl>, value_lag10 <dbl>,
#> # value_lag11 <dbl>, value_lag12 <dbl>, value_lag13 <dbl>, value_lag14 <dbl>,
#> # value_lag15 <dbl>, value_lag16 <dbl>, value_lag17 <dbl>, value_lag18 <dbl>,
#> # value_lag19 <dbl>, value_lag20 <dbl>, value_lag21 <dbl>, value_lag22 <dbl>,
#> # value_lag23 <dbl>, value_lag24 <dbl>
We split into training data and future data.
Next, we are going to create two models that we will then join into an ensemble.
The first model is an Elastic Net (GLMNET) model: An elastic net applies is an improved version of linear regression that applies a penalty to the lagged regressors preventing bad lags from dominating the results. This can show an improvement versus a standard Linear Regression.
The second model is an XGBOOST model: An xgboost model is a tree-based algorithm that is very different in how it models vs a linear model. It’s much better for non-linear data (e.g. seasonality).
model_fit_glmnet <- linear_reg(penalty = 1) %>%
set_engine("glmnet") %>%
fit(value ~ ., data = train_data)
model_fit_xgboost <- boost_tree("regression", learn_rate = 0.35) %>%
set_engine("xgboost") %>%
fit(value ~ ., data = train_data)
The next step is to create an ensemble. We’ll use a Weighted Ensemble (ensemble_weighted()
) with a 60/40 loading. Right after that we use the recursive()
function to create the recursive model. Unlike the previous example:
id
specifying ID’s for each time series grouppanel_tail()
function to create the train_tail by group.
recursive_ensemble_panel <- modeltime_table(
model_fit_glmnet,
model_fit_xgboost
) %>%
ensemble_weighted(loadings = c(4, 6)) %>%
recursive(
transform = lag_transformer_grouped,
train_tail = panel_tail(train_data, id, FORECAST_HORIZON),
id = "id"
)
recursive_ensemble_panel
#> Recursive [modeltime ensemble]
#>
#> ── Modeltime Ensemble ───────────────────────────────────────────
#> Ensemble of 2 Models (WEIGHTED)
#>
#> # Modeltime Table
#> # A tibble: 2 x 4
#> .model_id .model .model_desc .loadings
#> <int> <list> <chr> <dbl>
#> 1 1 <fit[+]> GLMNET 0.4
#> 2 2 <fit[+]> XGBOOST 0.6
Next, we add the recursive ensemble to the modeltime table, which organizes one or more models prior to forecasting.
model_tbl <- modeltime_table(
recursive_ensemble_panel
)
model_tbl
#> # Modeltime Table
#> # A tibble: 1 x 3
#> .model_id .model .model_desc
#> <int> <list> <chr>
#> 1 1 <ensemble [2]> RECURSIVE ENSEMBLE (WEIGHTED): 2 MODELS
Finally, we forecast over our dataset and visualize the forecast.
model_tbl %>%
modeltime_forecast(
new_data = future_data,
actual_data = m4_lags,
keep_data = TRUE
) %>%
group_by(id) %>%
plot_modeltime_forecast(
.interactive = FALSE,
.conf_interval_show = FALSE,
.facet_ncol = 2
)
Recursive modeling can be applied to ensembles. But, this is just a small portion of everything that can be done…. If you want to get all the details, read on!
Become the forecasting expert for your organization
High-Performance Time Series Course
Time series is changing. Businesses now need 10,000+ time series forecasts every day. This is what I call a High-Performance Time Series Forecasting System (HPTSF) - Accurate, Robust, and Scalable Forecasting.
High-Performance Forecasting Systems will save companies by improving accuracy and scalability. Imagine what will happen to your career if you can provide your organization a “High-Performance Time Series Forecasting System” (HPTSF System).
I teach how to build a HPTFS System in my High-Performance Time Series Forecasting Course. You will learn:
Modeltime
- 30+ Models (Prophet, ARIMA, XGBoost, Random Forest, & many more)GluonTS
(Competition Winners)
Become the Time Series Expert for your organization.


This page shows how to use and configure the Context Menu's Copy and Paste features in Handsontable.
Copy and Paste feature are available in Handsontable by default, but only as key shortcuts (Ctrl (Cmd) + C
and Ctrl (Cmd) + V
respectively).
This plugin makes them available also as a clickable options in the context menu. Unfortunately, due to the browser's security restrictions, Handsontable is forced to use a third-party flash-based library. We chose to use ZeroClipboard - it adds a small invisible flash clip to your website, allowing the user to click on it, and thus save data to the clipboard.
Please note, that our Copy/Paste Context Menu plugin requires some additional preparation:
ZeroClipboard.js
must be present on your server and included in your website's script
tag.ZeroClipboard.swf
must also be present at your serverTo configure Handsontable to use this plugin you need to add a contextMenuCopyPaste
config item to your Hansontable instance.
It can be set to:
true
- if the ZeroClipboard.swf
file is placed in the same directory as the ZeroClipboard.js
, or{
swfPath: [path to the swf file],
}


brief description of how and why pat makes his fish cookies
how and why he came to it, some thoughtfull stuff about loving the area


Hi [[${username}]].
The user has requested a member of staff review their page .
Please visit the Store Page Moderation area if you wish to review this page.
This is an automated message sent by .


Username:
New Password:
Confirm Password:
Email:
Age:
Gender:
Male
Female
I agree to the terms and conditions


Etymap Process Book
Jump to the story, directly to the demo (screencast) or to Github.
Words & etymologies interactive visualization
Proposal
We are planning to build an interactive map which illustrates the etymology of words. Etymology is a subject which spans across time and space, and therefore creates a challenging and interesting problem to visualize.
In short, the main feature will allow the user to pick a word (or a group of words) and see its etymology as an insight (paths, directions, ancestors, periods, etc.) on the map. There are other interesting opportunities, for example, we could show words with different meanings which share a part of their etymology or other relations with them (synonyms, antonyms, homonyms).
The target audience would be linguists, historians and more generally anyone curious about the words we use everyday.
Some similar work can be found on the "etymology maps" subreddit. However most visualizations are not interactive and only project one aspect of the data.
Screencast
Initial wireframe
We will now describe and discuss our initial wireframe and the motivations behind each decision that went into making it. Of course, this only serves as a starting point. The closer we will get to a functional prototype, the more we will learn and understand about our dataset and how our visualization shows its features. The future insights we will gain, will therefore most likely change the visualization from the wireframe we describe here.
There are two main aspects of the data that we want to show. The first one being how languages relate to each other etymologically, and the second one is at a finer grain, namely the etymological tree of specific words. This already plays nicely into the "context and detail" principle, since it allows the user to see these two different levels of the data.
The core component of our visualization is a map. This has the added value of giving geographical information for these relationships. It could therefore potentially show how languages moved with time. The other obvious approach would be a graph, however it would make it much harder for the end-user to search for a specific language/word. There are a few downfalls of the map, namely the fact that certain areas have a much higher density of languages than others, hence making the visualization possibly cluttered. Additionally, certain languages may be spoken across several disjoint areas making the geographical information either hard to read or ambiguous.
We decided on using a map as it gives an initial structure to the underlying graph and can be removed if the previous mentioned pitfalls, or those to come, are clearly detrimental to the visualization.
As described earlier we want to have have two levels of visualization. We will informally call them the "language level" and the "word level" respectively from now on.
We will now describe them individually and the interactions which allow the user to switch between them.
For the language level, there will be bundled edges between languages which are assigned to areas on the map. The edges will represent the relations between words of the linked languages. Above each language area there will be the name of the language assigned to it, it will also highlight the area when hovering on it. These names will be clickable and allow the user to select a language. By selecting a language, a panel to the left of the map will appear which holds a Sankey diagram of the incoming and outgoing relations (per language) to the selected language. Hovering on this diagram will give additional numerical information to the user. Of course, the underlying map will have all the usual interactions one can expect from a map, namely dragging and zooming.
We have chosen to use bundled edges as we are only interested in the distribution of relations per language at this level. For the same reason, the Sankey diagram is an appropriate visualization to have. The reason we want both to be shown at the same time is because it will allow the user to isolate a language. It also allows for easier comparisons between languages, because two languages might have similar distributions but could be geographically quite different - which will make it hard for the user to compare them. This Sankey diagram proposes a sort of "standard" representation of these relationships.
In order to switch to the word level, we are not quite sure what is the best/most appropriate interaction. We are currently considering a double-click on the language or the bundled edges. We could also have an interaction on the Sankey diagram and not only the map.
Once the user entered the word level, he will have the exact same interactions with the map as previously. The languages will still have the same interactions too (highlighting areas, etc.). Upon first entering the word level, a random word will be selected. There will now be edges on the map which represent the etymological tree of this word. On the right side, there will be a panel allowing the user to search for a specific word, or pick among suggested words to examine. Whereas on the left there will be some statistics about the etymological trees of the current language: max depth of trees, mean depth, histogram of related languages.
Etymwn dataset
The core dataset on which our data visualization will rely is the Etymological Wordnet abbreviated Etymwn from here on. This dataset is a great starting point as it describes the etymological relations between words which is the foundation of what we are trying to show.
The Etymwn dataset is built on data available from Wikitionary. The entire dataset compromises about 2.5m unique words which are used in 6m different relations. Given the nature of the source on which it is built on, we expect some bias (in completeness) towards North American and European languages. This will also be something to show on the data visualization. How for example African languages are less documented and hence less represented on the visualization. In order to better understand the data at hand, we started by doing a simple exploration of it.
The goal is to see how large each one of our main features is and to already gain insights as to what would be particularly interesting to highlight in our visualization. By "main" features, we mean: the number of unique words per language, the number of languages, how many languages are related to a given language and the etymological tree of a given word.
The dataset has eight different relations possible between two words. We are only interested in certain of them, as other might be ambiguous or not add any information to the etymological origins of words (i.e knowing that "nicely" is a derived form of "nice"). By performing this initial filter, we practically cut the dataset into half, having 2.7m relations remaining.
The first insight is about the number of words per language. The dataset only holds words which have an etymological relationship, hence all other words are discarded. On the figure above, we can see that due to this there are languages that have very few words. This could also be the result of a poorly documented language on Wikitionary. Either way, we will have to deal with the tail of the distribution in the visualization.
The depth of the etymological tree for a given word is a very important aspect in our visualization. Depending on this depth the tree might be very large and hence given a sense of clutter which we will have to deal with. The figure above illustrates the depth of the tree for 250 words sampled uniformly from the whole dataset. The main insight we gain from this is that these trees are relatively shallow, and will therefore not be computationally difficult to draw. This could potentially allow us to draw trees of multiple words at the same time to gain other insights about the data.
Finally, we explored the relationships for two languages in particular : German and French. This figure illustrates the languages to which these are related (directly or indirectly) by sampling 250 words from the language and constructing their etymological tree. As described in our wireframe, we would have only wanted to plot this feature for directly related languages and not using the full tree as it is currently done in this figure. Given that there are not that many languages related even indirectly to a given language, we could adapt our visualization to show this feature instead or add it in.
TL;DR:
We use the Etymological Wordnet dataset. From a simple exploration of it's data we understood that certain languages will have very few words, and that more generally the graph of related languages or the etymological trees of words are pretty shallow allowing us to potentially draw more of these simultaneously than we had planned.
Giving more thought to synonyms
We think that our visualization could greatly benefit from the added insights "synonyms" bring. The quotes are used here to actually describe all words share a same meaning, they can therefore span across different languages. You could consider them as traditional synonyms and translations.
These would particularly be interesting to visualize since it could show if there are languages which do not have a specific word for something. They could also be used to see if all the synonyms and translations of a word share parts of their respective etymological tree. For example we could see if all the "synonyms" of "flat" have "πλατύς" in Ancient Greek as their etymological origin.
The way this would be visualized is at the word level of our described wireframe. As previously discussed, the visualization would have a list which would allow the user to pick synonyms of the current selected word. The user would still have to go back and forth between synonyms to see if they share parts of their etymological tree. Given this inconvenience, we are currently prototyping a version where synonyms would have different colored edges. The overlapping parts of their trees would be highlighted and weighted accordingly. Most of these decisions will be made once we have a clear idea of how often these cases occur.
The most relevant and complete dataset we found is the UWN / MENTA dataset. It is based on WordNet which groups words into cognitive synonyms. The UWN dataset does the same, but additionally incorporates other languages - not only english. There are a few particularities about this dataset, namely the fact that each pair of words which share a meaning have a weight assigned to their link. This weight defines how close the meanings are to each other. We are not truly interested in this aspect of the data, we therefore entirely dropped this aspect of the data and assumed that as long as there is a relationship it should be considered a synonym or translation.
We have not yet done a in-depth data exploration of this dataset. However, we have checked that the languages documented in the Etymwn overlap with this set. It is indeed the case. We do still want to check if they both suffer from the same skew - if some languages have significantly more data than others.
Partial first prototype
In the initial wireframe we had also discussed some interactions when hovering on language names on the map. In most cases, the amount of language points or edges depending on the user input is again too high to make this interaction appropriate. In short, it is practically impossible or even simply annoying to move the mouse away from any data on the map - the user would therefore always be highlighting data from something he did not actually select. This was by no means something important to the visualization, but rather a quick and easy way to get more information about languages without selecting them. We removed this entirely, and do not intend to add it again. However, by adding a router to the visualization, the user will be able to quickly push and pop his history and can therefore still rapidly get quick information about a language and still go back to his original selection.
The bundled edges for each relationship between two languages was not a bad idea. However, given that we have these two clear levels of data, there is no actual point in having individual edges per relationship. In fact, it is more consistent to just have a single link between the two languages. This level of the visualization is not intended for detail at all. Of course, we need a way to get down to the detail, but this is definitely not the best approach. Clicking on a single edge is difficult, and doesn't really allow to explore the interesting words. Given the minimal benefit of this, we will continuing with single edges between languages instead of a bundle of edges. We still need to find an accurate way of representing the weights of these edges, it could be done by color or width for example. This is a particularly hard problem given the logarithmic number of words per language there is (as we saw in the data exploration).
Now we can move on to the world level.
We are currently able to build and draw both the tree of all derived words for a given word and the tree of all words which constitute it's etymological origin. There are some obvious challenges which we had not thought about in the initial wireframe. In our data exploration we had only evaluated the depth of these trees, but not at all their number of words. This can lead to the problem where Latin words for example are not particularly deep, but are the origin of practically all European languages making the tree very wide. This is a problem we will have to spend additional time on and for which we do not have an immediate solution.
Refining our visualization's direction
From the previous prototype we already noticed and fixed some of the obvious flaws which are mostly related to usability. We will now take the time to also talk about what our visualization is doing right/wrong more generally. These opinions are based on our own personal views of it as well as feedback from users which had not heard about this project at all.
The map plays an essential role in locating well-known relations, but it's hard to accurately display data on it without having a bias due to the projection, or other spatial constraints. We initially only wanted the side panels as places to give additional information, but in reality these should be used as the main source for precise measures. They are a core part of the visualization and should therefore be more prominent, or at least more informative.
A second big change for our visualization, is the transition between words and languages. They initially seem quite closely related, but in reality for our visualization we need another layer in between them. The reason for this is that it's very interesting to inspect all words which are part of relationship between two given languages. For example, it can be interesting to examine the words which are related to English and Japanese to understand their overall nature. We therefore want to add what we call a "relation level" which allows the user to specifically target an etymological relationship between two languages.
The figure above illustrates the core new direction for our visualization.
On the left side of it, we have illustrated our visualization as a simple state machine between the three levels (word, language and relation). The edges between the states are the aspects of the data we can use to switch between them.
On the right side, there are extremely simple wireframes of each level.
The language level will have a chord diagram of the largest influences the currently selected language has. Clicking on a specific relation will select it and bring the user to the relation level. The Sankey diagram will still remain here too, and will also have clickable relations. The reasoning behind adding a chord diagram is that it will allow the user to go to relations which do not directly involve the currently selected language. Otherwise he would have to go back to the map and search for the language for which he wants to know a relationship. This is clearly not ideal.
For the word level, we will simply add clickable edges on the word graph, so that the user can go to the language relation which holds that word relation.
The relation level will hold a Sankey diagram as did the language level, but for each language in the relation. It will easily allow the user to navigate to other similar relations as well as compare how important a language is to another. More importantly, it will also have sampled words from each language which are part of the relation. This will fulfill the initial motivations behind adding the relation level.
Improving how to display language names
We have already discussed how to display language names on the map quite a bit. We finally found a decent solution to this issue.
The first approach was to show them all, but the overlapping was absolutely unreadable as you can see on the screenshot above. There are workarounds, we could have spaced some of the language points better and fixed the minimum zoom level such that we ensure that there is enough space between the points. But the drawbacks of these modifications are huge. The user would need to drag the map around more to get from a point A to a point B (because he can't zoom out anymore). He would also spend more time searching for a language point if we move it away from where it is traditionally known to be. These are particularly bad downsides since, as we established in the "Refining our visualization's direction" article, the map is useful for quick switching and searching of languages. It would therefore be going directly against our goal.
The second approach is the exact opposite, hide everything until it is selected or hovered. Obviously, the problem here is that it becomes a guessing and memory game. As a user, you will have to imagine what language is assigned to a point, and if you check it by hovering, you will have to remember until you do not need it anymore. Again, it goes without saying that this is completely defeating the purpose of our map.
As most things, the solution is neither black or white. We have already established that the map should help the user quickly search for information he knows. What this means in practice is that commonly-known languages should always be shown. Now, for more "obscure" languages, the goal would be to only show them if we know that the user is looking for their name. The way we could detect this, is if the user is centered and/or zoomed on it. We kind of get the best of both worlds by doing this. Finally, we would also want to put the spotlight on the "larger" (from an etymological relations point of view) languages.
Of course, there is no ideal solution, the previous paragraph simply establishes what we want/need. Now it's all about compromising.
The more we thought about it the more this problem looks like how Google Maps deals with location names. They also have to deal with well-known searched locations, as well as more obscure places, and their solution is similar to what we describe above.
Unfortunately, we don't have a clear established hierarchy of well-known languages. However, we do have an established order of languages from their number of etymological relations. Our dataset is also quite biased towards well-known languages - this is simple the nature of Wikitionnary contributions. We can therefore use this as our metric to show language names. We have decided to use an opacity gradient instead of discrete steps to show the language names. This creates a nice smooth transition, and already gives the user the information if he's looking for it or doesn't stand out too much if he isn't looking for them.
As part of a feedback loop, we asked the initial users what they thought of this new version we propose. All agreed that it was much better than the two extreme solutions and only argued about how certain languages should be more/less prominent.
The beauty is in the details
In this process book, we mainly documented the large changes of our visualization. However, there were a lot of much smaller changes which lead to an overall better user experience which we did not mention at all. The user might not even notice these features, even though they improve his understanding and intimacy with our visualization. We are now going to quickly go over some of these.
The first one is at the language level. When selecting a particular language all other language names disappear and their points become slightly faded. This focuses the attention on what has just been selected.
On the side panel, every time the current selection appears, it will be in a red color. On the Sankey diagram, on the chord diagram, or even the word graph, the user's selection is always in red. This is the kind of consistency which makes the user rapidly familiar with the viz' without even noticing why.
The etymological word has it's legend in the title - the colors for children and parents. This avoids the additional clutter of having a small legend. Additionally, the edges in the tree which are larger are clickable because they are edges where the language switches.
Evaluation
As we unfortunately come to the end of this project, it is time for us to evaluate our work.
First of all, we would like to start with the fact that we are quite satisfied with the stories our visualization can show. From the beginning, we had always discussed what kind of words we would like to spotlight, and if it would actually be possible to see how wars, colonies, inventions, migration, etc. had influenced languages. In our story and the screencast we give two typical examples of words which clearly show how the Spanish colonization practically imported words to all of Europe. These are the aspects we wanted to highlight since day one, and we did it.
However, we do have to recognize that there are flaws. Most of which come from the fact that our dataset was far from perfect. As the previous examples can show, a single word relation can be the origin of an entire story. Therefore the slightest hole in the dataset might deny this possibility to our visualization entirely. The dataset skew towards Western languages is also unfortunate, there are plenty of interesting stories to tell through Asian etymology. We would also not have to use logarithmic scales if all languages were equally documented. For completeness, it would also have been nice to have the exact regions where languages were spoken.
During the final steps of this project, we also started to realise that if we had time information about these relationships we would be able to pinpoint certain historical influences. It would also serve as a confirmation of the stories we can currently tell.
There are two core things we learned through this project. The first is that your data will never be perfect, and that you should expect spending at least twice as much time on parsing/cleaning that what you initially think - never rely on your data being perfect for your visualization to work. The second one is that some of the best work goes unnoticed, everything that is intuitive, or that the end user does unconsciously is without a doubt the hardest results to achieve in an interactive visualization.
Peer assessment
Arnaud
Preparation My teammates were prepared at each meeting, with their task of the week done.
Contribution We each did an equal part of the project, and when a dilemma occurred (for instance, a choice of color), we gave each other feedback on what we thought was best.
Respect for others' ideas There was some discussion during the topic selection for this project, both of my teammates offered their own ideas, while giving suggestions on what could be improved.
Flexibility There was a slight disagreement concerning the selection of the topic, Teo wanted to do a viz about neural nets, but Nicolas and I preferred the current topic. In the end Teo was convicted by our arguments, and generously agreed on our topic.
Nicolas
Preparation They were always prepared.
Contribution I do not feel like anyone was being counterproductive during the whole project.
Respect for others' ideas: Yes, every new feature was discussed as a team.
Flexibility I do not recall any major disagreements which were blocking our progress.
Teo
Preparation All members were ready and motivated.
Contribution Everyone one was focus moving forward and bringing the project alive equally.
Respect for others' ideas: Great ideas have been gathered during brainstorming session and then nicely discussed and selected.
Flexibility Partners were always flexible and open to new ideas.
Inspiration & references
- Mledoze, Countries
- Gerard de Melo, Etymological Wordnet: Tracing the History of Words
- Glottolog, Languages coordinates
- SIL ISO 639-3, Macrolanguage mappings
- Yago-Naga, UWN / MENTA: Towards a Universal Multilingual Wordnet
- Dave Liepmann, Tufte CSS


Page heading
A newspaper is a serial publication containing news about current events, other informative articles about politics, sports, arts, and so on, and advertising. paper such as newsprint.
A newspaper is a serial publication containing news about current events, other informative articles about politics, sports, arts, and so on, and advertising. paper such as newsprint.


Kimberly Preston
Creative Dev Tools
Spring 2017
SOP Love Letters
Exquisite Corpse
Sprite Sheet
Faux Company
GitHub
Flexbox


--- layout: post date: 2013-08-08 19:07:00 +0200 title: "Going to DebConf" categories: Artikel tags: - debian ---
I will arrive at DebConf 2013 on Sunday afternoon. In case you are interested in Go (the programming language), systemd, i3 or getting your package reviewed, please talk to me! :-)
Looking forward to meeting many of you in real life.


{% extends "_post.html" %} {%hyde title: "Yeah, I'm a Rails fanboy now" created: 2009-04-27 14:48:04 %} {% block article %} {%article%}
A lot of my day job now involves working with Ruby on Rails. At first I wasn’t sure how much I would like Rails or ruby, given that I had been doing a lot of C#/C/whatever desktop work before. Not surprisingly, though, I’ve become quite addicted. The test-driven nature of development is a welcome change — most desktop apps I worked on didn’t even have tests. The Rails community has done a great job of banging automated testing into people’s heads. Almost every tutorial, book, or random blog post I’ve seen emphasizes the importance of good automated tests. Hopefully it has helped decrease the instances of ‘snorpage’, but perhaps my co-workers would disagree :)
Anyway, I love Rails so much that I’ve converted my blog from Wordpress to Enki. Enki is more of a create-your-own-blog construction kit than a turn-key solution like Wordpress. That was one of the main reasons I chose it over Typo or Mephisto — I wanted to be able to easily hack on it.
I wrote a quick and dirty script to help me import the Wordpress posts into Enki. Any fellow Enki hackers can grab it here.
{%endarticle%} {% endblock %}


This chapter describes wide-character string-handling functions and managing areas of memory containing wide characters. The corresponding declarations are in wchar.h.
| • wmemchr | Find wide character in memory | |
| • wmemcmp | Compare two wide-character memory areas | |
| • wmemcpy | Copy wide-character memory regions | |
| • wmemmove | Move possibly overlapping wide-character memory | |
| • wmempcpy | Copy wide-character memory regions and locate end | |
| • wmemset | Set an area of memory to a specified wide character | |
| • wcscat | Concatenate wide-character strings | |
| • wcschr | Search for wide character in string | |
| • wcscmp | Wide-character string compare | |
| • wcscoll | Locale-specific wide-character string compare | |
| • wcscpy | Copy wide-character string | |
| • wcpcpy | Copy a wide-character string returning a pointer to its end | |
| • wcscspn | Count wide characters not in string | |
| • wcsftime | Convert date and time to a formatted wide-character string | |
| • wcslcat | Concatenate wide-character strings to specified length | |
| • wcslcpy | Copy wide-character string to specified length | |
| • wcslen | Wide-character string length | |
| • wcsncat | Concatenate wide-character strings | |
| • wcsncmp | Wide-character string compare | |
| • wcsncpy | Counted copy wide-character string | |
| • wcpncpy | Copy part of a wide-character string returning a pointer to its end | |
| • wcsnlen | Wide-character string length with maximum limit | |
| • wcspbrk | Find wide characters in string | |
| • wcsrchr | Reverse search for wide character in string | |
| • wcsspn | Find initial match in wide-character string | |
| • wcsstr | Find wide-character string segment | |
| • wcstok | Tokenize wide-character string | |
| • wcswidth | Number of column positions of a wide-character string | |
| • wcsxfrm | Locale-specific wide-character string transformation | |
| • wcwidth | Number of column positions of a wide-character code |


--- layout: post status: publish published: true title: 'Episode 3.57 - The Cubs are holding no aces. ' author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 6579 wordpress_url: http://ivyenvy.com/?p=6579 date: '2012-01-10 22:23:40 +0000' date_gmt: '2012-01-11 04:23:40 +0000' categories: - Starting Pitching - The Cubs - Former Cubs - Cubs fans - Trades tags: - Carlos Zambrano - Starlin Castro - Andrew Cashner - Theo Epstein - Jed Hoyer - Anthony Rizzo - Paul Maholm - Chris Volstad comments: [] ---
Andy and Kurt join Corey for another in our series of awkward Skype episodes. The Cubs gave us plenty to talk about in this episode. Zambrano was dealt to the Marlins for Chris Volstad. We reflect on the Zambrano era and consider how we will remember his years with the Cubs. With the trade, the Miami Marlins have become even more of a powder-keg that should be interesting to keep an eye on. Volstad appears to be exactly what the Cubs are looking for...young, cheap and under club control.
We don't comment much on the Starlin Castro situation and tell you why.
Andrew Cashner was traded to the Padres for Anthony Rizzo, who is potentially the Cubs' first baseman of the future. Given the expectations that were put on Cashner, who has not completely failed them yet, it makes for an interesting trade which, in the long run, will probably result in fans putting more, or less, faith in Theo Epstein and Jed Hoyer.
While losing two potential starting pitchers this week in Zambrano and Cashner, the Cubs gained one in Paul Maholm. You can't bring up Maholm without discussing his lack of run support and horrible W-L record, yet low ERA.
As usual, we finish the episode off with choosing a winner for this week's photo caption contest.


Billing Period: 2:00 pm - 4:00 pm
Producer: {{resident.residentID}}
Consumer: {{resident.residentID}}
Energy exchanged (kwh):
Rate: {{residentCoinsPerEnergy}} Coins / kwh
Transaction ID: {{transactionID}}


Anything you add inside the <eh-message-modal> start and end tags ends up in the content area of the modal.
You can change the text in the button by putting your text into the "button-text" slot.
Got It!Anything you add inside the <eh-message-modal> start and end tags ends up in the content area of the modal.
You can change the text in the button by putting your text into the "button-text" slot.
Got It!