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---
layout: post
title: ! 'Rake Migration: Track Rake Tasks with versions'
tags:
- rails
- rake
- ruby
- ruby on rails
- Technology
status: publish
type: post
published: true
meta:
_su_rich_snippet_type: none
_edit_last: '2'
_wp_old_slug: ''
dsq_thread_id: '219274761'
---
I have started working on a plugin which helps rails projects to maintain the list of rake tasks.
We are working on a project there are four to six teams at different geo-locations Bangalore, Kolkata, Edmonton etc.For the same project we have different environments like Developemnt, Testing, Staging, QA, QA2, Beta etc.All teams are working with new features, as well as bug fixes.
Many times we found a situation that a specific rake task should be run on a specific environment to fix the data. A lot of time team members forgot to shoot a mail and tell every team about a rake task which will fix a bug on specific environment. As other people update code base and start using the application they got stuck and it take a lot of time to resolve the issue that a specific task was not run because team did not get any information as such.
To resolve this issue we got a idea form rake tasks to migrate database (db:migrate). So if we can manage rake tasks with versions and if we can keep track of tasks those have been run, and yet to run on system. One can generate a ruby file write there any ruby code or invoke any rake task, and upload to repository other people only take update from repo and run a simple commend and the system will update.
Here we don’t have to worry to inform everybody about new task to fix bug or update system.
Here is the URL for plugin
http://github.com/vatrai/rake_migration
By using generators one can generate blank ruby files prefix with time-stamped version. Version helps to keep track of tasks that are Run, yet to Run on the system. One can specify Rails environment in ruby files, specify what data fix should be run on a specified environment using simple if condition.
To generate simple ruby file use:
ruby script/generate rake_migration <file_name>
This command creates a blank ruby file in {RAILS_ROOT}/rake/migrate directory. Write ruby code or invoke rake task in the generated ruby file.
To run generated files run rake command:
{RAILS_ROOT} rake rake_migration:migrate
This command runs remaining(yet to run) ruby files in {RAILS_ROOT}/rake/migrate and saves version in rake_migrations table in database.


--- title: Beginner's Health and Fitness Guide layout: post ---
I don't want to become some huge bodybuilder freak, I just want to get in better shape and look better. Should I read this?That's what this guide is for. It's a basic guide to diet & fitness for beginners who want to get in better shape. If you want to look better, improve your overall athletic ability, or just improve your health, read on. If you're a bodybuilder or athlete, you probably already know most of this stuff.


Which topics spark the most heated debates on social media? How do social media users interact when they disagree? Can we nudge them towards constructive disagreement? Answering these questions helps us understand large-scale societal mechanisms - including phenomena such as partisan sharing, echo chambers, and filter bubbles, which might be detrimental to the democratic process. It also allows us to develop tools and techniques that can be used by journalists to understand which issues divide the public; social scientists to understand how polarization is manifested in social interactions; and web users to improve their experience online.
This tutorial presents a systematic review of polarization as manifested online, and in particular on social media. In the beginning, we clarify the concept of polarization and the related nomenclature, drawing from the social and political sciences. Subse- quently, we review algorithmic techniques for detection, quantification, and mitigation of polarization. We conclude the tutorial by presenting open challenges and promising research directions for Web Scientists.
The slides are available here (Dropbox, ~80MB).
For convenience, we also split the slides into different sections:
Part1: Introduction
Part2: Exploring Polarization
Part3: Polarization Models
Part4: Measuring Polarization
Part5: Mitigating Polarization
Part6: Future Work
Kiran Garimella is a postdoc at EPFL. He recently finished his PhD at Aalto University. His research focuses on identifying and combating filter bubbles on social media. Previously he worked as a Research Engineer at Yahoo Research, QCRI and as an Research Intern at LinkedIn and Amazon. His research on reducing polarization on social media received the best student paper awards at WSDM and WebScience 2017.
Twitter: @gvrkiran
Gianmarco De Francisci Morales is a Research Leader at ISI Foundation. Previously he worked as a Scientist at QCRI, as a Visiting Scientist at Aalto University in Helsinki, as a Research Scientist at Yahoo Labs in Barcelona, and as a Research Associate at ISTI-CNR in Pisa. He received his Ph.D. in Computer Science and Engineering from the IMT Institute for Advanced Studies of Lucca in 2012. His research focuses on scalable data mining, with an emphasis on Web mining and data-intensive scalable computing systems. He is an active member of the open source community of the Apache Software Foundation, working on the Hadoop ecosystem, and a committer for the Apache Pig project. He is one of the lead developers of Apache SAMOA, an open-source platform for mining big data streams. He co-organizes the workshop series on Social News on the Web (SNOW), co-located with the WWW conference.
Twitter: @gdfm7
Michael Mathioudakis is an assistant professor at the University of Helsinki, and Chair for Algorithmic Data Science at the Helsinki Center for Digital Humanities (HELDIG). Prior to that, he was a Postdoctoral Researcher at Aalto University and received his PhD from the University of Toronto. His research focuses on the analysis of user generated content on social media, with a recent emphasis on online polarization and algorithmnic fairness.
Twitter: @mmathioudakis
Aristides Gionis is a professor in the department of Computer Science in Aalto University. He was a visiting professor in the University of Rome in fall 2016, and a senior research scientist in Yahoo! Research between 2006 and 2012. He is currently serving as an action editor in the Data Management and Knowledge Discovery journal (DMKD), an associate editor in the ACM Transactions on Knowledge Discovery from Data (TKDD), and a managing editor in Internet Mathematics. He has contributed in several areas of data science, such as algorithmic data analysis, web mining, social-media analysis, data clustering, and privacy-preserving data mining. His current research is funded by the Academy of Finland (projects Nestor, Agra, AIDA) and the European Commission (project SoBigData).
Twitter: @gionis
Go to top


Represents an individual BLOCKS device.
Inherits juce::ReferenceCountedObject.
Public Member Functions | |
| ~Block () override | |
| Destructor. More... | |
| bool | operator== (const Block &other) const noexcept |
| Two blocks are considered equal if they have the same UID. More... | |
| bool | operator!= (const Block &other) const noexcept |
| Two blocks are considered equal if they have the same UID. More... | |
| virtual Type | getType () const =0 |
| Returns the type of this device. More... | |
| bool | isControlBlock () const |
| Returns true if this a control block. More... | |
| virtual juce::String | getDeviceDescription () const =0 |
| Returns a human-readable description of this device type. More... | |
| virtual float | getBatteryLevel () const =0 |
| Returns the battery level in the range 0.0 to 1.0. More... | |
| virtual bool | isBatteryCharging () const =0 |
| Returns true if the battery is charging. More... | |
| virtual bool | isConnected () const =0 |
| Returns true if this block is connected and active. More... | |
| virtual juce::Time | getConnectionTime () const =0 |
| Returns the time this block object was connected to the topology. More... | |
| virtual bool | isConnectedViaBluetooth () const =0 |
| Returns true if this block or the master block this block is connected to, is connected via bluetooth. More... | |
| virtual bool | isMasterBlock () const =0 |
| Returns true if this block is directly connected to the application, as opposed to only being connected to a different block via a connection port. More... | |
| virtual UID | getConnectedMasterUID () const =0 |
| Returns the UID of the master block this block is connected to. More... | |
| virtual int | getWidth () const =0 |
| Returns the width of the device in logical device units. More... | |
| virtual int | getHeight () const =0 |
| Returns the height of the device in logical device units. More... | |
| virtual bool | isHardwareBlock () const =0 |
| Returns true if the device is a physical hardware block (i.e. More... | |
| virtual float | getMillimetersPerUnit () const =0 |
| Returns the length of one logical device unit as physical millimeters. More... | |
| virtual BlockArea | getBlockAreaWithinLayout () const =0 |
| Returns the area that this block covers within the layout of the group as a whole. More... | |
| virtual int | getRotation () const =0 |
| Returns the rotation of this block relative to the master block in 90 degree steps clockwise. More... | |
| virtual LEDGrid * | getLEDGrid () const =0 |
| If this block has a grid of LEDs, this will return an object to control it. More... | |
| virtual LEDRow * | getLEDRow ()=0 |
| If this block has a row of LEDs, this will return an object to control it. More... | |
| virtual juce::Array< StatusLight * > | getStatusLights () const =0 |
| If this block has any status LEDs, this will return an array of objects to control them. More... | |
| virtual TouchSurface * | getTouchSurface () const =0 |
| If this block has a pressure-sensitive surface, this will return an object to access its data. More... | |
| virtual juce::Array< ControlButton * > | getButtons () const =0 |
| If this block has any control buttons, this will return an array of objects to control them. More... | |
| virtual bool | supportsGraphics () const =0 |
| This returns true if the block supports generating graphics by drawing into a JUCE Graphics context. More... | |
| virtual juce::Array< ConnectionPort > | getPorts () const =0 |
| Returns a list of the connectors that this device has. More... | |
| virtual juce::Result | setProgram (std::unique_ptr< Program >, ProgramPersistency persistency=ProgramPersistency::setAsTemp)=0 |
| Sets the Program to run on this block. More... | |
| virtual Program * | getProgram () const =0 |
| Returns a pointer to the currently loaded program. More... | |
| void | addProgramLoadedListener (ProgramLoadedListener *) |
| Adds a new listener for program load completions. More... | |
| void | removeProgramLoadedListener (ProgramLoadedListener *) |
| Removes a listener for program load completions. More... | |
| virtual void | sendProgramEvent (const ProgramEventMessage &)=0 |
| Sends a message to the currently loaded program. More... | |
| void | addProgramEventListener (ProgramEventListener *) |
| Adds a new listener for custom program events from the block. More... | |
| void | removeProgramEventListener (ProgramEventListener *) |
| Removes a listener for custom program events from the block. More... | |
| virtual juce::uint32 | getMemorySize ()=0 |
| Returns the overall memory of the block. More... | |
| virtual juce::uint32 | getHeapMemorySize ()=0 |
| Returns the size of the data block that setDataByte and other functions can write to. More... | |
| virtual void | setDataByte (size_t offset, juce::uint8 value)=0 |
| Sets a single byte on the littlefoot heap. More... | |
| virtual void | setDataBytes (size_t offset, const void *data, size_t num)=0 |
| Sets multiple bytes on the littlefoot heap. More... | |
| virtual void | setDataBits (juce::uint32 startBit, juce::uint32 numBits, juce::uint32 value)=0 |
| Sets multiple bits on the littlefoot heap. More... | |
| template<typename Type > | |
| void | setData (juce::uint32 offset, Type value) |
| Sets a single, 32 bit or less, value on the littlefoot heap. More... | |
| virtual juce::uint8 | getDataByte (size_t offset)=0 |
| Gets a byte from the littlefoot heap. More... | |
| virtual void | saveProgramAsDefault ()=0 |
| Sets the current program as the block's default state. More... | |
| virtual void | resetProgramToDefault ()=0 |
| Resets the loaded program to the block's default state. More... | |
| void | addConfigItemListener (ConfigItemListener *) |
| Adds a new listener for config item changes. More... | |
| void | removeConfigItemListener (ConfigItemListener *) |
| Removes a listener for config item changes. More... | |
| virtual juce::uint32 | getMaxConfigIndex ()=0 |
| Returns the maximum number of config items available. More... | |
| virtual bool | isValidUserConfigIndex (juce::uint32 item)=0 |
| Determine if this is a valid config item index. More... | |
| virtual juce::int32 | getLocalConfigValue (juce::uint32 item)=0 |
| Get local config item value. More... | |
| virtual void | setLocalConfigValue (juce::uint32 item, juce::int32 value)=0 |
| Set local config item value. More... | |
| virtual void | setLocalConfigRange (juce::uint32 item, juce::int32 min, juce::int32 max)=0 |
| Set local config item range. More... | |
| virtual void | setLocalConfigItemActive (juce::uint32 item, bool isActive)=0 |
| Set if config item is active or not. More... | |
| virtual bool | isLocalConfigItemActive (juce::uint32 item)=0 |
| Determine if config item is active or not. More... | |
| virtual ConfigMetaData | getLocalConfigMetaData (juce::uint32 item)=0 |
| Get config item metadata. More... | |
| virtual void | requestFactoryConfigSync ()=0 |
| Request sync of factory config with block. More... | |
| virtual void | resetConfigListActiveStatus ()=0 |
| Reset all items active status. More... | |
| virtual void | factoryReset ()=0 |
| Perform factory reset on Block. More... | |
| virtual void | blockReset ()=0 |
| Reset this Block. More... | |
| virtual bool | setName (const juce::String &name)=0 |
| Set Block name. More... | |
| virtual void | setLogger (std::function< void(const Block &block, const juce::String &)> loggingCallback)=0 |
| Allows the user to provide a function that will receive log messages from the block. More... | |
| virtual bool | sendFirmwareUpdatePacket (const juce::uint8 *data, juce::uint8 size, std::function< void(juce::uint8, juce::uint32)> packetAckCallback)=0 |
| Sends a firmware update packet to a block, and waits for a reply. More... | |
| virtual void | addDataInputPortListener (DataInputPortListener *) |
| Adds a new listener for the data input port. More... | |
| virtual void | removeDataInputPortListener (DataInputPortListener *) |
| Removes a listener for the data input port. More... | |
| virtual void | sendMessage (const void *messageData, size_t messageSize)=0 |
| Sends a message to the block. More... | |
Static Public Member Functions | |
| static bool | isControlBlock (Block::Type) |
| Returns true if Block::Type is a control block. More... | |
Public Attributes | |
| const juce::String | serialNumber |
| The Block's serial number. More... | |
| juce::String | versionNumber |
| The Block's version number. More... | |
| juce::String | name |
| The Block's name. More... | |
| const UID | uid |
| This Block's UID. More... | |
| ProgramPersistency | programPersistency { ProgramPersistency::setAsTemp } |
Protected Member Functions | |
| Block (const juce::String &serialNumberToUse) | |
| Block (const juce::String &serial, const juce::String &version, const juce::String &name) | |
Protected Attributes | |
| juce::ListenerList< ProgramLoadedListener > | programLoadedListeners |
| juce::ListenerList< ProgramEventListener > | programEventListeners |
| juce::ListenerList< ConfigItemListener > | configItemListeners |
| juce::ListenerList< DataInputPortListener > | dataInputPortListeners |
Classes | |
| struct | BlockArea |
| A simple struct representing the area of a block. More... | |
| struct | ConfigItemListener |
| Listener interface to be informed of block config changes. More... | |
| struct | ConfigMetaData |
| Metadata for a given config item. More... | |
| struct | ConnectionPort |
| These are the edge-connectors that a device may have. More... | |
| struct | DataInputPortListener |
| Interface for objects listening to input data port. More... | |
| struct | Program |
| A program that can be loaded onto a block. More... | |
| struct | ProgramEventListener |
| Interface for objects listening to custom program events. More... | |
| struct | ProgramEventMessage |
| A message that can be sent to the currently loaded program. More... | |
| struct | ProgramLoadedListener |
| Listener interface to be informed of program loaded events. More... | |
Public Types | |
| enum | Type { unknown = 0 , lightPadBlock , liveBlock , loopBlock , developerControlBlock , touchBlock , seaboardBlock , lumiKeysBlock } |
| The different block types. More... | |
| enum class | ProgramPersistency { setAsTemp , setAsDefault } |
| Determines whether set program will be a temporary or default script saved to flash. More... | |
| using | Ptr = juce::ReferenceCountedObjectPtr< Block > |
| The Block class is reference-counted, so always use a Block::Ptr when you are keeping references to them. More... | |
| using | Array = juce::ReferenceCountedArray< Block > |
| The Block class is reference-counted, so Block::Array is useful when you are storing lists of them. More... | |
| using | UID = juce::uint64 |
| This type is used for the unique block identifier. More... | |
| using | Timestamp = juce::uint32 |
| This type is used for timestamping events. More... | |
|
override |
Destructor.
|
protected |
|
protected |
|
noexcept |
Two blocks are considered equal if they have the same UID.
References uid.
|
noexcept |
Two blocks are considered equal if they have the same UID.
References uid.
|
pure virtual |
Returns the type of this device.
| bool Block::isControlBlock | ( | ) | const |
Returns true if this a control block.
|
static |
Returns true if Block::Type is a control block.
|
pure virtual |
Returns a human-readable description of this device type.
|
pure virtual |
Returns the battery level in the range 0.0 to 1.0.
|
pure virtual |
Returns true if the battery is charging.
|
pure virtual |
Returns true if this block is connected and active.
|
pure virtual |
Returns the time this block object was connected to the topology.
Only valid when isConnected == true.
|
pure virtual |
Returns true if this block or the master block this block is connected to, is connected via bluetooth.
Only valid when isConnected == true.
|
pure virtual |
Returns true if this block is directly connected to the application, as opposed to only being connected to a different block via a connection port.
|
pure virtual |
Returns the UID of the master block this block is connected to.
|
pure virtual |
Returns the width of the device in logical device units.
|
pure virtual |
Returns the height of the device in logical device units.
|
pure virtual |
Returns true if the device is a physical hardware block (i.e.
not a virtual block).
|
pure virtual |
Returns the length of one logical device unit as physical millimeters.
|
pure virtual |
Returns the area that this block covers within the layout of the group as a whole.
The coordinates are in logical block units, and are relative to the origin, which is the master block's top-left corner.
|
pure virtual |
Returns the rotation of this block relative to the master block in 90 degree steps clockwise.
|
pure virtual |
If this block has a grid of LEDs, this will return an object to control it.
Note that the pointer that is returned belongs to this object, and the caller must neither delete it or use it after the lifetime of this Block object has finished. If there are no LEDs, then this method will return nullptr.
|
pure virtual |
If this block has a row of LEDs, this will return an object to control it.
Note that the pointer that is returned belongs to this object, and the caller must neither delete it or use it after the lifetime of this Block object has finished. If there are no LEDs, then this method will return nullptr.
|
pure virtual |
|
pure virtual |
If this block has a pressure-sensitive surface, this will return an object to access its data.
Note that the pointer returned does is owned by this object, and the caller must neither delete it or use it after the lifetime of this Block object has finished. If the device is not touch-sensitive, then this method will return nullptr.
|
pure virtual |
|
pure virtual |
This returns true if the block supports generating graphics by drawing into a JUCE Graphics context.
This should only be true for virtual on-screen blocks; hardware blocks will instead use the LED Grid for visuals.
|
pure virtual |
Returns a list of the connectors that this device has.
|
pure virtual |
|
pure virtual |
Returns a pointer to the currently loaded program.
| void Block::addProgramLoadedListener | ( | ProgramLoadedListener * | ) |
Adds a new listener for program load completions.
| void Block::removeProgramLoadedListener | ( | ProgramLoadedListener * | ) |
Removes a listener for program load completions.
|
pure virtual |
Sends a message to the currently loaded program.
To receive the message the program must provide a littlefoot function called handleMessage with the following form:
| void Block::addProgramEventListener | ( | ProgramEventListener * | ) |
Adds a new listener for custom program events from the block.
| void Block::removeProgramEventListener | ( | ProgramEventListener * | ) |
Removes a listener for custom program events from the block.
|
pure virtual |
Returns the overall memory of the block.
|
pure virtual |
Returns the size of the data block that setDataByte and other functions can write to.
|
pure virtual |
Sets a single byte on the littlefoot heap.
Referenced by setData().
|
pure virtual |
Sets multiple bytes on the littlefoot heap.
|
pure virtual |
Sets multiple bits on the littlefoot heap.
| void Block::setData | ( | juce::uint32 | offset, |
| Type | value | ||
| ) |
Sets a single, 32 bit or less, value on the littlefoot heap.
References setDataByte().
|
pure virtual |
Gets a byte from the littlefoot heap.
|
pure virtual |
Sets the current program as the block's default state.
|
pure virtual |
Resets the loaded program to the block's default state.
| void Block::addConfigItemListener | ( | ConfigItemListener * | ) |
Adds a new listener for config item changes.
| void Block::removeConfigItemListener | ( | ConfigItemListener * | ) |
Removes a listener for config item changes.
|
pure virtual |
Returns the maximum number of config items available.
|
pure virtual |
Determine if this is a valid config item index.
|
pure virtual |
Get local config item value.
|
pure virtual |
Set local config item value.
|
pure virtual |
Set local config item range.
|
pure virtual |
Set if config item is active or not.
|
pure virtual |
Determine if config item is active or not.
|
pure virtual |
Get config item metadata.
|
pure virtual |
Request sync of factory config with block.
|
pure virtual |
Reset all items active status.
|
pure virtual |
Perform factory reset on Block.
|
pure virtual |
Reset this Block.
|
pure virtual |
Set Block name.
|
pure virtual |
Allows the user to provide a function that will receive log messages from the block.
|
pure virtual |
Sends a firmware update packet to a block, and waits for a reply.
Returns an error code.
|
virtual |
Adds a new listener for the data input port.
|
virtual |
Removes a listener for the data input port.
|
pure virtual |
Sends a message to the block.
| using Block::Ptr = juce::ReferenceCountedObjectPtr<Block> |
The Block class is reference-counted, so always use a Block::Ptr when you are keeping references to them.
| using Block::Array = juce::ReferenceCountedArray<Block> |
The Block class is reference-counted, so Block::Array is useful when you are storing lists of them.
| using Block::UID = juce::uint64 |
This type is used for the unique block identifier.
| using Block::Timestamp = juce::uint32 |
This type is used for timestamping events.
It represents a number of milliseconds since the block device was booted.
| enum Block::Type |
The different block types.
|
strong |
| const juce::String Block::serialNumber |
The Block's serial number.
| juce::String Block::versionNumber |
The Block's version number.
| juce::String Block::name |
The Block's name.
| const UID Block::uid |
This Block's UID.
This will be globally unique, and remains constant for a particular device.
Referenced by operator!=(), and operator==().
| ProgramPersistency Block::programPersistency { ProgramPersistency::setAsTemp } |
|
protected |
|
protected |
|
protected |
|
protected |


Main section
This is a paragraph. If you say it's not, then you are Wrong! Check the html it's a paragraph. That's right its a paragraph about a paragraph, even though it's totally lacking in content and creativity but what the hell. It's friday friday something something friday.


Agnes at State College
After Agnes was refused entry to the Pennsylvania State Forestry Academy, she didn’t give up on her ambitions for higher education. In the fall of 1917, she was one of five “farmerettes” studying agriculture at State College (now Pennsylvania State University). “Five girls with back-to-the-farm hankerings, are studying scientific farming in the two-year agricultural course at the Pennsylvania State College,” the Indiana Gazette reported. Even though the United States was by then at war, the newspaper account claimed that this had “nothing to do whatever in their choice of a profession. They simply wanted to learn how to feed chickens, hoe beans, milk cows and plough. Later they expect to use their knowledge in managing their own farms.”
State College’s two-year course in agriculture was, according to the 1917-18 course catalog, “designed to meet the needs of young men with farm experience who are not prepared to enter the four-year courses in agriculture.” (91) The emphasis on young men was not entirely true; in 1912, the course had been formally opened to women–albeit with modification. Students could take courses in the domestic arts, while also developing knowledge in scientific agriculture, with the ultimate goal of being able to “make a living on the farm.” “Country girls” who graduate “find on their return home that their interests are elsewhere. They have been unfitted rather than fitted for life in the country,” wrote Margaret B. MacDonald in The Penn State Farmer. By allowing women to gain a more well-rounded knowledge of agriculture, “the object of the course is to make successful, resourceful, happy women of farmers’ wives and daughters.” (201)
Both the newspaper account and Penn State’s own publication attributed the goals of the two-year agriculture program and the women who attended it to developing the knowledge and skills to work on farms, often as wives and daughters of farmers. For someone as independent as Agnes, who had at one point aspired to the male-dominated profession of forestry, would this have been her goal?
Agnes’s ultimate goal may in fact have been to further her education beyond the initial two-year program, as she subsequently enrolled in the four-year course in Horticulture at Penn State. This program included courses on plant breeding, floriculture, vegetable gardening, landscape gardening, and entomology, as well as a summer practicum, consisting of “six weeks of survey work in commercial truck gardens, florists’ establishments, nurseries, orchards, greenhouses, and small fruit plantations.” (126) Classes, as described in the course catalog, included recitation and practicum hours, emphasizing the practical application of the studies the students were undertaking.
Apart from her studies, Agnes appears to have been an active student at State College. She was a member of the Press Club, Crab Apple Club, Current Events Club, and Penn State Grange, and was active in athletics. She played hockey and basketball, received class numerals for her high scoring, and even served as president of the Women’s Athletic Association during her senior year.
One of Agnes’s more amusing activities involved serving on a committee that banned “improper dancing,” such as “cheek-to-cheek” or “toddling,” at house parties and college dances. The committee was “instructed to demonstrate before the Women’s Student Association just what is and what is not acceptable as proper form on the dance floor. This group will meet at the close of the Christmas vacation and their recommendations will be law.”
When Agnes graduated from State College in 1922, she became the first in the Newman family to earn a college degree. As the youngest child, she likely benefitted from changing attitudes about higher education for women. It is somewhat surprising, however, that only a few months after her graduation, Agnes married a farmer, fulfilling Penn State’s goal for her to become a “successful, resourceful, happy” farmer’s wife.
Agnes and her husband, Milton Lightwood, performed agricultural work at her sister Meg’s settlement house and then started their own, ultimately unsuccessful, fruit farm in Maryland. Agnes’s horticultural education would continue, however, as she later attended the Ambler School of Horticulture for Women, and after her divorce from Milton in the 1940s, she finally embarked on the professional career in horticulture that she had initially prepared for during her time at State College.
Works Referenced
“Five Girls Study Farming.” The Indiana Gazette (Indiana, Pennsylvania), 9 October 1917, p. 9.
“Improper Dancing Ban.” The Reading Times (Reading, Pennsylvania), 18 December 1920, p. 3.
MacDonald, Margaret B. “Education of Girls for Life on the Farm.” The Penn State Farmer, 1912, p. 200-201.
Pennsylvania State College. The Pennsylvania State College Bulletin: General Catalogue 1917-1918. State College, 1918.
Pennsylvania State College. The Pennsylvania State College Bulletin: General Catalogue 1919-1920. State College, 1920.
Image: “Farming Country” by G. M. Schwartz from the University of Wisconsin Digital Collections.


HOME - ABOUT US
VITELLIUS LOGISTICS, INC. was established in March 2003 as a firm servicing the customs brokerage requirements of clients. It first held office in the Regina Building in Escolta, Manila. Since it was located in the heart of Manila, only a few minutes away from the Manila International Container Port, Port of Manila, and the Ninoy Aquino International Airport it was easily accessible and highly convenient for the company to facilitate its operational activities and requirements.
Since its establishment in 2003, the company has been experiencing exponential growth. Such growth resulted to an increase in its manpower resources thus, new divisions such as Brokerage, Sales, Human Resources, Trucking and Warehousing were created to ensure that the high quality of service being provided is sufficiently monitored and maintained. In 2005 it became inevitable that the company moved to a bigger place to enable it to operate efficiently and fulfill the company’s service commitment to its customers. For its ability to provide fast, cost efficient and reliable service solutions to the complex and high demands of its customers that the reputation of the company has been built on.
In July of 2005, VITELLIUS LOGISTICS, INC. strategically moved office to Parañaque City to increasing trade requirements such as cargo warehousing and space for its pool of rolling and moving equipments. The move was in-line with the company’s vision of a full-service cargo handling company that aims to partner with its client in producing the highest level of performance and products that meets the ever changing and highly demanding requirements of the global business community. The warehouse is fully operational and equipped with material and moving resources, and is well secured and has safety hazard protection.
VITELLIUS LOGISTICS, INC. is managed by the General Manager who has a vast 30-year forwarding and customs brokerage experience. It also has in its pool, a group of highly skilled Managers who lead a group of well trained staff in providing a highly efficient and reliable service. All personnel are continuously trained to ensure that our commitment to provide service and product consistency exceeds customer expectation.
Today, VITELLIUS LOGISTICS, INC. is committed to maintain fast, reliable and cost-efficient service, which is our competitive edge. Through its partners, the company is in a great position to carry out its service commitments to all clients in the Philippines, and the global community.


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@855
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5 months |
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updated copyright to 2016
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@800
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11 months |
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updated to use pathos.pools
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17 months |
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copyright updated to 2015; added to examples2
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added license and copyright to every file in certain branches
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merged UQ and OUQ examples into trunk; update use of pm.coords to …
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renaming of some of the measure methods, including dirac_measure to …
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func_pickle not needed for MPI2 either, so commented it out;
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@677
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updated solver docs to use Pool; nested solver examples use …
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fix: fixed typo in save state for nested optimizers;
updated UQ 'examples' …
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@675
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updated UQ branch to use new pathos/pyina Pools
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updated to new sausage model; added vaA model viewer
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memoized0 functions renamed to memoized, memoized class to memoize; …
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update caching to explicitly use deep_round
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added hausdorff sausage code and partial envelope code
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allow hausdorff normalization of y
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TEST_OUQ_1dSurr* demonstrates passing in a monitor for all print …
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@585
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added constraints code to impose bounds constraints in legacy
added …
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made fixed lower bound for Y a little more generic
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added 'info' keyword to LoggingMonitor? for logging info during init;
added …
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merge of dirac_measure plus compressed, paramtrans, and legacydata to …
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data plotter now 'scenario' plotter
support options similar to …
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enable toggle between 'expected' coord alignment and values-last alignment
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@564
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cone plotter now a more generic script, takes commandline input;
replaces …
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enable selection of color for datapoints and cone
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better bounds clipping for datapoints; allow coneless plotting of data
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fmin_powell with full_output return more standard (moved direc to end)
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npop to 20 for set_feasible; expose maxiter to user in impose_short; …
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set_valid default maxiter to 1000;
fix validation test code in paramtrans
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fix: graphical_distance optimization is short-circuited when Cx = 0;
tuned …
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bug fix: correct upper bounds Y_upper not Y_lower, uncommented …
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tjs |
Added 'sausage' branch with working OUQ sausage code using …
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tjs |
Added 'sausage' branch with working OUQ sausage code using …
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bugfix for cutoff == True; speedup for flatten and graphical_distance
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moved valid to paramtrans; moved dataset to legacydata;
tighter coupling …
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bugfixes to valid, impose_valid, etc for model validity as …
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commented out unused functions: expand, split_xy, mend_xy, generate, …
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fix set_valid passing of kwds (esp. cutoff); TEST* scripts for model …
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short* and valid* are now primarily dataset methods;
added check for model …
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fix: don't set cutoff=Cv when raw=True
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give short_wrt_* and valid_wrt_model more options (raw, all, cutoff, ...)
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added model validity core code
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fix: lipschitz_distance only uses tol; however can also take cutoff, ytol
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added short_ytol and ytol to allow for wiggle room in shortness of values
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from cutoff to tol,ytol in lipschitz_distance and lipschitz_max;
bugfix …
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bugfix: overriding default monitors was broken in solver one-liners
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enable diffev solvers to accept strategy;
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enable fmin_powell one-liner to configure generations termination …
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fixed init funciton for scenarios so accepts product measures;
allow …
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split dataset files and dataset reader/writers
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added set_expect and get_expect for dirac_measures; easier debug for …
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updated multiprocessing version of OUQ_StAlData to scenarios
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added scenario class, a product_measure with values;
added repeat and …
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safe is one-sided, not pointwise
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added check short_wrt_self in main constraints function
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set short_tol to 1e-9
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added data (and cone) plotter
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added multiprocessing version of StAl? driver
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StAlData?: zero out short_tol, set ngen = 100
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tuning optimization of legacy shortness
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added datapoints for examples in figure 5.2
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added 1D examples; bugfix to catch short_wrt_self violations
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blamelist fail return the pairs of failure indexes or set of failure …
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transpose returned matrix in lorentz_metric
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bugfix euclidean distance, now is manhattan distance
modify 'select' to …
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initial version of calculating UQ diameters with multiprocessing
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further documentation for code in legacy branch;
scaled back import …
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added docstrings for some of the new methods in legacy branch
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added legacyOUQ branch
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populate SetConstraints? method to UQ branch
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new methods for product measure: load, flatten, pts, wts, pos;
more …
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change some examples to rely less on monitors and more on solver internals
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migrated "Null" to monitors; set StepMon/Evalmon? is now a method
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moved _flat_split to split_param
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migrated almostEqual from approx_equal to numpy.allclose
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mmckerns |
updated with the Sow to Monitor change from r466
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@465
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5 years |
mmckerns |
all solvers import through 'solvers', and tools through 'tools'
renamed …
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5 years |
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allow 'impose_expectation' to take constraints function: x' = …
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@444
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5 years |
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cleanup: these are included in mystic.math
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@443
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updated basic OUQ example to use measure math in mystic.math
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@414
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6 years |
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updated queue submission examples for 'scheduler' keyword
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6 years |
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bugfix in best_dimensions; examples2 files now use scripts
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6 years |
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improved OUQ examples, allow tweakable scale in cost
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6 years |
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extended Sows/Solvers? to log solver 'rank' (see ticket #94)
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6 years |
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deleted outdated example
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@255
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6 years |
mmckerns |
OUQ code and plotters
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@253
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6 years |
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added parallel diameter batchgrid for QSUB
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6 years |
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cleanup for mystic tests; added UQ example with mapped diameter …
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moved "approx_equal" to mystic.math
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6 years |
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created "math" subdirectory, migrated "grid" and "poly" tools
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added ScattershotSolver? to nested solvers;
merged scatter.py to …
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added BatchGridSolver? and abstract_nested_solver class
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mmckerns |
mod of "QSUB" code to run on with moab+slurm instead of torque+openmpi
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6 years |
mmckerns |
added function for "approximately_equal" comparisons
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6 years |
mmckerns |
allow settable tmpfile directory, to better deal with queue launches; …
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6 years |
mmckerns |
bugfix (hopefully) for torque_launcher.
now waits until "-o outfile" …
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mmckerns |
exended ez_map to work with the torque_launcher.
Broken, as qsub is …
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mmckerns |
modified example to use new SetMapper? interface
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removed obsolete launchers.py
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Personally I think JavaScript looks more like CSS code than HTML code and that is about where the similarities end. JavaScript is an incredibly powerful and popular programming language which is not just limited to webpage design, it can be found in programs used for word processing and PDF viewing/editing. The main function of JavaScript on websites is to help make them a lot more interactive for users.
Control flow is the order in which things are done, generally following the left to right, top to bottom order. The exception to this order is within loops, if you have a loop in your code then as long as certain conditions are met, the program will run inside the loop within the main code.  You get up (way too early) in the morning, drive to work and then start baking. So far you have followed a "control flow". Once at work you start baking, you are making cookies today and you need to stir the mixture in the bowl. Obviously to make good cookies you need to stir it more than once, so the repetitive action of stirring is comparable to a "loop" within the code. Once certain conditions are met (the cookie batter is combined properly) you exit the loop and continue with the next steps (the rest of the main code).
The main difference batween accessing data from an array over an object is that you need to specify which specific piece of data you want from the array. You could think of the array as being a numbered list of items, and you need to include instructions in your code as to which list it should be looking at first, and then the number(s) of the specific item(s) you want from that list.
A function is sort of like a miniature code within the main code. Functions usually exist within the main code and can be "called" at any time from anywhere within that main code. Functions are often used to deal with variables, an example would be you have a question at the start of your code "Is it AM or PM?" You would then have the program read the time and depending on whether it was AM or PM jump to the appropriate function (AM or PM) and follow the code there. You can have multiple points within your code which ask this question and will jump to the appropriate place depending on the answer. The use of functions allows the code to remain as short as possible by not having the same basic steps repeated every time you want to ask the same question within your code.


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Download the video from iTunes U or the Internet Archive.
Description: This lecture begins with a brief discussion of cross-modal coupling. Prof. Winston then reviews big ideas of the course, suggests possible next courses, and demonstrates how a story can be understood from multiple points of view at a conceptual level.
Instructor: Patrick H. Winston
Lecture 23: Model Merging, ...
Related Resources
Coen, Michael. "Learning to Sing Like a Bird: Self-Supervised Acquisition of Birdsong (PDF)." Proceedings of the AAAI, 2007.
Coen, Michael. "Multimodal Dynamics: Self-Supervised Learning in Perceptual and Motor Systems." PhD thesis, MIT, 2006.
PATRICK WINSTON: Well, don't stop.
Shoot.
I guess we've got to stop.
I will soon go into withdrawal symptoms that will last about six weeks.
But, on the other hand, we all are beginning to develop a sort of tired and desperate look.
And perhaps it's a good thing to get the semester behind us and go into solstice hibernation.
Anyway, there's a lot to do today.
I want to wrap up a couple things, talk about what's next, and maybe get into some big issues, perhaps a little Genesis demo, that sort of thing.
So here's what we're going to do first.
Last time, I talked about this whole idea of structure discovery.
And really, the whole reason I cracked and started talking about basic methods is because of the potential utility of taking that idea one step further and finding structure in situations where you might not otherwise find it.
It's still an open question about whether that's best way to think about it.
But here it goes.
Imagine you've got a couple of stories.
And these circles represent the events in the story.
And now what you'd like to get out of these stories is some kind of finite state graph that describes the collection of stories.
So you might discover, for example, that these two events are quite similar.
And these two events are quite similar.
So you might use that as a basis for speculating that maybe a more compact way of representing the stuff in the story would look like this.
Where this one-- let's see.
This one goes with this one, this one goes with this one and there's a possibility of another state in between.
So that's the notion of Bayesian story merging.
Now I'd like to show you a little bit more convincing demonstration of that.
Here's how it goes.
So there are the two stories.
This is just a classroom demonstration, no big deal.
But you can see there's a sort of parallel structure in there.
So this is the work of a graduate student, Mark Finlayson, who processed those stories to produce those kinds of events and those kinds of events that get assembled into two story graphs.
And the question is, is the most probable way of explaining that corpus of stories?
And of course, the answer is no.
If you merge some things like chase and stop, then you get a simpler graph, one that is more probable in the same sense that we discussed last time.
Then you can merge run and flee because they're similar kinds of events.
And finally, you've got think and decide.
Boom.
There is your story graph.
And this is the same idea taken several levels higher that produce the capacity to discover, in these two stories, the concept of revenge, as promised at the beginning of our last discussion.
So sometimes the Bayesian stuff is the right thing to do, especially if you don't know anything.
But sometimes you do know stuff.
And when you do know stuff it's possible that you can do something very much more efficient.
This sort of thing takes clouds of computers to process.
But we learned a lot of stuff in the course of our development that we don't use a cloud of computers to figure out.
We learned how to associate the gestures of our mouth with the sounds that we make, for example.
So I want to spend a minute or two talking about some work that someday will be the subject of a couple of lectures, I think.
But it's the question of how to use multiple modalities and correspondences between them to sort out both of the contributing modalities.
That sounds contradictory.
Let me show you an example.
This is the example, a zebra finch.
And it's showing you the result of a program written by Michael Coen, now a professor at the University of Wisconsin.
So the male zebra finch learns to sing a nice mating song from its daddy.
And this is what one such zebra finch sounds like.
[BIRD SONG PLAYING] Nice, don't you think?
And here's what was learned by a program that uses no probabilistic stuff at all, but rather the notion of cross-modal coupling.
[BIRD SONG PLAYING] Can you tell the difference?
It's not known if this particular song turns on the female zebra finch.
But to the untrained human ear, they sure sound a whole lot alike.
So how does that work?
Here's how that works.
Well, I'm not going to show you how that works.
What I'm going to show you is how the classroom example works, the first chapter example in Coen's Ph.D. Thesis.
Here's what happens.
When we talk, we produce a Fourier transform that moves along with our speech.
And if we say a vowel like aah, you get a fairly constant Fourier spectrum.
And you can say, well, where are the peaks in that Fourier spectrum?
And how do they correspond to the appearance of my mouth when I say the vowel?
So here's how that works.
So here's the Fourier spectrum of a particular vowel.
And when you smooth that, those peaks are called formants.
And so we're just going to keep track of the first and second formant.
But when I say those things, I also can form an ellipse around my mouth when I say them.
And when I form an ellipse around my mouth when I say them, that gives me this second modality.
So the question is, is there a way of associating the gestures that produce the sound with the sound itself?
Well, there's the human data conveniently provided by a variety of sources, including Michael Coen's wife who produced the lip contour data on the right.
So that's all marked up and color coded according to the particular vowels in English.
I guess there are ten of them.
So we humans all learn that.
But guess what?
We don't learn it from this.
Because we don't get to work with any marked up data.
We learn it from that.
Somehow we're exposed to the natural world, and we dig the vowel sounds out.
It's fantastic how we do that.
But we do have cross modal coupling data and maybe that's got something to do with it.
So here is a particular cluster of sounds.
And what I want to know is, can I merge any of these two clusters to form a bigger cluster with a corresponding meaning?
So what I can do is, I can say, well, I can watch these.
I know what the lip form is when a particular sound is made.
So I have these correspondences.
So maybe there are four of those, like so.
And maybe this same guy projects a couple of tones into that.
And the question is, can this guy be combined with any of these guys?
And the answer is yes.
If they're close together on one side, maybe that suggests you ought to cluster them on the other side.
But there's a question about what close means.
So let's suppose that we also look at how these guys, these other two guys, project.
And suppose this guy projects twice up here and once over here.
And this guy down here just projects like crazy into that guy.
Which are closer?
These two or these two?
Well, my diagram's getting a little closer.
But if you paid attention when I was drawing it, you would see that this guy projects in proportion to that guy.
So if we look at the-- if we take each of these projections as the components of a vector, then those two vectors are in the same direction.
And the cosine between them is zero.
So these are the two that are closest together from that sort of perspective of that kind of metric.

Would you like to see a demonstration?
Yeah.
OK, here's a demonstration based on Coen's work.
So here we have two sides.
We could think of one side as being vowel sounds and the other side as being lip contours or something.
But you don't see anything in the diagram so far about how these things ought to be sorted out into groups.
So if I just take one step, why, it discovers that those two guys had the same projection pattern as each other.
So if I take another step and do the same thing on the other side, and now in the third step, the two areas that were formerly combined now form a super area.
And they're seen to project in the same way as the blue area.
So using this kind of projection idea, I can gradually build up an understanding of how those regions go together.
And I discover, in this contrived example, that there's a vertical arrangement on the right side that corresponds to a horizontal arrangement on the left side.
Now, you say to me, I'd like to see something a little bit more like the lip contour data.
I'm just stepping through here until I get something I kind of like.
Oh, that sounds good.
That seems good.
So there's a correspondence here.
This is all made up data, Gaussians of various shapes and orientations.
Let's see what happens when I run the clustering algorithm on that.
Something definite was learned at every step.
We find the correspondence between the pink region on the right and the pink region on the left.
In some cases, where the regions are rather blurred together, the other side is the one that helps the system figure out how things are organized.
So I cite this as an example of something I think is very important.
Number one, it's possible to discover regularity without being obsessively concerned with Bayesian probability.
And also, that there's very likely a whole lot of this going on in human intelligence.
When we emerge and begin to examine and explore the world around us, we're presented with a lot of unlabeled data that we've got to make sense of.
And I believe that this kind of cross modal coupling idea is very likely to be bound up in our understanding of that world that's presented to us.
It's fast, it's direct.
It doesn't take thousands of data points.
It just happens.
And it happens effortlessly.
And if this isn't built in-- if this isn't determined to be built in, you can come back to MIT in 15 years and put me and jail.
Because I think this is really the way it works.
So there it is.
There's a couple of things to have wrapped up.
And now the next thing I want to do for the rest of our last time together in this format is talk to you about a variety of things.
And I'll depart from my usual practice and move to some slides.
So Dave, could we have the center screen, please?
So first, a brief review of where we've been and where we've come.
I think in the very first class, I talked about what artificial intelligence was.
And I talked about how you could view it from either an engineering perspective or a scientific perspective.
I'm on the scientific perspective side.
And I think, nothing against applications, but I think we'll be able to make much more sophisticated and wonderful applications if we have not only the engineering perspective about building stuff but also the scientific perspective about understanding the stuff to begin with.
So both perspectives are important.
And in this case you can see that they all involve representations, methods, and architectures.
Dave, I've changed my mind.
Could you also give me the side screen so I can see it too?
So, that's that.
What's next?
The business perspective, which we talked about on Thanksgiving.
The important idea being that the knee-jerk expectation that the commercial value of something is in replacing people is something that is not sensible in the first instance, and demonstrated to be unlikely and untrue in the second instance.
The thing that turns people on from the point of view of applications is not replacing people but making new revenue, making new capability.
And that at once licenses you to not have something done exclusively by a computer but something that can be done in partnership with a person.
So all the important applications of artificial intelligence involve people and computers working in tandem, with each doing what they do best-- not with replacing people.
So that's that.
Here's what AI does that makes AI different from the rest of the fields that attempt to contribute to an understanding of intelligence.
Now, we have the benefit of having a language for procedures.
We have all the metaphors that we are the custodians of in consequences of knowing about programming.
We have the metaphor of garbage collection.
We can talk about all sorts of things with programming metaphors that are unavailable to people in other fields that are interested in psychology.
We have a way to make models because we can write programs.
And when we write programs, there's no question of sweeping things under the rug.
We have to work out the details.
And once we've done all that, then we have opportunities to experiment that are beyond the ability to experiment in most other fields.
Oh, magnificent experiments are done these days in developmental psychology and all the rest of-- all the other branches of psychology, including MRI studies that probe into your brain and see how it's consuming sugar.
But it's very difficult to ablate or take away some piece of your knowledge and see how you work without it.
I can take the line-drawing program that we talked about and say, how will it do if it doesn't know anything about fork junctions?
And we can determine an answer.
But I can't reach into Sebastian's head here with a surgical procedure and take out his knowledge of fork junctions.
It just can't be done.
And finally, another reason why we're different is because we can put upper bounds on how much knowledge is needed in order to perform a certain kind of task.
These days, with bulldozer computing, the question most often asked is, how can you get billions of the things off the web and use them.
We-- I especially-- sometimes ask the opposite question, which is how little knowledge can you have and still understand a story?
That's what's interesting to me.
So there's a methodological slide that talks to the question of how you do artificial intelligence in particular and, I suppose, science in general, engineering in general.
There's a great tendency in this field to fall in love with particular methods.
And we've had people who've devoted entire careers to neural nets, genetic algorithms, Bayesian probability.
And that's mechanism envy.
And a better way, in my judgment, is to say, what is the problem?
Scientific method-- what's the problem?
And then bring the right machinery to bear on the problem, rather than looking for things to do with a particular kind of machinery.
So this is the methodology that first articulated in a forceful way, by David Marr.
You want to start with the competence you're trying to understand, then bring a representation to bear on it, a representation that exposes the constraints and regularities.
Because without those, you can't make models.
And without those models you can't understand it, explain it, predict it, or control it.
So it seems to make sense from a kind of MIT, model-centered point of view.
And only when you've got all that straight do you start working on your methods and implement an experiment and then go around that loop.
So that's all I want to say by way of review, I suppose.
I want to take a minute or two and just remind you of what's on the final.
And there's nothing to remind because you all know what's on the final already.
We'll have four sections corresponding with four exams.
Then we'll have a fifth and final question that will be everything else.
All that stuff you slept through will be featured there, as well a little problem on Bayesian inference.
We rearranged the subject, mostly so I could write the demonstrations.
So that the Bayesian stuff didn't come before the fourth quiz.
Therefore the Bayesian stuff that you see on those previous quizzes is likely to be harder than the stuff that we'll ask on the final, because you haven't had as much experience with it as people did last year.
I've got a few icons on there to remind me to tell you a few things.
As always, open everything except for computers.
You can wear a costume.
You can do anything you like as long as it doesn't disturb your neighbor, within reason.
Well, I guess if it doesn't disturb neighbor, it is within reason.
So maybe that's all I need to say.
I'm not sure where we're going to be.
But it's certainly the case that, historically, there are no visible clocks.
So, we soon run out of all of our cellphones, wrist watches, and other time pieces as we hand them out.
So it pays to remember to bring some kind of timepiece, because we won't be able to convey the time very well.
And finally, I see a little calculator there.
I don't recall any exam where you actually needed a calculator.
But it's sort of a security blanket to have one.
People sometimes see a problem and say, oh my God, what am I going to do?
I left my calculator at home.
So as to avoid that anxiety, you might want to bring one even though you won't need it.
So that's the final.
I'm sure there are no questions.
Are there?
It's obvious.
Everybody will do well.
Two shots, that whole thing.
Now, what to do next?
Suppose this subject has turned you on.
There are a variety of things that you should be thinking about doing next semester.
And I wanted to review just a few of those.
One of them is Marvin Minsky's subject, Society of Mind.
It's very different from this class.
There are no prepared lectures.
Marvin doesn't rehearse.
He doesn't think about what he's going to say in advance.
It's like this except it's just a conversation with Marvin.
So many people find themselves bored stiff for two lectures out of three.
But then in the third lecture, Marvin will say something that you'll think about for a year or for the rest of your life.
That's what happens to me.
I'm bored stiff two out three times.
And then the third lecture he says something, and I think about it for at least a year and maybe permanently.
So it's an opportunity to see one of MIT's true geniuses think out loud.
So it's an experience that you don't want to miss because that's what you come here for, is to see the geniuses think out loud.
Speaking of geniuses, then there's Bob Berwick.
And he heroically is doing two subjects in the spring.
Both of which I'd take if I could.
One is his subject on Language Understanding.
And the reason I'd take that is because I believe that language is at the center of any explanation of our intelligence.
So that's the subject I would be, I suppose, most inclined to take if I were you.
Well, maybe Minsky's.
It's hard to say.
And incidentally, very heroically, Bob is also teaching a course on how evolution works, how it really works-- in so far as we know how it really works-- as well.
So both of those will be offered in the spring.
I don't know how he does it.
I don't know how he does two all at the same time.
Of course there are lots of places where you can go to school, and the faculty will be teaching five courses at the same time.
I just think they're crazy or something.
I don't know how that works.
Gerry Sussman will be teaching his Large Scale Symbolic System subject.
That's sometimes-- oh, I forgot what he wasn't able to call it, something that wasn't politically correct about programming for people who really, really like to program.
It's a splendid course on how to build really big systems.
And we use the ideas in that subject in our research system, because it's the only way-- understanding how that works is the only way that you can build systems that are too big to be built.
I may say a word about that a little later.
So those are my favorite three/four picks.
But there's lots of other stuff, too many things to cover-- the media lab, [INAUDIBLE] psychology.
There's tons of stuff out there.
And I would only mention that courses that have those three names on them are bound to be good.
These are colleagues that I think I have a important perspective-- not necessarily one I agree with, but an important perspective that you should understand-- Richards, Tenenbaum, and Sinha.
And now we come to my spring course, the Human Intelligence Enterprise.
It's 6.XXX not because there's anything pornographic about it but because for a long time, I couldn't remember it's number.
So I developed a habit of referring to it as 6.XXX and it seems to have stuck.
Here's what that's about.
Yeah, that might be interesting.
It's taught like a humanities course, though.
No lectures, I just talk.
And all the TAs are veterans of that class so if you want to know if you should do it, you have several resources.
You can talk to them.
Or you could look at the sorts of things we talk about.
Here are some things we talk about by way of packaging.
Yeah, I can hear a little tittering there because people have discovered the last element.
Some people take the whole subject because they want to be present for that unit.
And we talk about all those kinds of things.
And we look to see what the common elements are in all those kinds of packaging problems of the sort that you will face over and over again when you become an adult, no matter what you do.
If you become a business person, an entrepreneur, a military officer, a scientist, or an engineer, that packaging stuff will often make the difference between whether you succeed or don't.
And then, that's the second way you can figure out whether you want to take the subject.
The content, the TAs, and then of course you can always appeal to the Underground Guide.
And that's why it's very rare for someone that takes 6.XXX who hasn't been at this final lecture because they read the Underground Guide.
Here is an element that appeared in the Underground Guide a few years back.
There are no exams.
But there is a tradition of hacking the Underground Guide.
So this is another example of something that appeared.
So it all came about because early in the teaching of 6.XXX, I was whining to the students about the fact that I've been at MIT for a long time, since I was freshman.
And I still have yet to have any person I report to say anything about my teaching-- good, bad, indifferent.
Nothing.
Not a word.
So the students decided that it would be interesting to see if they could say something sufficiently outrageous to force a conversation between the department chairman and me.
And so far they've been totally unsuccessful.
And I've tried everything.
Winston shows up late if he shows up at all.
Good instructor but constantly sipping from a brown paper bag.
All kinds of stuff.
But there it is.
It's a lot of fun.
It's a little oversubscribed so we have to have a lottery and there's about 50% chance and so on and so forth.
But many of you will find it a good thing to do.
Oh, yeah.
And now I also want to remind myself that there is a IP event that's become kind of MIT tradition.
It's the How to Speak lecture that I give.
This year it'll be on January 28 in 6120.
6120 holds about 120 people and about 250 show up.
So if you want to go to that lecture you should show up 15 minutes early.
That's a little secret just between me and 6034 students.
It's about packaging, too.
It's a one-lecture version of 6.XXX.
But it's very nonlinear because one thing that you pick up from that one hour may make the difference between you getting the job and some other slug getting the job.
So it's one of those sorts of things that can make a big difference in a short period of time.
You may sleep through 50 minutes of the 55 minutes in that lecture and stay awake for that one magical five minutes when you learn something about when to tell a joke or how to open a lecture or how to conclude one or a job talk or a sales presentation or anything.
And that will make it worthwhile for you.
And then of course there's the possibility of your-- anybody who's doing [? UROP ?] with me is likely to be interested in what I've recently come to call a strong story hypothesis, something that we've talked about from time to time.
That's what makes us humans, and that's not what they are.
They're orangutans or chimpanzees, even though the DNA that we share is-- it goes up and down.
At one point it was 96%, then it went to 98%.
Now I think it's back down to 97%.
But whatever we are, it's not because of a huge, massive difference in DNA between us and our cousins.
So in my group we build a Genesis system, modestly called.
And that's what it looks like.
And it has in it all the sorts of things that we've talked about from time to time in 6034.
And it's about to move into areas that are especially interesting, like can you detect the onset of a possible disaster before it happens and intervene?
Can you retrieve presses based on higher-level concepts?
Things of that sort.
Would you like to see a demonstration?
OK.
So you've see in a little bit of this before.
In fact, I'm not even sure what exactly I've already shown you.
Let me just get over there to see what goes on here.
What I'm going to do right now is I'm just going to read about Macbeth.
A short precis of the plot.
Not the whole thing, of course.
Just a few sentences about the plot.
Right now what it's doing is absorbing the English and translating into a sort of internal language.
A sort of universal, internal language that's all about trajectories and transitions and social relationships and all that.
So it's being read there by two different persona.
Each of those personas has a different educational background, you might say.
They might represent different cultures.
So eventually they build up graphs like that.
And everything in white is stuff that's explicit in the story.
And everything that's in grey is stuff that's been inferred by the system.
So there are several layers of understanding.
One is what's there explicitly.
And the other thing that's there is stuff that's readily inferred.
And because these persona have different educational backgrounds, you might say they see the killing of Macbeth at the end of the play in a different light from one another.
One sees it as an act of insane violence and the other sees it as a consequence of a revenge.
So once you've got that capability, you can do all sorts of things.
For example, you can ask questions.
So let me arrange it to ask-- by the way, this is a live demonstration.
I'm thrilled to pieces that it actually works so far.
Let's see.
Why did Macbeth kill Duncan?
You all know why, right?
Yeah, you're right.
He didn't actually do that.
On a common sense level, neither Dr. Jeckll nor Mr.
Hyde have an opinion.
On a reflective level neither Dr. Jeckll more Mr. Hyde have an opinion.
That's because it didn't happen.
So we call these two persona Doctor Jeckll and Mr. Hyde.

Well, that's because with this spelling the speech generator makes it sound a little bit more like when we say Jekyll.
But what really happened is that Macduff killed Macbeth.
On a common sense level, it looks like Dr. Jeckll thinks Macduff kills Macbeth because Macduff is insane.
It looks like Mr. Hyde thinks Macduff kills Macbeth because Macbeth angers Macduff.

It looks like Mr. Hyde thinks Macduff kills Macbeth as part of acts of mistake, Pyrrhic victory, and revenge.
Isn't that cool?
I bet you'd get an A if you had said that in eighth grade.
But once you've got this ability to understand the story from multiple points of view, you begin to think of all kinds of wonderful things you can do.
For example, you can have Dr. Jeckll negotiate with Mr.
Hyde, because Dr. Jeckll will be able to understand Mr.
Hyde's point of view and demonstrate to Mr. Hyde that he thinks that point of view is legitimate.
Or, Dr. Jeckll can teach Mr. Hyde the subject matter of a new domain.
Or Dr. Jeckll can watch what's happening in Mr. Hyde's mind and avert disaster before it happens.
So let me just show you another situation here.
I want to turn on the onset detector and read another little snippet.
This one is about-- what should I do?
We'll do the Russia and Estonia cyber war.
It's reading background knowledge right now.
But pretty soon, in the upper left-hand corner, as it begins to read the story, you'll see it spotting the onset of potential revenge operations or potential Pyrrhic victories, and show their foundations begin to emerge and giving the system an opportunity to intervene.
So there you can see all the things that it thinks might happen.
Not all of them do happen.
But some of them do.
And you'll note, incidentally, that this is another case of Dr. Jeckll and Mr. Hyde having different cultural perspectives.
One's an ally of Russia and one's an ally of Estonia.
One sees it as unwarranted revenge and the other sees it as teaching a lesson.
So, I don't know.
What else have we got here?
Oh yeah, president recall.
A long time ago, we talked about doing information retrieval based on vectors of keyword counts.
That's cool but not this cool.
This is doing it on vectors of concepts that appear in the stories, such as revenge, even though the word revenge doesn't appear anywhere.
So because we're able to understand the story on multiple levels, we can use those higher levels that don't involve the words in the story at all to drive the retrieval process.
So all that is a consequence of a variety of things, one of which is the specialists that translate the English into an internal language.
And it's also, incidentally-- I mentioned it a little before-- it's also a consequence of our use of Gerry Sussman's propagator architecture.
So a student comes into our group and says he wants to do something.
And we say OK, here's how the system is organized.

So you get a box and we'll tell you what the inputs are going to look like.
And we'll tell you what we want on the outputs.
And if you don't like the inputs, just ignore them.
And if we don't like your outputs, we'll just ignore that.
So nobody can screw up anything because they have a very circumscribed piece of the system to work with.
So I can say, for example, the president wanted Iraq to move toward democracy.
And bingo.
That starts a propagation through that network.
All this would be unconvincing, in my view, if it weren't eventually connected to perception.
Because if it's not eventually connected with perception, it's yet another system that demonstrates how smart it can seem to be without actually knowing anything.
So another half of what we do is an early stage attempt to connect the language stuff with things that are going on in the world.
So we say, imagine a jumping action.
And there is a jumping action that's part of a test sweep developed by the Defense Research Projects Agency to drive what they call the Mind's Eye program, which was developed largely as a consequence of work done here at MIT, focused on the idea that if we're going to understand the nature of intelligence, we have to understand how language is coupled into our perceptual systems and how those perceptual systems can answer questions posed to them by the language system.
That's a little demo of the Genesis system.
Here are the issues that we're trying to explore.
Nothing too serious, just the nature of what is extraordinarily fundamental to any explanation of human thinking.
Now, all of this might turn you on.
And you say to me, well, you're sick and tired of MIT.
You'd like to go somewhere else for graduate school.
So now that I've demonstrated what we do here, one of the many things we do here, I'll talk a little bit about other places you can go.
This is a sort of MIT-centric view of the world.
It represents all of the places you could go when I was a kid.
But while I've got this particular diagram on here, I just-- sort of testing my MIT arrogance-- I remember a story often told by my colleague Peter Szolovits.
He says that when he came to a job interview from Caltech to MIT, he was sitting here for three days and nobody spoke to him.
So eventually he said, I've got to do something.
He walked up to a graduate student and said, hi my name is Peter Szolovits.
I'm from Caltech.
And the graduate student said, Caltech sucks, and walked away.
Anyway, we've populated all these places now that you see here, and more.
This is just a list that I scratched up this morning.
I'm sure I've forgotten many that have equal right to be on this list.
But in the end, which one you go to depends on who you want to apprentice yourself to.
Because a graduate school is an apprenticeship.
And that means if you go to a place with just one person, it's OK if that's the person you want to apprentice yourself to.
Each of these places has a different focus because they have different people.
So you need to find out if there's somebody at any of these places.
It doesn't matter if it's AI or some other field.
Theoretical physic-- you've got to find out if there's somebody at that place you want to apprentice yourself to.
So those site visits are really important.
And I would like to also stress that when you make your application to graduate school, it's very different from applying to undergraduate school.

So don't get confused and talk about how it's a wonderful fit for you.
Because what they're interested in is whether you're going to contribute to their research program.
Oh, I should say that if you're applying to artificial intelligence that means you don't say, I'm interested in all aspects of thinking.
You need to be focused.
There's another reason why you don't say that you're interested in all aspects of thinking and that is the defect theory of AI career selection.
It seems to be the case, strange though it may seem, that people in artificial intelligence often specialize their research on the things that they don't do very well themselves.
So people who study language, with the exception of Bob Berwick, often have trouble getting out a coherent sentence.
And people who do hand-eye coordination are the sorts who spill their coffee.
So don't say you want to study all thinking because-- The most extreme case of this, though, is-- if you don't mind, I'll tell you a story about an extreme case in this.
We had a visitor from Japan in the old artificial intelligence lab many years ago.
He came for a year.
Let's call him Yoshiaki, just to pick a name.
Yoshiaki spent a year at the artificial intelligence lab, and he left his wife in Japan.
And the reason was, she was pregnant.
And at that time, you could not get a visa to the United States unless you had a smallpox vaccination.
And because she was pregnant, she didn't want to get a smallpox vaccination because there's a small danger to the fetus if you get a smallpox vaccination while you're pregnant.
So she stayed back there.
So Yoshiaki, let us call him-- it was a day before he was to get on the airplane to go home.
I walked into his office and his desk was covered with pictures of his wife.
By the way, Yoshiaki, I should tell you, is a computer vision guy, interested in object recognition.
So you might suspect he has some problem.
So he's looking at these pictures.
I thought, oh my God, this is a tender moment.
He's anticipating his return to Japan and reunion with his wife.
So I muttered something to that effect.
And then he looked at me like I was the king of the fools.
And he said, it's not a question tenderness.
I'm afraid I won't recognize her at the Tokyo airport.
So I said, Yoshiaki.
How can this be?
You study computer vision.
You study object recognition.
This is your wife.
How can you think you wouldn't recognize her at the Tokyo airport?
And then he looks at me, and-- God is my witness-- he says, they all look alike.
Well now as we come close to the end, what are the big questions?
Is it useful?
Of course it's useful.
It's part of the toolkit, now, of everybody who claims to be a computer scientist.
What are the powerful ideas and these things?
Well, here's the most powerful, powerful idea is the idea of powerful idea.
And here are a few of my favorites.
No surprises there.
That's just Winston's picks.
But there's one more I would like to add.
And that is all great ideas are simple.
A lot of times we at MIT confuse value with complexity.
And many of the things that were the simplest in this subject are actually the most powerful.
So be careful about confusing simplicity with triviality and thinking that something can't be important unless it's complicated and deeply mathematical.
It's usually the intuition that's powerful, and the mathematics is the [INAUDIBLE] element.
Sometimes people argue that real intelligence is possible.
One of the most common arguments is, well what if we had a room?
And you're in the room and you're asked to translate some Chinese documents.
You've got a bunch of books.
And in the end you could do the translation.
But you cannot be said to understand Chinese.
This is the argument of Berkeley philosopher named Sorel.
So the trouble is, it's also true-- well, the argument is the books aren't intelligent.
They're just ink on a page.
And the person is just a computer, just a processor.
It doesn't actually know anything.
So since it can't be in either the person or the books, it can't be.
And that just forgets that there's a magic that comes about when a running program, when a process, executes in time over knowledge that it continually contributes to.
So the reductionist arguments are among the many that have been ineffectually posed to argue that artificial intelligence is impossible.
But that bears longer discussion.
Let me just bring up the biggest issue in my mind, which is, it's not the question of whether we humans are too smart to have our intelligence duplicated or excelled in a computer.

I once had a pet raccoon.
Now, it's illegal to have a pet raccoon.
But this one was an orphan.

A friend of mine brought the raccoon to me knowing I kind of like animals.
And I have to say, I kept the raccoon for a year.
At that point, she wanted to go out and be on her own.
So I had this raccoon.

Within a day, she learned how to pry the refrigerator door open.

She wouldn't eat hot dogs.
And I wanted her to eat hot dogs desperately because they're cheap and easy to serve.

So one day I said, well, I'm going to play a trick on her.
I took a chicken bone.

And she went for it.
Her genes took over and she went for it.
And she was happy with hot dogs ever after.
She wouldn't let me read.

You'd be amazed at how much a raccoon can suck.
It's just extremely powerful.
The best parts were when she would go bike riding with me.
I put on a heavy sweater because they have a pretty good grip.
I'd put on a heavy sweater and she'd kind of mount herself on my back and look out over my shoulder, stopped traffic for miles around.
So she was really smart.
But the interesting thing is that at no point did I ever presume that that raccoon was smart enough to build a machine that was as smart as a raccoon.
So when we think that we can, it involves a certain element of hubris that may or may not be justified.
Well, there it is.
Just a couple more things to do.
One of which is, you should understand that Kendra and Kenny and Yuan and Martin and Gleb are doing a lot of stuff that's outside their job description.
All of these quiz review deals that they've arranged are not in their job description.
I didn't ask them to do it.
That's all just plain old professionalism.
So they've been wonderful to work with and I'd just like to-- [APPLAUSE] --offer them a round of applause.
And of course, Bob and Randy and Mark have done fabulous stuff as well.
And we of the staff, the TAs, Mark, Bob, and Randy, have nothing else to do except wish you good hunting on the final and a good long winter solstice hibernation period after that.
And that is the end of the story.
And we hope you live happily ever after.


[gecode-users] How can I make this constraint
Guido Tack
tack at ps.uni-sb.de
Thu Feb 14 22:42:48 CET 2008
Mauricio Toro wrote:
> Sorry... I meant this
>
> 2008/2/14, Guido Tack <tack at ps.uni-sb.de>:
> Am 14.02.2008 um 21:23 schrieb Mauricio Toro:
>> How can I make this constraint?
>>
>>
>> int const x[] = {0,2,5,8,9,10};
>> answer = IntVarArray(this,n,1,11);
>>
>> for (int i = 0; i < n-1; i++){
>> // x[i] - x[i+1] = answer[i] - answer[i+1]
for (int i=0; i<n-1; i++)
post(this, x[i] - x[i+1] == answer[i] - answer[i+1]);
should do the trick (you have to include gecode/minimodel.hh for this
to work).
Cheers,
Guido
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NAMEI(1) User Commands NAMEI(1) NAME namei - follow a pathname until a terminal point is found SYNOPSIS namei [options] pathname... DESCRIPTION namei uses its arguments as pathnames to any type of Unix file (symlinks, files, directories, and so forth). namei then follows each pathname until an endpoint is found (a file, a directory, a device node, etc). If it finds a symbolic link, it shows the link, and starts following it, indenting the output to show the context. This program is useful for finding "too many levels of symbolic links" problems. For each line of output, namei uses the following characters to identify the file type found: f: = the pathname currently being resolved d = directory l = symbolic link (both the link and its contents are output) s = socket b = block device c = character device p = FIFO (named pipe) - = regular file ? = an error of some kind namei prints an informative message when the maximum number of symbolic links this system can have has been exceeded. OPTIONS -l, --long Use the long listing format (same as -m -o -v). -m, --modes Show the mode bits of each file type in the style of ls(1), for example 'rwxr-xr-x'. -o, --owners Show owner and group name of each file. -n, --nosymlinks Don't follow symlinks. -v, --vertical Vertically align the modes and owners. -x, --mountpoints Show mountpoint directories with a 'D' rather than a 'd'. -h, --help Output help text and exit. -V, --version Output version information and exit. AUTHOR The original namei program was written by Roger Southwick<EMAIL_ADDRESS>The program was re-written by Karel Zak<EMAIL_ADDRESS>BUGS To be discovered. SEE ALSO ls(1), stat(1) AVAILABILITY The namei command is part of the util-linux package and is available from ftp://ftp.kernel.org/pub/linux/utils/util-linux/. util-linux June 2011 NAMEI(1)


class Openwsman::Filter
Filter
are evaluated on the server side and help to reduce the amount of processing and information transport.
There are five basic ways to filter
-
associations
-
references
-
XPath
-
CQL (CIM query language)
-
WQL (WS-Management query language)
Openwsman
does not do any filter processing by itself but passes it to the backend CIMOM. Support for filters and query languages thus depends on the used CIMOM.
Public Class Methods
new(p1)
click to toggle source
Create empty filter
() { return filter_initialize(); } ~filter_t() { filter_destroy( $self ); } /* * Set associators filter * call-seq: * filter.associators(end_point_reference, assoc_class_name, result_class_name, role, result_role, result_prop[], prop_num) * */ int associators( VALUE epr_v = Qnil, VALUE assocClass_v = Qnil, VALUE resultClass_v = Qnil, VALUE role_v = Qnil, VALUE resultRole_v = Qnil, VALUE resultProp_v = Qnil, VALUE propNum_v = Qnil) { return associators_references( $self, 0, epr_v, assocClass_v, resultClass_v, role_v, resultRole_v, resultProp_v, propNum_v); } /* * Set references filter * * call-seq: * filter.references(end_point_reference, assoc_class_name, result_class_name, role, result_role, result_prop[], prop_num) * */ int references( VALUE epr_v = Qnil, VALUE assocClass_v = Qnil, VALUE resultClass_v = Qnil, VALUE role_v = Qnil, VALUE resultRole_v = Qnil, VALUE resultProp_v = Qnil, VALUE propNum_v = Qnil) { return associators_references( $self, 1, epr_v, assocClass_v, resultClass_v, role_v, resultRole_v, resultProp_v, propNum_v); } /* * Set simple dialect/query filter * call-seq: * filter.simple(dialect, query) * */ int simple(const char *dialect, const char *query) { return filter_set_simple($self, dialect, query ); } /* * Set XPath filter * call-seq: * filter.xpath(query) * */ int xpath(const char *query) { return filter_set_simple($self, WSM_XPATH_FILTER_DIALECT, query ); } /* * Set CQL (CIM query language) filter * call-seq: * filter.cql(query) * */ int cql(const char *query) { return filter_set_simple($self, WSM_CQL_FILTER_DIALECT, query ); } /* * Set WQL (WS-Management query language) filter * call-seq: * filter.wql(query) * */ int wql(const char *query) { return filter_set_simple($self, WSM_WQL_FILTER_DIALECT, query ); } }
Public Instance Methods
cql(query)
click to toggle source
Set CQL (CIM query language) filter
int cql(const char *query) { return filter_set_simple($self, WSM_CQL_FILTER_DIALECT, query ); } /* * Set WQL (WS-Management query language) filter * call-seq: * filter.wql(query) * */ int wql(const char *query) { return filter_set_simple($self, WSM_WQL_FILTER_DIALECT, query ); } }
simple(dialect, query)
click to toggle source
Set simple dialect/query filter
int simple(const char *dialect, const char *query) { return filter_set_simple($self, dialect, query ); } /* * Set XPath filter * call-seq: * filter.xpath(query) * */ int xpath(const char *query) { return filter_set_simple($self, WSM_XPATH_FILTER_DIALECT, query ); } /* * Set CQL (CIM query language) filter * call-seq: * filter.cql(query) * */ int cql(const char *query) { return filter_set_simple($self, WSM_CQL_FILTER_DIALECT, query ); } /* * Set WQL (WS-Management query language) filter * call-seq: * filter.wql(query) * */ int wql(const char *query) { return filter_set_simple($self, WSM_WQL_FILTER_DIALECT, query ); } }
wql(query)
click to toggle source
Set WQL (WS-Management query language) filter
int wql(const char *query) { return filter_set_simple($self, WSM_WQL_FILTER_DIALECT, query ); } }
xpath(query)
click to toggle source
Set XPath filter
int xpath(const char *query) { return filter_set_simple($self, WSM_XPATH_FILTER_DIALECT, query ); } /* * Set CQL (CIM query language) filter * call-seq: * filter.cql(query) * */ int cql(const char *query) { return filter_set_simple($self, WSM_CQL_FILTER_DIALECT, query ); } /* * Set WQL (WS-Management query language) filter * call-seq: * filter.wql(query) * */ int wql(const char *query) { return filter_set_simple($self, WSM_WQL_FILTER_DIALECT, query ); } }


Create an app that lets me type in an overseas phone number, goes to localphone.com and gets the cheaper local number, then dials that number.
If you have a solution, then post it here. If your solution is accepted then...


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---
layout: en/default
class: cloud
title: "Cloud - The easiest way to install & host Rocket.Chat"
description: |
Rocket.Chat Cloud is the easiest way to install & manage Rocket.Chat.
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permalink: /cloud
theme: light
redirect_from:
- /hosting/
- /cloud/
---
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General Elements
Contextual alternatives :
Panel Primary
models模态框 :
Modal title
New message
Small modal
滚动监听|ScrollSpy example :
Item 1
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