--- layout: post title: Lemon Basil Gelato date: '2011-08-29T08:27:00+02:00' tags: - ice cream - kitchen tumblr_url: http://dotmr.tumblr.com/post/9543426649/lemon-basil-gelato ---
Started another small batch of gelato. Trying to find a baseline recipe for small batch by weight gelato.
——————————-
500g Whole Milk
75g Sugar
Cornstarch slurry (instead of egg yolk)
[ 100g Whole Milk ]
[ 20g Cornstarch ]
25g Basil leaves
Zest of 1 lemon
——————————-
Mix up slurry until Cornstarch dissolves (prob lower the # CS next time)
Combine basil, zest, sugar, whole milk in sauce pan and heat until it starts to bubble.
Add slurry, simmer for a couple minutes, cool completely (fridge overnight).


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Innovations that increase detection of, and response to, criminal attacks of financial systems.In this episode of the O’Reilly Podcast, I talk with Simon Moss, vice president of industry consulting and solutions, Americas, at Teradata. We discuss how machine learning and deep learning techniques are being used to fight financial crimes, such as credit card fraud, identity theft, health care fraud, and money laundering. Discussion points: Moss says AI techniques are “a new set of weapons” against perpetrators of financial crime. “If we use them right, we can finally at least slow down the constant tide of financial crime.” AI can be more effective than traditional methods of combatting identity fraud, health care fraud, and money laundering, because for those issues, he explains, “you’re not looking for a needle in a haystack. You’re looking for a needle in a stack of needles. You are trying to find individuals whose nefarious activity is disguised and hidden in pure normality, by completely innocuous activity.” Moss compares the use of machine learning techniques to a rules engine: “a rules engine looks for behaviors that have already happened, whereas machine learning is trying to connect different bread crumbs. It’s running multiple scenarios at the same time to try to look at the problem from multiple different angles.” Machine learning can add efficiency to the detection process: “It can take multiple data sources, map the data to a case, analyze it, and then in seconds, make a decision on whether it’s a false positive, whether it’s normal business activity, whether it’s something that needs further investigation, or whether it is outright criminality,” Moss says. Other links: Think Big Analytics, the consulting division of Teradata Moss’ recent LinkedIn article on the fight against money laundering This post is a collaboration between Teradata and O’Reilly. See our statement of editorial independence. Continue reading Simon Moss on using artificial intelligence to fight financial crimes.


For the complete list of my publications, see here.
This is my main work since I joined the bidding models team. In the past year, I have learned how to build a robust and reliable model for predicting value per click, including how to handle data spasity, how to iterate and deploy a model in production, how to monitor the performance of a model by dashboarding, and how to use offline evaluationa and AB testing for choosing the right model.
At trivago, my first project is to predict users booking intent. We asked users to report their booking intent when they landed on our webpage. More than 10200 users responded. The behavioral data of those users were extracted and merged with the attitudinal data for further analysis. Methods like logistic regression were used to find out the most important predictors of user intent. Various machine learning techniques (e.g., GradientBoosting) were also used to predict user intent.
During my PhD, I worked for a ERC(European Research Council)-funded project called "Redefining Tie Strength". It explores how social media, such as Facebook or Twitter, can help us gain informational and emotional benefits. I mainly do research on the psychological effects of social media usage. Besides this, I am also interested in how social media usage can influence consumer behavior. You can also find more info about my dissertation here.
PhD, Economics
Master of Science, Innovation Sciences
Bachelor in Engineering, Bio-engineering


Quickly build an OAuth 2.0 client that enables you to get an OAuth access and refresh token for your Jive instance with this form. The access token provides controlled API access to content in Jive to a third-party service. For more information on gaining an access token with Authorization Code Grant, Resource Owner Password Credentials Grant and more, check out the Jive Developer Community.


--- layout: blog title: "Blog" is_homepage: false pagination: enabled: true ---
Have something to share with the community? Let us know on the mailing list!


Triple-gold haul for India shooters
Mehuli, Elevenil and Divyansh on target
by Sports BureauIt was a golden day for Indian shooting as Manu Bhaker, Elavenil Valarivan and Divyansh Singh Panwar won gold at the prestigious World Cup Final here on Friday.
The gold haul was triggered by Manu who won with a World junior record score of 244.7. She beat Zorana Arunovic of Serbia by 2.8 points.
Elavenil qualified in second place with 631.1 and beat the topper Ying-Shin Lin of Chinese Taipei by 0.1 point for the women’s air rifle gold.
Mehuli Ghosh also made the final, but World No. 1 and 2 Apurvi Chandela and Anjum Moudgil were not at their best.
Divyansh Singh Panwar added to the gold spree by winning the men’s air rifle by a 0.1 point margin over Istvan Peni of Hungary.
Two of the best shooters of the season, Saurabh Chaudhary and Abhishek Verma finished sixth and fifth respectively. It did not matter as the team reached the top of the medals table once again.
The results: Men: 10m air rifle: 1. Divyansh Singh Panwar 250.1 (627.1); 2. Istvan Peni (Hun) 250.0 (627.4); 3. Patrik Jany (Svk) 228.4 (626.8).
10m air pistol: 1. Pang Wei (Chn) 243.7 (587); 2. Park Daehun (Kor) 241.7 (585); 3. Artem Chernousov (Rus) 220.6 (583); 5. Abhishek Verma 179.4 (588); 6. Saurabh Chaudhary 159.8 (581).
Women: 10m air rifle: 1. Elavenil Valarivan 250.8 (631.1); 2. Ying-Shin Lin (Tpe) 250.7 (632.3); 3. Laura-Georgeta Coman (Rou) 229.0 (629.3); 6. Mehuli Ghosh 163.8 (629.3); 13. Anjum Moudgil 624.9; 15. Apurvi Chandela 622.7.
10m air pistol: 1. Manu Bhaker 244.7 (WRJ) 578; 2. Zorana Zrunovic (Srb) 241.9 (581); 3. Wang Qian (Chn) 221.8 (583); 6. Yashaswini Singh Deswal 158.8 (578).


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| Model | Double Gear system 2020 |
|---|---|
| Pto Shaft Rotations | 450 RPMs |
| Propeller Shaft Rotations | 450 RPMs |
| Conveyor Chain Revolutions | 270 Rev/min |
| Blade Stroke Speed | 900 Strokes/min |
| Blade Cutting Width | 3 Inch (7.5cm) |
| Power | 50 hp or above |
| Fuel Consuption | 1.8 liter per acre |
| Number of Blades | 28 |
| Machine Cutting Width | 87 Inch |
| Cutting Height | 50mm |
| Machine Height | 26 Inch |
| Machine Width | 31 Inch |
| Machine Length | 92 Inch |
| Machine Weight (Without Attachment) | 218kg |
| Massey 240 Attachment Weight | 85kg |
| Fiat 480 Attachment Weight | 98kg |
| Model | (n)Blade 2020 |
|---|---|
| Pto Shaft Rotations | x |
| Propeller Shaft Rotations | x |
| Blade Line Rotations | x |
| Blade Rotations Speed | x |
| Blade Line Width | x |
| Power | 50 hp or above |
| Fuel Consuption | x |
| Number of Blades | 36v, 42v, 48v, 54v, 60v |
| Blade Tilling Depth | x |
| Machine Height | x |
| Machine Width | x |
| Machine Length | x |
| Machine Weight | x |
| Model | x |
|---|---|
| Pto Shaft Rotations | x |
| Propeller Shaft Rotations | x |
| Conveyor Router Revolutions | x |
| Sheller Stroke Speed | x |
| Machine Router Width | x |
| Power | x |
| Fuel Consuption | x |
| Number of Shellers | x |
| Machine Router Diameter | x |
| Machine Height | x |
| Machine Width | x |
| Machine Length | x |
| Model | Heavy Crop 2020 |
|---|---|
| Pto Shaft Rotations | 450 RPMs |
| Propeller Shaft Rotations | 450 RPMs |
| Conveyor Chain Revolutions | 270 Rev/min |
| Blade Stroke Speed | 900 Strokes/min |
| Blade Cutting Width | 3 Inch (7.5cm) |
| Power | 50 hp or above |
| Fuel Consuption | 1.8 liter per acre |
| Number of Blades | 28 |
| Machine Cutting Width | 87 Inch |
| Cutting Height | 50mm |
| Machine Height | x |
| Machine Width | 31 Inch |
| Machine Length | 92 Inch |
| Machine Weight (Without Attachment) | x |
| Massey 240 Attachment Weight | 85kg |
| Fiat 480 Attachment Weight | 98kg |
| Model | Belt Conveyor system 2020 |
|---|---|
| Pto Shaft Rotations | x |
| Propeller Shaft Rotations | x |
| Conveyor Belt Revolutions | x |
| Blade Stroke Speed | x |
| Blade Cutting Width | 3 Inch (7.5cm) |
| Power | 50 hp or above |
| Fuel Consuption | x |
| Number of Blades | 28 |
| Machine Cutting Width | 87 Inch |
| Cutting Height | 50mm |
| Machine Height | 26 Inch |
| Machine Width | 31 Inch |
| Machine Length | 92 Inch |
| Machine Weight (Without Attachment) | x |
| Massey 240 Attachment Weight | 85kg |
| Fiat 480 Attachment Weight | 98kg |
| Model | x |
|---|---|
| Number of Disks | 3 |
| Space Between Blades | x |
| Power | x |
| Fuel Consuption | x |
| Machine Working Width | x |
| Cutting Depth | x |
| Machine Height | x |
| Machine Width | x |
| Machine Length | x |
| Model | x |
|---|---|
| Tine Depth | x |
| tine Cutting Width | x |
| Power | x |
| Fuel Consuption | x |
| Number of Tines | x |
| Machine Working Width | x |
| Machine Overall Width | x |
| Machine Height | x |
| Machine Width | x |
| Machine Length | x |
| Machine Weight | x |
| Model | x |
|---|---|
| Seed Capacity | x |
| fertilizer Capacity | x |
| Seed Bucket Volume | x |
| Fertilizer Bucket Volume | x |
| Seed Sower Distance | x |
| Power | x |
| Fuel Consuption | x |
| Number of Sowers | x |
| Machine Working Width | x |
| Machine Working Depth | x |
| Machine Height | x |
| Machine Width | x |
| Machine Length | x |
| Machine Weight | x |
| Model | x |
|---|---|
| Engine Type | x |
| Engine Power | x |
| Fuel Consuption | x |
| Number of Blades | x |
| Blade Stroke Speed | x |
| Blade Cutting Width | x |
| Machine Cutting Width | x |
| Cutting Height | x |
| Machine Height | x |
| Machine Width | x |
| Machine Length | x |
| Machine Weight | x |


🏹 Stencil Arrow
Generate files out of your Archerfile (like this one). For more information about Archery itself head to vknabel/Archery.
Render Stencil-Templates with contents of your Archerfile.
{
"scripts": {
"readme": {
"arrow": "vknabel/StencilArrow",
"template": "README.md.stencil",
"destination": "README.md",
"searchPaths": ["Scripts"]
}
}
}
This will insert your metadata into your template and write its contents to README.md
.
Available Options
| Name | Type | Default |
|---|---|---|
| template | String |
Required |
| destination | String? |
Print to stdout |
| metadataName | String? |
Globally available. Contains the Archerfile |
| argumentsName | String? |
arguments contains all command line args |
| searchPaths | [String]? |
["."] search on current directory |
Contributors
- Valentin Knabel, @vknabel<EMAIL_ADDRESS>@vknabel on Twitter
License
Archery is available under the MIT license.


Creates a new local group, or updates the settings for an existing group.
Install-Group [-Name] <String> [[-Description] <String>] [[-Member] <String[]>] [-PassThru] [-WhatIf] [-Confirm] [<CommonParameters>]
Install-Group
creates a local group, or, updates a group that already exists.
YOu can get a System.DirectoryServices.AccountManagement.GroupPrincipal
object representing the group returned to you by using the PassThru
switch. This object implements the IDisposable
interface, which means it uses external resources that don't get garbage collected. When you're done using the object, make sure you call Dispose()
to free those resources, otherwise you'll leak memory. All over the place.
| Name | Type | Description | Required? | Pipeline Input | Default Value |
|---|---|---|---|---|---|
| Name | String | The name of the group. |
true | false | |
| Description | String | A description of the group. |
false | false | |
| Member | String[] | Members of the group. |
false | false | @() |
| PassThru | SwitchParameter | Return the group as a This object uses external resources that don't get cleaned up by .NET's garbage collector. In order to avoid memory leaks, make sure you call its |
false | false | False |
| WhatIf | SwitchParameter | false | false | ||
| Confirm | SwitchParameter | false | false | ||
| CommonParameters | This cmdlet supports common parameters. For more information type Get-Help about_CommonParameters . |
Install-Group -Name TIEFighters -Description 'Users allowed to be TIE fighter pilots.' -Members EMPIRE\Pilots,EMPIRE\DarthVader
If the TIE fighters group doesn't exist, it is created with the given description and default members. If it already exists, its description is updated and the given members are added to it.


Folding preferences
Use the Folding preference panel to customize the C/C++ editor folding behavior.
| Option | Description | Default |
|---|---|---|
| Enable folding when opening a new editor | If enabled, apply folding rules to the new editor. | |
| Select folding to use | Select the folding to use from the available choices. | |
| Enable folding of preprocessor branches (#if/#endif) | If enabled, fold preprocessor branches. | |
| Enable folding of control flow statements (if/else, do/while, for, switch) | If enabled, fold control flow statements. | |
| Macros | If enabled, fold macro definitions. | On |
| Functions | If enabled, fold functions. | Off |
| Methods | If enabled, fold methods. | Off |
| Structures | If enabled, fold structures. | On |
| Comments | If enabled, fold comments. | Off |
| Header Comments | If enabled, fold header comments. | On |
| Inactive Preprocessor Branches | If enabled, fold inactive processor branches. | On |


|
| virtual string | DefaultDocumentRoot [get, set] |
| | The root to be used if documentRoot is empty and a root is required to form a valid XML document. More...
|
| |
| virtual string | DocumentRoot [get, set] |
| | The name of the root element of the document. Defaults to 'xmlData'. If there is more than 1 record and the root is not specified, the default document root will still be used to ensure a valid XML document is created. More...
|
| |
| virtual string | Header [get, set] |
| | A header to use in the XML document (such as setting the encoding or version). Defaults to ''. More...
|
| |
| virtual string | Record [get, set] |
| | The name of the node to use for each record. Defaults to 'record'. More...
|
| |
| virtual string | NameProperty [get, set] |
| | This property is used to read the key for each value that will be sent to the server. For example: More...
|
| |
| virtual bool | WriteAllFields [get, set] |
| | True to write all fields from the record to the server. If set to false it will only send the fields that were modified. Defaults to true. More...
|
| |
| virtual string | GetRecordDataHandler [get, set] |
| | Formats the data for each record before sending it to the server. This method should be overridden to format the data in a way that differs from the default. Parameters record : Object The record that we are writing to the server. Returns An object literal of name/value keys to be written to the server. By default this method returns the data property on the record. More...
|
| |
|
virtual string | FilterRecordHandler [get, set] |
| |
|
virtual string | FilterFieldHandler [get, set] |
| |
|
virtual string | PrepareHandler [get, set] |
| |
| virtual bool | ExcludeId [get, set] |
| |
| virtual bool | SkipIdForPhantomRecords [get, set] |
| |
| virtual bool | SkipPhantomId [get, set] |
| |
|
|
void | OnMetadataCreated (ModelMetadata metadata) |
| |
|
const string | KEY = "__Ext.Net.Mobile.Storewriter" |
| |
◆ DefaultDocumentRoot
| virtual string Ext.Net.Mobile.MVC.XmlWriterAttribute.DefaultDocumentRoot |
|
getset |
The root to be used if documentRoot is empty and a root is required to form a valid XML document.
◆ DocumentRoot
| virtual string Ext.Net.Mobile.MVC.XmlWriterAttribute.DocumentRoot |
|
getset |
The name of the root element of the document. Defaults to 'xmlData'. If there is more than 1 record and the root is not specified, the default document root will still be used to ensure a valid XML document is created.
◆ Header
| virtual string Ext.Net.Mobile.MVC.XmlWriterAttribute.Header |
|
getset |
A header to use in the XML document (such as setting the encoding or version). Defaults to ''.
◆ Record
| virtual string Ext.Net.Mobile.MVC.XmlWriterAttribute.Record |
|
getset |
The name of the node to use for each record. Defaults to 'record'.
The documentation for this class was generated from the following file:
- MVC/MetadataAware/XmlWriterAttribute.cs


The secret is (not) to bang the rocks together
So many people seem to purchase a stack of kit, and want it to magically work together, or see the low cost of entry by using an open source project, and assume they don’t have to learn. If there’s one thing I’ve learned when, well, tackling anything new, it’s that learning is key. You can’t just bang random rocks together and expect fire it to work.
The problem(s)
Many people seem to tackle home automation as if it’s a kind of magic - if they just repeat some incantation, change a few things, and it’ll work. The number of times I’ve seen people blindly copy and paste somebody else’s work, or an example, change things at random and then complain that it’s not working…
Actually, if I’m honest, it’s not just home automation, it’s anything outside of their experience. Lurking on the various Tales from X subreddits makes that very clear, even if you haven’t experienced it yourself first hand.
In only seven days
See if these sound familiar:
- Asking the same question repeatedly, in the apparent hope that the answer will change2
- Blindly hacking configurations (banging the rocks together)
- Complaining that the YouTube video from some random person didn’t work
- When directed to the documentation, laughing it off or ignoring it
- Ignoring attempts to help them that don’t fit with what they think is the problem
- Complaining that the platform doesn’t do something, or does something wrong
- Making unfounded assumptions, and insisting that these assumptions are true, despite evidence otherwise
Anybody on any forum or chat about a product (whether software, hardware, or pretty much anything) will be familiar with these behaviours.
If you want point and click magic, then (some) commercial solutions are likely to be a better choice than most of the open source solutions. Even then, if you don’t take the time to learn then you’re going to have a hard time.
It’s like driving a car, riding a bike, or doing whatever your day job is. That knowledge and skill didn’t suddenly appear in your brain at the stroke of midnight. You had to learn it, and in many cases understand what’s going on when you do certain things. For complex things you’ll have read documentation to gain that understanding. This is a process that takes time, from weeks to months until you become good at it, potentially longer. In my day job for example, the assumption is that it typically takes 6 months to become good enough to work things unsupervised.
Home automation is no different.
Doing (it) all right
If you take the time to read up on the platform you’re using (official documentation, forums, etc, maybe even read some of the developer documentation) then you’ll understand how to make it work. That understanding makes your own efforts more effective, and reduces frustration all round.
Next, read the error messages. Sure, sometimes the error message is an obscure something went wrong, but most of the time it’ll tell you at least where in your configuration the error is. Often the error will tell you enough that if you read the documentation you’ll have it fixed in no time.
When you ask for help, don’t ignore the things you don’t want to do, or you disagree with. You asked for help after all. If people direct you to some documentation then read it. If you don’t understand it, explain what you’re having problems with. Don’t be surprised if people direct you to learn other things so that what you’re reading makes sense.
Oh, and if you avoid becoming a help vampire and people will be more likely to want to help you3.


Topsy-Turvy
rated R 160 minutes October Films starring Jim Broadbent, Allan Corduner, Lesley Manville, and Ron Cook written and directed by Mike Leigh
A Review by Frankie Paiva
A well made period piece is often a tough sell for audiences. Most of these films are highly dramatic and offer little in the areas of excitement or humor. Mike Leigh's new film Topsy-Turvy which explores Gilbert and Sullivan in a career slump breaks all of those rules. Blending a mix of colorful sets, great music, genuinely funny scenes and dialog, and wonderful performances, this movie keeps you interested for it's entire 160 minute length.
Famed playwright composer duo Gilbert (Broadbent) and Sullivan (Corduner) have just opened their latest production, Princess Ida, at the Savoy theater in England. The audience immediately proclaims it another hit, but the newspaper theater critic says otherwise. This critic says he sees no progress in artistic development coming from them, and says he cannot recommend the play. Sullivan feels the same way, he's tired of using the same music again and again and wants to write a grand opera, one so fantastic it will blow people away.
But there are concerns as to their future. The contract with the Savoy says that they must produce a new play when asked, and while Gilbert has one already written, Sullivan refuses to compose for he believes it's a rehash of what's been done before. Gilbert is hard set in a writer's block and doesn't know what to do. All of this changes when Gilbert is dragged by his wife to a local Japanese exhibition. He is appalled and intrigued at the same time about the native way of life there. This inspires him to write a grand play, The Mikado, a play sure to woo Sullivan back and draw large audiences. But at what price will it take to get the play onstage?
Another wonderful film that shows the lives of the actor. Offering much more behind the scenes process than All About My Mother did, it really gives us an idea of how much work went into these plays. The script was written with these scenes in mind, and original musical composer Carl Davis (Sullivan himself is also credited) adds some enchanting music to go along with them. This gives the film an upbeat pace, despite many of it's sad undertones. The star of the film has to be the woman (who's name escapes me) who researched the time period for the film. There are many great touches that really give us a feel for the era, including a very humorous scene in which Gilbert uses a telephone, which were just being introduced in their time. Leigh does a wonderful job of shifting the focus throughout the movie. For the first hour we are drawn into Sullivan's problems and by the 100 minute mark, we have nicely switched over to Gilbert's troubles. Other examples of this include the plights of various Savoy players who've been in all the plays the two created. Much of the humor is bittersweet, and really keeps this thing chugging along. While the length is an issue for some, so many of the scenes are carefully selected that you never get bored with redundant information. The only scene I thought was unneeded was an early scene where Sullivan watches two bare breasted women perform some type of mini-musical. If this scene had been removed, it easily could have achieved a PG-13 rating. And you haven't seen anything until you see Gilbert pretending to be a Japanese Samurai warrior.
All of the actors (and actors playing actors) really bring their characters to life. Towards the end, I found myself forgetting that this was a movie, that while fact based, was not entirely true. I felt like I was there, watching the entire thing happen. Another great film to add to Mike Leigh's filmography, and another great film that might change the way period pieces are made. This is fun, energetic, and at times exciting, bravo Gilbert and Sullivan, I give you a standing ovation.
A-
Frankie Paiva<EMAIL_ADDRESS>http://www.homestead.com/CinemaParadise/mainpage.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


The smallest duragesic patches are 25/ug per hour release 1.8mg over three days before they are changed for a fresh patch. This actually theoretically leaves .7mg of fentanyl in the spent patches. Fentanyl being soulable in alcohol, the spent patches were cut up in small peices and soaked in a small amount of 99% anhydrous isopropyl alcohol (70% would probably work too). After some time, overnight or even weeks as the spent patches were simply added to the jar, the alcohol was filtered and the filter expressed so as much of the substance would fall in a glass dish. Basil leaf or some other smokeable herb was placed in the alcohol and the alcohol was allowed to evaporate. The herb was smeared and even a razor used to scrap up any residue to place it on the herb.
This fentanyl-laced herb was smoked for strong opiate effect. The amount of herb used determines potency, more patches and less herb obviously makes it more potent. One or two hits would produce not a rush but a definite floating feeling with colorful CEV's. Standing up assured one was very intoxicating as one felt wobbly. After a few small bowls, sweat would appear on the forehead and one certainly felt 'loaded' for a few hours.
Warning, Fentanyl is extremely potent, this is why the smoking method was chosing by the explorer, as titration is easier.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Freshman Davis scores 17, Tide gets first win for Nate Oats
by KATIE WINDHAMTUSCALOOSA, Ala. (AP) - After redshirting last season due to injury, Javian Davis has been waiting almost two years to play live basketball again. He took advantage of his starting opportunity for Alabama on Monday night.
Davis scored 19 points and Alabama beat Florida Atlantic 78-59 to earn the first victory of the Nate Oats era.
“It’s been a long journey. It’s been a year and eight months since I played an actual basketball game,” Davis said. “I can’t take it for granted, just trying to improve everyday with my teammates and coaches.”
In his first career start, Davis also recorded nine rebounds and two assists.
Both teams got off to slow starts offensively as the game was tied at five at the first TV timeout.
Florida Atlantic held the Alabama offense to two points for a more than five minutes stretch starting at the 9:57 mark in the first half.
Alabama responded by scoring 20 points over the last 4:48 of the first half to go into halftime with a 43-25 lead.
“During that run, I thought they shared the ball and played much more unselfish than us,” said Florida Atlantic head coach Dusty May on Alabama’s run before halftime.
The Crimson Tide was able to maintain that lead throughout the second half.
Alabama had to play with a shorter bench after two players fouled out for the Crimson Tide, and Herbert Jones did not play after suffering an injury against Penn.
“You know we had an eight-man rotation today that I thought played pretty hard, especially when you’ve got two guys foul out with 11 minutes to play,” Oats said.
Another freshman Jaden Shackleford added 17 points off the bench for Alabama, and Kira Lewis Jr. finished with 16 points, eight assists and six rebounds.
Junior guard Richardson Maitre finished with 18 points and seven rebounds for Florida Atlantic.
Oats said after the loss last week and the disappointing news about the eligibility of Jahvon Quinerly, this win was a positive step for the team.
“That loss in the opener to Penn gave us a wakeup call. We’re 1-1, and it’d be great to be 2-0 going into our first road game,” Oats said. “But I think the guys are playing well and gaining some confidence as they play the way we’re asking them to.”
BIG PICTURE
Florida Atlantic: FAU shot 35.3-% from the free throw line, making only 6 of 17 of attempts.
Alabama: Alabama got 31 points from the bench, led by 17 from Jaden Shackelford compared to 19 total bench points from FAU.
QUINERLY INELIGIBLE
Villanova transfer and former five-star recruit Jahvon Quinerly was denied his appeal by the NCAA to become eligible for Alabama for the 2019-2020 season. Alabama announced the decision less than three hours before tipoff Monday.
UP NEXT
Florida Atlantic hosts Palm Beach Atlantic on Saturday.
Alabama faces their first road test of the year with a trip to Rhode Island on Friday night.
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THING FROM ANOTHER WORLD, THE (director: Christian Nyby; screenwriter: Charles Lederer/1938 story by John W. Campbell Jr. "Who Does There"; cinematographer: Russell Harlan; editor: Roland Gross; cast: Kenneth Tobey (Captain Patrick Hendry), Margaret Sheridan ("Nikki" Nicholson), Robert Cornthwaite (Dr. Arthur Carrington), Douglas Spencer (Ned "Scotty" Scott), Dewey Martin (Bob-Crew Chief), James Arness ("The Thing"), Eduard Franz (Dr. Stern), David McMahon (Gen. Fogarty), James Young (Lt. Eddie Dykes), Robert Nichols (Lt. MacPherson ), Bill Self (Corporal Barnes), Sally Creighton (Mrs. Chapman), Nicholas Byron (Radioman Tex Richards); Runtime: 87; 1951)
Reviewed by Dennis Schwartz
"The Thing" was long suspected of being directed by Howard Hawks--much later on this was confirmed by the actors. Christian Nyby was Hawks's longtime editor and was looking to advance his career, but had trouble handling the directing chores, which induced Hawks to step in and help his friend out.
This is one of the better science-fiction cheapie films, one that became a cult classic. It is a wonderfully banal film about a flying saucer landing on the North Pole and a superior alien, who looks like Frankenstein, being thawed out. The alien will attack a group of scientists and Air Force personnel in the scientists' Arctic outpost. Hawks wastes no time with any liberal messages about why this creature came here, instead the film has a jovial Air Force crew snappily banter at each other, a sparring romantic relationship develop between the womanizing captain and the scientist's independent-minded secretary cut through the fierceness of the monster story, and for quirkiness, we see plants as monsters crying for more blood to spawn more monsters. The cast is perfect, their non-chalant attitude gives the film its raucous mood and allows the warlike atmosphere between beast and man to be a battle of both wits and brawn.
The film opens with General Fogarty (McMahon) at the Air Force base in Anchorage, receiving an urgent call from Dr. Carrington (Cornthwaite) at his scientific outpost for botanists and experimental lab scientists at the North Pole, telling him to send a search party, that an unidentified metallic flying object crashed near-by. Captain Hendry (Kenneth Tobey) is dispatched there with his genial crew and with a wisecracking journalist, Scotty (Spencer).
The bumbling military men detonate the found spacecraft but accidently destroy it, but they capture the alien (James Arness) who is frozen in a lump of ice and bring it back to their outpost to await orders from General Fogarty. They store the monster in a freezing store room, but accidently, while on guard duty, their electric blanket gets too close to it and it thaws out, whereby it escapes, killing their sled dogs in the process, but losing an arm.
After the brilliant but misguided Carrington experiments on the recovered arm, he sees no blood or nervous system and boldly concludes it is some form of a vegetable, that through evolution lives on human or animal blood and has developed a more superior intelligence than humans.
A nice little confrontation takes place between the Air Force men and the scientist over what to do with the monster. Dr. Carrington wants to communicate with this superior being, he states, "There are no enemies in science, only phenomena to study." But the Air Force is only interested in the safety of everyone concerned and see no redeeming value in communicating with the alien. Captain Hendry takes charge of the outpost; and because of his professional duties, he curtails his romantic advances on the pretty secretary, Nikki (Margaret Sheridan), who is trapped in the Arctic with the brainy scientists. He says the scientists are like kids with a new toy, making a big fuss over this alien, and he proceeds to treat them like children who need a father to discipline them, while he waits for further orders.
While Carrington retreats to the greenhouse and discovers the alien was there, he decides not to tell Hendry where it is and goes ahead trying to raise new monsters by feeding them with frozen bags of blood plasma.  Nikki snaps back, "You boil it." When the inept military men try to douse it with kerosene and set it on fire, they nearly burn down their building and hardly harm the creature in the process, though they do incur its wrath.
The monster comes back to the greenhouse and kills the two scientist doing guard duty. Then, as an ironic twist, the monster cuts off the heat in the building. Hendry now follows the advice of a scientist, who suggests they electrocute it with the power from their generator. But Carrington has gone crazy, clammoring "I want to understand it," and has shut off the generator. The monster rewards him by swatting him away, as if he were a fly, but in its pursuit of blood, it steps on the electric trap and sizzles to death.
The film closes with the excited Scottie breaking the story to the world, screaming into the microphone: " I bring a warning--to every one of you listening to the sound of my voice. Tell the world, tell this to everyone wherever they are: watch the skies, watch everywhere, keep looking--watch the skies! "
This is a fast-paced and enjoyable B-film, giving us a feel for the cold war paranoia taking hold of the country at the time. It is about how anyone different is viewed as an enemy, and how there is a sense of isolation for intellectuals in the country. It also shows how rational people when just trying to do their professional jobs, still act irrationally. This is evidenced by the conflict between the scientists versus the military, with this reactionary film clearly looking at the common man types who are in the military as a better alternative than the arrogant intellectual-minded scientists, who are skeptically viewed as being so different from the man in the street that they are not to be trusted.
REVIEWED ON 7/17/2000 GRADE: A
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
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{% extends "base.html" %} {% block title %}
Medieval catalogues > BENEDICTINES > Peterborough > Books given by Bishop Æthelwold (d. 984)
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All data was derived from the List of Identifications by Professor Richard Sharpe.
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better known by his stage name Buck 65, is a Canadian alternative hip hop artist. Underpinned by an extensive background in abstract hip hop, his more recent music has extensively incorporated blues, country, rock, folk and avant-garde influences.
Terfry is also a radio host, hosting the weekday Radio 2 Drive show on CBC Radio 2 since September 2, 2008.[2] In addition, he once hosted a weekday program on CBC Radio 3's web radio station.[3]
Discography


April 09th,2021
5 Simple Tips for the search Bar
How to make search bar more effective in 5 ways
UI is the saddle, the stirrups, & the reins. UX is the feeling you get being able to ride the horse.
The Search bar, despite its simplicity, is usually one of the most frequently used elements on websites or applications. This makes the search bar design and usability a big deal.
Here are some of the best tips on how to design it correctly:
1. The placeholder text :
The placeholder text in the search bar describe the context of what we can look for on a given website or mobile application.
2. Don't Use a font size that is too small :
The font size in the search bar should be 16px - iOS browsers will zoom in on the search bar often obscuring the right side.
3. Include the search icon:
Often designers use icons to visually convey what the button is doing. In this case the magnifies icon acts as a button.
4. Don't Make the search box short:
The search bar should be long enough to contain the whole entered word or sentence. On mobile it should be almost the full width of the screen
5. Don't overdo it with creativity:
Designers want to be creative, and that's good but the search bar has to be a simple field to fill in and search for the phrase you want.
Final Thoughts
UX and UI are inextricably linked, but they are two very separate roles.
UI is all about the touchpoints the user encounters to navigate from A to B, such as buttons,searchbar, scrollbars and swipeable screens. All of these components have a huge impact on the overall UX of a product, and you can’t have one without the other.


The documentation begins on the Natural Language Classifier service overview page.
If you're looking for information about how to create and train a classifier or the API, try these links:


Show navigation
Hide navigation
`
Back to Home
Summary.js Demo
Open Repo
Summary.js
This is the
sentence long summary
Summarize It!


[1]
air conditioning was good throughout the room was busy.
[2]
air conditioning was good throughout the room or the bedroom.


A version of Fish is available online at http://abouttag.appspot.com/fish or http://fish.abouttag.appspot.com.
This version provides full access to the whole of Fish with very few exceptions and changes.
Key things to know are:
You can log into Shell-Fish, the on-line version, with any Google account. Shell-Fish does not see your Google password.) If you do this, you can go into Settings and store one or more sets of Fluidinfo credentials; thereafter, when you are logged in through your Google account, you will be able to interact with Fluidinfo using those credentials. (The su command will switch between users.) You can also specify whether you wish to use full Fluidinfo-style paths or abbreviated Unix-style paths with Fish online.
If you don’t log in, you will be able to interact with Fluidinfo using the user called fish. This user has restricted permissions, meaning that you can perform any normal read operations, and can tag things with tags fish/a through fish/z, but not create new tags or namespaces, or delete tags.
When interacting with Shell-Fish, you use exactly commands as at the command line except that you may omit the fish, i.e you can use
ls
instead of
fish lsetc.
This help is available using the Help link at the top of the Shell-Fish page.
There is a bookmarklet called az-fish towards top right of the screen. If you drag this to your browser’s tool bar and the then click on it when you are on an Amazon UK or Amazon US product page for a book, e-book, CD or MP3 track, it will take you into Shell-Fish and attempt to construct the appropriate about tag for that item using the amazon`` command anf the abouttag library.
The Shell-Fish service runs on Google’s App Engine, which has limits on how long HTTP calls can take. The practical result of this is that complex fish commands may time out; for example, running the tests would be ill-advised. Timeouts will obviously be more common at times when Fluidinfo is under particularly heavy load.
If you use an iPhone or iPad, you can add the Fish page to your homescreen and get a “web app” version, which should show up looking like the one at the top of the page.


{include file="../application/index/view/index/_commoncss.html" /} {include file="../application/index/view/index/_head.html" /}


CSS
struct CSS
CSS colors.
-
hex #F0F8FF
Declaration
Swift
public static let aliceBlue: Color
-
hex #FAEBD7
Declaration
Swift
public static let antiqueWhite: Color
-
hex #00FFFF
Declaration
Swift
public static let aqua: Color
-
hex #7FFFD4
Declaration
Swift
public static let aquamarine: Color
-
hex #F0FFFF
Declaration
Swift
public static let azure: Color
-
hex #F5F5DC
Declaration
Swift
public static let beige: Color
-
hex #FFE4C4
Declaration
Swift
public static let bisque: Color
-
hex #000000
Declaration
Swift
public static let black: Color
-
hex #FFEBCD
Declaration
Swift
public static let blanchedAlmond: Color
-
hex #0000FF
Declaration
Swift
public static let blue: Color
-
hex #8A2BE2
Declaration
Swift
public static let blueViolet: Color
-
hex #A52A2A
Declaration
Swift
public static let brown: Color
-
hex #DEB887
Declaration
Swift
public static let burlyWood: Color
-
hex #5F9EA0
Declaration
Swift
public static let cadetBlue: Color
-
hex #7FFF00
Declaration
Swift
public static let chartreuse: Color
-
hex #D2691E
Declaration
Swift
public static let chocolate: Color
-
hex #FF7F50
Declaration
Swift
public static let coral: Color
-
hex #6495ED
Declaration
Swift
public static let cornflowerBlue: Color
-
hex #FFF8DC
Declaration
Swift
public static let cornsilk: Color
-
hex #DC143C
Declaration
Swift
public static let crimson: Color
-
hex #00FFFF
Declaration
Swift
public static let cyan: Color
-
hex #00008B
Declaration
Swift
public static let darkBlue: Color
-
hex #008B8B
Declaration
Swift
public static let darkCyan: Color
-
hex #B8860B
Declaration
Swift
public static let darkGoldenRod: Color
-
hex #A9A9A9
Declaration
Swift
public static let darkGray: Color
-
hex #A9A9A9
Declaration
Swift
public static let darkGrey: Color
-
hex #006400
Declaration
Swift
public static let darkGreen: Color
-
hex #BDB76B
Declaration
Swift
public static let darkKhaki: Color
-
hex #8B008B
Declaration
Swift
public static let darkMagenta: Color
-
hex #556B2F
Declaration
Swift
public static let darkOliveGreen: Color
-
hex #FF8C00
Declaration
Swift
public static let darkOrange: Color
-
hex #9932CC
Declaration
Swift
public static let darkOrchid: Color
-
hex #8B0000
Declaration
Swift
public static let darkRed: Color
-
hex #E9967A
Declaration
Swift
public static let darkSalmon: Color
-
hex #8FBC8F
Declaration
Swift
public static let darkSeaGreen: Color
-
hex #483D8B
Declaration
Swift
public static let darkSlateBlue: Color
-
hex #2F4F4F
Declaration
Swift
public static let darkSlateGray: Color
-
hex #2F4F4F
Declaration
Swift
public static let darkSlateGrey: Color
-
hex #00CED1
Declaration
Swift
public static let darkTurquoise: Color
-
hex #9400D3
Declaration
Swift
public static let darkViolet: Color
-
hex #FF1493
Declaration
Swift
public static let deepPink: Color
-
hex #00BFFF
Declaration
Swift
public static let deepSkyBlue: Color
-
hex #696969
Declaration
Swift
public static let dimGray: Color
-
hex #696969
Declaration
Swift
public static let dimGrey: Color
-
hex #1E90FF
Declaration
Swift
public static let dodgerBlue: Color
-
hex #B22222
Declaration
Swift
public static let fireBrick: Color
-
hex #FFFAF0
Declaration
Swift
public static let floralWhite: Color
-
hex #228B22
Declaration
Swift
public static let forestGreen: Color
-
hex #FF00FF
Declaration
Swift
public static let fuchsia: Color
-
hex #DCDCDC
Declaration
Swift
public static let gainsboro: Color
-
hex #F8F8FF
Declaration
Swift
public static let ghostWhite: Color
-
hex #FFD700
Declaration
Swift
public static let gold: Color
-
hex #DAA520
Declaration
Swift
public static let goldenRod: Color
-
hex #808080
Declaration
Swift
public static let gray: Color
-
hex #808080
Declaration
Swift
public static let grey: Color
-
hex #008000
Declaration
Swift
public static let green: Color
-
hex #ADFF2F
Declaration
Swift
public static let greenYellow: Color
-
hex #F0FFF0
Declaration
Swift
public static let honeyDew: Color
-
hex #FF69B4
Declaration
Swift
public static let hotPink: Color
-
hex #CD5C5C
Declaration
Swift
public static let indianRed: Color
-
hex #4B0082
Declaration
Swift
public static let indigo: Color
-
hex #FFFFF0
Declaration
Swift
public static let ivory: Color
-
hex #F0E68C
Declaration
Swift
public static let khaki: Color
-
hex #E6E6FA
Declaration
Swift
public static let lavender: Color
-
hex #FFF0F5
Declaration
Swift
public static let lavenderBlush: Color
-
hex #7CFC00
Declaration
Swift
public static let lawnGreen: Color
-
hex #FFFACD
Declaration
Swift
public static let lemonChiffon: Color
-
hex #ADD8E6
Declaration
Swift
public static let lightBlue: Color
-
hex #F08080
Declaration
Swift
public static let lightCoral: Color
-
hex #E0FFFF
Declaration
Swift
public static let lightCyan: Color
-
hex #FAFAD2
Declaration
Swift
public static let lightGoldenRodYellow: Color
-
hex #D3D3D3
Declaration
Swift
public static let lightGray: Color
-
hex #D3D3D3
Declaration
Swift
public static let lightGrey: Color
-
hex #90EE90
Declaration
Swift
public static let lightGreen: Color
-
hex #FFB6C1
Declaration
Swift
public static let lightPink: Color
-
hex #FFA07A
Declaration
Swift
public static let lightSalmon: Color
-
hex #20B2AA
Declaration
Swift
public static let lightSeaGreen: Color
-
hex #87CEFA
Declaration
Swift
public static let lightSkyBlue: Color
-
hex #778899
Declaration
Swift
public static let lightSlateGray: Color
-
hex #778899
Declaration
Swift
public static let lightSlateGrey: Color
-
hex #B0C4DE
Declaration
Swift
public static let lightSteelBlue: Color
-
hex #FFFFE0
Declaration
Swift
public static let lightYellow: Color
-
hex #00FF00
Declaration
Swift
public static let lime: Color
-
hex #32CD32
Declaration
Swift
public static let limeGreen: Color
-
hex #FAF0E6
Declaration
Swift
public static let linen: Color
-
hex #FF00FF
Declaration
Swift
public static let magenta: Color
-
hex #800000
Declaration
Swift
public static let maroon: Color
-
hex #66CDAA
Declaration
Swift
public static let mediumAquaMarine: Color
-
hex #0000CD
Declaration
Swift
public static let mediumBlue: Color
-
hex #BA55D3
Declaration
Swift
public static let mediumOrchid: Color
-
hex #9370DB
Declaration
Swift
public static let mediumPurple: Color
-
hex #3CB371
Declaration
Swift
public static let mediumSeaGreen: Color
-
hex #7B68EE
Declaration
Swift
public static let mediumSlateBlue: Color
-
hex #00FA9A
Declaration
Swift
public static let mediumSpringGreen: Color
-
hex #48D1CC
Declaration
Swift
public static let mediumTurquoise: Color
-
hex #C71585
Declaration
Swift
public static let mediumVioletRed: Color
-
hex #191970
Declaration
Swift
public static let midnightBlue: Color
-
hex #F5FFFA
Declaration
Swift
public static let mintCream: Color
-
hex #FFE4E1
Declaration
Swift
public static let mistyRose: Color
-
hex #FFE4B5
Declaration
Swift
public static let moccasin: Color
-
hex #FFDEAD
Declaration
Swift
public static let navajoWhite: Color
-
hex #000080
Declaration
Swift
public static let navy: Color
-
hex #FDF5E6
Declaration
Swift
public static let oldLace: Color
-
hex #808000
Declaration
Swift
public static let olive: Color
-
hex #6B8E23
Declaration
Swift
public static let oliveDrab: Color
-
hex #FFA500
Declaration
Swift
public static let orange: Color
-
hex #FF4500
Declaration
Swift
public static let orangeRed: Color
-
hex #DA70D6
Declaration
Swift
public static let orchid: Color
-
hex #EEE8AA
Declaration
Swift
public static let paleGoldenRod: Color
-
hex #98FB98
Declaration
Swift
public static let paleGreen: Color
-
hex #AFEEEE
Declaration
Swift
public static let paleTurquoise: Color
-
hex #DB7093
Declaration
Swift
public static let paleVioletRed: Color
-
hex #FFEFD5
Declaration
Swift
public static let papayaWhip: Color
-
hex #FFDAB9
Declaration
Swift
public static let peachPuff: Color
-
hex #CD853F
Declaration
Swift
public static let peru: Color
-
hex #FFC0CB
Declaration
Swift
public static let pink: Color
-
hex #DDA0DD
Declaration
Swift
public static let plum: Color
-
hex #B0E0E6
Declaration
Swift
public static let powderBlue: Color
-
hex #800080
Declaration
Swift
public static let purple: Color
-
hex #663399
Declaration
Swift
public static let rebeccaPurple: Color
-
hex #FF0000
Declaration
Swift
public static let red: Color
-
hex #BC8F8F
Declaration
Swift
public static let rosyBrown: Color
-
hex #4169E1
Declaration
Swift
public static let royalBlue: Color
-
hex #8B4513
Declaration
Swift
public static let saddleBrown: Color
-
hex #FA8072
Declaration
Swift
public static let salmon: Color
-
hex #F4A460
Declaration
Swift
public static let sandyBrown: Color
-
hex #2E8B57
Declaration
Swift
public static let seaGreen: Color
-
hex #FFF5EE
Declaration
Swift
public static let seaShell: Color
-
hex #A0522D
Declaration
Swift
public static let sienna: Color
-
hex #C0C0C0
Declaration
Swift
public static let silver: Color
-
hex #87CEEB
Declaration
Swift
public static let skyBlue: Color
-
hex #6A5ACD
Declaration
Swift
public static let slateBlue: Color
-
hex #708090
Declaration
Swift
public static let slateGray: Color
-
hex #708090
Declaration
Swift
public static let slateGrey: Color
-
hex #FFFAFA
Declaration
Swift
public static let snow: Color
-
hex #00FF7F
Declaration
Swift
public static let springGreen: Color
-
hex #4682B4
Declaration
Swift
public static let steelBlue: Color
-
hex #D2B48C
Declaration
Swift
public static let tan: Color
-
hex #008080
Declaration
Swift
public static let teal: Color
-
hex #D8BFD8
Declaration
Swift
public static let thistle: Color
-
hex #FF6347
Declaration
Swift
public static let tomato: Color
-
hex #40E0D0
Declaration
Swift
public static let turquoise: Color
-
hex #EE82EE
Declaration
Swift
public static let violet: Color
-
hex #F5DEB3
Declaration
Swift
public static let wheat: Color
-
hex #FFFFFF
Declaration
Swift
public static let white: Color
-
hex #F5F5F5
Declaration
Swift
public static let whiteSmoke: Color
-
hex #FFFF00
Declaration
Swift
public static let yellow: Color
-
hex #9ACD32
Declaration
Swift
public static let yellowGreen: Color


Tagged Questions
Scala is a general purpose programming language principally targeting the Java Virtual Machine. Designed to express common programming patterns in a concise, elegant, and type-safe way, it fuses both imperative and functional programming styles. Its key features are: advanced static type system ...
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request-reply with akka-camel and ActiveMQ
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val ...
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If I load my database connection pool does it affect the main netty thread?
Say I have a action method that connects to the database like this:
@Singleton
class Users @Inject()(userService: UserService) extends Controller {
def dbtest = Action {
val user = ...
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after installing java, scala scalding on OSX i have the following error when i try to run the WordCountJob file
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Kafka Consumer not consuming full message
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Generating all possible combinations from a List[List[Int]] in Scala
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5
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Java 8 parallel sorting vs Scala parallel sorting
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You have just installed RBlog. RBlog is a modern blog engine with elements of social network, written with Ruby On Rails. If you have any questions, please mail to<EMAIL_ADDRESS>or to<EMAIL_ADDRESS>After installation RBlog created a default user for you. Here are credentials.
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In this chapter we will learn about some standard probability distributions and how to generate random samples from them.
We will consider the following distributions
In R we use the following syntax while dealing with a distribution
The Binomial distribution has the following probability function.
\[ P(X=x)={}^nC_x p^x q^{n-x} \] \[x=0,1,2,3,...,n ; q=1-p\] Here n and p are the parameters of the distribution. n is the size or number of times any experiment is repeated and p is the probability of success.
Note: Binomial distribution is applicable only when the experiment or information under consideration can result in two distinct outcomes. Say, Pass and Fail, Dead or alive etc.
R has four in-built functions to generate binomial distribution. They are described below.
dbinom(x, size, prob)
pbinom(x, size, prob)
qbinom(p, size, prob)
rbinom(n, size, prob)
Following is the description of the parameters used −
x is a vector of numbers.
p is a vector of probabilities.
n is number of observations.
size is the number of trials.
prob is the probability of success of each trial.
dbinom()
This function gives the probability density distribution at each point.
# Create a sample of 30 numbers
# which are incremented by 1.
<- seq(0, 30, by = 1)
x
# Create the binomial distribution.
<- dbinom(x, 30, 0.5)
y
# Plot the graph for this sample.
plot(
x,
y,main = "Density of Binomial Distribution",
ylab = "Probabilities",
xlab = "Number of Successes",
type = "o"
)
pbinom()
This function gives the cumulative probability of an event. It is a single value representing the probability.
# Probability of getting 25 or less heads
# from a 50 tosses of a coin.
= pbinom(25, 50, 0.5)
x x
[1] 0.5561376
= seq(0, 50, 1)
x = pbinom(x, 50, 0.5)
y plot(
x,
y,main = "Distribution Function",
ylab = "Probabilities",
xlab = "Less than x successes",
type = "o"
)
This function takes the probability value and gives a number whose cumulative value matches the probability value.
# How many heads will have a probability
# of 0.25 will come out when a coin
# is tossed 51 times.
<- qbinom(0.25, 51, 1 / 2)
x x
[1] 23
rbinom()
This function generates required number of random values of given probability from a given sample.
# Find 20 random values from a sample of
# 150 with probability of 0.4.
<- rbinom(20, 150, .4)
x x
[1] 62 49 59 57 60 58 60 68 59 62 55 55 60 66 63 70 65 59
[19] 59 62
hist(x)
Let us consider the following example-
A coin is tossed 20 times. What is the probability that you will get 10 heads? Assuming the coin is fair.
Solution:
Let us consider getting a head as success. Here, n=20 and since the coin is fair, hence p= Probability of getting a head is 1/2 = 0.5
Now, we need to find out
\[P(\text{10 successes}) = {}^{20}C_{10} (0.5)^{10}(1-0.5)^{(20-10)}\] This can be done using the following R program
dbinom(10, 20, 0.5)
[1] 0.1761971
Hence from calculation we see that the probability of 10 successes is 0.1761971.
If we are interested in getting the probability of getting at less than 10 successes, then we can use pbinom
pbinom(10, 20, 0.5)
[1] 0.5880985
Now let us try to generate a random sample from the above example.
= rbinom(30, 20, 0.5)
sample sample
[1] 9 11 9 10 12 7 13 9 12 9 9 10 13 12 9 12 14 10
[19] 11 9 9 12 8 11 7 8 8 8 7 11
hist(sample, main = "Binomial distribution")
\[ P(X=x) = \dfrac{e^{-\lambda}\lambda^x}{x!} \\ x=0,1,2,...\] Here, \(\lambda\) is the parameter of the distribution.
R has four in-built functions to generate Poisson distribution. They are described below.
dpois(x, lambda)
ppois(q, lambda)
qpois(p, lambda)
rpois(n, lambda)
Following is the description of the parameters used −
dpois()
This function gives the probability density distribution at each point.
# Create a sample of 30 numbers
# which are incremented by 1.
<- seq(0, 30, by = 1)
x
# Create the binomial distribution.
<- dpois(x, 2)
y
# Plot the graph for this sample.
plot(
x,
y,main = "Density of Poisson Distribution",
ylab = "Probabilities",
xlab = "Number of events",
type = "o"
)
ppois()
This function gives the cumulative probability of an event. It is a single value representing the probability.
# Probability of getting 25 or less
# heads from a 50 tosses of a coin.
= ppois(5, 2)
x x
[1] 0.9834364
= seq(0, 50, 1)
x = ppois(x, 2)
y plot(
x,
y,main = "Distribution Function",
ylab = "Probabilities",
xlab = "Less than x occurances",
type = "o"
)
qpois()
This function takes the probability value and gives a number whose cumulative value matches the probability value.
<- qpois(0.5,2)
x x
[1] 2
This function is used to generate random numbers whose distribution is normal. It takes the sample size as input and generates that many random numbers. We draw a histogram to show the distribution of the generated numbers.
# Create a sample of 100 numbers
# which are Poisson distributed.
<- rpois(100, lambda = 2)
y
# Plot the histogram for this sample.
hist(y, main = "Poisson DIstribution",
xlab = "Values")
Let us consider the following example
The number of misprints per page in a book of 300 pages follows Poisson distribution with parameter 2. Find the probability of getting exacty 4 misprints in a page. Also find out the probability of getting less than 5 misprints.
Solution:
Given,
\(\lambda\) = 2 We are to find \(P(X=4) = \dfrac{e^{-2}2^4}{4!}\)
This can be done in R as
# the probability of 4 misprints
dpois(4, 2)
[1] 0.09022352
# the probability of getting less than 5 misprints
ppois(5, 2)
[1] 0.9834364
A random sample from Poisson distribution can be generated using the syntax
rpois(size= ,lambda= )
For example let us generate a random sample of size 30 from a Poisson population with parameter 2
rpois(30,2)
[1] 4 1 2 0 3 1 3 1 1 2 1 1 2 2 0 1 3 5 0 3 5 3 1 2 5 5 1 1
[29] 1 1
The normal distribution has the following probability function:
\[f(x)=\dfrac{1}{\sigma\sqrt{2\pi}}e^{-\dfrac{(x-\mu)^2}{2\sigma^2}} \\ -\infty<x,\mu<\infty\\ \sigma^2 \ge 0 \]
Here, \(\mu\) and \(\sigma\) are the parameters of the distribution. \(\mu\) is the mean, and \(\sigma\) is the standard deviation of the distribution.
In a random collection of data from independent sources, it is generally observed that the distribution of data is normal. Which means, on plotting a graph with the value of the variable in the horizontal axis and the count of the values in the vertical axis we get a bell shape curve. The center of the curve represents the mean of the data set. In the graph, fifty percent of values lie to the left of the mean and the other fifty percent lie to the right of the graph. This is referred as normal distribution in statistics.
R has four in built functions to generate normal distribution. They are described below.
dnorm(x, mean, sd)
pnorm(x, mean, sd)
qnorm(p, mean, sd)
rnorm(n, mean, sd)
Following is the description of the parameters used in above functions −
x is a vector of numbers.
p is a vector of probabilities.
n is number of observations(sample size).
mean is the mean value of the sample data. It’s default value is zero.
sd is the standard deviation. It’s default value is 1.
dnorm()
This function gives height of the probability distribution at each point for a given mean and standard deviation.
# Create a sequence of numbers between
# -10 and 10 increasing by 0.1.
<- seq(-10, 10, by = .1)
x
# Choose the mean as 2.5 and standard
# deviation as 0.5.
<- dnorm(x, mean = 0, sd = 2)
y
# Plot the density curve
plot(
x,
y,main = "Density curve for normal distribution",
xlab = "Values",
ylab = "Probability",
type = "h"
)
pnorm()
This function gives the probability of a normally distributed random number to be less that the value of a given number. It is also called “Cumulative Distribution Function”.
# Create a sequence of numbers between
# -10 and 10 increasing by 0.2.
<- seq(-10, 10, by = .2)
x
# Choose the mean as 2.5 and standard
# deviation as 2.
<- pnorm(x, mean = 2.5, sd = 2)
y
# Plot the graph.
plot(
x,
y,main = "Distribution curve for normal distribution",
xlab = "Values",
ylab = "Probabilities",
type = "o"
)
qnorm()
This function takes the probability value and gives a number whose cumulative value matches the probability value. It gives the area under normal curve.
# Create a sequence of probability values
# incrementing by 0.01.
<- seq(0, 1, by = 0.01)
x
# Choose the mean as 2 and standard
# deviation as 3.
<- qnorm(x, mean = 2, sd = 1)
y
# Plot the graph.
plot(
x,
y,type = "o",
xlab = "Probabilities",
ylab = "Values",
main = "Area under normal curve"
)
rnorm()
This function is used to generate random numbers whose distribution is normal. It takes the sample size as input and generates that many random numbers. We draw a histogram to show the distribution of the generated numbers.
# Create a sample of 100 numbers which
# are normally distributed.
<- rnorm(100, mean = 2, sd = 2)
y
# Plot the histogram for this sample.
hist(y, main = "Normal DIstribution",
xlab = "Values")


Course Outline: Each of the students should complete the software project separately. They will be marked based on their individual software. Student will be encouraged to develop software which requires significant “problem solving” effort. The project should be sufficiently large and the size of the project will mostly depend on “problem solving” effort. Besides, students must showcase the skills they have acquired from their so far completed courses.


Relative path to debug symbols. Supports variable substitution.
For example: three/days/casey.apk or three/days/${SYMBOLS}.apk
three/days/casey.apk
three/days/${SYMBOLS}.apk


Linkrot helps you scan pdfs for links written in plaintext and check if they are active. It then generates a report of its findings with references (pdf, url, doi, arxiv) and metadata from the PDF.
LINK: