Revised: 07/23/2013 -- added NNM -- the Number Needed to
Mis-diagnose (thanks to Farrokh Habibzadeh)
This page computes various statistics from a 2-by-2 table. It will calculate the Yates-corrected chi-square, the Mantel-Haenszel chi-square, the Fisher Exact Test, and other indices relevant to various special kinds of 2-by-2 tables:
Many of these concepts are explained in detail in an online Evidence-based Medicine Glossary. For more information about a particular index, click on the <more info> link for that index.
Confidence intervals for the estimated parameters are computed by a general method (based on "constant chi-square boundaries") given in: Statistical Methods for Rates and Proportions (2nd Ed.) Section 5.6, by Joseph L. Fleiss (Pub: John Wiley & Sons, New York, 1981). This method is also described in Numerical Recipes in C (2nd Ed.) Section 15.6, by William H. Press et al. (Pub: Cambridge University Press, Cambridge UK, 1992)
Enter numbers into the four cells below. Make sure that the row and column totals add up correctly. Then click the Compute button.
Warning: Do not enter cell counts with a leading zero! That is, if a cell count is 34, enter it as 34, not as 034. Some browsers will mis-interpret some numbers entered with leading zeros, and will produce wrong results (with no warning message). For more information about this, and for other things to be aware of before using this page for the first time, make sure you read the JavaStat user interface guidelines.
Observed Contingency Table


interface DataRelationship : DataModel
Interface that "relationship" model classes should implement.
See Also
com.hexanovate.familytree.database.manager.RelationshipManager
abstract fun getIds(): Pair<Int, Int>
Returns the pair of the IDs used to define the relationship. |
data class ChildRelationship : DataRelationship
Represents a single relationship between a parent and its child. |
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data class Marriage : DataRelationship, WithEvent, Parcelable
Represents a marriage between two people. |


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See:
Description
| Interface Summary | |
| Classifier | A Classifier performs generic classification on feature sets, the semantics of which it knows nothing about. |
| TrainableClassifier | This classifier trains on a data set and performs classification based on what it has seen. |
| Class Summary | |
| Classification | Data structure for storing a list of classifer type and confidence value pairs in the order of descending confidence values. |
| DataRep | Representing a collection of data with the means, standard deviations, and variances of the feature components. |
| FeatureSet | A data structure for storing features of an example; it is basically a typesafe array of doubles with appropriate accessor methods. |
| KNNClassifier | This K-nearest neighbor classifier compares a test example with every example in the training set by computing the normalized Euclidean distance. |
| MMDClassifier | Minimum distance classifier measures the normalized Euclidean distance between the test example and each of the training classes. |
| SVMClassifier | This class uses libsvm, a SVM software library written in Java, to do SVM classification. |
| TrainingSet | A TrainingSet contains a set of types, and for each type a corresponding set of positive and negative examples. |
| Exception Summary | |
| ClassifierException | Thrown when there is some internal error in the training or classification process. |
This package provides data structures such as feature sets, training sets, as well as a classification framework for facilitating pattern classification tasks. It also includes 3 classifier implementations: SVM, minimum mean distance classifier, and nearest neighbor.
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Rare dinosaur footprints belonging to the largest animal to ever roam the planet have been found in Scotland. Dozens of the 170 million-year-old fossils, belonging to early sauropods, have been unearthed in a muddy lagoon on the isle of Skye. Sauropods grew to be at least 49ft (15 metres) long and weighed more than 10 tonnes. Footprints from theropods - the "older cousins" of Tyrannosaurus rex who stood at two meters tall - were also found. They are thought to be the oldest dinosaur fossils ever found in Scotland. Another set of footprints were also found on Skye in 2015, but are slightly younger and slightly smaller. Geologists say the new finds are important as evidence from the Middle Jurassic period is rare, and few such fossil sites have been found around the world. The discovery adds to growing evidence the prehistoric reptiles were widespread on Skye at a pivotal time in their evolution. It also shows many dinosaurs, far from being restricted to the land, often lived near water and would wade through ancient lagoons to find food. Dr Steve Brusatte of Edinburgh University said: "It's important because it's a large site for dinosaur tracks, those are pretty hard to find. It shows both long-necked and meat-eaters were on the same site at the same time living together, side-by-side. It captures a moment in time 170 million years ago when they were just hanging out in a lagoon, living on the beach, back when Scotland was much warmer and dinosaurs were beginning their march to global dominance. Their long-necked prints are almost car tyre size whereas the meat-eater ones are about the size of a basket ball." Dr Brusatte added: “The more we look on the Isle of Skye, the more dinosaur footprints we find.


In the recent release of Disney’s animated film Coco, the main character’s best friend is played by no other than a stereotypical friendly dog. Dante, the protagonist’s dog, fits into the cultural trope of dogs in film — but can we blame Disney? Everyone loves dogs. It’s expected that the loyal sidekick role would be played by a dog given its already achieved popularity, and maybe that’s just the problem.
When it comes to Disney movies, an animal is never just an animal. Every animated character in Disney’s animal kingdom is divided into one of two categories: The Good Guys and The Bad Guys.
Cute and harmless animals, from dogs and rabbits to mice and elephants, are almost always cast as the protagonists and affable sidekick. And when Disney has a protagonist, they must always balance it with an antagonist — these designated villains often take the form of sharks, snakes, crocodiles, predatory birds, and weasels.
The Walt Disney Animation Studios gained its popularity from creating adored characters like Dumbo, Bambi, and Lady and the Tramp. Disney’s target audience is children, and children are well known to use the information given to them to make assumptions about the world around them. Since much of cultural understanding is drawn from media, companies such as Disney play an influential role in how children (and adults) determine the value of ideas, objects, and animals.
“Humans tend to place more value on vertebrates that are cute & fluffy or large and interesting,” said Michael Donaldson, a research specialist and biology professor at Carleton University. “Creepy/crawly species tend to receive less attention and may even be considered “less important” even though they can have very important biological and ecological functions that support large charismatic species.”
If every single movie tells a child that all snakes are villainous and all rabbits are helpful friends, it would be likely that a child would deflect those personalities onto every snake and rabbit they saw.
This is exactly why in the weeks after the 2003 release of Finding Nemo, clownfishes became the leader of aquarium sales. Every little kid wanted a to own their own Nemo. However, people did not take into account that 90% of clown fish sold are taken from the wild. Because of this, many areas where clownfish lived experienced a local extinction and pushed an already threatened species to the brink.
Time and time again, Disney has proven that they have a complicated relationship with any animal that seems unhuggable. Disney’s latest film featuring the dog Dante will add onto to the already long list of protagonist dogs featured in Disney’s animated movies. In an analysis of 35 Disney movies, 37% of those movies featured dogs as their leading roles. Out of 37% of the dogs, all but two played the protagonists in the given film. In the same 35 Disney movies, 20% of those movies featured cats. Contrastingly, every cat besides one played an antagonist role, and that’s not even counting the characters in the big cat family.
Compiled data from 35 of Disney’s most popular animated movies featuring animals shows how certain species are only given villainous roles and are never depicted as heroes. Similarly, some animal species are always granted the role of the protagonist or lovable friend. Animals including crocodiles, sharks, vultures, and snakes did not play a single heroic role in the course of the 35 Disney movies analyzed. This differs from animals like bunnies, elephants, and deer, who always play a protagonist role.
Disney not only restricts these animal species to protagonist or antagonist roles, but they also change their animation styles depending on the species they are illustrating. For example, notice how all of the animals who consistently play antagonist roles are pictured with conniving smirks, a devious persona, and darker shades. This contrasts with the animals who consistently play protagonist roles who are all pictured with a welcoming, loving smile, and typically brighter colors.
“[People] remember movies most vividly when they do have predators as antagonists and more lovable animals as victims. Conventional roles stick with the viewer better,” said Henry Bernstein, an animator at Pixeldust Studios. “If you have predatory animal like a crocodile or a snake, it is much more believable that they are the villain because that is their role in real life.”
While we might want to give Disney the benefit of the doubt and suggest they don’t create and perpetuate negative stereotypes about certain animals purposely, make no mistake — this is done deliberately. An interesting case for this is Kaa in the movie The Jungle Book, a sneaky snake who has the power of hypnotizing his victims before devouring them alive. However, while he tried to prey on the child in the movie, the original book version describes Kaa as the child’s protector and helpful companion.
The idea of a friendly snake doesn’t fit into the cultural trope about slithery malevolent snakes, so it’s likely that Disney changed the nature of Kaa to fit the evil narrative snakes have been innately dealt.
“Presumed animal behaviors and attitudes have historically been mapped to animal species resulting in established stereotypes,” said Dawnja Burris, a media researcher and producer who focuses her research in animal representation in media. “Such stereotypes limit understanding of certain animals and relegate conception of these animals to small and contrived sets.”
With Disney and other mega media brands designating these species as the dangerous adversaries that prey on the cute protagonists, it comes as no surprise that people grow up irrationally afraid of these animals.
Let’s take sharks for example. Sharks can be seen as the main antagonists in nearly any Disney animation film that takes place underwater. From Bruce in Finding Nemo to Glut the Shark in the Little Mermaid, sharks are depicted as the sharp-toothed predators that commonly haunt the dreams of any beachgoer. Disney is guilty of making sharks look like they lurk in the shallow shores waiting to take a bite out of the first person they see.
However, statistically speaking, you have a 1 in 3,748,067 chance of dying in a shark attack, according to the International Shark Attack File of the University of Florida’s Museum of Natural History. According to an analysis of CDC data from LCB, only one person per year is killed by a shark in the United States. To put these numbers into perspective, an estimated of 120 people are killed annually by deer and 28 people are killed by dogs.
While shark attack fatalities remain low for humans, fatalities for sharks are egregiously high — an estimated amount of 100 million sharks are killed by humans every year. Despite this, sharks seem to receive limited conservation advocacy in comparison to other animals.
While it is well known that our beloved elephants are endangered, many people might not know that great white sharks are even more endangered. There is only an estimated amount of 3,500 of these big bad boy sharks left in the wild. Comparatively, there is an estimated amount of 450,000–700,000 African elephants and between 35,000–40,000 Asian elephants in the wild today.
“Charismatic megafauna tends to be what people care about, hence they get funding and attention. For example, it is no random occurrence that the Panda is the symbol of WWF,” said Sam Edwards, the director of animal conservation and care at Green Mountain College. “”Protect our elephants” is more likely to get support than protect our yellow jackets, jelly fish, sea urchins, etc.”
This is likely the reason why sharks continuously receive less conservation efforts and research programs in comparison to endangered mammals, such as elephants. The Association of Zoos and Aquariums is a non-profit organization dedicated to creating and tracking international programs for animal welfare, conservation efforts, and scientific education. Since 2010, they have consistently reported a rise in programs for African and Asian elephants. In comparison, programs for sharks are seeing a rise in recent years but still remain consistently low.
Attention given to animals within conservation and media are interlinked. Media companies, such as Disney, help inform our biases for or against certain animals. Consequently, these biases help us decide which animals to feature in ad campaigns and promote conservation for.
It is likely that you have seen WWF commercials about ending ivory trade with elephants and ASPCA commercials about saving puppies. And while these commercials are incredibly important, it is also important to note that you’ve probably never seen a commercial about stopping shark finning.
While animal symbolism and perceptions may vary between cultures, a string of some type of animal stereotype can be found as the common thread in nearly every culture. This isn’t to say that you should jump into a school of wild sharks or second guess your dog loving nature, but rather just reconsider which animals you classify as good and which animals you write off as bad. While some of these stereotypes may even be based in a grain in truth, it’s important to think about how media creates and reinforces assumptions of our furry, scaly, and feathered friends.
“Animal species that are not apex predators and therefore pose little to no threat to humans are the ones always chosen as featured protagonist characters,” said Dawnja Burris. “In the case of protection of wildlife and animals, the systematic lack of inclusion and recognition of the “uncharismatic” animal types accounts for the perpetuation of their exploitation.”


Introduction
General description of SFU project
SFUOT project aims to represent the knowledge graph of the Six Feet Under TV Series and to compose the character-oriented ontology. Moreover, it goals to achieve a web page that makes ontological knowledge accessible to ordinary users. In addition, determining the words frequently used in the series and aimed to make literary criticism on themes of permanence, negativity, and change. At last, it aims create sentiment analysis of meaningful quotes from the series
This project has been created by student of the Digital Humanities and Digital Knowledge program for the Knowledge Representation and Extraction course taught by Professor Aldo Gangemi at the University of Bologna.
SFUOT: Six Feet Under Ontology
Ontology is a defined model that organizes structured and unstructured information through entities, their properties, and the way they relate to one another. As we know, ontologies are machine readable. This means that search engines are able to understand the content. While creating SFUOT ontology, I aimed to make the cultural heritage I understood and acquired can be used and accessible to everyone.The project offers a wide variety of features for viewing, manipulating and creating ontologies in OWL for interconnected data.
SFOUT: Six Feet Under Ontology
I intended my ontology to provide new ways for users to find and discover new content. The ontology I created can strengthen the directional search or allow people to browse related content based on the people, places mentioned in the scenario.
Given that one of our main purposes consists of making the knowledge I gained accessible to everyone, I created that ontology with Protégé, that allowed to represent in a suitable way my ontology. I used Widoco, WebVOWL and RDF Grapher.
Sparql Query
SPARQL is the standard query language and protocol for Linked Open Data and RDF databases.
See Sparql Queries of SFULinguistic Analysis
The term linguistic analysis covers a lot of territory. We will use it in the narrow sense of a computer’s attempt to extract meaning from text.
Go Down to SeeSentiment Analysis
The project offers sentiment analysis with Natural Language Toolkit. NLTK is the basis for a lot of text analysis done in Python.
Linguistic Analysis
I extracted the most spoken words from 5 different episodes of the series by using Python's wordcount function by eliminating the stopwords.We can see that the most spoken words in the series are listed in the table below.
The table is known as a frequency distribution, and it tells us the frequency of vocabulary item in the text. (In general, it could count any kind of observable event.) It is a "distribution" because it tells us how the total number of word tokens in the text are distributed across the vocabulary items.
View of results in pie chart and table:
| Word | Frequency |
|---|---|
| god | 73 |
| time | 73 |
| life | 62 |
| love | 50 |
| father | 49 |
| home | 34 |
| Original sentence | Discourse analysis | Theme |
|---|---|---|
| "Everything ends. It isn't good, it isn't bad. It just is." | The situation is neither good nor bad, but there is no positive meaning. | Negative |
| "You can't take a picture of this, it's already gone" | Taking a photo won't make it last, it's a piece of her life that has come and gone. | Negative |
| “Well, we’re all wounded.  Things happen that leave a mark in space, in time. In us.” | What we go through throughout life is always with us. | Permanency |
| “How can you grow as an artist, if you don’t have the freedom to fail now and then?”. | Being independent in making mistakes enables the artist to improve herself. | Change |
Sentiment Analysis with Natural Language Toolkit
Before starting the Sentiment Analysis, I determined 3 themes. Permanency, change and negativity. I quoted sentences with these themes from the series Six Feet Under. Then I determined the negative, neutral, positive values of the sentence with NLTK. Natural Language Toolkit is the basis for a lot of text analysis done in Python. To determine sentiment, I used a tool called VADER.
| Sentences | Positive Sentiment | Neutral Sentiment | Negative Sentiment |
|---|---|---|---|
| "Everything ends. It isn't good, it isn't bad. It just is." | 20.0 % | 63.1 % | 16.9 % |
| "You can't take a picture of this, it's already gone" | 0.0 % | 100.0 % | 0.0 % |
| “Well, we’re all wounded.  Things happen that leave a mark in space, in time. In us.” | 6.2 % | 76.5 % | 17.4 % |
| “How can you grow as an artist, if you don’t have the freedom to fail now and then?”. |
17.7 % | 67.5 % | 14.8 % |
Ontology Visualization and Knowledge Graph
I started one of my main goal consists of making the knowledge I gained accessible to everyone, I used couple of tools that allowed me to represent in a suitable way my ontology.
Click here to view the SFUOT Ontology documentation published thanks to Widoco and WebVOWL.
--> Outcome of loading the Turtle code of the ontology.
--> RDF Graph of the ontology
--> XML code of SFUOT ontology
Author&Publisher
SFUOT project has been realized as final examination for the “Knowledge Representation and Extraction” course of Digital Humanities and Digital Knowledge Master Degree at the University of Bologna, under prof. Aldo Gangemi, for the a.y. 2019/2020.


I spent some time last night working on Kata 19 (these Katas are little programming exercises, a nice programming break from writing Useful Code). This was definitely the hardest one I've done so far -- you find paths between words, where words are connected if they only differ by one letter. For example: beast to least to leant to leans to loads to loons to loops.
The algorithm I used was pretty quick. Searches take at most 0.1sec, return the shortest path, and do not block on impossible paths. It does a breadth-first search, starting from both the first and terminal words (finding where they meet somewhere in the middle).
The problem was that it was really slow to start up. Reading my dictionary of 96 thousand words took about 53sec (and 166Mb of memory) on my Athlon 650MHz PC. Once it is loaded it is really fast. Perfect for a word-path-finding-server. But I don't think this justifies a persistent server.
Here is this original code. I then set upon optimizing the start time. Here's the things that worked well:
By using Psyco I can cut the 8sec (with all the little optimizations) down to 3.5sec, using psyco.full() It only brings the original down to 41sec (and increases memory to 180Mb), which is still pretty slow. Pysco plus turning GC off gives us 11sec, which is pretty good -- it does better when we tell Psyco psyco.bind(load_words) (i.e., tell Psyco to only try to optimize the one function: 11sec vs 15sec). In contast, psyco.bind doesn't even effect our optimized load_words, only psyco.full helps there.
I'm pretty happy with the finished program. For the most part all the important, time-critical parts are already in C -- they are dictionaries, sets, and lists. These data structures make algorithm implementation in Python really easy and scalable all at once. While you could write this in C for more performance, it would take a lot of work just to get something that worked, and a lot more work to match the speed of Python's built-in data structures. Maybe a language like OCaml or Haskell could match (or beat) Python's agility and performance. I'd be curious.
For more on Python optimization: loop optimization, another anecdote, and an anecdote using images. Some specific tips, and some general tips
Just a minor nit: sets aren't in C yet. They're a 100% Python library module. If there's enough interest (and I think there is) they'll become a builtin (see http://python.org/peps/pep-0218.html).# Johannes Gijsbers
I didn't bother optimising the initial dictionary loading: instead I built a precompiled dictionary for each word-length. As graphs of linked word-nodes, they're pretty small.
[epiphany:~/Code/kata19] cmiller% ./nodef.rb ruby gold
dictionary loaded in: 0.397383s
ruby => rubs => cubs => cues => cued => cued => coed => cold => gold
261 nodes touched in 0.020318s
Erk. Just noticed the bug in the output. :)
My coworker and I had a good time with this kata.
After finishing it I created a corollary. Find the longest word chain. For example, the longest word chain for all three letter words is [asp ask ark are abe aye rye rae ray say sky ski sri uri uzi]. That took 210 milliseconds to find.
I highly recommend trying the corollary.
My longest time are for the 8 letter words. The chain is 30 words long and it takes 991 milliseconds to find.


I went through the
World Value Survey
(WVS) documentation in order to find interesting questions where the answers
had evolved over time. I saved the snapshots of my findings to create a data record
of eight variables. See choosen variables in slides below.
Slide left / right to showcase different data variables
What To Ask The Data
Studying the values of individual countries I wondered if there's
any correlation between different questions. Especially I wanted to
investigate a preconception of mine, if one beleives religion is of
great importance, does this lessen the feeling of freedom in life?
An other interesting questions would be if importance of work has a negative
or a positive correlation with importance of leisure time, working more
would likely increase how much one values time off, or is it the other way around?
Trying to bring in time as a variable, it would be really neat to see if
the feeling of happiness is increasing or decreasing in the world
(fingers crossed!).
Short version
Analytic trail 1
High importance of religion in a country may, or may not,
indicate less feeling of freedom.
Please be patient when changing Wave, the loading might take a while...
Wave:
Select a column, then a country on the map to display it's it's results in WVS questions
Current country
World average
1995 - 1998

1999 - 2004

2005 - 2009

2010 - 2014

What Did We Find?
Is the a correlation between religion and freedom?
As we look at the radar charts at top to the right representing Algeria,
Lybia and Yemen we can tell that though all are clearly above average when
it comes to importance of religion all are also around avera when it comes
to feeling of freedom. Furthermore if we look at contries with religion
clearly below average on religion (Sweden, China and Germany) all of these
are also around average when it comes to feeling of freedom. Conclusion,
there are no obvious correlation on religion and freedom from this data.
Are we getting happier?
Representing the numerical data (percent of people feeling happy or
very happy with their life) with a shade of blue in the map at a glance
it's very easy to tell that the overall feeling of happiness have increased
in the world when moving the slider from the earliest wave to the most
recently and comparing these views above.
Learnings
During the making of this page and the visualizations I've learned a lot more
about D3JS and javascript in general as this course is my first encounter
with js. I also relised the challanges that occur when trying to visualize
many different variables at once and learned a few tricks like radar charts
when it comes to categorical data (as siggested in the latest reading) and
how making use of placement makes much sense when working with something as
familiar as countries. I still got a lot to learn :)


Pitfall Creation Dashboard
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GO Pack GO!
I love the Green Bay Packers! They are going all the way this year baby and you know it! I have been a die hard packers fan since birth and will always will be a cheese head.
Some Facts
The Green bay packers have been world champions 13 times. Which is the most champoinships in the NFL. They won in 1929, 1930, 1931, 1936, 1939, 1944, 1961, 1962, 1965, 1966, 1967, 1996, and 2010. In those championships the packers won the first three Super Bowls and the super bowl trophy ended up being called after the packers head coach - Vince Lombardi.
Key Players
Aaron Rodgers: Quarter Back - #12
Clay Matthews: Linebacker - #52
Jordy Nelson: Wide Reciever - #87
Eddie Lacy: Running Back - #27
Randall Cobb: Wide Reciever - #18


2011
December, 2011
The Immortal Life of Henrietta Lacks
Rebecca Skloot
October, 2011
The Happiness Project: Or, Why I Spent a Year Trying to Sing in the Morning, Clean My Closets, Fight Right, Read Aristotle, and Generally Have More Fun
Gretchen Rubin
August, 2011
Freedom
Jonathan Franzen
May, 2011
The Kitchen House: A Novel
Kathleen Grissom
March, 2011
The Kitchen House: A Novel
Kathleen Grissom


Appropriate selection of a control system for a complex industrial process is very difficult. The main part of control is often retained by men and, then, the computer function is limited to adequate determination and provision of comprehensive information concerning the plant operation status in a readable form to enable making optimal decision by a dispatcher. This kind of computer system has been applied to the open pit in Bełchatów Poland. It is one of the largest brown coal mines all over the world, with coal output of 38500000 Mg and overlay output of 125 Mm3 per annum. Coal is conveyed to a 4320MW power plant. The exploitation process employs the following machines:
Each machine has, among others, a measurement device providing an instantaneous output value and a current machine state (work/standstill) signal. For excavators there are available signals indicative of coal or overlay digging and for loader-dumpers - signals of conveying direction. Directly accessible signals have been insufficient for efficient manual control. Available information should take the following form, for convenience of the dispatcher:
The part of this information is important as it is used in economic accounts. Current information has to be provided continuously using a radio link. A dedicated real time computer system has been designed for this critical task. It measures signals and processes them to display required information in a readable form on a CRT display and it prints out reports. A report is printed out at request and automatically after the end of each shift. Considering the place where the computer system takes over the control hierarchy, its reliability is of decisive importance. Therefore, there were designed two identical computers working simultaneously but independently of each other. This ensures an increased hardware reliability. The next step towards the reliability improvement is a special algorithm construction. The computer system is designed to acquire and process data, and finally to display and print appropriate information describing the process state independently of the technologic and energy consumption points of view. Output data enable the dispatcher to control the work of all mining devices and guarantee:
The computer system consists of the following (fig):
The mentioned computers exchange data using the local network. The data acquisition and processing computer (APD) reads data from sensors at discrete intervals, processes them and saves the description of the mining process current state results. A system printer can be connected optionally to APD or MS. The result data from APD are provided to both computers by the local network. The monitoring station (MS) is responsible for displaying vital information about the current mining state on the 6 following CRT's designed for:
To increase reliability, monitoring stations equipped with additional CRT's can work as dispatcher workstations. In that case the possibility of standstill description in not available. The dispatcher workstation makes system configuration possible and enables the input of process parameters and data not available from sensors, e.g. substitution values for selected signals, standstill reasons, mining device names, power limits, current time and date, etc. Monitoring of the power supply system is divided into:
If ordered power is exceeded the system warns and aids reduction of current power.
10.1016/0141-9331(90)90012-K
.A DOI is a unique and permanent number used to identify digital content. DOIs provide a reliable link to your work online, making it easy for others to cite you. Please make a note of your DOIs for future reference.
To learn more about DOI visit the DOI® Handbook


Hey, another part - possibly fewer lines than last time!
I think that I got:
We've but one word, my Lord, and that is'Rapture'
but at least I had a role!
Sad to say, when I was taking photos of HMS Pinafore, I managed to have my camera on the wrong flash synchronisation. That meant that the photo was half illuminated, half in darkness. So the production photographs from HMS Pinafore are rather ropey, to say the least, but it's nice to have a few as an archive, so I have left them here.


THE
MUSEUM
OF
FLIGHT
Sketchfab API - Stranger than Fiction: Body in Flight
3D Model Annotation
Read Aloud
Skeleton2
Skeleton3


merz
Businessmodel of Merz
Customer Segments
Merz produces products that are meant for the general consumer. However, these products are not always sold to the retail consumer – some of them require experts, often physicians, to apply them. One example is the Botox injection product for skin wrinkles – these have to be applied by a qualified physician as they can be highly dangerous if injected into the wrong area or into the bloodstream.
- Aesthetics – Merz has five major aesthetics brands – Merz Aesthetics (various products), Belotero (dermal fillers made of hyaluronic acid), NEOCUTIS (topical cosmetics), Radiesse (dermal fillers), and Ultherapy (ultrasound skin therapy). Of the five, none are sold over the counter – even NEOCUTIS, which manufactures topical cosmetics, requires dispensation from physicians.
- Dermatology – Merz has three major dermatological brands – Contractubex (scar treatment), Mederma (scar treatment), and Pantogar (hair loss). All three are available for sale to the general public, with or without a prescription.
- Consumer Care – Merz has two major consumer care brands – Merz Spezial (oral and topical skin and hair products) and tetesept (general pharmaceutical products – certain European countries only). Both sell products to the general public.
- Others – Aside from the above mentioned products, Merz also has products and research targeted at liver disease (Hepa-Merz) and Alzheimer’s (no brand). Neither sells products to the general public. ### Value Proposition
Merz is a well-known and old company with a history of making effective products. This adds to its attractiveness to consumers. Further, it produces certain treatments that are unique to it.
For example, it is one of the world’s leading producers of botulinum toxin-based products, including Botox injections.
Channels
As the bulk of its products are available only through physicians and medical institutions, Merz sells directly to these. It also sells to distributors, who in turn sell to pharmacies, or to major pharmacy brands.
Customer Relationships
Merz creates customer relationships through the use of marketing, either directly (through campaigns and personal professional representatives) or through partnerships, either internal (i.e. intra-group partnerships/agreements) or external.
An example of an intra-group partnership is Merz Pharma Canada’s exclusive distribution agreement with Ulthera, a subsidiary of Merz Group, to distribute Ulthera’s products throughout Canada. An example of an external partnership is Merz North America’s exclusive distribution agreement with Tanner Pharma Group granting Tanner the exclusive right to distribute Cuvposa, a Merz product, in Latin America.
Key Activities
Merz is involved in the research, development, production, distribution, and sale of medical products, primarily cosmetic products and treatment options, to licensed physicians.
Key Partners
Aside from research and production partners, Merz also distributes its products through partners. Examples are covered in the “Customer Relationships” section above.
Merz also puts in venture capital into companies and/or other investments that it finds that will provide research, production, distribution or other forms of benefits – these venture strategies can take the form of joint ventures formed with some of Merz’s partners.
Key Resources
While hard data is unavailable, it is likely that Merz’s key resources are similar to other global pharmaceutical companies - key resources are its Property, Plant and Equipment, its Goodwill, and its intellectual properties (i.e. patents for drugs and other pharmaceuticals) and other intangible goods.
Cost Structure
While hard data is unavailable, it is likely that Merz’s key resources are similar to other global pharmaceutical companies - key costs are in: Materials and production, marketing and administration, and research and development.
Revenue Streams
Merz splits its revenue streams by region and not by business segment. The highest performing region by sales is North America, followed by Europe. The fastest growing region is the Asia-Pacific region, where Merz is only just expanding.
Source of Revenue Revenue (FY 2015, million EUR) % of Total Revenue Revenues 1,157.0 100% EMEA 422.6 37% North America 588.4 51% Latin America 48.4 4% APAC 97.6 8%


{{template "wizhead.html" .}}
This is a virtual rally so you need to specify these variables to be applied to all entrants.
This wizard is now complete and the installation is ready for use.


Changelog
36.0
35.0
- Add genstat, gentoo, gimp, gitcommit, gitmerge, glade, glide, gltf, gnome, golo, gauss, grammatical framework, glyphs, gn, gnuplot, gosu, gravit, greenkeeper, pointwise, snowpack
- Fix bundle size
- Fix bad associations
34.0
- add mapbox, markdownlint, materialize, mathjax, max, mdx, mediawiki, mercury, nano, nanoc
- add MS infopath, lync, visio, publisher, outlook, project, meson, metal, minecraft, minizinc, mirah, mirc, mkdocs, modelica, modernizr, modo, moho, modula2, modula3, moleculer, moment, monkey
- add reasonstudios, rebol, red2, redhat, reek, rneovate, requirejs, rexx, rhino3d, riemann, ring, riot2, robot2, rss, rstudio
33.0
- fix init.py, add eclipselang, eagle, easybuild, ec, ecere, eleectron, email, emberscript, eq, esdoc, extjs
32.0
- Add ios, iosApp, androidApp, backend, desktop, buildSrc, repository, exception, usecase
- Add django associations and eslintignore
- Add the ability to disable associations
- Fix the bug with Edit/Clone associations
31.0
- Remove dependency to the Material Theme and add Javassist to fix the IconLoader issue.
- Fix possible NPE
- New file icons: UIKit, Unibeautify, Uno, Urweb, Paket, Pan, Papyrus, Parrot, Pascal, Patreon, Pawn, PCD, Pegjs, Phoenix, Oracle, Phrase, Pickle, Pico8, Picolisp, Pike, Pinescript, Platform.IO, PM2, Pod, PgSQL, PogoScript, Pony, Povray, Powwerbuilder, Precommit, Propellet, PROS, Proselint, Pullapprove, Pure, PHP2, LabView, Lasso, Leaflet, Lean, Lefthook, Leiningen, Lekto, Lex, LFE, Lightwave, Lilypond, Link, Lime, Lisp, LLVM, LogTalk, Lolcode, LSL, Lua, Livescript, alexignore, boringignore, D3, darcsignore, darcs, deps, dockerignore, fossaignore, gitignore, helmignore, herokuignore, dashboard, dataweave, dbase, debian, devcontainer, devicetree, dhall, Dia, Digdag, DNS, Docbook, Doclets, Docpad, Docz, Dogescript, Dojo, Dosbox, Doxygen, Dragula, Drone, Dyalog
- Add
index.scss
, index.css
and index.html
to the index family
- Add more associations to markdown, manpage, manifest, maya, mercurial, mjml, mustache
- Recolored some icons
30.0
- New icons and folder associations: public_html, redis db
- New UI Icons: Checkboxes, Inlay icons, CodeWithMe, Emoji Picker, Tool Window Analyze...
- Pseudo-fix: Add leading slash relatively to new EAP refactor
29.0
- Add new icon sets: Spring, Kubernetes, Slim, Swagger, Sass, Swift, Rider, PostCSS, XSLT
- New icons: ngrx, RxJs, Protobuf, R, Swagger, Tapestry
- Add more UI Icons
- Fix: regression issue with UI icons not disabling
- Fix: popup menus: restore active indicator
- Feature: Hide Folders
- Feature: Show Custom and Default file icons in the Commit Window and Panel
- New associations: command, console folders, public_html, entities, effects, stylelintrc
28.0
- Support for 2020.3
- Support for more UI icons
27.0
26.0
- New Option: "**Folder Color**" to customize Folder Colors from the current theme.
- Better detection of the current theme's accent color
- Add Checkboxes to Accent Color and Folder Color to allow customizing such colors instead of picking them from the theme
- Improve Hollow Folders opened files detection
- Put "Custom file associations" under the "Atom File Icon Settings"
- New Icons: brew, harbour, holyc, hjson, hoplon, houndci, hp, hy, hyper, question
25.3
- Fixes many issues with custom associations
25.2
25.1
- Fix Psi Icons for PHP files
25.0
- The finally awaited Custom Icon Associations is here! This is an alpha version so it can contain bugs :)
- Assign custom file associations and folder associations from the Settings
- Preview Default File and Folder Associations from the Settings
- Assign icons from your file system
- Important note: most of the settings won't be applied to custom icons, so use them sparingly!
- The project has been revamped to Kotlin! This is a huge step so please report any issues you can find :)
- Fix issue with monospace colors not being persisted
- Changed color scheme of Kotlin PSI Icons, to differentiate with Java PSI Icons
- Now the PSI Icons setting is dependent on the UI Icons setting, as this wouldn't work without it.
- And the Hollow Folders Setting is dependent on the Folder Decorations Setting as well.
- New folder associations: widgets, elements, users, members, partners, friends, projects, ui, dev, staging, qa, prod, serializers, types, io, stdlib, deps
- New file associations:
*_test.go
, *_spec.go
, Chart.yaml
, values.yaml
, helmfile.yaml
, scala test files
- Added
jsconfig
and tsconfig
24.0
- Added accent color selection in the settings
- new UI/PSI icons: Scala, Ruby, Typescript
- new redux icons: redux saga and redux epics, tweaked other colors too
- new test icons: test dart, test go, test haskell, test perl, test rust
- switched typescript and tslint icons
- new icons: icomoon, idl, igor, imba, index, inform, ink, inkscape, inno, ioke, isabelle, jake, jasmine, jison, jolie, json5, jsonld, jsonnet, junos
- new/updated folders: acre, agda, alacritty, app, appstore, arttext, atom, aurelia, bazaar, cabal, chef, client, cluster, container, content, controllers, coverage, cvs, messages
- new folder icons: viewmodel, deno, dependabot, devcontainer, dropbox, gitlab, istanbul, yarn, ruby, mercurial, meteor, svn, textmate, vagrant, vim, svg, firebase, xcassets, glyph
- Try to fix the weird border at start
- Fix wrong associations
More info about associations here and here
23.0
- More icons: walt, watchman, wdl, webgl, owl, webvtt, wenyan, wget, wix, wordpress, workbox, wurst, x10, x11, xmos, xojo, xpages, xproc, xtend, yara, yorick, yui, yasm, zbrush, zeit, zenscript, zig, zilog, zimpl, zork, awk, bazaar, brewfile, hitachi, intel, vax, kerboscript, keybase, keynote, kicad, kitchenci, kml, knime, kotlin, knockout, krl, kubernetes, q, qasm, qlikview, qt, quasar
- New angular icon: interceptor
- New redux icons: saga and selector
- New pattern: main.js is now associated with nodejs
- Add cron/scheduler folder icons
22.0
- You can now preview icons at https://github.com/mallowigi/a-file-icon-idea !
- You can now get the list of available associations at http://www.material-theme.com/docs/reference/associations/ and http://www.material-theme.com/docs/reference/folder_associations/ !
- Extracted icons to its own repository so it can be used with multiple projects
- Optimized icons (reduce icons size, set colors in paths, etc)
- Also the icons look much more like the Atom original plugin ones
- Added fileNames in associations, to be used with the examples generator
- Added colors in associations, for use with the font generator
- Update UI Icons with latest icons
- New/Updated UI Icons: Ant, Haml, Handlebars, DataGrip, JavaScript, Kotlin, DevKit, Dart, Docker
- New icons: 4d, agda, alpine linux, analytica, adobe animate, ansible, antwar, aplus, buck, build boot, caddy, caffe, caffe2, cakefile, carthage, chai, chapel, chartjs, cheetah, chocolatey, cpp, csharp, cdf, chrome, chuck, circuit, cirru, clarion, clean, click, clips, closuretpl, cloudfoundry, cocoapods, codacy, codeclimate, cokekit, codeship, conan, conda, conll, coq, corel, coveralls, cp, cpan, credits, creole, crowdin, csound, cuneiform, curl, curry, cwl, collada, nvidia, fabric, factor, falcon, fancy, fantom, fexl, fbx, faust, fasta, finaldraft, firebase bolt, firefox, flask, flutter, flux, font bitmap, fontforge, fossa, fountain, fanca, frege, fuel ux, fusebox, futhark, Jetbrains Theme Files
- Update icon associations: actionscript, ansible, antlr, applescript, asciidoc, asm, atom, atoum, babel, backbone, behat, bison, bootstrap, bower, cabal, c, composer.lock, chef, credits, csharp, cypress, todo, finder, firebase, flash, fortran, gem, archives, audio, video
21.0
- Fix issue with Arrow Colors being black in Darcula
- Fix issue with Plugins labels being black in Darcula
- Add new 2020.1 UI Icons
- Add folder associations: bin and units
20.0
- Restore the "Accent Color" function to colorize icons with the Accent color (defined from Material Theme, or from the current active tab indicator color)
- Fix issue where arrows style were not persisted
- Add sql/mysql/pgsql folder
- Fix Kotlin icons being unaffected by PSI File Icons setting
- Add bz2, xar, egg and sit to "Archive" file association
- Make Icon Settings "dumb aware" (not affected by the indexing process)
19.0
- New feature: Arrows Style
- Fix issue with icons not being applied on start
- Add missing icons since Nov 2019
- New pattern: angular controller
18.0
17.0
- New Icons:
- 1c, 3dmodel, 3dsmax, abap, abif, acre, advpl, affectscript, affinity, alacritty, alex, alloy, ampl, amusewiki, angelscript, animestudio, ant
- apache, apl, appcelerator, arc, archlinux, asymptote, atoum, ats, audacity, augeas, avro, backbone, bnf
- bem, bibtext, biml, bintray, blender, bluespec, boo, bootstrap, brakeman, broccoli, brotli, browsersync, brunch, byond, gnu
- New Feature: Hide File Icons
- New Feature: Hollow Directories
16.0
- New icons: Cargo, Codecov, codeowners, cypress, cython, gridsome, netlify, pnpm, posthtml, sapper, svelte-config, uml, v, vala
- New folders: events, gulp, json, netlify, relay
- Sync with new UI Icons
15.0
14.0
- New File Icons:
- edge, autoit, azure, bithound, blink, bucklescript, buildkite, certificate, commitlint, credits, history
- graphcool, helm, istanbul, key, kivy, lib, livescript, markojs, mdx, merlin, mint, moonscript, mxml, nest
- houdini, now, nunjucks, prisma, processing, restql, san, sequelize, swc, unity, velocity, vm, webassembly, webhint, wepy, yang
- New Folder Icons:
- ci, class, container, content, css, delta, dump, error, examples, flow, helper, modals, maps
- pipe, prisma, private, stack, utils, vm
- Sync with Material Icons
13.0
- New Icons and associations
- Sync with Material Icons
12.0
- Support for 2019.2
- Sync with Material Icons
11.0
- Add light equivalents of icons
- Update new icons: Resharper (Rider)
- Sync with Material Icons
- Fix errors
10.0
- New setting: PSI Icons. Replaces icons about program structure: classes, interfaces, methods, enums etc.
- Import last set of UI Icons from the Material Theme
- Update for 2019.1
9.0
- Add Monochrome Icons' tint color selection
- Fix UI Icons setting needing the IDE to be restarted
- Fix settings not being persisted
- Add more contrast to monochrome icons
- Fix some directories icons' contrast between the directory and the icon
- Add more directories: guard, providers, animations, grunt, icons, e2e, custom, rules, screens, storybook, stylus, syntax, security, meta-inf, fixtures, channels, concerns, support, features, fabricators, nyc, reviews
- Add more files: ANTLR, brainfuck, cobol, delphi, eiffel, fortran, idris, io, j, lerna, postscript, prolog, racket, red, supercollider, scheme, terraform, test-react, turing, toml
8.0
- Atom File Icons has now the complete UI Icons feature, allowing you to replace IntelliJ icons with Material Icons
- New Option: Monochrome Icons
7.0
6.0
- Added new file icons: Jenkins, Rspec, Rubocop
- Added new folder icons: android, deploy, api, archives, config, constants, core, download, env, exclude, functions, generated, hooks, ios, include, jinja, job, keys, layouts, mailers, meta, middleware, notification, other, packages, posts, react, resourceIOS, routes, scripts, server, serverless, shared, sublime, tasks, themes, utils, upload, vendors, views, vue
5.0
- Added new file icons: Arduino, Assembly, Authors, Ballerina, Crystal, CSSMap, Dotjs, DTS, Favicon, Firebase, Flash, Gatsby, Gemfile, Po, JSMap, MJML, Nimble, Raml, Razor, Redux Actions/Stores/Reducers, Smarty, Solidity, Sonar, Stencil, Storybook, Wallaby
- Added new folder icons: benchmarks, coverage, controllers, debug, excluded, expo, jinja, less, maven, messages, models, plugin, python, react, redux, routes, scripts, sublime, sync, tasks
4.0
- Convert icons to SVG
- Add more system UI icons
3.0
- Add settings page to control which components to enable or disable.
- Components: File Icons, Directory Icons and UI Icons (experimental)
2.0
- Add folder icons feature
- Add more icons
1.2
- feat(project): add PHPStorm and Pycharm files and plugin support
- fix(project): rename "files" to "files" to that it replaces all icons
- feat(project): Add "nodes" icons for various file trees
- fix(FileIconProvider): make it DumbAware
- chore(project): Add markdown to html for changelog
- chore(project): add gradle.properties for easy installing
- feat(icons): add new icons
- Github Code of conduct, Github Contributing, Commit message convention, Github Template
- README
- Prefs
- Atom files
- Angular component, service, directive, guard, pipe, routing, resolver
- Autohotkey
- API Blueprint
- Appveyor
- Java Beans
- Browserslist
- Cabal
- CNAME
- Compass files
- C++
- Dockerignore
- Doxygen
- Dylib
- Eslintignore
- MAC OSX files
- Flow Config
- Ghostscript
- Godot
- Gradlew
- H files
- Adobe Indesign
- Jekyll config.yml
- jQuery
- Makefile
- Markdown
- Manpage
- Mathematica
- Maven pom.xml
- Maya
- Mocha
- Nib
- NPM package.lock
- NVM
- OpenOffice
- Objective C
- Patch files
- Phalcon
- PostCSS Config
- Prettier
- Powershell
- ReasonML
- Restructured
- Robot
- RVM
- Spring
- Tern
- Tomcat
- Travis
- VHDL
- Webpack
- XCode
- Yarn files
- Minified javascripts


Shortcut QML Type
Provides keyboard shortcuts More...
| Import Statement: | import QtQuick 2.7 |
| Since: | Qt 5.5 |
Properties
- autoRepeat : bool
- context : enumeration
- enabled : bool
- nativeText : string
- portableText : string
- sequence : keysequence
- sequences : list<keysequence>
Signals
Detailed Description
The Shortcut type provides a way of handling keyboard shortcuts. The shortcut can be set to one of the standard keyboard shortcuts, or it can be described with a string containing a sequence of up to four key presses that are needed to activate the shortcut.
Item { id: view property int currentIndex Shortcut { sequence: StandardKey.NextChild onActivated: view.currentIndex++ } }
It is also possible to set multiple shortcut sequences, so that the shortcut can be activated via several different sequences of key presses.
See also Keys and shortcutOverride().
Property Documentation
This property holds whether the shortcut can auto repeat.
The default value is true
.
This property holds the shortcut context.
Supported values are:
Qt.WindowShortcut
(default) - The shortcut is active when its parent item is in an active top-level window.Qt.ApplicationShortcut
- The shortcut is active when one of the application's windows are active.
Shortcut { sequence: StandardKey.Quit context: Qt.ApplicationShortcut onActivated: Qt.quit() }
This property provides the shortcut's key sequence as a platform specific string. This means that it will be shown translated, and on macOS it will resemble a key sequence from the menu bar. It is best to display this text to the user (for example, on a tooltip).
This QML property was introduced in Qt 5.6.
See also sequence and portableText.
This property provides the shortcut's key sequence as a string in a "portable" format, suitable for reading and writing to a file. In many cases, it will look similar to the native text on Windows and X11.
This QML property was introduced in Qt 5.6.
See also sequence and nativeText.
This property holds the shortcut's key sequence. The key sequence can be set to one of the standard keyboard shortcuts, or it can be described with a string containing a sequence of up to four key presses that are needed to activate the shortcut.
The default value is an empty key sequence.
Shortcut { sequence: "Ctrl+E,Ctrl+W" onActivated: edit.wrapMode = TextEdit.Wrap }
See also sequences.
This property holds multiple key sequences for the shortcut. The key sequences can be set to one of the standard keyboard shortcuts, or they can be described with strings containing sequences of up to four key presses that are needed to activate the shortcut.
Shortcut { sequences: [StandardKey.Cut, "Ctrl+X", "Shift+Del"] onActivated: edit.cut() }
This QML property was introduced in Qt 5.9.
Signal Documentation
This signal is emitted when the shortcut is activated.
The corresponding handler is onActivated
.
This signal is emitted when the shortcut is activated ambigously, meaning that it matches the start of more than one shortcut.
The corresponding handler is onActivatedAmbiguously
.


| Shard | 迁移检测 | 原主机房预迁移 | 目标主机房迁移 | 其他机房迁移 | 结果 |
|---|---|---|---|---|---|
| {{migrationShard.migrationShard.shard.shardName}} |
Success
Failed
Waiting
|
Success
Failed
Waiting
|
Success
Failed
Waiting
|
Success
Failed
Waiting
|
Success
Failed
Waiting
|


|
|
Even though computers can perform literally millions of mathematical computations per second, when a problem gets large and complicated, performance can nonetheless be an important consideration. One of the most crucial aspects to how quickly a problem can be solved is how the data is stored in memory.
class ListNode { String data; ListNode nextNode; } ListNode firstNode;You could then write a method to add new nodes by inserting them at the beginning of the list: ListNode newNode = new ListNode(); NewNode.nextNode = firstNode; firstNode = newNode; Iterating through all of the items in the list is a simple task: ListNode curNode = firstNode; while (curNode != null) { ProcessData(curNode); curNode = curNode.nextNode; }A related data structure, the doubly linked list, helps this problem somewhat. The difference from a typical linked list is that the root data structure stores a pointer to both the first and last nodes. Each individual node then has a link to both the previous and next node in the list. This creates a more flexible structure that allows travel in both directions. Even still, however, this is rather limited. Queues A queue is a data structure that is best described as "first in, first out". A real world example of a queue is people waiting in line at the bank. As each person enters the bank, he or she is "enqueued" at the back of the line. When a teller becomes available, they are "dequeued" at the front of the line. Perhaps the most common use of a queue within a TopCoder problem is to implement a Breadth First Search (BFS). BFS means to first explore all states that can be reached in one step, then all states that can be reached in two steps, etc. A queue assists in implementing this solution because it stores a list of all state spaces that have been visited. A common type of problem might be the shortest path through a maze. Starting with the point of origin, determine all possible locations that can be reached in a single step, and add them to the queue. Then, dequeue a position, and find all locations that can be reached in one more step, and enqueue those new positions. Continue this process until either a path is found, or the queue is empty (in which case there is no path). Whenever a "shortest path" or "least number of moves" is requested, there is a good chance that a BFS, using a queue, will lead to a successful solution. Most standard libraries, such the Java API, and the .NET framework, provide a Queue class that provides these two basic interfaces for adding and removing items from a queue. BFS type problems appear frequently on contests; on some problems, successful identification of BFS is simple and immediately, other times it is not so obvious. A queue implementation may be as simple as an array, and a pointer to the current position within the array. For instance, if you know that you are trying to get from point A to point B on a 50x50 grid, and have determined that the direction you are facing (or any other details) are not relevant, then you know that there are no more than 2,500 "states" to visit. Thus, your queue is programmed like so: class StateNode { int xPos; int yPos; int moveCount; } class MyQueue { StateNode[] queueData = new StateNode[2500]; int queueFront = 0; int queueBack = 0; void Enqueue(StateNode node) { queueData[queueBack] = node; queueBack++; } StateNode Dequeue() { StateNode returnValue = null; if (queueBack > queueFront) { returnValue = queueData[queueFront]; QueueFront++; } return returnValue; } boolean isNotEmpty() { return (queueBack > queueFront); } }Then, the main code of your solution looks something like this. (Note that if our queue runs out of possible states, and we still haven't reached our destination, then it must be impossible to get there, hence we return the typical "-1" value.) MyQueue queue = new MyQueue(); queue.Enqueue(initialState); while (queue.isNotEmpty()) { StateNode curState = queue.Dequeue(); if (curState == destState) return curState.moveCount; for (int dir = 0; dir < 3; dir++) { if (CanMove(curState, dir)) queue.Enqueue(MoveState(curState, dir)); } }Stacks Stacks are, in a sense, the opposite of queues, in that they are described as "last in, first out". The classic example is the pile of plates at the local buffet. The workers can continue to add clean plates to the stack indefinitely, but every time, a visitor will remove from the stack the top plate, which is the last one that was added. While it may seem that stacks are rarely implemented explicitly, a solid understanding of how they work, and how they are used implicitly, is worthwhile education. Those who have been programming for a while are intimately familiar with the way the stack is used every time a subroutine is called from within a program. Any parameters, and usually any local variables, are allocated out of space on the stack. Then, after the subroutine has finished, the local variables are removed, and the return address is "popped" from the stack, so that program execution can continue where it left off before calling the subroutine. An understanding of what this implies becomes more important as functions call other functions, which in turn call other functions. Each function call increases the "nesting level" (the depth of function calls, if you will) of the execution, and uses increasingly more space on the stack. Of paramount importance is the case of a recursive function. When a recursive function continually calls itself, stack space is quickly used as the depth of recursion increases. Nearly every seasoned programmer has made the mistake of writing a recursive function that never properly returns, and calls itself until the system throws up an "out of stack space" type of error. Nevertheless, all of this talk about the depth of recursion is important, because stacks, even when not used explicitly, are at the heart of a depth first search. A depth first search is typical when traversing through a tree, for instance looking for a particular node in an XML document. The stack is responsible for maintaining, in a sense, a trail of what path was taken to get to the current node, so that the program can "backtrack" (e.g. return from a recursive function call without having found the desired node) and proceed to the next adjacent node. Soma (SRM 198) is an excellent example of a problem solved with this type of approach. Trees Trees are a data structure consisting of one or more data nodes. The first node is called the "root", and each node has zero or more "child nodes". The maximum number of children of a single node, and the maximum depth of children are limited in some cases by the exact type of data represented by the tree. One of the most common examples of a tree is an XML document. The top-level document element is the root node, and each tag found within that is a child. Each of those tags may have children, and so on. At each node, the type of tag, and any attributes, constitutes the data for that node. In such a tree, the hierarchy and order of the nodes is well defined, and an important part of the data itself. Another good example of a tree is a written outline. The entire outline itself is a root node containing each of the top-level bullet points, each of which may contain one or more sub-bullets, and so on. The file storage system on most disks is also a tree structure. Corporate structures also lend themselves well to trees. In a classical management hierarchy, a President may have one or more vice presidents, each of whom is in charge of several managers, each of whom presides over several employees. PermissionTree (SRM 218) provides an unusual problem on a common file system. bloggoDocStructure (SRM 214) is another good example of a problem using trees. Binary Trees A special type of tree is a binary tree. A binary tree also happens to be one of the most efficient ways to store and read a set of records that can be indexed by a key value in some way. The idea behind a binary tree is that each node has, at most, two children. In the most typical implementations, the key value of the left node is less than that of its parent, and the key value of the right node is greater than that of its parent. Thus, the data stored in a binary tree is always indexed by a key value. When traversing a binary tree, it is simple to determine which child node to traverse when looking for a given key value. One might ask why a binary tree is preferable to an array of values that has been sorted. In either case, finding a given key value (by traversing a binary tree, or by performing a binary search on a sorted array) carries a time complexity of O(log n). However, adding a new item to a binary tree is an equally simple operation. In contrast, adding an arbitrary item to a sorted array requires some time-consuming reorganization of the existing data in order to maintain the desired ordering. If you have ever used a field guide to attempt to identify a leaf that you find in the wild, then this is a good way to understand how data is found in a binary tree. To use a field guide, you start at the beginning, and answer a series of questions like "is the leaf jagged, or smooth?" that have only two possible answers. Based upon your answer, you are directed to another page, which asks another question, and so on. After several questions have sufficiently narrowed down the details, you are presented with the name, and perhaps some further information about your leaf. If one were the editor of such a field guide, newly cataloged species could be added to field guide in much the same manner, by traversing through the questions, and finally at the end, inserting a new question that differentiates the new leaf from any other similar leaves. In the case of a computer, the question asked at each node is simply "are you less than or greater than X?" Priority Queues In a typical breadth first search (BFS) algorithm, a simple queue works great for keeping track of what states have been visited. Since each new state is one more operational step than the current state, adding new locations to the end of the queue is sufficient to insure that the quickest path is found first. However, the assumption here is that each operation from one state to the next is a single step. Let us consider another example where you are driving a car, and wish to get to your destination as quickly as possible. A typical problem statement might say that you can move one block up/down/left/right in one minute. In such a case, a simple queue-based BFS works perfectly, and is guaranteed to provide a correct result. But what happens if we say that the car can move forward one block in two minute, but requires three minutes to make a turn and then move one block (in a direction different from how the car was originally facing)? Depending on what type of move operation we attempt, a new state is not simply one "step" from the current state, and the "in order" nature of a simple queue is lost. This is where priority queues come in. Simply put, a priority queue accepts states, and internally stores them in a method such that it can quickly pull out the state that has the least cost. (Since, by the nature of a "shortest time/path" type of problem, we always want to explore the states of least cost first.) A real world example of a priority queue might be waiting to board an airplane. Individuals arriving at their gate earlier will tend to sit closest to the door, so that they can get in line as soon as they are called. However, those individuals with a "gold card", or who travel first class, will always be called first, regardless of when they actually arrived. One very simple implementation of a priority queue is just an array that searches (one by one) for the lowest cost state contained within, and appends new elements to the end. Such an implementation has a trivial time-complexity for insertions, but is painfully slow to pull objects out again. A special type of binary tree called a heap is typically used for priority queues. In a heap, the root node is always less than (or greater than, depending on how your value of "priority" is implemented) either of its children. Furthermore, this tree is a "complete tree" from the left. A very simple definition of a complete tree is one where no branch is n + 1 levels deep until all other branches are n levels deep. Furthermore, it is always the leftmost node(s) that are filled first. To extract a value from a heap, the root node (with the lowest cost or highest priority) is pulled. The deepest, rightmost leaf then becomes the new root node. If the new root node is larger than its left child, then the root is swapped with its left child, in order to maintain the property that the root is always less than its children. This continues as far as necessary down the left branch. Adding a value to the heap is the reverse. The new value is added as the next leaf, and swapped upward as many times as necessary to maintain the heap property. A convenient property of trees that are complete from the left is that they can be stored very efficiently in a flat array. In general, element 0 of the array is the root, and elements k + 1 and k + 2 are the children of element k. The effect here is that adding the next leaf simply means appending to the array. Hash Tables Hash tables are a unique data structure, and are typically used to implement a "dictionary" interface, whereby a set of keys each has an associated value. The key is used as an index to locate the associated values. This is not unlike a classical dictionary, where someone can find a definition (value) of a given word (key). Unfortunately, not every type of data is quite as easy to sort as a simple dictionary word, and this is where the "hash" comes into play. Hashing is the process of generating a key value (in this case, typically a 32 or 64 bit integer) from a piece of data. This hash value then becomes a basis for organizing and sorting the data. The hash value might be the first n bits of data, the last n bits of data, a modulus of the value, or in some cases, a more complicated function. Using the hash value, different "hash buckets" can be set up to store data. If the hash values are distributed evenly (which is the case for an ideal hash algorithm), then the buckets will tend to fill up evenly, and in many cases, most buckets will have no more than one or only a few objects in them. This makes the search even faster. A hash bucket containing more than one value is known as a "collision". The exact nature of collision handling is implementation specific, and is crucial to the performance of the hash table. One of the simplest methods is to implement a structure like a linked list at the hash bucket level, so that elements with the same hash value can be chained together at the proper location. Other, more complicated schemes may involve utilizing adjacent, unused locations in the table, or re-hashing the hash value to obtain a new value. As always, there are good and bad performance considerations (regarding time, size, and complexity) with any approach. Another good example of a hash table is the Dewey decimal system, used in many libraries. Every book is assigned a number, based upon its subject matter� the 500's are all science books, the 700's are all the arts, etc. Much like a real hash table, the speed at which a person could find a given book is based upon how well the hash buckets are evenly divided� It will take longer to find a book about frogs in a library with many science materials than in a library consisting mostly of classical literature. In applications development, hash tables are a convenient place to store reference data, like state abbreviations that link to full state names. In problem solving, hash tables are useful for implementing a divide-and-conquer approach to knapsack-type problems. In LongPipes, we are asked to find the minimum number of pipes needed to construct a single pipe of a given length, and we have up to 38 pieces of pipe. By dividing this into two sets of 19, and calculating all possible lengths from each set, we create hash tables linking the length of the pipe to the fewest number of segments used. Then, for each constructed pipe in one set, we can easily look up, whether or not we constructed a pipe of corresponding length in the other set, such that the two join to form a complete pipe of the desired length. Conclusion The larger picture to be seen from all of this is that data structures are just another set of tools that should be in the kit of a seasoned programmer. Comprehensive libraries and frameworks available with most languages nowadays preempt the need for a full understanding of how to implement each of these tools. The result is that developers are able to quickly produce quality solutions that take advantage of powerful ideas. The challenge lies in knowing which one to select. Nonetheless, knowing a little about how these tools work should help to make the choices easier. And, when the need arises, perhaps leave the programmer better equipped to think up a new solution to a new problem� if not while on the job doing work for a client, then perhaps while contemplating the 1000 point problem 45 minutes into the coding phase of the next SRM.
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I think it’s probably true to say that, unlike the sun god, and the Gods of monotheism, Whitehead’s god has no face. This God is far too immersed in the complexity and variation of world. It is not the face so much as relational contrasts (that is, intensities) that connect in process. This perhaps make the term “interface” redundant. (Andrew Murphie, not yet published)


Contributor summit - Kubecon 2017
@AUTHORS - CONNOR DOYLE
@SLIDE AUTHORS ARE THE PRESENTERS
@SKETCHNOTES AUTHOR DAN ROMLEIN
Presenters: Jaice, Aparna, Ihor, Craig, Caleb
Slidedeck: https://docs.google.com/presentation/d/10AcxtnYFT9Btg_oTV4yWGNRZy41BKK9OjK3rjwtje0g/edit?usp=sharing
What is SIG PM: the “periscope” of Kubernetes
They look out for what’s next, translate what’s going on in the community to what that means for Kubernetes
Responsible for Roadmap and Features Process
Understanding the release notes is difficult sometimes since the docs aren’t always done by the time the release team is compiling the notes.
What did we do since Seattle
Feedback on how we can enhance SIG-PM
Moving from “product-driven” to “project-driven” where SIGs are defining their roadmaps based on market, end-use input etc.
Major 2017 Features:
(Apps) Workloads API to Stable
(Scalability) 5k nodes in a single cluster
(Networking) NetworkPolicy
(Node) CRI, GPU support
(Auth) RBAC stable
(Cloud providers) Out of core
(Cluster Lifecycle) kubeadm enhancements - road to GA in 2018?
(Autoscaler & instrumentation): custom metrics for HPA
(Storage) CSI (Container Storage Interface)
How did we do on the contributor roadmap?
Audience Feedback:
Liked that it felt like there was a common vision or theme last year.
Liked that there was a PM rep saying “do docs”, “your tests are failing” etc
Leadership summit 6 months ago: shot heard called was “stability releases, stability releases”. Not sure that 1.8 was really a stability release, not sure 1.9 is either. Will 2018 be the year of stability (on the desktop)
(Brian Grant) Come to the feature branch session!
Notion of stability needs to be captured as a feature or roadmap item to talk and brag about. Quantify, talk about as roadmap item
Idea for 2018: how do you measure and gamify stability? See a number in the red, people will want to fix. Testing, code quality, other metrics - might improve stability organically
Context of stability and testing: achievement was conformance program. 30+ conformant distros!
Want to see project continue to be useful: within your SIG, invest in conformance, extending suite. Going back to what is and is not k8s - define core, extensions: don’t compromise the stability of the core.
Please come see Eric Tune and define stability :
“cluster crashed”
“too many features”
“an API I was using stopped working”
“community is chaotic, how do I navigate that”
There are many new alpha features in each new release. Please prioritize graduating and stabilizing the existing features. (More than 50 APIs already)
Looking for volunteers on writing a stability proposal?
Jaice has one already!
May have broken the comment limit on Google Docs
Need to define lens:
architecture, community etc; look at a proposal under each.
Brian is working on arch stability.
Contribex is looking at mentorship and ladder.
Myriad of ways to approach problem set. How do we mature the processes of the Kubernetes ecosystem?
Looking for co-authors?
(Caleb)
Please hang out in SIG-Arch, SIG-Contribex, SIG-PM to drive this process forward
Looking at “is this feature ready to move to the next stability milestone?” (Alpha to Beta, Beta to GA etc)
Proposals are now Kubernetes Enhancement Proposals
Piece-by-piece over on more multiple releases (living documents)
Looked at a lot of other open source projects, e.g. the Rust community (RFC Process)
designed in the era of GitHub; decided on a lightweight process that works well with the VCS.
Talk about what we want to do without a long spec doc, about what we agreed to ahead of time, but* don’t want to diverge 2 years later*.
Helps tracking individual features (easier to read release notes)
Release note writing take tracking down a lot of docs, GitHUb issues, design docs, Slack and Google Group comments; combine from a bunch of places
Hard to tell from the release notes what’s important and what’s a minor detail.
Every SIG should set their own roadmap - the KEP proposal enables that.
Template that asks you to think ahead for the lifecycle of the feature; let people know what you’re planning to do.
It’s a medium for comms; not saying “It has to be done this way” but saying why this is important.
Inspired by “Toward Go 2” blog post by rsc
Has been tested - draft KEP for Cloud Providers, Tim St. Clair has tested.
Want to make easier for new contributors to write KEPs.
Starting with “what is a unit of work, how do people care”
Questions:
Are KEPS google docs, or pull requests, etc? How do you submit one?
Original intend: something that lives in source control. Discoverable like any part of the code. Attempt to combine design proposals and umbrella GitHub issues, link to 10s of other issues. They will live as long as we’re a project; doesn’t depend on hosting providers.
Vision is that writing KEPs, know from them what the roadmap is; can write the blog post based on the value articulated in the KEPs.
Right now they are buried in community repo 3 levels deep: a lot of great feedback so far. Joe wouldn’t object to making it more discoverable.
Kep.k8s.io for rendered versions?
Rust community has a sub-repo just for this (rust-lang/rfcs)
More than one person has said that KEPs weren’t known about - move to somewhere discoverable sooner rather than later. Who can own that action? Matt Farina from Samsung is keen to help but doesn’t have resources to lead.
Can only have its own repo if we get rid of features repo!
Don’t want anyone to do anything not adding value to work; hope is that KEP is worthwhile and adds value. Caleb will help drive, and create repos as needed.
(Jaice)
Features repo and process: I will say what I’m not happy about and what I’ve heard, but I do want to say there has been so much work from Ihor and SIG-PM to get where we are. If you haven’t seen the machinations of feature/release product you won’t know!
At velocity we have outgrown the notion of a central body leading. Seeing increasing cross-SIG concern where some SIGs rely on others to get their work done.
We need to find ways to detangle those dependencies earlier.
KEPs are focusing on enhancements, changes in ecosystem. A feature has a connotation of being user facing or interactive. KEP can be for something contributor facing, doc facing transparent. Get out of mindset we’re delivering a “thing” - we’re delivering value to user, contributor community, or both.
Currently the process is cumbersome. We want to follow agile principles about local control, local understanding, sharing amongst teams.
KEP provides opportunity for “steel thread” of custody. A KEP, as a living Markdown doc with metadata, lets you see high level idea at any group of time. A SIG can break this down into meltable ideas for each release. A KEP can last multiple milestones. In terms of features/issues, defined by SIGs, issue should be actionable. If a SIG writes an issue for that release milestone it should be approachable by any contributor who is a SIG member.
PRs roll up to the issue: links to this issue, which links to this KEP. For the first time we would be able to see at the PR level, what the grand scheme behind everything we do, is. Not heavyweight - just linking of issues. Limit administrivia, paperwork to delivery value.
Q:
For CloudProvider - discovery, had an idea, people started digging in; how do you keep updating the KEP? Do you update as you go, you odn’ tknow what you need?
Give an analysis on why issues in feature repo didn’t solve this problem and why KEPs will?
From features standpoint: SIGs interacted with features only when they had to. By trying to keep all that info separate from PRs, issues in each milestone: no way to tie that work back to the feature issue. No way to easily understand where in this features repo issue, long if multi-milestone: where was work, and the link to the issue? Eliminate the work
KEP is not solving that problem. KEP is saying “how do we best define and discuss the value we’re adding to the ecosystem”. Learns from patterns and antipatterns of other communities.
Features process is central body of people not doing the work.
Some friction with the GitHub mechanics of issues, relabeling quarterly, etc; would be nice to keep pace with the number of issues. Moving to files to provide value will help make that clearer.
Managing issues in the features repo: hundreds of issues from the last year, created spreadsheets etc. Bringing value but consuming extra resources. Not synced with features repo. Good we have a spreadsheet, but difficult to manage.
Started going through this process in SIG-Cluster LIfecycle: replacing GitHub thread (no one updates top) with a living document (use git history for mutations; see concise summary) - think it will be a huge improvement.
Does this mean the features repo is going away?
We need clear communication about where we are in this process. Are KEPs required, encouraged, etc? Trying with one project, be useful to know what the granularity is.
“It’s in Alpha now” - trying to validate some assumptions.
Has momentum with SIG-Arch and SIG-PM
Assumption we will try and see if it works.
Want to steward people into trying it to see if it’s valuable. If not, how do we make it so?
Community size and velocity now makes it difficult to radiate information to get what you need to know.
Kubernetes 1.10 would be a great place.
Will it still be true in 1.10 that you need features? Can you have KEP instead of a Feature issue? Make it very obvious for 1.10 please.
One thing we need to sort out
1.10 will have existing features process
Cluster Lifecycle are experimenting with how to do differently
Would love to see SIGs try the KEP process but it’s not a full surrogate for the features process yet.
Existing features can be sorted, filtered etc - will there be tooling around KEPs? Until that’s ready, I wouldn’t want to switch
How are the issues tied to the KEP?
Ties to this markdown file, in /kep/____
We need to work out the details.
When I create issue template, it will have a link to that KEP.
Make sure it’s searchable!
(Jago Macleod) Be explicit of scope of a KEP. A trend to more SIG ownership, code, roadmap etc; context is a SIG plans their own work. Certain faster moving SIGs, more capacity, to solve problems in the wrong component. Some KEPs will span SIG boundaries and should be explicit about this in comms.
(Tim Hockin) GitHub UX is not going to be great for this. It’s not built for what we’re trying to do. All of this predicates on having an actual site that manages, a web app?
If that’s true, can we start to collect the expertise?
Is there a SaaS tool for this?
* See other projects using tracking tooling, used on files in source control
* Won't be pretty or searchable in first iteration.
* Want to see built out as they're consumed. Don't build tooling before people are using the process
* *GH search is less than usable*
* Do you have a place to host this? We will find a place to host if someone is willing to write. Matt will help write.
* As someone involved with Maven repositories (trello) - it's a total pain in the neck. More in favour of PRs, discoverability, etc. Keep PRs for process. Push a site for discoverability.
(Joe Beda) Current processes are discussion, argument, write-only: comment threads no-one reads. Make it more discoverable, more readable: check stuff into GitHub, use a static site generator, publishes it somehow, crosslinks between documents. Just like when you go to an RFC, reference one there’s a link; that’s the ecosystem of discoverability we want.
(Eric Tune) I created features process so I’m a little attached. This discussion is a refactor vs rewrite debate. The feature repo template is there; in GitHub; change it. See how many incremental changes we can make to solve proposals. Put fields there and yell at people who don’t fill it in.
(Angus, Bitnami) As someone involved in Rust community:
fairly well-read Rust weekly news summary, including a section with a summary on outstanding proposals, broken down into early and late discussion phases. Read late phase to see what’s a done deal vs. what’s up in the air. There’s also a RFC podcast, where they get a couple of people, have a chat show about what’s involved in that proposal. Lots of ways as a community member to stay up to date.
Fixed timeline: trying to get approval. If nothing happens by the end it’s approved by default.
May not want to copy but good to know.
(Daniel Smith, Google) summarising: problems are mostly discoverability: we’ll write tooling. Why can’t we write tooling against that existing process? Both current and hypothetical new process suffer
Interacting with objects in GitHub is hard at our scale, we have a limited number of tokens.
Procedural aspects: if I look at a PR, there’s a link to an issue: that will tie up to a KEP.
Discoverability of relationships: exposed in the API. Links on GitHub are implemented by full-text search, not hard to do this.
(Chen Goldberg) Schedule follow-up sometime this week - communicating is hard, we’re all here!
(Henning, Zalando) Structured format with some metadata: all in one repo, or distributed amongst incubator projects etc? Are KEPs with a unique identity going to live in other project repos? Was this an idea?
If you’re not excited about features process, try a KEP!
Reach out to SIG-PM - calebamiles@
(Jaice) Have planning sessions about what SIGs are hoping to deliver for any milestone. Want to facility planning meetings in a more structured way (Planning as a Service). I did this for a proposal SIG-Cluster Lifecycle are working on: to have the discussion early and untangle dependencies, see when things could go off the rails, etc. Will talk to SIG leaders.
This planning activity will be one of the key success factors for the project moving forward.
Notes by @jberkus
Speakers (check spelling): Apprena Singha, Igor, Jaice DuMars, Caleb Miles, someone I didn’t get. SIG-PM
We have the roadmap, and we have this thing called the features process, which some of you may (not) love. And then we write a blog post, because the release notes are long and most of the world doesn’t understand them.
Went over SIG-PM mission. We had several changes in how the community behave over 2017. We are moving to a model where SIGs decide what they’re going to do instead of overall product decisions.
2017 Major Features listed (workloads API, scalability, networkpolicy, CRI, GPU support, etc.). See slides. The question is, how did we do following the 2017 roadmap?
Last year, we got together and each SIG put together a roadmap. In your SIG, you can put together an evaluation of how close we came to what was planned.
Q: Last year we kept hearing about stability releases. But I’m not sure that either 1.8 or 1.9 was a “stability release”. Will 2018 be the “year of the stability release?”
Q: Somehow the idea of stability needs to be captured as a feature or roadmap item.
Q: More clearly defining what is in/out of Kubernetes will help stability.
Q: What do we mean by stability? Crashing, API churn, too many new features to track, community chaos?
Q: Maybe the idea for 2018 is to just measure stability. Maybe we should gamify it a bit.
Q: The idea is to make existing interfaces and features easy to use for our users and stable. In SIG-Apps we decided to limit new features to focus everything on the workloads API.
Proposals are now KEPs (Kubernetes Enhancement Proposals) are a way to catalog major initiatives. KEPs are big picture items that get implemented in stages. This idea is based partly on how the Rust project organizes changes. Every SIG needs to set their own roadmap, so the KEP is just a template so that SIGs can plan ahead to the completion of the feature and SIG-PM and coordinate with other SIGs.
Q: How do you submit a KEP? A: It should live in source control. Each KEP will releate to dozens or hundreds of issues, we need to preserve that as history.
If you look at the community repo, there’s a draft KEP template in process. We need to make it a discoverable doc.


[gecode-users] Gecode terminates on incomplete solution
Philipp Keck
philipp.keck at gmx.de
Sun May 18 18:38:22 CEST 2014
Hi,
I am new to Gecode and also to Constraint Programming. While my first
problem may be a general CP question (so off-topic here? In that case
ignore it please.), my second problem is Gecode-specific.
My first problem is that Gecode either finds a solution immediately
(<1ms) and without any backtracking (peak-depth equals explored
nodes-1), or takes longer than I want to wait (at least 2 hours). This
problem might be related to my problem instances, because or-tools shows
exactly the same behaviour. My problem instances have 1,000 to 10,000
boolean variables and 400 to 2,500 constraints. There are both large and
small instances that can be solved within milliseconds, and both large
and small instances that take a long time. For those that take more than
2 hours, I still am sure that there is a solution, because Gurobi finds
one when I formulate the same problem as an LP.
How could I improve the running time of Gecode here? Does adding more
constraints make finding (any feasible) solution faster (because the
search space is more restricted and therefore the search tree is
smaller) or slower (because there are simply less solutions)? Should I
add redundant constraints?
For a set of boolean variables, if I want at most one of them to be 1,
is it better to add "a+b+c+... <= 1" using a linear-Constraint, or
should I use "a!=b", "a!=c", "b!=c", ... instead? Unfortunately I have
difficulties finding out the answers by experimenting because Gecode
runs for such long times. Is there a way to get some output during the
computation?
My second problem is a weird behaviour of Gecode terminating with some
variables remaining unassigned:
My models have the following structure: I have boolean variables only
and two kinds of constraints. The first kind of constraints requires
exactly c variables out of a certain subset to be 1, e.g. "a+c+d+x+y =
3" or "a+b = 1". The second kind allows at most one variable to be 1,
e.g. "a+b+r <= 1". That's all.
As mentioned above, Gecode either terminates immediately, or takes a
very long time. However, I have a particular problem instances that
makes Gecode terminate and report "solutions: 1" without having all the
variables set. So there are variables that still have [0..1] instead of
a specific value and val() throws ValOfUnassignedVar. Why does Gecode
terminate before it has a solution?
I call it like this:
branch(*this, allVariablesArgs, INT_VAR_NONE(), INT_VAL_MIN());
Using this call on the other hand makes Gecode compute forever (i.e.
more than 2 hours):
branch(*this, allVariablesArgs, INT_VAR_RND(someRnd),
INT_VAL_RND(someOtherRnd));
The problem might be related to how I implemented the copy function. I
have my variables inside a std::map<std::string, BoolVar> *and* inside a
BoolVarArgs and clone them like this:
variablesMap = s.variablesMap;
allVariablesArgs = BoolVarArgs(s.allVariablesArgs);
I don't know if that's the correct way to go. In particular, my copy
implementation never uses the share-parameter.
After reading the thread "Integer Variable Randomization" on this
mailing list, I also tried setting -c-d and -a-d to high values, but
still the copy-method was called many times.
Thank you for any help!
Philipp
Platform: Windows 7 x64, Visual Studio 2013 x64, Gecode 4.2.1
More information about the users
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BrawlCrate v0.40a
Wii File Editor
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A modification of David Amenta's RecycleBin code More...
Public Types | |
| enum | FileOperationFlags : ushort |
| Possible flags for the SHFileOperation method. More... | |
| enum | FileOperationType : uint |
| File Operation Function Type for SHFileOperation More... | |
Static Public Member Functions | |
| static bool | Copy (string path1, string path2, bool deleteFirst=false, bool confirmOverwrite=true) |
| static bool | Rename (string path1, string path2) |
| static bool | Delete (string path, FileOperationFlags flags) |
| Send file to recycle bin More... | |
| static bool | Delete (string path) |
| Send file to recycle bin; display warning if files are too big to fit (FOF_WANTNUKEWARNING) More... | |
| static string | SanitizeFilename (string filename) |
A modification of David Amenta's RecycleBin code
Possible flags for the SHFileOperation method.
File Operation Function Type for SHFileOperation
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inlinestatic |
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inlinestatic |
Send file to recycle bin; display warning if files are too big to fit (FOF_WANTNUKEWARNING)
| path | Location of directory or file to recycle |
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inlinestatic |
Send file to recycle bin
| path | Location of directory or file to recycle |
| flags | FileOperationFlags to add in addition to FOF_ALLOWUNDO |
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inlinestatic |
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inlinestatic |


Dan grew up in West Point, Nebraska. He has been in the glass business for over 40 years, the last 25 years as owner of Midwest Glass Service, Inc. He and his wife Mona, son Ryan, and daughter Katie, moved to Columbus Nebraska in December of 1990, and began to manage Midwest Glass Service Inc. in January of 1991.
Dan loves being a fan of all Husker sports, is a member of Peace Lutheran Church, and most of all, spending time with his family, including a young grandson, Elliot.
Mike Brandt was the first employee that Dan hired in 1991. He is a native of Columbus, Nebraska. He has worked at Midwest Glass for over 25 years. Mike started working at Midwest Glass shortly after graduating from high school. His pride in workmanship and quality of work shows in the work he performs.
Mike and his wife, Amy, have 3 daughters and 1 son. They are members of St Bonaventure Church, and their children attend St Bonaventure School and Scotus Central Catholic School. Mike is also a Husker fan, and spends a lot of time helping with the sporting activities of his children.


About Me
September 6, 2014
My name is Dakota Meadows and am currently enrolled at DevBootcamp. I have never done any coding, so this is an entirely new experience for me.
I am 22 and currently living just north of New York City, but I grew up in Washington State. I moved out here for college, and have transferred to Columbia University
I love to be adventurous and active. Wakeboarding, snowboarding, sky diving, hiking travelling, inner tubing, Spartan Race, Tough Mudder...I'm game!


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Tech Blog2
What is the difference between Margin, Border, and Padding?
Explanation of the different parts:
Content - The content of the box, where text and images appear
Padding - Clears an area around the content. The padding is transparent
Border - A border that goes around the padding and content
Margin - Clears an area outside the border. The margin is transparent


Directives start with the symbol `:-'. Any required output must be programmed explicitly; e.g. the directive:
:- member(3, [1,2,3]), write(ok).
asks the system to check whether 3
belongs to the list
[1,2,3]
. Execution of a directive terminates when all the
goals in the directive have been successfully executed.
Other alternative solutions are not sought. If no solution can be
found, the system prints:
* Goal - goal failed
as a warning.
The principal use for directives (as opposed to queries) is to allow files to contain directives that call various predicates, but for which you do not want to have the answers printed out. In such cases you only want to call the predicates for their effect, i.e. you don't want terminal interaction in the middle of consulting the file. A useful example would be the use of a directive in a file that consults a whole list of other files, e.g.:
:- consult([ bits, bobs, main, tests, data, junk ]).
If a directive like this were contained in the file myprog, typing the following at top-level would be a quick way of reading in your entire program:
| ?- [myprog].
When simply interacting with the top-level, this distinction between queries and directives is not normally very important. At top-level you should just type queries normally. In a file, queries are in fact treated as directives, i.e. if you wish to execute some goals, the directive in the file must be preceded by `:-' or `?-'; otherwise, it would be treated as a clause.


Perth to mark Remembrance Day
Commemorations held this weekend
by Rachel Clark, https://www.dailyrecord.co.uk/authors/rachel-clark/Perth will be marking Remembrance Day will events this weekend.
The annual Remembrance Sunday commemorations will begin at 9.40am on Sunday, November 10 with the military parade.
It will set off from Thimblerow down the Old High Street.
The civic parade with the provost, councillors, council officers and members of the High Constables of the City of Perth will then leave at 10.10am, led by Perth and District Pipe Band.
This parade will be processing from 2 High Street to St John’s Kirk for the service of remembrance at 10.30am.
Following on from the service, the military parade of local veterans, cadets and representatives from the Royal Regiment of Scotland, will form up for a march past and salute, taken by the lord-lieutenant, Stephen Leckie, on Tay Street.
The commemorations follow on to Monday, November 11 where the provost has been invited to attend the Bowerswell Remembrance service.
He will visit Bowerswell House for the service at 10.30am, and lay a wreath at the Bowerswell Memorial.
On the same day, Cllr Chris Ahern, Perth and Kinross Council’s armed forces and veterans champion, will lay a wreath at a short ceremony at Pullar House at the Pullars War Memorial at 11am.
Provost Dennis Melloy said: “We owe our veterans and serving forces personnel a great debt of gratitude and each yar we are proud to remember those who gave their lives in conflict to preserve our freedoms.
“Remembrance Sunday is a day to reflect on their sacrifices and pay tribute to them all.”
This comes after the provost, deputy lord-lieutenant of Perth and Kinross, the Earl of Kinnoull, and representatives from the armed forces and veterans’ associations lay wreaths earlier today (Friday, November 8) at the 51st Highland Memorial on the North Inch Perth.
The group also attended at the Mercat Cross in the city centre for the Poppyscotland remembrance event, where the provost laid a wreath and the crowd observed a two-minute silence at 11am.