hess-corporation
Businessmodel of Hess Corporation
Customer Segments
Hess provides a range of products and services to commercial customers operating primarily in the oil and gas sector. The Company’s two operating segments serve different customers segments:
- Exploration and Production, which sells crude oil, natural gas, and natural gas liquids to companies operating across the automotive, aviation, chemicals processing, refining, and fuel and lubricants markets, among others;
- Bakken Midstream, which provides a range of midstream services to various industrial customers, including oil and natural gas producers, natural gas liquid and natural gas gathering and processing companies, propane distributors, ethanol producers, petrochemical and refining companies, natural gas distribution companies, electric-generation facilities, large industrial companies, and marketing companies. Hess also serves certain government bodies, including municipal, state, and federal organisations. The Company does not name any of its major clients on its website.
Hess principally provides products and services to customers in its domestic market of the US. The Company also serves clients across three other geographic categories: Africa, Europe, and Asia and Other Countries.
Value Propositions
Hess provides value to its customers in the following ways:
- Its industry standing and track record, with the Company established as a reliable and efficient supplier of crude oil, natural gas, and natural gas liquids, as well as related services, having a positive reputation within the oil and gas industry
- Its portfolio of products and services, with the Company providing services to a broad spectrum of industries, including processing, fractionation, terminaling and loading, and transportation services;
- Its international reach, with the Company serving an extensive customer base in the US, as well as an international network of clients across Africa, Europe, and Asia, as well as in certain other jurisdictions;
- Its technology and processes, with the Company employing state-of-the-art processes and technologies across its operating segments and facilities to ensure that it is able to provide effective and reliable services to its customers; and
- Its industry expertise and experience, with the Company employing specialist technical personnel across its operating segments and facilities, as well as a team of experienced industry executives. ### Channels
Hess operates a website at www.hess.com, through which it provides information on its various products, services, and operating locations. The Company does not operate an online sales channel, nor does it provide customers with an online customer portal.
Hess operates an in-house direct sales force, which is organised by geographic region and operating department. These sales personnel deal directly with the Company’s customers and operate of the Company’s international network of office, including its principal offices in New York, Houston, and Kuala Lumpur, as well as an international network of local and regional offices spanning the Americas, Africa, Europe, and Asia. Hess’s Bakken Midstream segment provides services directly to customers through its own dedicated sales and service teams.
Hess operates its own exploration and production assets, primarily across the US, Europe, and Africa, as well as parts of Asia and Latin America. The Company also operates its own processing and distribution infrastructure, including various refining, terminaling, storage, pipeline, and distribution facilities around the world.
Customer Relationships
Hess does not provide products and services to its customers on a self-service basis. The Company makes its sales through its own in-house sales personnel, who consult directly with clients in order to fully ascertain their individual needs and conditions. The Company works closely with its large commercial clients, seeking to establish longstanding relationships and secure recurring business.
Hess provides support to its customers through dedicated account management teams and account executives, who serve as the first point of contact. The Company also provides contact details for all of its offices around the world, enabling customers to contact the relevant offices with queries and concerns. New and existing customers can also make enquires with the Company through an online contact form.
Additionally, Hess provides a range of online support resources. This includes media, news coverage, project information, and sustainability information. Customers can also follow the Company’s operations, and interact with staff directly, through its social media accounts, including with Facebook, Twitter, LinkedIn, and YouTube
Key Activities
Hess is an oil and gas exploration and production company. The Company is engaged in exploration, development, production, transportation, processing, and the purchase and sale of crude oil, natural gas liquids, and natural gas.
Hess operates through two reportable business segments: Exploration and Production, which is engaged in the sale of crude oil, natural gas liquids and natural gas; and Bakken Midstream, which provides services, including crude oil and natural gas gathering, processing, fractionation of natural gas liquids, transportation of crude oil by rail car, terminaling and loading crude oil and natural gas liquids, and the storage and terminaling of propane, primarily through facilities located in the Bakken shale play of North Dakota.
Hess has production operations located in the US, Denmark, Equatorial Guinea, the Joint Development Area of Malaysia and Thailand, Malaysia and Norway, and serves an international customer base.
Key Partners
Hess works in conjunction with a range of companies and organisations that support and supplement the Company’s services across its operating segments. These partners can be categorised broadly as:
- Supplier and Vendor Partners, including suppliers of materials, equipment, services tools, and technologies that are used in the Company’s various production, processing, and distribution operations;
- Manufacturing and Contracting Partners, including oil and gas production companies and other contracting firms that work with the Company on various production projects around the world;
- Joint Venture Partners, including oil and gas companies across the production and distribution chain with which the Company jointly provides services and products through mutually owned entities; and
- Sustainability and Community Partners, including various non-profits and charitable organisations, with which the Company collaborates on sustainability and community projects worldwide. Hess has a number of joint venture partnerships in place, including a 50/50 operation with a subsidiary of Petroleos de Venezuela SA. The Company has also recently partnered with Exxon Mobil on an exploration project, and agreed a farm-out deal with Kosmos Energy in Suriname.
Key Resources
Hess’s key resources are its materials and supply chains, its operating and exploration licenses and permits, its exploration and production equipment and infrastructure, its midstream and distribution infrastructure, its sales channels, its partnerships, and its personnel.
Hess owns and or leases a range of physical properties and facilities around the world that are key to its ongoing activities. This notably includes its production and exploration assets, as well as its network of offices, its pipeline network, its processing and refining facilities, its storage and distribution centres, its terminaling infrastructure, and its rail loading facilities.
Despite its use of technology and state-of-the-art equipment, searches of records published by the US Patent and Trademark Office identified no patent applications filed in Hess’s name.
Cost Structure
Hess incurs costs in relation to the procurement of materials and equipment – including the purchase of crude oil, the operation of its exploration and production assets, the operation of it midstream and distribution infrastructure, the operation of its sales channels, the management of its partnerships, and the retention of its personnel.
In 2015 Hess recorded cost of products sold in the amount of $1.29 billion and total operating costs and expenses in the amount of $2.03 billion. The Company also accrued exploration costs totalling $881 million and general and administrative costs in the amount of $557 million.
Revenue Streams
Hess generates revenue through the operation of oil and gas exploration and production assets, as well as midstream and distribution services. The Company’s revenue can be divided into two principal streams:
- Sales revenue derived from the sale of crude oil, natural gas, and natural gas liquids; and
- Service revenue derived from long-term, fee-based service agreements for its midstream services. In 2015 Hess generated annual revenue of $6.64 billion, down on the $10.74 billion recorded by the Company in 2014. The Company attributed this to reduced drilling activity and divestment of certain assets. The majority of the Company’s revenue, around $5.90 billion, was generated through the sale of Crude oil and natural gas liquids, with natural gas sales accounting for just $1.05 billion.


Good and Bad Design Principles
1. Chunking
Good: http://www.buzzfeed.com/tag/lists
- I think BuzzFeed does an excellent job with chunking. Most of their articles contain lists, which are easier to read for a user. People have short attention spans and want their information to be short and sweet.
Bad: http://www.theatlantic.com/features/archive/2014/09/searching-for-the-good-life-in-the-bakken-oil-fields/380677/?src=longreads
- Here we have a very long story that takes several minutes to read. Usually, people don’t have the time or patience for that. The information is split up into paragraphs and that is it. The paragraphs do not function without the other, so there is no quick read here.
2. Signal to Noise Ratio
Good: http://www.wolframalpha.com/
- This computational tool is aesthetically pleasing and displays the information you want in an effective way. Usually, when doing math problems, it computes extra graphs and results, but they’re useful and are appropriately labeled.
Bad: http://wiki.answers.com/Q/Does_stock_have_a_low_or_high_risk
- I think Wiki Answers does a terrible job at displaying information. I have an ad blocker, and even with that there is a ton of irrelevant information, which is completely unrelated to what you’re asking.
3. Hick's Law
Good: http://45royale.com/company/
- This website does a good job at lessening the amount of options a user has. It is simple and aesthetically pleasing. The options for the user are clear, and the website can be easily navigated.
Bad: http://www.cnn.com/
- I think there is too much going on here.  There appear to be two main menus, each with several options. The sidebars are also too complex.
4. Ockham’s Razor
Good: http://pollenlondon.com/
- This website is simple, functional, and aesthetically pleasing. The menu options are displayed when you hover over a photo.  First of all, the menu options are bunched, and don’t show the entire title of the menu. Second, when you hover over the menu, more options appear that don’t go away until you hover over the menu option again. There is also a ton of clustered pictures that make this website more complicated than it has to be.
5. Mapping
Good: http://www.netflix.com
- I think Netflix has great controls. Pretty simple: pause, play, next episode, fast forward, etc. It’s also very easy to see an episode list for a show, or pick a specific season for a show. The layout is clear and very user friendly.
Bad: http://www.arngren.net/
- This website is just a mess. Who could possibly navigate this? It’s clustered and confusing to anyone. No one would know where to click or where to go. Clicking on a number which I assume is a price takes you to an equally convoluted page.


"My wife and I noticed what we thought was a star. It then started moving up and down, side to side and at 90 degree angles," reads a September report marked as coming from Hastings, Minn. "I have never seen anything like this before."
"I was driving to work early in the morning and noticed double-layered lights surrounding a massive circular object in the sky around 494 and Minnetonka Blvd," reads another from Minnetonka in August.
“Just got home from buying a dirt bike for my kids and took it for a drive in the dark to the end of the driveway,” described another from Mora in June, “I saw a fireball looking circle moving around slightly about a half mile away, about 60 ft up, it just suddenly disappeared.”
Nearly a hundred times each year, Minnesotans file reports of suspected UFO encounters with a volunteer organization known as the National UFO Reporting Center, which makes them available to be searched online.
Extraterrestrial encounters have been creeping back into the zeitgeist this year, with the U.S. Navy acknowledging the existence of mysterious flying objects in September. Soon after, thousands of revelers descended on Area 51 as part of a viral stunt that began on Facebook.
Meanwhile, Minnesotans have been quietly celebrating the 40th anniversary of the state’s most famous encounter, and scientists and media outlets paying closer attention to out-of-this-world sightings.
“People are looking up in the sky, people are watching and they know to report what they see,” said Tom Maher, Minnesota State Director of the Mutual UFO Network, one of the world's oldest and largest organizations of paranormal enthusiasts, which also collects local encounters.
About half of Minnesota’s roughly UFO 1,700 sightings since the 1940s have taken place in this decade – perhaps in part because the skies are increasingly becoming crowded with drones, planes, weather balloons, and other objects that might be confused with alien technology.
These reports are collected by the National UFO Reporting Center, a Washington-based organization that has investigated UFOs for nearly a half century. The Center also flags apparent hoaxes or incidents that could have simple explanations, like casino advertising lights, lens flares or satellites sweeping through night skies.
But not everything is so readily explainable, with even the Pentagon struggling to account for every strange object spotted by its pilots. In recently released videos, Navy pilots have reported seeing oddly shaped aircraft traveling at hypersonic speeds — which, so far, have defied clear explanation.
“They’re not swamp gas, they’re not balloons, they’re something they can’t explain,” said Mike Harris, a field investigator in Minnesota’s chapter of the Mutual UFO Network, whose role involves parsing everyday phenomena from the unknown.
Floating lights, circles, triangles and spheres are the most commonly submitted reports from Minnesotans. Sightings purportedly last anywhere from one second to over an hour.
Harris said paranormal activity in television shows have drawn more people’s interest to the unexplained, and acknowleged the use of drones by hobbyists and governments could also be behind some incidents.
Maher described himself as a skeptic, but not a cynic, and keeps himself open to possibilities of alien life, while acknowledging many UFO sightings have other plausible explanations.
Maher said the Mutual UFO Network collects a separate set of privately submitted local reports, but that the group's investigators sometimes consult what appears in the National UFO Reporting Center's public database online.
Both Harris and Maher have been involved with the network for years. The group holds monthly meetups in New Brighton, where attendees with talk about their experiences, show videos and listen to guest speakers on a wide array of topics.
Meanwhile, government agencies and research institutions continue to cast their electronic eyes upon the skies looking for signs we aren't alone in the universe. And earlier this year, the SETI Institute released a new database of searches for signs of extraterrestrial life since 1960.
“There’s so much in the universe we don’t understand,” Maher said. “We can start going down the rabbit hole and never stop.”


By filling out the profile information below you help us learn more fully about the individuals who make pledges and what factors those individuals use to decide. As a community we can grow richer by learning together.
In that spirit, all of the profile information is optional. We invite you to provide as much of the information as you are comfortable offering us. Your information is confidential - we will only ever show your information to you. We will use the collective pool of information to generate statistics about different groups of people and how much money they give.


Central Processor Job introduces build windows and central processor for Jenkins builds.
The job contains two parts configurations. Build Window and Central Processor Build.
Build windows can be configured in Jenkins Global Configuration page.A central processor job can apply one or more the build windows.The build request will be controlled by build window. If the all the applied windows are closed, the build requests will be queued.When any applied window is open, all queued requests will be fired.
If the Central processor is applied, queued build requests will be grouped into one or more central processor build based on the selected processor(DefaultProcessor or GroupBuildProcessor).


Class Lane
public class Lane
extends java.lang.Object
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Field Summary
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Constructor Summary
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Method Summary
Modifier and Type Method Description int
getLeftBoundary()
Gets the lane's left boundary.int
getObstacleLimit()
Gets the obstacle limitjava.util.ArrayList<Obstacle>
getObstacles()
Gets the list of obstacle in a laneint
getRightBoundary()
Gets the lane's right boundary.int
getTotalObstacles()
Gets the total number of obstaclesvoid
RemoveObstacle(Obstacle obstacle)
Removes obstacle from obstacle list.void
RemovePowerUp(PowerUp powerUp)
Removes power-up from powerUps list.void
SpawnObstacle(int x, int y, java.lang.String obstacleType)
Spawns obstacle in the lane.void
SpawnPowerUp(int x, int y, java.lang.String powerUpType)
Spawns power-ups in the lane.Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Field Details
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obstacles
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powerUps
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Constructor Details
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Lane
public Lane(int leftBoundary, int rightBoundary)Creates a lane instance.- Parameters:
leftBoundary
- X-position for the left boundary of the lane.rightBoundary
- X-position for the right boundary of the lane.
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Lane
public Lane(int leftBoundary, int rightBoundary, int obstacleLimit)Creates a lane instance.- Parameters:
leftBoundary
- X-position for the left boundary of the lane.rightBoundary
- X-position for the right boundary of the lane.obstacleLimit
- Limit for the number of obstacles in the lane.
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Method Details
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SpawnObstacle
public void SpawnObstacle(int x, int y, java.lang.String obstacleType)Spawns obstacle in the lane.
Spawns specified obstacle in the lane. Checks that the obstacle limit hasn't been reached, if not checks the obstacle type for Goose or Log and instantiates it as the corresponding obstacle, with the correct texture. Then adds it to the Lane's obstacle list.
- Parameters:
x
- X-position for the obstacle spawn location.y
- Y-position for the obstacle spawn location.obstacleType
- Obstacle type.
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SpawnPowerUp
public void SpawnPowerUp(int x, int y, java.lang.String powerUpType)Spawns power-ups in the lane.
Spawns specified power-up in the lane. Checks that the obstacle limit hasn't been reached, if not checks the obstacle type for Invincibility, repair, TimeReduction, Maneuverability or Acceleration and instantiates it as the corresponding power-up, with the correct texture. Then adds it to the Lane's power-ups list.
- Parameters:
x
- X-position for the obstacle spawn location.y
- Y-position for the obstacle spawn location.powerUpType
- Power-up type.
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RemoveObstacle
Removes obstacle from obstacle list.
Obstacle should be removed upon collision with boat or leaving the course. area.
- Parameters:
obstacle
- Obstacle to be removed.
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RemovePowerUp
Removes power-up from powerUps list.
PowerUps should be removed upon collision with boat or leaving the course. area.
- Parameters:
powerUp
- PowerUp to be removed.
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getLeftBoundary
public int getLeftBoundary()Gets the lane's left boundary.- Returns:
- Int representing the x-position of the lane's left boundary.
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getRightBoundary
public int getRightBoundary()Gets the lane's right boundary.- Returns:
- Int representing the x-position of the lane's right boundary.
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getObstacleLimit
public int getObstacleLimit()Gets the obstacle limit- Returns:
- Int representing the maximum number of obstacles in a lane.
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getTotalObstacles
public int getTotalObstacles()Gets the total number of obstacles- Returns:
- Int representing the total number of obstacles in a lane.
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getObstacles
Gets the list of obstacle in a lane- Returns:
- ArrayList containing all the obstacles in a lane.
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Welcome to our App!
This Application will help you get more likes/followers/views and comments.
You can try our FREE promo for likes by clicking the banner on top
or you can go to Market section and get all our services
For any problem with orders,contact ASAP with us to our email
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--- layout: page weight: 0 title: Event Notification navigation: show: true ---
The Event Notification App controls webhook notifications for events, such as bounces, clicks, opens, and more. This App allows these events to be POSTed to a URL of your choosing.
{% info %} You can read more about the Event Notification service. {% endinfo %} {% anchor h2 %} Settings {% endanchor %}| Name | Required | Description |
|---|---|---|
| Emails are "x" | As needed | Enables the selected notifications. |
| Post Event URL | Yes | Sets the entered URL as the target of notification posts. |
Settings may be changed through:


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Overview
Package
Class
Deprecated
Index
Help
Frames
No Frames
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
Y
Z
_
A
accountExpired
- Property in
User
accountLocked
- Property in
User
addToFragments(ArrayList, SortedSet)
- Method in
XmlDatabasePopulator
allowedMethods
- Property in
AtomController
allowedMethods
- Property in
MoleculeController
allowedMethods
- Property in
ReactionController
assignStartAndEndNums(int, int)
- Method in
XyzFileCreator
Atom
- Class in
reaktor
Defines an atom
Atom()
- Constructor in
Atom
AtomController
- Class in
reaktor
AtomController()
- Constructor in
AtomController
authority
- Property in
Role
B
beforeInsert()
- Method in
User
beforeUpdate()
- Method in
User
belongsTo
- Property in
Atom
belongsTo
- Property in
Molecule
belongsTo
- Property in
Reaction
BootStrap
- Class in
BootStrap
BootStrap()
- Constructor in
BootStrap
C
calculate()
- Method in
CalculateController
CalculateController
- Class in
reaktor
CalculateController()
- Constructor in
CalculateController
calculateProduct(def, User, Populator)
- Method in
ProductCalculatorService
Displays lowest energy product from given input
checkIsFile(def)
- Method in
XmlDataParser
clean(Reaction)
- Method in
ReactionController
completeMoleculeProperties(Molecule)
- Method in
XmlDatabasePopulator
constraints
- Property in
Atom
constraints
- Property in
Molecule
constraints
- Property in
Reaction
constraints
- Property in
Role
constraints
- Property in
User
constraints
- Property in
UserRole
create()
- Method in
AtomController
create()
- Method in
MoleculeController
create()
- Method in
ReactionController
create(User, Role, boolean)
- Method in
UserRole
createAtomFromXml(def)
- Method in
XmlDatabasePopulator
createAtomFromXyz(Collection, Molecule)
- Method in
XyzDatabasePopulator
createCombinedFileArray(List, File, List)
- Method in
XyzFileCreator
createElementMap()
- Method in
Molecule
createFile(def, def)
- Method in
DefineFileCreator
Creates turbomole define file in specified path
createFile(def, def)
- Method in
FileCreator
createFile(def, def)
- Method in
XyzFileCreator
Creates xyz file from given molecule in productCalculatorService filePath.
createFilesFromMultipleFiles(Reaction)
- Method in
DefineFileCreator
createFilesFromMultipleFiles(Reaction)
- Method in
FileCreator
createFilesFromMultipleFiles(Reaction)
- Method in
XyzFileCreator
Merges more than two molecule xyz files into numFilesToMake for calculation.
createInputFiles(def)
- Method in
ProductCalculatorService
createMessageString()
- Method in
ProductCalculatorService
createMoleculeFromXml()
- Method in
XmlDatabasePopulator
createMoleculeFromXyz(File)
- Method in
XyzDatabasePopulator
createMoleculeName()
- Method in
Molecule
Creates a name for the molecule
createProjectFilePath()
- Method in
ProductCalculatorService
createReaction(ArrayList, User)
- Method in
ProductCalculatorService
createTwoXyzFiles()
- Method in
ProductCalculatorService
createXyzDisplayFile(Reaction)
- Method in
XyzFileCreator
Creates an xyz file with spacing to be used in the jquery tables
D
dateCreated
- Property in
Reaction
defaultFolder
- Property in
CalculateController
defaultFolder
- Property in
ListenerService
defaultFolder
- Property in
OBabelWrapper
defaultFolder
- Property in
ProductCalculatorService
defaultFolder
- Field in
XyzDatabasePopulator
defaultFolder
- Field in
XyzFileCreator
DefineFileCreator
- Class in
reaktor.fileCreator
Creates a "define.inp" file to be used by turbomole.
DefineFileCreator()
- Constructor in
DefineFileCreator
defineFileCreator
- Property in
ProductCalculatorService
delete(Atom)
- Method in
AtomController
delete(Molecule)
- Method in
MoleculeController
delete(Reaction)
- Method in
ReactionController
destroy
- Property in
BootStrap
E
edit(Atom)
- Method in
AtomController
edit(Molecule)
- Method in
MoleculeController
edit(Reaction)
- Method in
ReactionController
element
- Property in
Atom
elementMap
- Property in
Molecule
email
- Property in
User
enabled
- Property in
User
encodePassword()
- Method in
User
equals(def)
- Method in
UserRole
error(def)
- Method in
CalculateController
errorMessage
- Property in
MessageParser
errorSubject
- Property in
MessageParser
exists(long, long)
- Method in
UserRole
exposes
- Property in
ListenerService
F
FileCreator
- Interface in
reaktor.fileCreator
filePath
- Field in
ProductCalculatorService
finalListCheck(ArrayList)
- Method in
XmlDatabasePopulator
findMatchingMolecule(Molecule)
- Method in
XmlDatabasePopulator
findMaxOrMin(boolean, File, int)
- Method in
XyzFileCreator
finishedMessage
- Property in
MessageParser
finishedSubject
- Property in
MessageParser
G
get(long, long)
- Method in
UserRole
getAuthorities()
- Method in
User
getErrorString(Process)
- Method in
OBabelWrapper
getFileToParse(def)
- Method in
XmlDataParser
getReactants()
- Method in
CalculateController
getUserIndex()
- Method in
ReactionController
H
hashCode()
- Method in
UserRole
hasMany
- Property in
Molecule
hasMany
- Property in
Reaction
hasMany
- Property in
User
I
idInMolecule
- Property in
Atom
index(Integer)
- Method in
AtomController
index()
- Method in
CalculateController
index(Integer)
- Method in
MoleculeController
index(Integer)
- Method in
ReactionController
init
- Property in
BootStrap
J
jmsService
- Property in
ProductCalculatorService
jmsService
- Property in
ReactionController
K
L
lastUpdated
- Property in
Reaction
ListenerService
- Class in
reaktor.services
Listener service for all queues
ListenerService()
- Constructor in
ListenerService
log
- Field in
LoggingAspect
logAround(ProceedingJoinPoint)
- Method in
LoggingAspect
Logs around all public reactor calls.
LoggingAspect
- Class in
reaktor.logging
Logger for reactor
LoggingAspect()
- Constructor in
LoggingAspect
M
mailService
- Property in
MessageParser
mappedBy
- Property in
Reaction
mapping
- Property in
Role
mapping
- Property in
User
mapping
- Property in
UserRole
mappings
- Property in
UrlMappings
MessageParser
- Class in
reaktor.parser
Parses JMS messages
messageParser
- Property in
ListenerService
MessageParser()
- Constructor in
MessageParser
Molecule
- Class in
reaktor
Defines a molecule
Molecule()
- Constructor in
Molecule
MoleculeController
- Class in
reaktor
MoleculeController()
- Constructor in
MoleculeController
molecules
- Field in
XmlDatabasePopulator
moleculeXMLNode
- Field in
XmlDatabasePopulator
N
name
- Property in
Molecule
notFound()
- Method in
AtomController
notFound()
- Method in
MoleculeController
notFound()
- Method in
ReactionController
numFilesToMake
- Field in
XyzFileCreator
O
obabel
- Property in
ListenerService
obabel
- Field in
XyzDatabasePopulator
OBabelWrapper
- Class in
reaktor.wrapper
Wrapper around obabel
OBabelWrapper()
- Constructor in
OBabelWrapper
P
parse(Object)
- Method in
MessageParser
Parses message into file name and file text, then creates and writes to files
parse(def)
- Method in
Parser
parse(Object)
- Method in
XmlDataParser
Parses XML data.
Parser
- Interface in
reaktor.parser
password
- Property in
User
passwordExpired
- Property in
User
populate(Object)
- Method in
Populator
populate(Object)
- Method in
XmlDatabasePopulator
Takes data in the form of nodes from the XMLDataParser class and populates the database with it.
populate(Object)
- Method in
XyzDatabasePopulator
Populates database from an ArrayList of user-input xyz files
populateReactionFolder(String)
- Method in
MessageParser
Populator
- Interface in
reaktor.populator
ProductCalculatorService
- Class in
reaktor.services
Readies files for calculation, then sends them to server.
productCalculatorService
- Property in
CalculateController
productCalculatorService
- Property in
ListenerService
ProductCalculatorService()
- Constructor in
ProductCalculatorService
Q
R
Reaction
- Class in
reaktor
Defines a reaction
reaction
- Property in
MessageParser
reaction
- Field in
ProductCalculatorService
Reaction()
- Constructor in
Reaction
ReactionController
- Class in
reaktor
ReactionController()
- Constructor in
ReactionController
reactionFolder
- Property in
MessageParser
RegisterController
- Class in
reaktor.security
RegisterController()
- Constructor in
RegisterController
remove(User, Role, boolean)
- Method in
UserRole
removeAll(Role, boolean)
- Method in
UserRole
resources
- Class in
spring
resources()
- Constructor in
resources
Role
- Class in
reaktor.security
Role()
- Constructor in
Role
role
- Property in
UserRole
run(Object, Object)
- Method in
OBabelWrapper
Runs obabel converter from smiles to xyz
run(Object, Object)
- Method in
Wrapper
runMentorReactants(def)
- Method in
ListenerService
S
save(Atom)
- Method in
AtomController
save(Molecule)
- Method in
MoleculeController
save(Reaction)
- Method in
ReactionController
saveMolecule(Molecule)
- Method in
XmlDatabasePopulator
sendFiles()
- Method in
CalculateController
sendMailToUser(String)
- Method in
MessageParser
separateInputMolecules()
- Method in
XmlDatabasePopulator
serialVersionUID
- Field in
UserRole
show(Atom)
- Method in
AtomController
show(Molecule)
- Method in
MoleculeController
show(Reaction)
- Method in
ReactionController
springSecurityService
- Property in
CalculateController
springSecurityService
- Property in
ReactionController
springSecurityService
- Property in
User
status
- Property in
Reaction
T
toString()
- Method in
Atom
toString()
- Method in
Molecule
toString()
- Method in
Reaction
toString()
- Method in
User
transients
- Property in
User
U
update(Atom)
- Method in
AtomController
update(Molecule)
- Method in
MoleculeController
update(Reaction)
- Method in
ReactionController
updateReactionWithProducts(def)
- Method in
ListenerService
UploadController
- Class in
reaktor.uploadr
UploadController()
- Constructor in
UploadController
UrlMappings
- Class in
UrlMappings
UrlMappings()
- Constructor in
UrlMappings
User
- Class in
reaktor.security
user
- Property in
Reaction
User()
- Constructor in
User
user
- Property in
UserRole
username
- Property in
User
UserRole
- Class in
reaktor.security
UserRole()
- Constructor in
UserRole
V
W
Wrapper
- Interface in
reaktor.wrapper
X
xCoord
- Property in
Atom
XmlDatabasePopulator
- Class in
reaktor.populator
Populates the database using XML input
XmlDatabasePopulator()
- Constructor in
XmlDatabasePopulator
XmlDataParser
- Class in
reaktor.parser
Parses XML data from file and creates Molecule and Atom instances
XmlDataParser()
- Constructor in
XmlDataParser
XyzDatabasePopulator
- Class in
reaktor.populator
Database populator for xyz files
xyzDatabasePopulator
- Property in
ListenerService
XyzDatabasePopulator()
- Constructor in
XyzDatabasePopulator
XyzFileCreator
- Class in
reaktor.fileCreator
Creates xyz files
xyzFileCreator
- Property in
CalculateController
xyzFileCreator
- Property in
ProductCalculatorService
XyzFileCreator()
- Constructor in
XyzFileCreator
Y
yCoord
- Property in
Atom
Z
zCoord
- Property in
Atom
_
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
Y
Z
_
Overview
Package
Class
Deprecated
Index
Help
Frames
No Frames
Groovy Documentation


{% extends 'planner/base.html' %} {% block title %}{{ project_name }}{% endblock %} {% block body_block %}
No feature currently in this project.
{{ result.summary }}


--- layout: default title: ICMTOD'17 - Keynote Speakers meta: The list of keynote speakers who will be presenting their lectures within the topics of mass transfer at ICMTOD. ---
We are very happy to announce the following keynote speakers for the 2nd International Conference on Mass Transfer Operation and Devices (ICMTOD'17):
Dr. Deborah Kays
Deborah Kays received her MChem (Hons) and PhD degrees in Chemistry from Cardiff University, Wales. After postdoctoral work, also at Cardiff University she took up a Junior Research Fellowship at Merton College, Oxford. She was appointed Lecturer in Inorganic Chemistry at the University of Nottingham in 2007, followed by promotion to Associate Professor in 2014. Her research interests involve the investigation of the synthesis and reactivity of low-coordinate main group and transition metal complexes, with a view to exploring their use in small molecule activation and catalysis.


I'm a certified pharmacy technician in a hospital with rather shoddy inventory control, at least with unscheduled substances such as Soma. Occasionally I'll also come across a stray controlled substance -- in this case, 1 mg clonazepam.
I suffer from major depression and panic disorder, and take 40 mg Prozac a day, plus the occasional mg of Ativan as needed.
 Really, really depressed. I had to do something to cheer myself up before I just crawled into bed and cried all night. I figured this combination could only help. I'd used Soma in the past, but this was my first experience with Klonopin. After eating something to prevent stomach irritation I tend to get, I took two 350 mg tabs of Soma. As for the Klonopin, I started small, approximately 1/4th the tab, crushed and snorted over the course of several minutes. Not unpleasant. Shortly after, my nose felt very cold, almost as if I had snorted snow. Odd, but not painful or worrisome. I would guess it was local vasoconstriction, and thus would not recommend snorting this regularly. Any drip was virtually tasteless.
From my original, unexpurgated report at the time, approximately 45 minutes post ingestion:
'Dancing to Goldie. Feel great. Getting a nod of sorts.hard to stand up. whee. spinning on my chair is a lot of fun. Felt the urge to put on some makeup, so I did. basically random scribbles around my eyes.'
Then my sister and her boyfriend came over to take me to a party I forgot about.  I'd definitely call this a party drug combination. Not overly sedating, felt like dancing, everything silly. I probably wouldn't attempt to drive under the influence, but otherwise, I was normally coherent and cognisant. I felt very inspired, artistically, and probably would have ended up painting or drawing if not for the party.
I wouldn't recommend this as a chronic treatment for depression, but it snapped me out of a near-suicidal mood. Similar to good marijuana, life was magical and interesting, the world my canvas to create upon.
I took another .25 mg of the Klonopin days later, when I went bowling with some people and had to be surrounded by rude, prissy teenagers and their horrid music. The Klonopin quickly erased any anxiety, and I felt more outgoing and cheerful. I'm a benzo fan for life and recommend them highly to anyone who needs them.
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.


---
layout: main
active: home
navigation: navbar-dark
leadIn: We are chalenging closed systems!
heading: Everything is Open
reference: mission
buttonText: dicover more
description: We are builing wearables for fitness and health monitoring. Check it out and join us! It is free :-)
---
We believe in open and friendly world. Everyone should have the same access to technical inventions without
any limitations. Open Source and Open Hardware initiatives allow us to make this real.
It requires lot of individual human beings to make something that is really powerful and can change the way we live.
We turn to the Community to ask for help with making our dream real. Lets build Icarus system together.
Whole idea behind Icarus system come from micro-devices that can interact with each other through the air.
Every single of them behave independently and can live on its own. That is why it is so easy to add new pieces.
Everything starts with a simple idea. It grows and become something real.
So real that you can almost feel that it is already done. Journey begins with planning, brainstorming,
collecting materials and tools.
With help of nRF51822 chip we were able to get some heartbeat from lifeless silicon
to our test phones. It was very important moment for all of us as every single components of
Icarus Sensor System will be based on that chip.
Our first goal is to build fully functional cadence and speed sensor that connect to your phone through
Bluetooth Low Energy interface. Product Specialist Technical Engineer Technical Engineer Technical Engineer
We believe in a community. If you have some free time, skills or willingness to learn, join us and lets
build better fitness products together.
Our Mission
We want to challenge status quo in fitness and health device ecosystems.
Open Source & Hardware
Community Driven
Fully Expandable
About
To build system like that it needs time, knowledge and lot of patient.
September 2014
Born of Icarus System
October 2014
Heartbeat of the system
"December 2014"
First test ride
Check out the Icarus Bike Sensor page for more details.
Be Part
Of Our
Story!Icarus Core Team
We join passion and contribution to build truly open source products.
Łukasz Bałczewski
Krzysztof Szcześniak
Marek Śmigielski
Andrzej Stasiak


|
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| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
See:
Description
| Class Summary | |
|---|---|
| AddNodeDemo | Demonstrates visualization of a graph being actively updated. |
| AnimatingAddNodeDemo | A variation of AddNodeDemo that animates transitions between graph states. |
| AnnotationsDemo<V,E> | Demonstrates annotation of graph elements. |
| BalloonLayoutDemo | Demonstrates the visualization of a Tree using TreeLayout and BalloonLayout. |
| ClusteringDemo | This simple app demonstrates how one can use our algorithms and visualization libraries in unison. |
| DrawnIconVertexDemo | A demo that shows drawn Icons as vertices |
| EdgeLabelDemo | Demonstrates jung support for drawing edge labels that can be positioned at any point along the edge, and can be rotated to be parallel with the edge. |
| GraphEditorDemo | Shows how to create a graph editor with JUNG. |
| GraphFromGraphMLDemo | Demonstrates loading (and visualizing) a graph from a GraphML file. |
| GraphZoomScrollPaneDemo | Demonstrates the use of GraphZoomScrollPane . |
| ImageEdgeLabelDemo | Demonstrates the use of images on graph edge labels. |
| InternalFrameSatelliteViewDemo | Similar to the SatelliteViewDemo, but using JInternalFrame. |
| L2RTreeLayoutDemo | A variant of TreeLayoutDemo that rotates the view by 90 degrees from the default orientation. |
| LensDemo | Demonstrates the use of HyperbolicTransform
and MagnifyTransform
applied to either the model (graph layout) or the view
(VisualizationViewer)
The hyperbolic transform is applied in an elliptical lens
that affects that part of the visualization. |
| LensVertexImageShaperDemo | Demonstrates the use of images to represent graph vertices. |
| LensVertexImageShaperDemo.PickWithIconListener | |
| MinimumSpanningTreeDemo | Demonstrates a single graph with 3 layouts in 3 views. |
| MultiViewDemo | Demonstrates 3 views of one graph in one model with one layout. |
| PersistentLayoutDemo | Demonstrates the use of PersistentLayout
and PersistentLayoutImpl . |
| PluggableRendererDemo | Shows off some of the capabilities of PluggableRenderer . |
| RadialTreeLensDemo | Shows a RadialTreeLayout view of a Forest. |
| SatelliteViewDemo<V,E> | Demonstrates the construction of a graph visualization with a main and a satellite view. |
| ShortestPathDemo | Demonstrates use of the shortest path algorithm and visualization of the results. |
| ShowLayouts | Demonstrates several of the graph layout algorithms. |
| ShowLayouts.GraphChooser | |
| SimpleGraphDraw | A class that shows the minimal work necessary to load and visualize a graph. |
| SubLayoutDemo | Demonstrates the AggregateLayout class. |
| TreeCollapseDemo | Demonstrates "collapsing"/"expanding" of a tree's subtrees. |
| TreeLayoutDemo | Demonsrates TreeLayout and RadialTreeLayout. |
| TwoModelDemo | Demonstrates a single graph with 2 layouts in 2 views. |
| UnicodeLabelDemo | A demo that shows flag images as vertices, and uses unicode to render vertex labels. |
| VertexCollapseDemo | A demo that shows how collections of vertices can be collapsed into a single vertex. |
| VertexCollapseDemoWithLayouts | A demo that shows how collections of vertices can be collapsed into a single vertex. |
| VertexImageShaperDemo | Demonstrates the use of images to represent graph vertices. |
| VertexImageShaperDemo.DemoVertexIconShapeTransformer<V> | this class exists only to provide settings to turn on/off shapes and image fill in this demo. |
| VertexImageShaperDemo.DemoVertexIconTransformer<V> | this class exists only to provide settings to turn on/off shapes and image fill in this demo. |
| VertexImageShaperDemo.PickWithIconListener<V> | When Vertices are picked, add a checkmark icon to the imager. |
| VertexImageShaperDemo.VertexStringerImpl<V,S> | A simple implementation of VertexStringer that gets Vertex labels from a Map |
| VertexLabelAsShapeDemo | This demo shows how to use the vertex labels themselves as the vertex shapes. |
| VertexLabelPositionDemo | Demonstrates vertex label positioning controlled by the user. |
| VisualizationImageServerDemo | Demonstrates VisualizationImageServer. |
| WorldMapGraphDemo | Shows a graph overlaid on a world map image. |
Sample applications created using JUNG, largely focused on visualization. Current features demonstrated in the samples include:
|
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| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


Create a file in your new repository, add something to that file and commit those changes to Git.
Now that you've got a repository started, add a file to it.
Open a text editor. Now write a couple of lines of text, perhaps
say hello, and save the file as readme.txt
in the 'hello-world' folder you created in the last challenge.
Next check the status of your repository to find out if there have been changes. Below in this terminal, you should still be within the 'hello-world' you created. See if there are changes listed:
$ git status
Then add the file you just created to the files you'd like to commit (aka save) to change.
$ git add readme.txt
Finally, commit those changes to the repository's history with a short description of the updates.
$ git commit -m "<your commit message>"
Now add another line to readme.txt
and save.
In terminal, you can view the difference between the file now and how it was at your last commit.
$ git diff
Now with what you just learned above, commit this latest change.
git-it verify
git-it
$ git status
$ git diff
$ git add <FILENAME>
$ git add .
$ git commit -m "<your commit message>"


Molds
For molds wherein something must be burned (away), and do not open before being reheated: do not cast before refiring/reheating. For large molds that produce large and wide casts, it is necessary to score it with strong notches so that the pitch of the metal does not run as forcefully. These will not make many burrs if they are pressed. Prior to doing so, place between the mold and the press pieces of thick felt for mittens, which will fill the cavities and protect the mold from cracking. The clamps should be placed prior to heating or drying.
at left top margin
When the ground from which you are making your earthen base to lay out your animal is too soft, the pins you place come out easily when you cast the sand and so the mold is spoilt and the design is defeated. Therefore when you know that your slab is too tender and soft, spread some hot cinders over it and blow with the bellows.
Sable
If you don’t add enough alum de plume or crocus your mold will easily crack when heated. But if your sand is mixed as it ought to be, the mold will sustain itself. You’ll know it’s of good quality when, while still hot after casting, it immoderately soaks up the water when dipped and breaks easily, because the alum and the crocus render it spongy. To the contrary, bad sand, which is composed of plaster and brick and is not well mixed with alum, breaks easily in fire and hardens in water. If possible, cast all at once.
Molds
When you cast lead, your molds must be very dry, even if the molds are large. The outside of the molds must be reddened, and it is necessary to keep them in continuous heat until they do not smoke anymore inside. Do not reheat your molds several times, but continue when you have begun and do not let them cool in the cold because they will crack. Let them cool near the fire. When your molds are still as warm as above, remark, you can put your finger into the casting gate without burning your skin. If your mold is large, it takes more time to cure and to dry, and you must also cast warmer.


Before you seek support, please check the online help or look in the online manual and see if the solution to your problem can be found there. Be sure to check the “Frequently Asked Questions” section. You can also check to see if your problem is addressed in the Support section of our website.
If you have a problem that you cannot resolve by these methods, the best way to seek help is by using our web form at www.stattransfer.com/support/help.html. We have found that the use of this form, rather than a free-form email, allows us to provide faster and better support. If you use this form, we are much more likely to get the information we need to address your problem on the first try. In addition, your request will be routed to the right person and automatically entered into a tracking system so that your problem will not fall through the cracks. To ensure the best service, please be sure to follow the instructions on the form and enter all of the information that is called for.
You can also seek support by using the Log tab. This method is particularly helpful if you think you have found a bug in Stat/Transfer, because it is possible to automatically send us a compressed and encrypted copy of the input file that was causing you problems, as well as a complete description of your environment and your own description of the problem. If you send a support request through this method, it is a very good idea to also use the form on our website. This will ensure that your problem is entered into our tracking system.
It is always good to make sure you are running the latest version of Stat/Transfer. You can go to the About menu tab and look up the exact version of Stat/Transfer that you are using. You can also check for updates from there.


This is for an example of the original website, you would upload an image and the site would detect the item and add it to your checklist


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Package com.dragonboatrace.tools
Class Hitbox
- java.lang.Object
-
- com.dragonboatrace.tools.Hitbox
-
public class Hitbox extends java.lang.Object
Represents an Entities Hitbox.
-
-
Constructor Summary
Constructors Constructor Description Hitbox(float x, float y, int width, int height)
Create a new hit box at a specified position with a width and height.
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description boolean
collidesWith(Hitbox box)
Check if the hit box is colliding with another hit box.int
getHeight()
Get the height of the hit box.int
getWidth()
Get the width of the hit box.float
getX()
Get the x coordinate of the hit box.float
getY()
Get the y coordinate of the hit box.boolean
leaves(Hitbox box)
Checks if the another hit box has left the area of this hit box.void
move(float x, float y)
Move the hit box's position to the one specified, not additive.
-
-
-
Constructor Detail
-
Hitbox
public Hitbox(float x, float y, int width, int height)
Create a new hit box at a specified position with a width and height.- Parameters:
x
- The x position of the bottom left corner.y
- The y position of the bottom left corner.width
- The width of the hit box.height
- The height of the hit box
-
-
Method Detail
-
move
public void move(float x, float y)
Move the hit box's position to the one specified, not additive.Used to make sure the hit boxes position is the same as the entity it represents.
- Parameters:
x
- The new x position.y
- The new y position.
-
collidesWith
public boolean collidesWith(Hitbox box)
Check if the hit box is colliding with another hit box.- Parameters:
box
- The hit box that the collision is being checked against.- Returns:
- A boolean of if the two hit boxes are intersecting.
-
leaves
public boolean leaves(Hitbox box)
Checks if the another hit box has left the area of this hit box.- Parameters:
box
- The other hit box.- Returns:
- A boolean of if the other hit box is partially outside of this hit box
-
getX
public float getX()
Get the x coordinate of the hit box.- Returns:
- A float of the x position of the bottom left corner.
-
getY
public float getY()
Get the y coordinate of the hit box.- Returns:
- A float of the y position of the bottom left corner.
-
getWidth
public int getWidth()
Get the width of the hit box.- Returns:
- An int representing how wide the hit box is.
-
getHeight
public int getHeight()
Get the height of the hit box.- Returns:
- An int representing how tall the hit box is.
-
-


Web development without image editing software, IDs or classes? What was impossible 5...
REGISTER
How about all of it, all in 1 day! In this full day workshop you will learn about the capabilities of CSS3, progressive design principles, time saving techniques, and debugging and development tools. Yes, we'll cover rounded corners, but this skills-based workshop will cover so much more, including selectors, fonts, media queries, performance, responsive features, background effects, gradients, animations, transitions and transformations.
What will be covered
Who this workshop for
This workshop is targeted at designers and developers who already work with CSS, and perhaps even use some features of CSS3, and want to become really proficient in advanced features of CSS3.
What you'll need
Estelle Weyl


@* * This template is called from the `index` template. This template * handles the rendering of the page header and body tags. It takes * two arguments, a `String` for the title of the page and an `Html` * object to insert into the body of the page. *@ @(title: String,usuario:Usuario, scripts: Html = Html(""))(content: Html)
@* Here's where we render the page title `String`. *@


Covid19
Home
Maps
Tables
Search
Confirmed
Active
Recovered
Deceased
Highlights Through Map
State
Confirmed
Active
Recovered
Deceased
Population


NOTE: This extension is only downloadable via Chromium browsers, and will uninstall if you ever disconnect from Wi-Fi on or power off a Chromebook (other devices not tested).
- Download the ZIP file.
- Unzip the new ZIP file,
wds-blog-searcher.zip
. - Go to
about:extensions
. - Turn on Developer mode at the top-right.
- Click Load unpacked.
- Open the unZIPed folder,
wds-blog-searcher
. - Click the Extensions jigsaw puzzle icon.
- Scroll to the WDS Blog Searcher extension, and click the pin icon.
- 🎉 Great! Now you can simply use 2 clicks (1 on the extension and pressing Enter, and 2 on the relevant search result).


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 1
Preheat the oven to 180C/350F/Gas 4.
For the sautéed mushrooms, heat half of the olive oil with the butter in a frying pan and lightly fry the mushrooms and garlic for five minutes. Squeeze over the lemon juice, drizzle over the balsamic vinegar and cook for a further 4-5 minutes, or until reduced slightly. Stir in the remaining olive oil and the chopped chives.
For the monkfish, heat the olive oil and butter in an ovenproof frying pan. Season the fish with salt and freshly ground black pepper, then add to the pan and fry for 2-3 minutes on each side, or until golden-brown. Squeeze over the lemon juice, then transfer to the oven to roast for 6-8 minutes, or until the fish is cooked through. Remove from the oven and rest for five minutes, then thickly slice.
For the 'mushroom' tatties, heat the olive oil in an ovenproof frying pan and lightly fry the mushroom-shaped potatoes for 4-5 minutes, or until they start to colour. Add the garlic and rosemary, then place the pan in the oven to roast for ten minutes, or until the potatoes are golden-brown and tender.
To serve, pile the sautéed mushrooms onto a serving plate and place the sliced monkfish on top. Spoon the roasted 'mushroom' tatties around the edges of the plate and serve.


Construct consensus genetic maps with LPmerge, see Endelman and Plomion (2014) <doi:10.1093/bioinformatics/btu091> and model the relationship between physical distance and genetic distance using thin-plate regression splines, see Wood (2003) <doi:10.1111/1467-9868.00374>. Perform quality control on input data and visualise intermediate steps.
| Version: | 0.1.2 |
| Depends: | igraph |
| Imports: | dplyr, ggplot2, mgcv, doParallel, parallel, foreach, stringi, plotly, visNetwork, LPmerge, lazyeval, tidyr |
| Suggests: | knitr, rmarkdown |
| Published: | 2017-10-10 |
| Author: | Dennis van Muijen, Ram Kumar Basnet, Nathalie J. Dek |
| Maintainer: | Dennis van Muijen <d.van.muijen at rijkzwaan.nl> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | mapfuser results |
| Reference manual: | mapfuser.pdf |
| Vignettes: |
Working with the MapFuser package |
| Package source: | mapfuser_0.1.2.tar.gz |
| Windows binaries: | r-devel: mapfuser_0.1.2.zip, r-release: mapfuser_0.1.2.zip, r-oldrel: mapfuser_0.1.2.zip |
| OS X binaries: | r-release: mapfuser_0.1.2.tgz, r-oldrel: mapfuser_0.1.2.tgz |
Please use the canonical form https://CRAN.R-project.org/package=mapfuser to link to this page.


--- layout: page ---
I'm Da Jun Yoo, a Visual designer based in Seoul & New York focusing on UI and UX Design. If you want to know more about my work, please get in touch<EMAIL_ADDRESS>Resume


Landing Page
Special Projects
This story is part of a series of specially designed stories that represents some of the best journalism The Post has to offer. Check out the rest of the special projects here.
TAYLOR JOHNSTON
05.25.17
Freshmen won’t be the only ones taking their first steps onto Ohio University’s campus this fall — OU President Duane Nellis will be joining them.
Between a nearly year-long presidential search and political tensions both on campus and off, the past year has been a period of transition for OU.
Patrick Connolly | FILE
Current Ohio University President Duane Nellis, who previously served as president of Texas Tech University and of the University of Idaho, fields questions at the first of the presidential candidate open forums in Baker Center Ballroom on Tuesday, Jan. 19, 2016.
Nellis takes office June 12, succeeding former OU President Roderick McDavis, who left the university in February to take an executive position with AGB Search, a search firm specializing in higher education leadership. In between presidential terms, David Descutner, former University College dean, has served as interim president. His term, although short, was not without its complications.
On Feb. 1, about two weeks before McDavis left office, 70 demonstrators were arrested in Baker Center. The arrests sparked debate over the legality and appropriateness of police action that night.
About a month later, two graduate students filed a federal complaint claiming the university failed to act on reports that an English professor sexually harassed female students for more than a decade.
In both cases, legal battles and public scrutiny ensued.
In January, Nellis made his first appearance at OU in a public forum, during which he fielded questions on a number of topics including diversity and university transparency.
“One of the things that will define the success of a major, distinguished public university is a commitment to diversity and inclusion and how well you do that,” Nellis said at the forum.
Nellis, whose presidency was officially announced in February, was the only one left standing in the presidential search after the other three candidates withdrew from the race within the same week.
Before applying for president at OU, Nellis was one of the four finalists for the chancellor position at the University of Alaska Fairbanks, according to a previous Post report, although none of those candidates were selected for the position. During his time at Texas Tech, he also ran for president at the University of Wyoming but was not chosen.
Earlier in his career, Nellis served as the president of the University of Idaho from 2009-2013 and spent 22 years at Kansas State University in a number of administrative and teaching roles in the department of geography.
Taking the job at OU means Nellis and his wife will be returning to Appalachia. They lived in West Virginia when Nellis served as a dean at West Virginia University from 1997-2004.
 “Ruthie (Duane’s wife) and I are so excited to be associated with the Bobcat family, to be part of Ohio University, a very distinguished university with a very rich history.”
During his first year, Nellis will receive a salary of $475,000, and will live off-campus. His wife, Ruthie, will receive a base salary of $35,000. His contract stipulates that he will be required to live in Athens County and will receive a $5,000 per month stipend to live in the residence of his choosing.
Back to The Orientation GuideLanding Page
This story is part of a series of specially designed stories that represents some of the best journalism The Post has to offer. Check out the rest of the special projects here.


When we talk about Shanghainese, what are we actually talking about? Who are the Shanghai residents we talked about in different periods? Who have become the so-called Shanghai residents at different times?
To answer these questions, we must firstly learn about the demographic changes in Shanghai in recent years. Our team constructs the following D3 graphs to observe the trend of Shanghai's population growth.
Graph 1
According to the data from Shanghai Open Data website, in the last 40 years, citizens in Shanghai had doubled from 11 million to over 24 million. Shanghai’s population is growing rapidly in terms of numbers, So how does Shanghai perform in terms of the population of each age group compared with other provinces in China?
Graph 2
Nevertheless, Shanghai's population and age structure have not taken an advanced position in China. Hu, represented as Shanghai, ranked 9th according to the 2020 Chinese statistical yearbook. It seems Shanghai does not have an advantage in labor force, but it still has a plenty of immigrant population flow which become the new Shanghai residents.
It would be strange to talk about Shanghainese 70 years ago, because at that time the proportion of people with local household registration in Shanghai was quite rare.
Our team designs a pie chart to describe the proportion of the registered population of the provinces temporarily residing in Shanghai in 1950. Data comes from the book named Research on the Population Changes in Old Shanghai.
Graph 3
In 1950, the second year of the founding of the People's Republic of China, most of Shanghai residents came from Jiangsu and Zhejiang province. These are two neighboring provinces of Shanghai. At that time, after war, China was in ruins, and traffic was interrupted. Only people from province next to shanghai can go to this land to make a living.
When these first people who built Shanghai had settled down in this land, they talked about Shanghainese as a complex group with diverse accents.
Based on the 2010 census data, a Chord Diagram was created to show the main provinces related to Shanghai's population flow.
The arrows on the map represent the direction of population flow and the color of the population flow is the same as the color of the province people are currently living in.
Distances between different provinces and Shanghai on the circle reflect real geographic distances to a certain extent.
Graph 4
Combining the pie chart and chord diagram, our team found some interesting conclusions. Due to the development of transportation in eastern China, which we will also talk about in the later traffic part, more people from remote and poor provinces can go to Shanghai to make a living such as Anhui, Jiangxi, Henan and Sichuan. On the other hand, because of the radiating effect of the economic center, Shanghai itself, people in the provinces surrounding Shanghai have lived a prosperous life, and they no longer need to leave their hometowns.
When the new generation of Shanghainese enters the society, the Shanghai residents they are talking about are already a group that not only has different accents, but also speaks different languages.
In the last census, there were more than 200,000 overseas personages in Shanghai. Similarly, we use the 2010 census data to design a flow chart for showing the situation of the overseas people temporarily living in Shanghai.
Graph 5
We define higher education as undergraduate. From the graph above，you can find that a considerable proportion of overseas population in Shanghai have received higher education, and nearly half of them come to Shanghai for work or business purposes.
Talents are attracted to this city to improve themselves
As a number of labor forces immigrate to Shanghai，the local economy has developed over the last decades.


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{collection}
{geographic_scope}
View map in Page Delivery Service
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Contains the main PTP-1588 driver implementation functions like ISR's, timers, synchronization, RCF calculation, line and peer delay calculation.
More...
|
| void | TimeSync_resetIEP (TimeSync_ParamsHandle_t timeSyncHandle) |
| | Resets CMP1 once first adjustment is done, else 1PPS signal doesn't trigger. More...
|
| |
| void | TimeSync_doFirstAdjustment (TimeSync_ParamsHandle_t timeSyncHandle, uint8_t portNum) |
| | Do initial adjustment for the IEP based on sync timestamp. More...
|
| |
| int8_t | TimeSync_processTimeOfDay (TimeSync_ParamsHandle_t timeSyncHandle, uint32_t nanoseconds, uint64_t seconds) |
| | When application receives the Time of Day information, it calls this API with the seconds and nanoseconds fields. This starts the time of day synchronization mechanism. Assumption : Latch0 input is also enabled and is being fed by 1PPS output. More...
|
| |
| void | TimeSync_processPTPFrame (TimeSync_ParamsHandle_t timeSyncHandle, uint8_t *pktBuffer, uint8_t portNum, uint16_t size, uint8_t isLinkLocal) |
| | Processes a PTP Announce message and extract fields. More...
|
| |
| void | TimeSync_processPdelayReqFrame (TimeSync_ParamsHandle_t timeSyncHandle, uint8_t *buff, uint8_t portNum) |
| |
| void | TimeSync_getGeneralMessage (TimeSync_ParamsHandle_t timeSyncHandle, int8_t *buff) |
| | Copies the PTP announce message data to PTP stack buffer. More...
|
| |
| uint8_t | TimeSync_isEnabled (TimeSync_ParamsHandle_t timeSyncHandle) |
| | Return True/False 1/0 if timeSync module is enabled. More...
|
| |
| void | TimeSync_updateParentAddress (TimeSync_ParamsHandle_t timeSyncHandle, uint8_t *parentMac) |
| | Write the MAC ID of PTP master to Firmware. BMC Algorithm calls this API. More...
|
| |
| void | TimeSync_getPrevAddress (TimeSync_ParamsHandle_t timeSyncHandle, uint8_t *prevMac) |
| | Retuns the previous master's MAC ID. BMC Algorithm calls this. More...
|
| |
| void | TimeSync_Port1linkResetCallBack (uint8_t linkStatus, void *arg2) |
| | Callback for link status change on Port 1. More...
|
| |
| void | TimeSync_Port2linkResetCallBack (uint8_t linkStatus, void *arg2) |
| | Callback for link status change on Port 2. More...
|
| |
| void | TimeSync_reset (TimeSync_ParamsHandle_t timeSyncHandle) |
| | Reset the state machine in firmware to restart synchronization (First adjustment happens again) More...
|
| |
| void | TimeSync_rxPhyDelayCorrection (TimeSync_ParamsHandle_t timeSyncHandle) |
| | Performs PHY delay correction on Rx timestamp Assumption : The function expects the timestamp in rxTimestamp_gPTP field on which it does correction. More...
|
| |
Contains the main PTP-1588 driver implementation functions like ISR's, timers, synchronization, RCF calculation, line and peer delay calculation.
Copyright (c) 2018, Texas Instruments Incorporated All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
- Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
- Neither the name of Texas Instruments Incorporated nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.


RAIN MAN A film review by Mark R. Leeper Copyright 1988 Mark R. Leeper
Capsule review: Barry Levinson's occasionally humorous drama of a razzle-dazzle car salesman and an autistic savant. This is perhaps Hoffman's most demanding role since his performance as Ratso Rizzo in MIDNIGHT COWBOY. RAIN MAN is one of the few films really worth seeing this holiday season. Rating: +2.
These days we see a lot of films about outsiders and how they see and fit into our society. SPLASH! showed us the theme with a mermaid; STARMAN, E.T., BROTHER FROM ANOTHER PLANET, and any number of others have used aliens; MOSCOW ON THE HUDSON and even RED HEAT did it with Soviets. Of course you do not have to go to another planet or the Soviet Union to find outsiders. We have institutions full of people whose view of the world is radically different from yours or mine. But where is the pleasure of seeing a film about people with so-called mental disorders? That is the stuff of television movies perhaps, but they rarely make it into theatrical films as anything but killers. But if anyone is going to make an original theatrical film about mental disability, few filmmakers can do it as well as Levinson.
Barry Levinson is one of these days' all-too-few filmmakers who is willing to take a chance on the type of film they make and then make it work for them. Besides making THE NATURAL--perhaps the best sports film ever--he made an enjoyable film about salesmen of aluminum siding, and, of course, his two best-known films, DINER and GOOD MORNING, VIETNAM. With the possible exception of GOOD MORNING, VIETNAM, his films are fresh and different from anything else being made.
In Levinson's latest film, RAIN MAN, Tom Cruise plays Charlie Babbitt.  Charlie is a wheeler-dealer who may have his hand in many pots but when we see him he is dealing in ultra-expensive cars, razzle-dazzling them past the EPA, and making enormous profits. He uses people like toys and loves only money. At the death of his father his only emotion is greed. He is all ready to happily inherit millions, but instead gets a shock. At the reading of the will he finds out that his father has chosen to leave the bulk of the estate to someone else. (Why? Well, I may be the only reviewer in the world who doesn't give away that plot twist.) The actual beneficiary is Raymond, an autistic savant. What is an "autistic savant?" It is a person who generally lives in a world of his own, but in just a few skills he is good enough to boggle the mind.
Now Raymond (played by Dustin Hoffman) has a rather remarkable mind. Like most autistic minds, his usually is off in a twilight zone of unrelated thoughts. He talks a sort of verbal fruit cocktail. Yet at the same time he is capable of incredible mental gymnastics. Given two three-digit numbers he can visualize their product and simply read it off. Overturn a box of toothpicks and he can almost instantly count them just by looking. Given a date, he knows its day of the week. (Actually, I can do this one myself, but it takes me twenty seconds or so; Raymond knows instantly.) Charlie formulates a scheme to steal the inheritance, but as it progresses Charlie finds he must spend more time with Raymond than he ever expected.. Initially Charlie has no sense of wonder about Raymond's mind, Charlie is just one more person to use. But eventually Raymond's lightning flashes of numerical brilliance and his innocence begin to win over even Charlie.
As with MIDNIGHT COWBOY, Dustin Hoffman does not play the main character--at least the character was not written that way. But let us face it, the day that Hoffman cannot out-act Cruise, he might as well hang it up. This is Hoffman's movie as much as or more so than MIDNIGHT COWBOY was. Tom Cruise does an adequate acting job and no more is really necessary. Even if Cruise were a much better actor than he is, when Hoffman is on the screen all eyes would still be on Hoffman. If Hoffman fails at all in this film, it is in not really giving us enough insight into Raymond's mind. We see enough of Raymond's world-view to whet our appetite to see more, but we never get sufficient insight into who his mind works. Perhaps nobody but an autistic savant knows how an autistic savant thinks. But in a very disappointing holiday season's crop of films RAIN MAN stands out like Raymond himself does. Rate it a +2 on the -4 to +4 scale.
Mark R. Leeper att!mtgzz!leeper<EMAIL_ADDRESS>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


All types of exercise, including walking, release endorphins in your brain which improve your mood. Try walking outside for a bit; it’s been shown to help reduce stress, not to mention getting a healthy dose of vitamin D.


- The Development Kit - C, C++, Perl, and Java, libraries as well as assorted documentation.
- FastCGI4D A Tango compatible FastCGI library for the D language
- Perl
- PHP
- Fastcgi for Ruby
- Python
- Jon Ribbens' multi-threaded 'servlet' interface - jonpy
- Peter Åstrand's multi-threaded module - thfcgi.py
- Andreas Jung's multi-threaded wrapper for fcgi.py - sz_fcgi.py
- Robin Dunn's improvements to Digicool's module - fcgi.py
- TCL - TCL
- Common Lisp
- Goanna Eiffel - The Goanna Eiffel project includes a native implementation of FastCGI for use with its web application libraries.
- Smalltalk
- Jeff Coffield's VMS module.


Networking
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We here at NTEP provide you platform to form and manage small students network for interpersonal development, bettering your networking skills ,your communication skills and to earn enough pocket money to be self dependent through most simplified network forming......


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This is a header.
This is the second paragraph.


--- layout: page title: About header-img: "img/about-bg.png" ---
After working for a year in workers' compensation, I realized I needed a change in careers.  So I turned to coding. It was something I'd enjoyed doing back in college, though I didn't have the time I needed to dedicate to it. So here I am. Back at it. This time to finish what I started those years ago and to make a better life for myself.


With the constant technological development we are witnessing in the world of hosting, it is necessary to familiarize ourselves with the terminology and meaning of the systems we are using. An important distinction that we need to make is between virtual machines and containers, as they are both widely used in the hosting industry, and yet they are often confused.
The discussion that frequently arises is which technology is better, virtualization, or containerization. The answer is not a simple one, as it depends heavily on the user’s needs and business requirements. To try and answer this question, we will first provide a rundown on both of these technologies, how they are used, in which situations they are most beneficial, and what the advantages and disadvantages are.
To better understand the functionalities of virtual machines, we need to understand why they were created in the first place. As bare-metal servers improved in processing power and capacity, applications and services that were running on those servers failed to effectively utilize all of the available resources and as such, those resources were essentially wasted. Virtualization was created to take better advantage of all of the available reserves on a single server. This allowed for multiple virtual machines to better apply the same amount of resources.
Virtualization provides for the existence of multiple, smaller virtual servers, within the framework of a larger server's physical environment. The virtualization software which runs on the parent basically allocates resources to each virtual server along with its own operating system, drivers, binaries, libraries, and applications. These virtual servers are isolated from each other and have no knowledge they are running within a virtualized platform nor aware that they are sharing resources with the other virtual machines.
Since each virtual machine is essentially a virtual copy of the hardware of the host server and uses its own operating system, it can be resource-heavy and slow, while consuming a great deal of memory and processing power. Each virtual machine can also be significant in size, which limits its portability and thus cannot easily be shared.
For more information on virtualization, please click here.


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New to edgarWebR 0.2.0 are functions for parsing SEC documents. While there are good R packages for XBRL processing, there is a gap in extracting information from other document types available via the site. edgarWebR currently provides functions for 2 of those -
parse_submission()
- Processes a raw SGML filing into component documents. These are the ‘Complete submission text file’ on filing pages. Similar to zip files, they contain all the files included in particular submission.parse_filing()
- Processes a narrative filing (e.g. 10-K, 10-Q) into paragraphs annotated with part and item numbers. In a submission with many files, this is the main form.This vignette will show how to use both functions to find the risks reported by in a company’s recent filing.
Using edgarWebR functions, we’ll first look up a recent filing.
ticker <- "STX"
filings <- company_filings(ticker, type = "10-Q", count = 40)
# Specifying the type provides all forms that start with 10-, so we need to
# manually filter.
filings <- filings[filings$type == "10-Q", ]
# We're only interested in a particular filing
filing <- filings[filings$filing_date == "2017-10-27", ]
filing$md_href <- paste0("[Link](", filing$href, ")")
knitr::kable(filing[, c("type", "filing_date", "accession_number", "size",
"md_href")],
col.names = c("Type", "Filing Date", "Accession No.", "Size", "Link"),
digits = 2,
format.args = list(big.mark = ","))
| Type | Filing Date | Accession No. | Size | Link | |
|---|---|---|---|---|---|
| 7 | 10-Q | 2017-10-27 |<PHONE_NUMBER>-17-323042 | 6 MB | Link |
We’ll next get the list of files and find the link to the complete submission.
docs <- filing_documents(filing$href)
doc <- docs[docs$description == 'Complete submission text file', ]
doc$md_href <- paste0("[Link](", doc$href, ")")
knitr::kable(doc[, c("seq", "description", "document", "size",
"md_href")],
col.names = c("Sequence", "Description", "Document",
"Size", "Link"),
digits = 2,
format.args = list(big.mark = ","))
| Sequence | Description | Document | Size | Link | |
|---|---|---|---|---|---|
| 12 | NA | Complete submission text file |<PHONE_NUMBER>-17-323042.txt | 6,983,971 | Link |
Normally, we would use filing_documents()
to get to the 10-Q directly, but as an example we’ll be using the complete submission file to demonstrate the parse_submission()
function. You would want to use the complete submission file if you want to access the full list of files - e.g. in this case there are 80 files in the submission, but only 10 available on the website and therefore available to filing_documents()
- or if you worry about efficiency and are downloading all of the documents.
Now that we have the link to the complete submission file, we can parse it into components.
parsed_docs <- parse_submission(doc$href)
knitr::kable(head(parsed_docs[, c("SEQUENCE", "TYPE", "DESCRIPTION", "FILENAME")]),
col.names = c("Sequence", "Type", "Description", "Document"),
digits = 2,
format.args = list(big.mark = ","))
| Sequence | Type | Description | Document |
|---|---|---|---|
| 1 | 10-Q | 10-Q | d432283d10q.htm |
| 2 | EX-10.1 | EX-10.1 | d432283dex101.htm |
| 3 | EX-10.3 | EX-10.3 | d432283dex103.htm |
| 4 | EX-10.4 | EX-10.4 | d432283dex104.htm |
| 5 | EX-31.1 | EX-31.1 | d432283dex311.htm |
| 6 | EX-31.2 | EX-31.2 | d432283dex312.htm |
And just for example, here’s the end of the full list - note the excel that isn’t on the SEC site for instance.
knitr::kable(tail(parsed_docs[, c("SEQUENCE", "TYPE", "DESCRIPTION", "FILENAME")]),
col.names = c("Sequence", "Type", "Description", "Document"),
digits = 2,
format.args = list(big.mark = ","))
| Sequence | Type | Description | Document | |
|---|---|---|---|---|
| 82 | 82 | XML | IDEA: XBRL DOCUMENT | R65.htm |
| 83 | 83 | EXCEL | IDEA: XBRL DOCUMENT | Financial_Report.xlsx |
| 84 | 84 | XML | IDEA: XBRL DOCUMENT | Show.js |
| 85 | 85 | XML | IDEA: XBRL DOCUMENT | report.css |
| 86 | 87 | XML | IDEA: XBRL DOCUMENT | FilingSummary.xml |
| 87 | 89 | ZIP | IDEA: XBRL DOCUMENT |<PHONE_NUMBER>-17-323042-xbrl.zip |
The 10-Q Filing document is Seq. 1, with the full text of the document in the TEXT column.
# NOTE: the filing document is not always #1, so it is a good idea to also look
# at the type & Description
filing_doc <- parsed_docs[parsed_docs$TYPE == '10-Q' &
parsed_docs$DESCRIPTION == '10-Q', 'TEXT']
substr(filing_doc, 1, 80)
#> [1] "\n<TITLE>10-Q</TITLE>\n\n \n<h5 align=\"left"
We can see that contains the raw document. For document types which are not plain text, e.g. the XBRL zip file, the content is uuencoded and would been further processing.
Fortunately edgaWebR functions that take URL’s will also take a string containing the document, so to parse the document, while we could have passed the URL to the online document we can just pass in the full string.
doc <- parse_filing(filing_doc, include.raw = TRUE)
unique(doc$part.name)
#> [1] "" "PART I" "PART II"
unique(doc$item.name)
#> [1] ""
#> [2] "ITEM 1. FINANCIAL STATEMENTS"
#> [3] "ITEM 2. MANAGEMENT'S DISCUSSION AND ANALYSIS OF FINANCIAL CONDITION AND RESULTS OF OPERATIONS"
#> [4] "ITEM 3. QUANTITATIVE AND QUALITATIVE DISCLOSURES ABOUT MARKET RISK"
#> [5] "ITEM 4. CONTROLS AND PROCEDURES"
#> [6] "ITEM 1. LEGAL PROCEEDINGS"
#> [7] "ITEM 1A. RISK FACTORS"
#> [8] "ITEM 2. UNREGISTERED SALES OF EQUITY SECURITIES AND USE OF PROCEEDS"
#> [9] "ITEM 3. DEFAULTS UPON SENIOR SECURITIES"
#> [10] "ITEM 4. MINE SAFETY DISCLOSURES"
#> [11] "ITEM 5. OTHER INFORMATION"
#> [12] "ITEM 6. EXHIBITS"
head(doc[grepl("market risk", doc$item.name, ignore.case = TRUE), "text"], 3)
#> [1] "ITEM 3. QUANTITATIVE AND QUALITATIVE DISCLOSURES ABOUT MARKET RISK"
#> [2] "We have exposure to market risks due to the volatility of interest rates, foreign currency exchange rates, credit rating changes, equity and bond markets. A portion of these risks may be hedged, but fluctuations could impact our results of operations, financial position and cash flows."
#> [3] "Interest Rate Risk. Our exposure to market risk for changes in interest rates relates primarily to our investment portfolio. As of September 29, 2017, we had no available-for-sale securities that had been in a continuous unrealized loss position for a period greater than 12 months. The Company determined no available-for-sale securities were other-than-temporarily impaired as of September 29, 2017. We currently do not use derivative financial instruments in our investment portfolio."
risks <- doc[grepl("market risk", doc$item.name, ignore.case = TRUE), "raw"]
Now the document is all ready for whatever further processing we want. As a quick example we’ll pull out all the italicized risks.
risks <- risks[grep("", risks)]
risks <- gsub("^.*|.*$", "", risks)
risks <- gsub("\n", " ", risks)
risks
#> [1] "Interest Rate Risk" "Foreign Currency Exchange Risk"
#> [3] "Derivatives and Hedging. " "Other Market Risks"
This is a fairly simplistic example, but should serve as a good tutorial on processing filings.
edgarWebR is available from CRAN, so can be simply installed via
If you want the latest and greatest, you can get a copy of the development version from github by using devtools:


Chapter 9 Modeling data
9.1 Load packages and set plotting theme
library("knitr") # for knitting RMarkdown
library("kableExtra") # for making nice tables
library("janitor") # for cleaning column names
library("tidyverse") # for wrangling, plotting, etc.
theme_set(theme_classic() + #set the theme
theme(text = element_text(size = 20))) #set the default text size
$set(comment = "",
opts_chunkfig.show = "hold")
9.2 Modeling data
9.2.1 Simplicity vs. accuracy trade-off
# make example reproducible
set.seed(1)
= 20 # sample size
n_samples = 2 # number of parameters in the polynomial regression
n_parameters
# generate data
= tibble(x = runif(n_samples, min = 0, max = 10),
df.data y = 10 + 3 * x + 3 * x^2 + rnorm(n_samples, sd = 20))
# plot a fit to the data
ggplot(data = df.data,
mapping = aes(x = x,
y = y)) +
geom_point(size = 3) +
# geom_hline(yintercept = mean(df.data$y), color = "blue") +
geom_smooth(method = "lm", se = F,
formula = y ~ poly(x, degree = n_parameters, raw = TRUE)) +
theme(axis.ticks = element_blank(),
axis.title = element_blank(),
axis.text = element_blank())
# make example reproducible
set.seed(1)
# n_samples = 20
= 3
n_samples
= tibble(x = runif(n_samples, min = 0, max = 10),
df.pre y = 2 * x + rnorm(n_samples, sd = 1))
# plot a fit to the data
ggplot(data = df.pre,
mapping = aes(x = x,
y = y)) +
geom_point(size = 3) +
# geom_hline(yintercept = mean(df.pre$y), color = "blue") +
geom_smooth(method = "lm", se = F,
formula = y ~ poly(x, 1, raw = TRUE)) +
theme(axis.ticks = element_blank(),
axis.title = element_blank(),
axis.text = element_blank())
9.2.2 Sampling distributions for median and mean
# make example reproducible
set.seed(1)
= 40 # size of each sample
sample_size = 1000 # number of samples
sample_n
# draw sample
= function(sample_size, distribution){
fun.draw_sample = 50 + rnorm(sample_size)
x return(x)
}
# generate many samples
= replicate(n = sample_n,
samples fun.draw_sample(sample_size, df.population))
# set up a data frame with samples
= matrix(samples, ncol = sample_n) %>%
df.sampling_distribution as_tibble(.name_repair = ~ str_c(1:sample_n)) %>%
pivot_longer(cols = everything(),
names_to = "sample",
values_to = "number") %>%
mutate(sample = as.numeric(sample)) %>%
group_by(sample) %>%
mutate(draw = 1:n()) %>%
select(sample, draw, number) %>%
ungroup()
# turn the data frame into long format and calculate the mean and median of each sample
= df.sampling_distribution %>%
df.sampling_distribution_summaries group_by(sample) %>%
summarize(mean = mean(number),
median = median(number)) %>%
ungroup() %>%
pivot_longer(cols = -sample,
names_to = "index",
values_to = "value")
And plot it:
# plot a histogram of the means with density overlaid
ggplot(data = df.sampling_distribution_summaries,
mapping = aes(x = value, color = index)) +
stat_density(bw = 0.1,
size = 2,
geom = "line") +
scale_y_continuous(expand = expansion(mult = c(0, 0.01)))
9.2.3 Residuals need to be normally distributed, not the data itself
set.seed(1)
= 1000
n_participants
= tibble(participant = 1:n_participants,
df.normal condition = rep(c("control", "experimental"), each = n_participants/2)) %>%
mutate(score = ifelse(condition == "control",
rnorm(n = n_participants, mean = 5, sd = 2),
rnorm(n = n_participants, mean = 15, sd = 3)))
# distribution of the data
ggplot(data = df.normal,
mapping = aes(x = score)) +
geom_density() +
geom_density(mapping = aes(group = condition,
color = condition))
# distribution of the residuals after having fitted a linear model
# we'll learn how to do this later
= lm(formula = score ~ 1 + condition,
fit data = df.normal)
ggplot(data = tibble(residuals = fit$residuals),
mapping = aes(x = residuals)) +
geom_density()
9.3 Hypothesis testing: “One-sample t-test”
= read_table2(file = "data/internet_access.txt") %>%
df.internet clean_names()
── Column specification ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
cols(
State = col_character(),
Internet = col_double(),
College = col_double(),
Auto = col_double(),
Density = col_double()
)
%>%
df.internet mutate(i = 1:n()) %>%
select(i, internet, everything()) %>%
head(10) %>%
kable(digits = 1) %>%
kable_styling(bootstrap_options = "striped",
full_width = F)
| i | internet | state | college | auto | density |
|---|---|---|---|---|---|
| 1 | 79.0 | AK | 28.0 | 1.2 | 1.2 |
| 2 | 63.5 | AL | 23.5 | 1.3 | 94.4 |
| 3 | 60.9 | AR | 20.6 | 1.7 | 56.0 |
| 4 | 73.9 | AZ | 27.4 | 1.3 | 56.3 |
| 5 | 77.9 | CA | 31.0 | 0.8 | 239.1 |
| 6 | 79.4 | CO | 37.8 | 1.0 | 48.5 |
| 7 | 77.5 | CT | 37.2 | 1.0 | 738.1 |
| 8 | 74.5 | DE | 29.8 | 1.1 | 460.8 |
| 9 | 74.3 | FL | 27.2 | 1.2 | 350.6 |
| 10 | 72.2 | GA | 28.3 | 1.1 | 168.4 |
# parameters per model
= 1
pa = 0
pc
= df.internet %>%
df.model select(internet, state) %>%
mutate(i = 1:n(),
compact_b = 75,
augmented_b = mean(internet),
compact_se = (internet-compact_b)^2,
augmented_se = (internet-augmented_b)^2) %>%
select(i, state, internet, contains("compact"), contains("augmented"))
%>%
df.model summarize(augmented_sse = sum(augmented_se),
compact_sse = sum(compact_se),
pre = 1 - augmented_sse/compact_sse,
f = (pre/(pa-pc))/((1-pre)/(nrow(df.model)-pa)),
p_value = 1-pf(f, pa-pc, nrow(df.model)-1),
mean = mean(internet),
sd = sd(internet)) %>%
kable() %>%
kable_styling(bootstrap_options = "striped",
full_width = F)
| augmented_sse | compact_sse | pre | f | p_value | mean | sd |
|---|---|---|---|---|---|---|
| 1355.028 | 1595.71 | 0.1508305 | 8.703441 | 0.0048592 | 72.806 | 5.258673 |
= 1
df1 = 49
df2
ggplot(data = tibble(x = c(0, 10)),
mapping = aes(x = x)) +
stat_function(fun = "df",
geom = "area",
fill = "red",
alpha = 0.5,
args = list(df1 = df1,
df2 = df2),
size = 1,
xlim = c(qf(0.95, df1 = df1, df2 = df2), 10)) +
stat_function(fun = ~ df(x = .,
df1 = df1,
df2 = df2),
size = 0.5) +
scale_y_continuous(expand = expansion(add = c(0.001, 0.1))) +
labs(y = "Density",
x = "Proportional reduction in error")
We’ve implemented a one sample t-test (compare the p-value here to the one I computed above using PRE and the F statistic).
t.test(df.internet$internet, mu = 75)
One Sample t-test
data: df.internet$internet
t = -2.9502, df = 49, p-value = 0.004859
alternative hypothesis: true mean is not equal to 75
95 percent confidence interval:
71.3115 74.3005
sample estimates:
mean of x
72.806
9.4 Building a sampling distribution of PRE
Here is the general procedure for building a sampling distribution of the proportional reduction in error (PRE). In this instance, I compare the following two models
- Model C (compact): \(Y_i = 75 + \epsilon_i\)
- Model A (augmented): \(Y_i = \overline Y + \epsilon_i\)
whereby I assume that \(\epsilon_i \sim \mathcal{N}(0, \sigma)\).
For this example, I assume that I know the population distribution. I first draw a sample from that distribution, and then calculate PRE.
# make example reproducible
set.seed(1)
# set the sample size
= 50
sample_size
# draw sample from the population distribution (I've fixed sigma -- the standard deviation
# of the population distribution to be 5)
= tibble(observation = 1:sample_size,
df.sample value = 75 + rnorm(sample_size, mean = 0, sd = 5))
# calculate SSE for each model, and then PRE based on that
= df.sample %>%
df.summary mutate(compact = 75,
augmented = mean(value)) %>%
summarize(sse_compact = sum((value - compact)^2),
sse_augmented = sum((value - augmented)^2),
pre = 1 - (sse_augmented/sse_compact))
To generate the sampling distribution, I assume that the null hypothesis is true, and then take a look at what values for PRE we could expect by chance for our given sample size.
# simulation parameters
= 1000
n_samples = 50
sample_size = 75 # true mean of the distribution
mu = 5 # true standard deviation of the errors
sigma
# function to draw samples from the population distribution
= function(sample_size, mu, sigma){
fun.draw_sample = mu + rnorm(sample_size,
sample mean = 0,
sd = sigma)
return(sample)
}
# draw samples
= n_samples %>%
samples replicate(fun.draw_sample(sample_size, mu, sigma)) %>%
t() # transpose the resulting matrix (i.e. flip rows and columns)
# put samples in data frame and compute PRE
= samples %>%
df.samples as_tibble(.name_repair = ~ str_c(1:ncol(samples))) %>%
mutate(sample = 1:n()) %>%
pivot_longer(cols = -sample,
names_to = "index",
values_to = "value") %>%
mutate(compact = mu) %>%
group_by(sample) %>%
mutate(augmented = mean(value)) %>%
summarize(sse_compact = sum((value - compact)^2),
sse_augmented = sum((value - augmented)^2),
pre = 1 - sse_augmented/sse_compact)
# plot the sampling distribution for PRE
ggplot(data = df.samples,
mapping = aes(x = pre)) +
stat_density(geom = "line") +
labs(x = "Proportional reduction in error")
# calculate the p-value for our sample
%>%
df.samples summarize(p_value = sum(pre >= df.summary$pre)/n())
# A tibble: 1 × 1
p_value
<dbl>
1 0.394
Some code I wrote to show a subset of the samples.
%>%
samples as_tibble(.name_repair = "unique") %>%
mutate(sample = 1:n()) %>%
pivot_longer(cols = -sample,
names_to = "index",
values_to = "value") %>%
mutate(compact = mu) %>%
group_by(sample) %>%
mutate(augmented = mean(value)) %>%
ungroup() %>%
mutate(index = str_extract(index, pattern = "\\-*\\d+\\.*\\d*"),
index = as.numeric(index)) %>%
filter(index < 6) %>%
arrange(sample, index) %>%
head(15) %>%
kable(digits = 2) %>%
kable_styling(bootstrap_options = "striped",
full_width = F)
| sample | index | value | compact | augmented |
|---|---|---|---|---|
| 1 | 1 | 76.99 | 75 | 75.59 |
| 1 | 2 | 71.94 | 75 | 75.59 |
| 1 | 3 | 76.71 | 75 | 75.59 |
| 1 | 4 | 69.35 | 75 | 75.59 |
| 1 | 5 | 82.17 | 75 | 75.59 |
| 2 | 1 | 71.90 | 75 | 74.24 |
| 2 | 2 | 75.21 | 75 | 74.24 |
| 2 | 3 | 70.45 | 75 | 74.24 |
| 2 | 4 | 75.79 | 75 | 74.24 |
| 2 | 5 | 71.73 | 75 | 74.24 |
| 3 | 1 | 77.25 | 75 | 75.38 |
| 3 | 2 | 74.91 | 75 | 75.38 |
| 3 | 3 | 73.41 | 75 | 75.38 |
| 3 | 4 | 70.35 | 75 | 75.38 |
| 3 | 5 | 67.56 | 75 | 75.38 |
9.5 Misc
Some code to plot probability distributions together with values of interest highlighted.
= 3.73
value_mean = 2.05/sqrt(40)
value_sd = qnorm(0.025, mean = value_mean, sd = value_sd)
q_low = qnorm(0.975, mean = value_mean, sd = value_sd)
q_high qnorm(0.975) * value_sd
[1] 0.6352899
# density function
ggplot(data = tibble(x = c(2.73, 4.73)),
mapping = aes(x = x)) +
stat_function(fun = ~ dnorm(.,
mean = value_mean,
sd = value_sd),
size = 2) +
geom_vline(xintercept = c(q_low, q_high),
linetype = 2)
# quantile function
= tibble(x = c(rep(c(0.025, 0.975), each = 2),
df.paths -Inf, 0.025, -Inf, 0.975),
y = c(2.9, q_low,
2.9, q_high,
q_low, q_low,
q_high, q_high),group = rep(1:4, each = 2))
ggplot(data = tibble(x = c(0, 1)),
mapping = aes(x = x)) +
stat_function(fun = ~ qnorm(.,
mean = value_mean,
sd = value_sd)) +
geom_path(data = df.paths,
mapping = aes(x = x,
y = y,
group = group),
color = "blue",
size = 2,
lineend = "round") +
coord_cartesian(xlim = c(-0.05, 1.05),
ylim = c(2.9, 4.5),
expand = F)
9.6 Additional resources
9.6.1 Reading
- Judd, C. M., McClelland, G. H., & Ryan, C. S. (2011). Data analysis: A model comparison approach. Routledge. –> Chapters 1–4
9.7 Session info
Information about this R session including which version of R was used, and what packages were loaded.
sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9 purrr_0.3.4
[5] readr_2.1.2 tidyr_1.2.0 tibble_3.1.7 ggplot2_3.3.6
[9] tidyverse_1.3.1 janitor_2.1.0 kableExtra_1.3.4 knitr_1.39
loaded via a namespace (and not attached):
[1] lattice_0.20-45 svglite_2.1.0 lubridate_1.8.0 assertthat_0.2.1
[5] digest_0.6.29 utf8_1.2.2 R6_2.5.1 cellranger_1.1.0
[9] backports_1.4.1 reprex_2.0.1 evaluate_0.15 highr_0.9
[13] httr_1.4.3 pillar_1.7.0 rlang_1.0.2 readxl_1.4.0
[17] rstudioapi_0.13 jquerylib_0.1.4 Matrix_1.4-1 rmarkdown_2.14
[21] labeling_0.4.2 splines_4.1.2 webshot_0.5.3 munsell_0.5.0
[25] broom_0.8.0 compiler_4.1.2 modelr_0.1.8 xfun_0.30
[29] pkgconfig_2.0.3 systemfonts_1.0.4 mgcv_1.8-40 htmltools_0.5.2
[33] tidyselect_1.1.2 bookdown_0.26 fansi_1.0.3 viridisLite_0.4.0
[37] withr_2.5.0 crayon_1.5.1 tzdb_0.3.0 dbplyr_2.1.1
[41] grid_4.1.2 nlme_3.1-157 jsonlite_1.8.0 gtable_0.3.0
[45] lifecycle_1.0.1 DBI_1.1.2 magrittr_2.0.3 scales_1.2.0
[49] cli_3.3.0 stringi_1.7.6 farver_2.1.0 fs_1.5.2
[53] snakecase_0.11.0 xml2_1.3.3 bslib_0.3.1 ellipsis_0.3.2
[57] generics_0.1.2 vctrs_0.4.1 tools_4.1.2 glue_1.6.2
[61] hms_1.1.1 fastmap_1.1.0 yaml_2.3.5 colorspace_2.0-3
[65] rvest_1.0.2 haven_2.5.0 sass_0.4.1


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@miniScore(innings: cricketModel.Innings) = {
@innings match {
case _ if (innings.declared) => { @innings.runsScored - @innings.wickets declared }
case _ if (innings.forfeited) => { @innings.runsScored - @innings.wickets forfeited }
case _ if (innings.allOut) => { @innings.runsScored }
}
}
@score(innings: cricketModel.Innings) = {
@innings match {
case _ if (!innings.closed) => { @innings.runsScored - @innings.wickets }
case _ if (innings.declared) => { @innings.runsScored - @innings.wickets declared }
case _ if (innings.forfeited) => { @innings.runsScored - @innings.wickets forfeited }
case _ if (innings.allOut) => { @innings.runsScored all out }
}
}


Unit Amenities
| Amenity | Available |
|---|---|
| Dishwasher | Unknown Yes No |
| Air Conditioning | Unknown Yes No |
| Furnished | Unknown Yes No |
| Flooring | Unknown {{unit.FlooringInfo}} |
Unit Attributes
| Amenity | Available |
|---|---|
| Property | Unknown {{unit.PropertyName}} |
| Square Feet | Unknown {{unit.SquareFeet}} |
| Bedrooms | Unknown {{unit.NumberOfBedrooms}} |
| Bathrooms | Unknown {{unit.NumberOfBaths}} |
| Gross Potential Rent | Unknown {{unit.GrossPotentialRent}} |
| Status | Unknown {{unit.UnitStatus}} |
| Address |
Unknown
{{unit.UnitAddress1}}
{{unit.UnitAddress2}} |
| Unit Type |
Unknown
{{unit.UnitType}}
|
Lease History
No leases
According to our files, this unit has never been leased!
| Tenant | Occ Type | Balance | |
|---|---|---|---|
| {{lease.FirstName}} {{lease.LastName}} Onboarding pending | Uknowm Former Current Info | {{lease.BalanceCents}} | Details |


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