Louis Barbieri
Chairman
About Us
Preserve affordable housing by bringing volunteers and communities together to rehabilitate the homes of low-income homeowners.
Operating in more than 865 cities and towns in all 50 states, Rebuilding Together rehabilitated more than 8,900 homes and non-profit facilities in 2006 with the volunteer power of 267,000 men, women and youth.
Assistance is focused on the low-income elderly, disabled and veteran homeowners that live in single family homes. Our method of assistance focuses on addressing all of the issues related to the home including but not limited to safety, comfort, health, energy efficiency and independence. Our primary objective is to restore safe and healthy living conditions through home repairs which have an immediate and long lasting impact. The Safe and Healthy Homes program has two signature initiatives: Safe at Home and Green Housing.
Our Safe at Home Initiative targets safety upgrades and modifications needed to allow the homeowner to age in place safely, comfortably and independently.
The Green Housing Initiative provides energy efficient retrofits to allow the homeowner to save money on their electric and water bill and help conserve our precious environmental resources. Assistance is provided at no cost to the homeowner.
Louis Barbieri
Chairman
Tsedey Betru
Member
Alex Bragg
Member
Marc N. Brambut
Member
John Corcoran
Member
Dorian DeBarr
Member
Jason Fernandez
Member
Stephanie H. Galer
Member
Camille Kesler
Executive Director
Terri Lee
Member
Chris Leutzinger
Member
Keith Mack
Member
Amanda Rhein
Member
Darice Rose
Member
Alyse Schwartz
Member
Greg Ward
Member
Eric Zwygart
Member


I have uploaded and hollowed out a small collection of previous versions of my websites, or projects I have previously been associated with. To come back to MattBurchett.com, please hit the back button on your browser.


Exotic Dilepton Search
(page last updated: Thu May 27 12:00:52 2021)
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Calendar export
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Select data sets to reintegrate by selecting a number of images in the DISTL plot. Provide unit cell parameters, space group, and high resolution cut off as needed. Click an existing cell to autofill


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| Methods' Details |
addBorder
- Description
- Enlarge the given rectangle by the size of the specified part of the
border. This method can be used to convert an inner bounding box
into the center box or the outer bounding box.
- Parameter sPaneBorderStyleName
- The pane style defines the sizes of the border.
- Parameter aRectangle
- This rectangle will be converted into a larger one. This should
be the center box or the inner bounding box of the border.
- Parameter eBorderType
- The part of the border to add to the given rectangle.
Use INNER_BORDER to convert an inner bounding box into the
center box or TOTAL_BORDER to convert it into the outer bounding
box. OUTER_BORDER can be used to convert the center box into
the outer bounding box.
|
|
removeBorder
- Description
- Shring the given rectangle by the size of the specified part of the
border. This method can be used to convert an outer bounding box
into the center box or the inner bounding box.
- Parameter sPaneBorderStyleName
- The pane style defines the sizes of the border.
- Parameter aRectangle
- This rectangle will be converted into a smaller one that lies
inside it. It should be the center box or the outer bounding
box of the border.
- Parameter eBorderType
- The part of the border to remove from the given rectangle.
Use OUTER_BORDER to convert an outer bounding box into the
center box or TOTAL_BORDER to convert it into the inner bounding
box. INNER_BORDER can be used to convert the center box into
the inner bounding box.
|
|
paintBorder
| void |
| paintBorder( |
[in] string |
sPaneBorderStyleName, |
| [in] ::com::sun::star::rendering::XCanvas |
xCanvas, |
| [in] ::com::sun::star::awt::Rectangle |
aOuterBorderRectangle, |
| [in] ::com::sun::star::awt::Rectangle |
aRepaintArea, |
| [in] string |
sTitle ); |
- Description
- Paint the border around a pane.
- Parameter sPaneBorderStyleName
- The pane style to use for painting the border.
- Parameter xCanvas
- The canvas onto which the border is painted.
- Parameter aOuterBorderRectangle
- The outer bounding box of the border. Use addBorder to convert
the bounding box of a pane (the inner bounding box of the
border) into this outer bounding box of the border.
- Parameter aRepaintArea
- The area in which the border has to be repainted. The clip
rectangle.
- Parameter sTitle
- The pane title. Supply an empty string for panes without
title. It is the responsibility of the caller to supply a title
only for pane border styles that support a title.
|
|
paintBorderWithCallout
| void |
| paintBorderWithCallout( |
[in] string |
sPaneBorderStyleName, |
| [in] ::com::sun::star::rendering::XCanvas |
xCanvas, |
| [in] ::com::sun::star::awt::Rectangle |
aOuterBorderRectangle, |
| [in] ::com::sun::star::awt::Rectangle |
aRepaintArea, |
| [in] string |
sTitle, |
| [in] ::com::sun::star::awt::Point |
aCalloutAnchor ); |
- Description
- Paint the border around a pane where the border includes a callout
that is anchored at the given point. Most arguments have the same
meaning as in the paintBorder.
- Parameter aCalloutAnchor
- The anchor point of the callout. It is usually located outside
the border.
|
|
getCalloutOffset
| ::com::sun::star::awt::Point |
| getCalloutOffset( |
[in] string |
sPaneBorderStyleName ); |
- Description
- Return the offset of a callout anchor with respect to the outer
border. This value is used when the callout is realized by a fixed
bitmap in order to determine the size and/or location of the outer
border for a given callout.
|
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Based on what you've told us:
You live in Northern Ireland
Most Health Service treatment is free if you live in Northern Ireland, although there may be charges for some things.
If you live in Northern Ireland you can find more detailed information at NIdirect.gov.uk.


Centres of Excellence..!!
Combining the best specialists and equipment to provide you
nothing short of the best in healthcare
Critical care Emergency Diabetic Cancer-care Bariatric-surgery Gastroenterology Heart Neurosciences Orthopaedics Preventive-medicine Robotics Spine Transplants


Here's a regular list:
Here's one with white space around items:
Here's one with too much space before items:
- list item
- another list item
Here's one with no space after markers:
-list item -another list item
Here's one where items contain line breaks:


For booking inquiries, please contact<EMAIL_ADDRESS>or call us at<PHONE_NUMBER>. We look forward to hearing from you!
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An error occurred while processing your request. Please return to the previous page and check everything before trying again. If the same error occurs again, please contact your system administrator or report error (see below).
Event type: error
Page: Constellation/html/error.html
Message
Undefined variable: test


[gecode-users] Estimating propagation times
Mauricio Toro
mauriciotorob at gmail.com
Thu Dec 11 21:58:45 CET 2008
Hello all,
It's me again trying to "abuse" from Gecode.
I am trying to use Gecode for real-time applications.
I want to measure how much time takes for a
"tell" a constraint in Concurrent Constraint Programming
given a certain propagator
and a certain constraint "store".
For instance, I would like to have data like this:
Equality domain propagator (a=b), for a store (a=2,b = [0..3]) takes to 20
ms
to achieve a partial fix point.
Also, in a later time I could have:
Equality domain propagator (a=b), for a store (a=2,b = 2) takes to 5 ms
to achieve a fix point.
I think that maybe I can train a neural network to learn that information.
Can you think of a way to model this problem?
Any suggestions are welcomed.
Thanks,
Mauricio
--
Mauricio Toro Bermudez
Estudiante de Ingeniería de Sistemas
Pontificia Universidad Javeriana, Colombia
Stagiare à l'Ircam
1, place Igor-Stravinsky 75004 Paris,
France de 2008 à 2009
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One held for trying to circulate fake currency in Ayanavaram
A total of 6 fake ₹2000 notes were seized
by Special CorrespondentThe Ayanavaram police detained a person for attempting to circulate fake currency on Saturday night.
A senior city police official said S. Elumalai, a resident of Otteri, purchased sweets by giving a ₹2,000 note at a shop in the Ayanavaram market and after getting the change from the shopkeeper, he started to run. The shopkeeper immediately checked the note and found that it was fake. He chased Elumalai, and caught him when the offender tried to escape in an autorikshaw on K.H. Road.
Later, Elumalai, who works in a catering unit, handed over to the Ayanavaram police.
The police, after booking a case based on a complained filed by S. Arunagirinathar of Elumalai Street, Ayanavaram, detained the accused and seized a total of 6 fake ₹2,000 notes from him.
The Ayanavaram police is enquiring about the manner in which Elumalai procured the fake currencies or whether there is any gang involved in this crime.


GBC Pokémon party export
1. Select a game:
Red/Blue
Crystal
2. Select options:
Include stat determinants
Include happiness
3. Select a .sav file:
Party:
PC:


{% extends "base.html" %} {% block title %}
Medieval catalogues > BENEDICTINES: THE SHORTER CATALOGUES > Worcester > Leland, c. 1536-40
{% endif %}16 identified entries found.
All data was derived from the List of Identifications by Professor Richard Sharpe.
{% if not printing %}
A key to codes used in the List is available (opens in new tab).{% endif %}


Hello! Welcome!
Test Pre
Hello World !
Test itablic and bold
bold
italic
bold and italic
Test emphasize and strong
emphasize
strong
strong and emphasize
- <Term>
- 〈Term〉The definition of the term is like this:...
- 〈Term〉
- <Term>The definition of the term is like this:...
- astray
- the meaning of this particular word
3.6-Displaying special characters
&, ©™〈〉
3.7-Controlling whitespace
3.8-Displaying images
Calculate getBoundingClientRect().width


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How to use it
Open document in editor
Copy actual link and paste it to the field below
Click on generated link (opens in new tab)
Copy received JSON for sharemap and paste it to text fild
Press 'Draw' button to get sharemap rendered
Alternatively you can use sample from the right block
Sample data
Some fall back text


|
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| PREV NEXT | FRAMES NO FRAMES |
| Packages that use BaseEvalTestCase | |
|---|---|
| org.apache.velocity.test | |
| org.apache.velocity.test.issues |
| Uses of BaseEvalTestCase in org.apache.velocity.test |
|---|
| Subclasses of BaseEvalTestCase in org.apache.velocity.test | |
|---|---|
class |
ArrayMethodsTestCase
Used to check that method calls on Array references work properly and that they produce the same results as the same methods would on a fixed-size List . |
class |
DefineTestCase
This class tests the #define directive |
class |
ForeachBreakTestCase
This class tests the break directive within Foreach loop. |
class |
IfNullTestCase
Used to check that nulls are properly handled in #if statements |
class |
PropertyMethodPrecedenceTestCase
Used to check that vararg method calls on references work properly |
class |
StaticUtilityMethodsTestCase
This class tests support for putting static utility classes like java.lang.Math directly into the context in order to use their methods. |
class |
StrictForeachTestCase
This class tests support for strict foreach mode. |
class |
StrictMathTestCase
This class tests support for strict math mode. |
class |
StrictReferenceTestCase
Test strict reference mode turned on by the velocity property runtime.references.strict |
class |
StringConcatenationTestCase
This class tests support for string concatenation. |
class |
URLResourceLoaderTimeoutTestCase
This class tests support for custom timeouts in URLResourceLoader. |
class |
VarargMethodsTestCase
Used to check that vararg method calls on references work properly |
| Uses of BaseEvalTestCase in org.apache.velocity.test.issues |
|---|
| Subclasses of BaseEvalTestCase in org.apache.velocity.test.issues | |
|---|---|
class |
Velocity355And552TestCase
This class tests VELOCITY-355 and its twin, VELOCITY-552. |
class |
Velocity532TestCase
This class tests VELOCITY-532. |
class |
Velocity544TestCase
|
class |
Velocity579TestCase
This class tests VELOCITY-579 and with some related stuff from VELOCITY-70 thrown in. |
class |
Velocity587TestCase
This class tests VELOCITY-587. |
class |
Velocity589TestCase
This class tests VELOCITY-589. |
class |
Velocity614TestCase
This class tests VELOCITY-614. |
class |
Velocity615TestCase
This class tests VELOCITY-615. |
class |
Velocity616TestCase
This class tests VELOCITY-616. |
class |
Velocity625TestCase
This class tests VELOCITY-625. |
class |
Velocity627TestCase
This class tests VELOCITY-627. |
class |
Velocity629TestCase
This class tests VELOCITY-629. |
class |
Velocity62TestCase
This class tests VELOCITY-62. |
class |
Velocity630TestCase
This class tests VELOCITY-630. |
class |
Velocity631TestCase
This class tests VELOCITY-631. |
class |
Velocity644TestCase
This class tests VELOCITY-644. |
|
||||||||||
| PREV NEXT | FRAMES NO FRAMES |


Wills primary responsibilities as a product owner can expand to three distinct sub-functions: Being out in the marketplace, sitting and listening to their business, Finding patterns across multiple customers Articulate problems from the customers to the team and fix those identified problems. It is owed to the product owner to actually interact with the customers. Then, being with the team to facilitate discussions to solve a problem. This specific job requires to be less technical, however you do need to talk to a team that works on the technical approach of things.
Spencers primary responsibilities working as an U.X designer can expand to designing eternal software, customer facing, testing the design, and research with developers. For example, working with another team on a particular feature that a customer wants, and research if its is dooible. A recurring objective amongst U.X designers is critique developed by the customer, as they make the broader customer commits to the design. Rather than implementing a specizaled customer commit, which then could generate problems in the long run.
Anthony's responsibilities working as an engineer is to write, maintain, test and review code, for the journey builder application which delivers digital marketing cloud solutions to customers. In addition, engineers also can take the appoarch in fixing/improving the U.I in a journey builder with middle tier review and write. Also, facilitating the ideals of SCRUM (framework for agile working), is apparate amongst all members in a team. Which then translates in an efficent workflow and as a result get projects done with customers quickly.
Todd’s primary responsibility as service is to work with customers while using a technical background and knowledge of marketing cloud, to then implement the results to the actual product. The technical background can showcase the understanding of data flow, however, talking to customers and flushing out a discussion with them in regards of a potential product is ideal. The project manager deals with the customer, however depending on the product and the project being worked with shows how much interaction someone working in service gets with a customer.
Dans primary responsibility as a technical writer is to provide documentation for customers to consult to, if help or technical solutions is needed for a specific tool or workflow. In doing so, the opportunity to write stuff down about a certain tool needs to be concise and readable for a non-technical audience. The technical writer does however need to have in a certain degree, an understanding about the specific tool and workflow in order to write about it.


Configuration ¶
Global Configuration ¶
Configuration file codeception.yml
is generated by codecept bootstrap
command. It has preconfigured settings you can change.
Here are global options you can change inside configuration:
actor: Tester
: changes suffix for Actor classes. This defines a rule to generate new test suites. If you changeTester
toNinja
, and generate newapi
test suite, you will getApiNinja
actor class.namespace
: set a namespace for tests. All new tests and support classes will be generated under that namespace. Allows to configure multiple test setups for one runner.include: []
: include additional Codeception configurations for multiple applications setup.paths
directories used by Codeception. Default values are:
paths:
# where the tests stored
tests: tests
# directory for fixture data
data: tests/_data
# directory for support code
support: tests/_support
# directory for output
output: tests/_output
# directory for environment configuration
envs: tests/_envs
settings
: provide additional options for test runner. They may dramatically change the way Codeception is executed. For instance, take a note ofshuffle
option which allows to randomize tests execution order andlint
option that toggles parsing a test file (usingphp -l
) before loading it.
settings:
# name of bootstrap that will be used
# each bootstrap file should be
# inside a suite directory.
bootstrap: _bootstrap.php
# enable/disable syntax of test files before loading
# for php < 7 exec('php -l') is used
# disable if you need to speed up tests execution
lint: true
# randomize test order
shuffle: true
# by default it's false on Windows
# use [ANSICON](https://github.com/adoxa/ansicon) to colorize output.
colors: true
# Generate XML JUnit report using strict schema
# Avoid putting additional report fields like steps or scenario names tot it
# Required for XML reports on Jenkins CI
strict_xml: false
# Tests (especially functional) can take a lot of memory
# We set a high limit for them by default.
memory_limit: 1024M
# This value controls whether PHPUnit attempts to backup global variables
# See https://phpunit.de/manual/current/en/appendixes.annotations.html#appendixes.annotations.backupGlobals
backup_globals: true
# PHPUnit can be strict about tests that do not test anything
# See https://phpunit.de/manual/current/en/risky-tests.html#risky-tests.useless-tests
report_useless_tests: false
# PHPUnit can be strict about output during tests.
# See https://phpunit.de/manual/current/en/risky-tests.html#risky-tests.output-during-test-execution
disallow_test_output: false
# PHPUnit can be strict about tests that manipulate global state.
# See https://phpunit.de/manual/current/en/risky-tests.html#risky-tests.global-state-manipulation
be_strict_about_changes_to_global_state: false
# Log the incomplete and skipped tests into junit report
# See https://phpunit.de/manual/current/en/appendixes.configuration.html
# Section logging > junit
log_incomplete_skipped: false
modules
: allows to create shared module configuration for all included suites.
modules:
config:
Db:
dsn: ''
user: ''
password: ''
dump: tests/_data/dump.sql
extends
: allows you to specify a file (relative to thecodeception.yml
file) that holds some already pre-defined values. This can be used to always use the same configuration for modules or whatever.extensions
: allows to enable and configure Codeception extensions, Group Objects, and Custom Commands.reporters
: allows to change default reporters of Codeceptioncoverage
: CodeCoverage settings.params
: allows to pass external parameters into module configuration.gherkin
: BDD-specific Gherkin options.
Suite Configuration ¶
Each generated suite have its own configuration inside directory set by paths: tests:
configuration option in codeception.yml
. Each suite configuration is named like suitename.suite.yml
. It allows to enable and configure modules, and more.
actor
: name of the actor class for current suite.modules
: list of enabled modules with their configuration.
modules:
# enabled modules and helpers
enabled:
# built-in modules are listed by their names
- PhpBrowser:
# module configuration
url: http://localhost
# this module is pre-configured in global config
- Db
# helper names are listed by their class names
# by convention their names start with \
- \Helper\Acceptance
# additional modules configuration
# can be used for modules which are not currently enabled
config:
WebDriver:
browser: firefox
# list of modules disabled for this suite
disabled:
- WebDriver
extends
: allows you to specify a file (relative to the*.suite.yml
file) that holds some already pre-defined values. This can be used to always use the same configuration for modules or whatever.namespace
: default namespace of actor, support classes and tests.suite_namespace
: default namespace for new tests of this suite (ignoresnamespace
option)env
: override any configuration per environment.groups
: groups with the list of tests of for corresponding group.formats
: formats with the list of extra test format classes.coverage
: pre suite CodeCoverage settings.gherkin
: per suite BDD Gherkin settings.error_level
: error level for runner in current suite. Should be specified for unit, integration, functional tests. Passes value toerror_reporting
function.
Config Templates (dist) ¶
To provide the same configuration template for your development team, you can create a codeception.dist.yml
config file, which will be loaded before codeception.yml
. The dist config provides shared options, while local codeception.yml
files override them on a per-installation basis. Therefore, codeception.yml
should be ignored by your VCS system.
Config templates can also be used for suite configuration, by creating a suitename.suite.dist.yml
file.
Configuration loading order:
codeception.dist.yml
codeception.yml
acceptance.suite.dist.yml
acceptance.suite.yml
- environment config


# Let's try each piece
input("Test")
TestOKAYYYYY
'OKAYYYYY'
import urllib
import json as m_json
query = raw_input ( 'Query: ' )
query = urllib.urlencode ( { 'q' : query } )
response = urllib.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response )
results = json [ 'responseData' ] [ 'results' ]
for result in results:
title = result['title']
url = result['url'] # was URL in the original and that threw a name error exception
print ( title + '; ' + url )
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-2-cb97e4039feb> in <module>()
1 import urllib
2 import json as m_json
----> 3 query = raw_input ( 'Query: ' )
4 query = urllib.urlencode ( { 'q' : query } )
5 response = urllib.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
NameError: name 'raw_input' is not defined
# Uh oh. An error. That's okay. We can search for it!
# If we google the error, the number 1 result has the fix
import urllib
import json as m_json
query = input ( 'Query: ' )
query = urllib.urlencode ( { 'q' : query } )
response = urllib.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response )
results = json [ 'responseData' ] [ 'results' ]
for result in results:
title = result['title']
url = result['url'] # was URL in the original and that threw a name error exception
print ( title + '; ' + url )
Query: test
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-4-1be6b285e7fd> in <module>()
2 import json as m_json
3 query = input ( 'Query: ' )
----> 4 query = urllib.urlencode ( { 'q' : query } )
5 response = urllib.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
6 json = m_json.loads ( response )
AttributeError: 'module' object has no attribute 'urlencode'
# Another error. Let's search for it again
import urllib
import json as m_json
query = input ( 'Query: ' )
query = urllib.parse.urlencode ( { 'q' : query } )
response = urllib.request.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response.decode('utf8') )
results = json [ 'responseData' ] [ 'results' ]
for result in results:
title = result['title']
url = result['url'] # was URL in the original and that threw a name error exception
print ( title + '; ' + url )
Query: Golf superstar
Superstar Golf! free online flash game - Free flash games, football ...; http://www.mousebreaker.com/games/superstargolf
Play Superstar Golf! - Sport Games – Free Online ... - Mousebreaker; http://www.mousebreaker.com/games/superstargolf/playgame
Superstar Golf - Free online games at Agame.com; http://www.agame.com/game/superstar-golf
Superstar Golf - Mini Putt; http://www.mini-putt.org/superstargolf.html
# Wait a sec - we want actual data - not web results. How can we get wikipedia only? Search for it!
import urllib
import json as m_json
query = input ( 'Query: ' )
query += ' site:wikipedia.org'
query = urllib.parse.urlencode ( { 'q' : query } )
response = urllib.request.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response.decode('utf8') )
results = json [ 'responseData' ] [ 'results' ]
for result in results:
title = result['title']
url = result['url'] # was URL in the original and that threw a name error exception
print ( title + '; ' + url )
Query: Golf superstar
Arnold Palmer - Wikipedia, the free encyclopedia; http://en.wikipedia.org/wiki/Arnold_Palmer
Mario Superstar Baseball - Wikipedia, the free encyclopedia; http://en.wikipedia.org/wiki/Mario_Superstar_Baseball
Harry Vardon - Wikipedia, the free encyclopedia; http://en.wikipedia.org/wiki/Harry_Vardon
Mario Superstar Baseball - Wikipedia; http://it.wikipedia.org/wiki/Mario_Superstar_Baseball
# That's more like it! Let's just return the first result and format it to be in the form of Jeopardy
# To do that, let's make this a function and do some string replacing so that it just returns the first answer!
import urllib
import json as m_json
def watson1(query):
query += ' site:wikipedia.org'
query = urllib.parse.urlencode ( { 'q' : query } )
response = urllib.request.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response.decode('utf8') )
results = json [ 'responseData' ] [ 'results' ]
for result in results:
title = result['title']
url = result['url'] # was URL in the original and that threw a name error exception
return title.replace(' - Wikipedia, the free encyclopedia','')
query = input ( 'Question: ' )
print(watson1(query))
Question: He is a golf superstar
Arnold Palmer
import json as m_json
import urllib
query = input ( 'Query: ' )
query += ' site:wikipedia.org '
query = urllib.parse.urlencode ( { 'q' : query } )
response = urllib.request.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response.decode('utf8') )
results = json [ 'responseData' ] [ 'results' ]
answers = []
for result in results:
title = result['title']
url = result['url']
answers += [title]
for answer in answers:
if query.lower().strip() not in answer.lower().strip():
# res = answer.replace(' - Wikipedia, the free encyclopedia','')
res = answer.replace(' - Wikipedia, the free encyclopedia','')
res = res.replace('','')
res = res.replace('','')
print("What is " + res + '?')
break
Query:
What is Wikipedia?
# As a function
import json as m_json
import urllib
def watson(query):
query += ' site:wikipedia.org '
query = urllib.parse.urlencode ( { 'q' : query } )
response = urllib.request.urlopen ( 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&' + query ).read()
json = m_json.loads ( response.decode('utf8') )
results = json [ 'responseData' ] [ 'results' ]
answers = []
for result in results:
title = result['title']
url = result['url']
answers += [title]
for answer in answers:
if query not in answer:
# res = answer.replace(' - Wikipedia, the free encyclopedia','')
res = answer.replace(' - Wikipedia, the free encyclopedia','')
res = res.replace('','')
res = res.replace('','')
return "What is " + res + '?'
return "No Results :("
football = "He was the highest paid football player in 2008."
print("Q:" + football)
print(watson(football))
query = input ( 'Jeopardy Question: ' )
print(watson(query))
Q:He was the highest paid football player in 2008.
What is Cristiano Ronaldo?
Jeopardy Question: Who is the best jeopardy player of all time?
What is Ken Jennings?
#Search Wikipedia Directly Instead of Google
import urllib
def searchWiki(q):
query = urllib.parse.urlencode ( { 'gsrsearch' : q } )
response = urllib.request.urlopen ( 'http://en.wikipedia.org/w/api.php?action=query&generator=search&prop=info&format=json&' + query ).read()
json = m_json.loads ( response.decode('utf8') )
# print(json)
return json['query']['pages']
# searchWiki("Highest paid football player")


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class: center, middle, inverse, title-slide # 3.3 — Social Functions of Market Prices ## ECON 306 • Microeconomic Analysis • Spring 2021 ### Ryan Safner
Assistant Professor of Economics
<EMAIL_ADDRESS>ryansafner/microS21
microS21.classes.ryansafner.com
--- class: inverse # Outline ### [Why Markets Tend to Equilibrate, Redux](#7) ### [The Social Functions of Market Prices](#23) ### [Uncertainty and Profits](#37) --- # The Model is Not the Reality I .pull-left[ .center[ ![](https://www.dropbox.com/s/17cb7ceqipgi8fs/citymodel.jpg?raw=1) ] ] .pull-right[ .smallest[ - This course is about economic modeling and formal theory - Applications in ECON electives - Models help us *understand* reality, but they *are not* reality! - Don't mistake the map for the territory itself > *"All models are wrong. Some are useful"* - George Box ] ] --- # The Model is Not the Reality II .pull-left[ .center[ ![](https://www.dropbox.com/s/17cb7ceqipgi8fs/citymodel.jpg?raw=1) ] ] .pull-right[ .smallest[ - Our models so far have given us interesting results: - Markets reach equilibrium - Economic profits are zero in the long run in competitive markets - Both are **fictional** - But the models **still** show us useful insights about how a market economy works - Some readings in today's readings page to help you understand ] ] --- # The Model is Not the Reality III .center[ ![:scale 25%](https://www.dropbox.com/s/in42z1ia3f8c18t/smbcmicro.png?raw=1) Source: [SMBC](https://www.smbc-comics.com/comic/2013-09-19) “Shame on the three of you who enjoyed this joke” ] --- # The Model is Not the Reality III .center[ ![](../images/science_vs_easy_answers.jpg) ] --- class: inverse, center, middle # Why Markets Tend to Equilibrate, Redux --- # The Law of One Price I .pull-left[ - .hi[Law of One Price]: *all* units of the *same* good exchanged on the market will tend to have the same market price (the market-clearing price, `\(p^*)\)` ] .pull-right[  ] --- # The Law of One Price II .pull-left[ .center[ ![:scale 100%](https://www.dropbox.com/s/pjp9bpvqp54ldn4/individual1.png?raw=1) ] ] .pull-right[ .smaller[ - Consider if there are *multiple* different prices for *same* good: - .hi-purple[Arbitrage] opportunities: optimizing individuals recognize **profit opportunity**: - Buy at low price, resell at high price! - There are possible gains from trade or gains from innovation to be had - .hi-purple[Entrepreneurship]: recognizing profit opportunities and entering a market as a seller to try to capture gains from trade/innovation ] ] --- # Arbitrage and Entrepreneurship I .center[ ![:scale 80%](https://www.dropbox.com/s/zbx1qdjzc2cs55z/20onsidewalk.jpg?raw=1) ] --- # Arbitrage and Entrepreneurship II .center[  ] --- # Arbitrage and Entrepreneurship III .center[  ] --- # Uncertainty vs. Risk .center[  ] --- # Uncertainty vs. Risk .left-column[ .center[ ![:scale 100%](../images/rumsfeld.png) ] ] .right-column[ - **“Known knowns”**: .hi-purple[perfect information] - **“Known unknowns”**: .hi-purple[risk] - We know the probability distribution of states that *could* happen - We just don't know *which* state will be realized - We can estimate probabilities, maximize expected value, minimize variance, etc. ] --- # Uncertainty vs. Risk .left-column[ .center[ ![:scale 100%](../images/rumsfeld.png) ] ] .right-column[ - **“Unknown unknowns”**: .hi[uncertainty] - We don’t even know the probability distribution of states that *could* happen - *No model to optimize* in a world of uncertainty! ] --- # The Role of Entrepreneurial Judgment .left-column[ .center[ ![](../images/ideaguy.jpg) ] ] .right-column[ - Under true .hi[uncertainty], it’s not that we can’t assign probabilities to each outcome; we do not even have the knowledge necessary to list all possible outcomes! - Requires .hi-purple[entrepreneurial judgment] to *both*: 1. estimate possible actions *and* 2. estimate the likelihood of their success - .hi[Entrepreneur] is central player, earns pure profits (a residual) for *bearing uncertainty* ] --- # Entrepreneurial Judgment .left-column[ .center[ ![:scale 80%](../images/henryford.jpg) .smallest[ Henry Ford 1863-1947 ] ] ] .right-column[ > “If I had asked people what they wanted, they would have said **faster horses**.” - Henry Ford ] --- # Entrepreneurial Judgment .pull-left[ .center[ ![](../images/steve_jobs_iphone.jpg) ] ] .pull-right[ > “It's really hard to design products by focus groups. A lot of times, **people don't know what they want until you show it to them**.” - Steve Jobs ] --- # Uncertainty and Entrepreneurship .left-column[ .center[ ![:scale 80%](../images/zuckerberg.png) Mark Zuckerberg 1984- ] ] .right-column[ > "Why were we the ones to build [Facebook]? We were just students. We had way fewer resources than big companies. If they had focused on this problem, they could have done it. The only answer I can think of is: **we just cared more**. **While some doubted** that connecting the world was actually important, **we were building**. While others doubted that this would be sustainable, **we were forming lasting connections**." ] --- # How Markets Get to Equilibrium I .pull-left[ .center[ ![](../images/kiviqauction.png) ] ] .pull-right[ .smaller[ - .hi-turquoise[Nobody knows “the right price” for things] - Each buyer and seller only know **their own** reservation prices - Buyers and sellers adjust their bids/asks - Markets do not *start* competitive, but *become* competitive! - New entrepreneurs enter to try to capture gains from trade/innovation - As these gains are exhausted, prices converge to equilibrium ] ] --- # How Markets Get to Equilibrium II .pull-left[ .center[ ![:scale 100%](../images/planning.png) ] ] .pull-right[ .smaller[ - Errors and imperfect information `\(\implies\)` multiple prices - `\(\implies\)` arbitrage opportunities `\(\implies\)` entrepreneurship - `\(\implies\)` correcting mistakes `\(\implies\)` people update their behavior & expectations - Markets are .hi-purple[discovery processes] that *discover* the right prices, the optimal uses of resources, and cheapest production methods, none of which can be known in advance! ] ] --- # How Markets Get to Equilibrium III .pull-left[ .center[ ![](../images/catandmouse.jpg) ] ] .pull-right[ .smallest[ - Economy as a cat-and-mouse game between: - **Mouse**: preferences, technologies, alternative uses of resources - **Cat**: market prices, least-cost technologies - Cat always chasing mouse - Mouse *always* moving - Any time cat hasn’t caught mouse: profit opportunities - **IF** mouse *froze*, market would rest at equilibrium ] ] --- class: inverse, center, middle # The Social Functions of Market Prices --- # Prices are Signals I .center[ ![:scale 60%](../images/kiviqauction.png) ] --- # Prices are Signals II .pull-left[ .center[ ![](../images/moneysignal.jpg) ] ] .pull-right[ .smallest[ - .hi-purple[Markets are social *processes* that generate information via prices] - .hi-purple[Prices are never "given"], prices .hi-purple[emerge] dynamically from negotiation and market decisions of entrepreneurs and consumers - **Competition**: is a .hi-purple[discovery process] which *discovers* what consumer preferences are and what technologies are lowest cost, and how to allocate resources accordingly ] ] --- # The Social Functions of Prices I .pull-left[ .center[ ![:scale 100%](../images/platinum.jpg) ] ] .pull-right[ .smaller[ A relatively high price: - .hi-purple[Conveys information]: good is relatively scarce - .hi-purple[Creates incentives for]: - **Buyers**: conserve use of this good, seek substitutes - **Sellers**: produce more of this good - **Entrepreneurs**: find substitutes and innovations to satisfy this unmet need ] ] --- # The Social Functions of Prices II .pull-left[ ![:scale 100%](../images/brick.jpg) ] .pull-right[ .smaller[ A relatively low price - .hi-purple[Conveys information]: good is relatively abundant - .hi-purple[Creates incentives for]: - **Buyers**: substitute away from expensive goods towards this good - **Sellers**: Produce less of this good, talents better served elsewhere - **Entrepreneurs**: talents better served elsewhere: find more severe unmet needs ] ] --- # The Social Functions of Prices III .pull-left[ .center[ ![](../images/priceuses.png) ] ] .pull-right[ .smaller[ - .hi-purple[Prices tell us how to allocate scarce resources among competing uses] - Think of diminishing marginal utility: - allocate scarce good to highest-valued use first - as supply becomes more plentiful (price falls), can allocate more units of the good to lower-valued uses (higher-valued uses already satisfied) ] ] --- # Knowledge, “Speculation,” and Prices .pull-left[ .smallest[ - Suppose (oil) producers believe there is going to be a shortage (of oil) in a year ] ] .pull-right[  ] --- # Knowledge, “Speculation,” and Prices .pull-left[ .smallest[ - Suppose (oil) producers believe there is going to be a shortage (of oil) in a year - Suppose they do nothing - In the future, a sudden spike in price - Demand is inelastic to sudden changes, consumers can’t adjust on the fly - A lot of lost economic surplus (shaded) ] ] .pull-right[  ] --- # Knowledge, “Speculation,” and Prices .pull-left[ .smallest[ - Suppose (oil) producers believe there is going to be a shortage (of oil) in a year - Suppose instead they .hi-purple[speculate], and try to profit from the future price change - TODAY: put some inventory .hi-purple[into storage] (take off market) - FUTURE: when price is higher, sell more .hi-purple[from inventories] ] ] .pull-right[  ] --- # Knowledge, “Speculation,” and Prices .pull-left[ .smallest[ - Suppose (oil) producers believe there is going to be a shortage (of oil) in a year - Suppose instead they .hi-purple[speculate], and try to profit from the future price change - TODAY: put some inventory .hi-purple[into storage] (take off market) - FUTURE: when price is higher, sell more .hi-purple[from inventories] - .hi[Price-smoothing] over time - Small loss in the present (gray shaded), larger gain in the future (green shaded) - Allows consumers to adjust their plans more over time (more elastic demand) ] ] .pull-right[  ] --- # Knowledge, “Speculation,” and Prices .pull-left[ - .hi[Futures markets]: where people buy/sell claims on *future* goods at specified prices - e.g. “10 barrels of oil at $30/barrel, delivered on November 2021” - allows producers to minimize their exposure to major price swings ] .pull-right[ .center[ ![](../images/oilfutures.png) ] ] --- # Knowledge, “Speculation,” and Prices .center[ ![:scale 75%](../images/oilnegative.png) ] --- # Knowledge, “Speculation,” and Prices .pull-left[ - .hi[Prediction markets]: where people buy/sell claims on *verifiable* future outcomes at specified prices - Hope to profit on information you believe to be true - Provides incentives for people to reveal private information for public benefit - If you want to know what somebody truly believes, leverage the power of prices and .hi-purple[make a bet] - Forces them to “put their money where their mouth is” and make a costly tradoff: false beliefs vs. losing money ] .pull-right[ .center[ ![](../images/bet.jpg) ] ] --- # Knowledge, “Speculation,” and Prices .pull-left[ .center[ ![](../images/prediction1.png) ] ] .pull-right[ .center[ ![](../images/prediction2.png) ] ] --- class: inverse, center, middle # Uncertainty and Profits --- # Uncertainty, Tacit Information, and Profit I .pull-left[ - **Economic theory**: in a perfectly competitive market, in the long run, economic profit `\(\rightarrow\)` to zero - **Real world**: there *are* often economic profits - Our blackboard models assume perfect information - In reality we have to deal with .hi-purple[uncertainty] ] .pull-right[ .center[ ![](../images/citymodel.jpg) ] ] --- # Uncertainty, Tacit Information, and Profit II .pull-left[ .smaller[ - Imperfect information: mispricing and multiple prices `\(\rightarrow\)` arbitrage/profit opportunities - Some people recognize opportunities ($20 bills) that others do not see - .hi-purple[In a world of certainty, there would be no profit] - The model world of perfect competition is a fictional world of certainty - The real world, *because* it’s uncertain, *has* profit opportunities! ] ] .pull-right[ .center[ ![](../images/choices.jpg) ] ] --- # Uncertainty, Tacit Information, and Profit III .pull-left[ .smallest[ - Firms don’t actually *maximize* profits, just a convenient assumption - In a world of uncertainty (unlike mere risk), there’s no way to *maximize* anything! - Real world is not merely a constrained maximization problem! - Better to think in **evolutionary** terms - Firms that *best* adapt to market circumstances will earn profit and merely *survive* - Whether by skill and talent or just dumb luck! ] ] .pull-right[ .center[ ![](../images/robustness.jpg) ] ] --- # Uncertainty, Tacit Information, and Profit IV .center[  ] --- # Reminder: Profits and Entrepreneurship .pull-left[ .center[ ![](../images/feedback.png) ] ] .pull-right[ .smaller[ - In markets, production faces .hi[profit-test]: - Is consumer's willingness to pay `\(>\)` opportunity cost of inputs? - Profits are an indication that **value is being created for society** - Losses are an indication that **value is being destroyed for society** - Survival for sellers in markets *requires* firms continually create value and earn profits or die ] ] --- # Why We Need Prices, Profits, and Losses I .pull-left[ .center[ ![](../images/planning.jpg) ] ] .pull-right[ .smaller[ - People often confuse the .hi[economic problem] with a .hi-purple[technological problem] - .hi-purple[Technological problem]: how to allocate scarce resources to accomplish a particular goal - e.g. buy the right combination of goods to maximize utility - e.g. buy the right combination of inputs and produce output to maximize profits - given stable prices, preferences, and technologies, **a computer can solve this problem** ] ] --- # Why We Need Prices, Profits, and Losses II .pull-left[ .center[ ![](../images/planning.jpg) ] ] .pull-right[ - .hi[Economic calculation problem]: how to determine which of the infinite technologically-feasible options are *economically* viable? - .hi-purple[How to best make use of dispersed knowledge to coordinate conflicting plans of individuals for their own ends?] - ONLY can be **discovered** through competition, prices, profits & losses ] --- # What if there Were No Prices? I .center[  ] --- # What if there Were No Prices? II .center[  ] --- # For More On The Socialist Calculation Debate .pull-left[ .center[ ![:scale 80%](../images/thought_hex2.png) ] ] .pull-right[ See lesson 4.2 in my History of Economic Thought Course: [The Socialist Calculation Debate](https://thoughtf20.classes.ryansafner.com/schedule) ] --- # And How Did The Soviet Union “Work” For So Long? .pull-left[ .center[ ![:scale 80%](../images/dev_hex.png) ] ] .pull-right[ See lesson 12 in my Economics of Development Course: [Russia and the Post-Communist Transition](https://devf19.classes.ryansafner.com/schedule) ]


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DP World Tour: Magnificent Jon Rahm poised for Dubai double
by FSA EditorWorld number five Jon Rahm could land a huge payday in Dubai on Sunday, with two titles in his sights.
Jon Rahm holds a share of the lead at the DP World Tour Championship and is on course to win the Race to Dubai title after a magnificent third round.
Rahm started moving day in joint-second place with Tommy Fleetwood – also battling to be crowned European number one – and will begin his final round level with Mike Lorenzo-Vera on 15 under.
The Spaniard matched his six-under opening round of 66 to catch Lorenzo-Vera at Jumeirah Golf Estates, where the leading duo hold a two-shot advantage over Rory McIlroy.
Fleetwood just about had the edge in the tussle for the Race to Dubai title at the halfway mark in the final tournament of the season, but it is advantage Rahm after the Englishman signed for a two-under 70.
World number five Rahm, four shots ahead of Fleetwood, will win the Race to Dubai if he repeats his 2017 triumph at the Earth Course and Bernd Wiesberger finishes lower than solo second.
Wiesberger began the week as the man to catch, but is down in a share of 24th place with his chances looking slim.
Second place will also be good enough for Rahm to overhaul Wiesberger if the Austrian finishes worse than solo 21st and none of Fleetwood, Shane Lowry or Matt Fitzpatrick win the title on Sunday.
Rahm birdied the first two holes and hit the turn in 34 after his only bogey of the day at the eighth, then picked up another four shots on the back nine to draw level with Lorenzo-Vera.
Lorenzo-Vera said he was wary of “big dogs” biting him after ending his second round with a three-shot lead and a solitary bogey at the 18th meant he had to settle for a second successive 69.
Fleetwood could only muster three birdies to leave himself with work to do, while McIlroy enhanced his chances of winning the tournament for a third time by shooting a brilliant seven-under 65 – including an eagle-three at the seventh.
Fitzpatrick is nine shots off the lead, with Lowry a further stroke back.


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+++ title = "More jungle romping" slug = "more-jungle-romping" date = 2007-06-18T10:00:00+10:00 tags = ["hiking", "jungle", "madidi"] locations = ["bolivia/rurrenabaque"] draft = false summary = """
We romped through the jungle on our first day here in Madidi. We did it again yesterday. And we had our final romp today. Not much different to the previous days of jungle walking, really: saw a few animals, saw lots of trees and smaller plants, but nothing hugely exciting. After all, jungle is jungle, and there's only so much of it you can see.
""" +++We romped through the jungle on our first day here in Madidi. We did it again yesterday. And we had our final romp today. Not much different to the previous days of jungle walking, really: saw a few animals, saw lots of trees and smaller plants, but nothing hugely exciting.


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Psalm 147
1 Praise Yahweh,
for it is good to sing praises to our God,
it is pleasant, and praise is suitable.
2 Yahweh rebuilds Jerusalem,
he gathers together the scattered people of Israel.
3 He heals the brokenhearted
and binds up their wounds.
4 He counts the stars,
he gives names to all of them.
5 Great is our Lord and awesome in power,
his understanding cannot be measured.
6 Yahweh lifts up the oppressed,
he brings the wicked down to the ground.
7 Sing to Yahweh with thanksgiving,
sing praises to our God with a harp.
8 He covers the heavens with clouds
and prepares rain for the earth,
making the grass to grow on the mountains.
9 He gives food to the animals
and to the young ravens when they cry.
10 He finds no delight in the strength of a horse,
he takes no pleasure in the strong legs of a man.
11 Yahweh takes pleasure in those who honor him,
who hope in his covenant faithfulness.
12 Praise Yahweh, Jerusalem,
praise your God, Zion.
13 For he strengthens the bars of your gates,
he blesses your children among you.
14 He brings prosperity inside your borders,
he satisfies you with the finest of wheat.
15 He sends out his commandment to earth,
his command runs very swiftly.
16 He makes the snow like wool,
he scatters the frost like ashes.
17 He dispenses the hail like crumbs,
who can withstand the cold he sends?
18 He sends out his command and melts them,
he makes the wind to blow and the water to flow.
19 He proclaimed his word to Jacob,
his statutes and his righteous decrees to Israel.
20 He has not done so with any other nation,
and as for his decrees, they do not know them.
Praise Yahweh.


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object jml.sequence.HMM
public class HMM
A Java implementation of basic Hidden Markov Model. Observation symbols and state symbols are discrete integers starting from 0. It is the responsibility of users to maintain the mapping from IDs to observation symbols and the mapping from IDs to state symbols.
| Field Summary | |
|---|---|
(package private) double[][] |
A
State transition probability matrix. |
(package private) double[][] |
B
Observation probability matrix. |
(package private) double |
epsilon
Convergence precision. |
(package private) int |
M
Number of distinct observation symbols per state. |
(package private) int |
maxIter
Maximal number of iterations. |
(package private) int |
N
Number of states in the model. |
(package private) int[][] |
Os
Observation sequences for training. |
(package private) double[] |
pi
Initial state distribution. |
(package private) int[][] |
Qs
Hidden state sequences for training data. |
| Constructor Summary | |
|---|---|
HMM()
Default constructor. |
|
HMM(int N,
int M)
Construct an HMM with default convergence precision being 1e-6 and maximal number of iterations being 1000. |
|
HMM(int N,
int M,
double epsilon,
int maxIter)
Construct an HMM. |
| Method Summary | |
|---|---|
double[][] |
allocateMatrix(int nRows,
int nCols)
Allocate memory for a 2D double array. |
double[] |
allocateVector(int n)
Allocate continuous memory block for a 1D double
array. |
int |
argmax(double[] V)
Compute the maximum argument. |
void |
assignVector(double[] V,
double v)
Assign a 1D double array by a real scalar. |
void |
assignVector(double[] V1,
double[] V2)
Element-wise assignment operation. |
void |
clearMatrix(double[][] M)
Clear all elements of a 2D double array to zero. |
void |
clearVector(double[] V)
Clear all elements of a 1D double array to zero. |
void |
divideAssign(double[] V,
double v)
Element-wise division and assignment operation. |
double |
evaluate(int[] O)
Compute P(O|Theta), the probability of the observation sequence given the model, by forward recursion with scaling. |
double |
evaluate2(int[] O)
Compute P(O|Theta), the probability of the observation sequence given the model, by forward recursion without scaling. |
void |
feedData(int[][] Os)
Feed observation sequences for training. |
void |
feedLabels(int[][] Qs)
Feed state sequences for training data. |
double[] |
genDiscreteDistribution(int n)
Generate a discrete distribution with sample size of n. |
static int[][][] |
generateDataSequences(int D,
int T_min,
int T_max,
double[] pi,
double[][] A,
double[][] B)
Generate observation sequences with hidden state sequences given model parameters and number of data sequences. |
double[][] |
getA()
|
double[][] |
getB()
|
double[] |
getPi()
|
private double[][] |
initializeA()
|
private double[][] |
initializeB()
|
private double[] |
initializePi()
|
void |
loadModel(java.lang.String filePath)
Load an HMM model from a file. |
static void |
main(java.lang.String[] args)
|
void |
plusAssign(double[] V1,
double[] V2)
Element-wise addition and assignment operation. |
int[] |
predict(int[] O)
Predict the best single state path for a given observation sequence using Viterbi algorithm with logarithms. |
int[] |
predict2(int[] O)
Predict the best single state path for a given observation sequence using Viterbi algorithm. |
void |
saveModel(java.lang.String filePath)
Save this HMM model to a file. |
void |
setA(double[][] A)
|
void |
setB(double[][] B)
|
void |
setOs(int[][] Os)
|
void |
setPi(double[] pi)
|
void |
setQs(int[][] Qs)
|
void |
showObservationSequence(int[] O)
Show an observation sequence. |
void |
showStateSequence(int[] Q)
Show a state sequence. |
double |
sum(double[] V)
Compute the sum of a 1D double array. |
void |
sum2one(double[] V)
Sum a 1D double array to one, i.e., V[i] = V[i] / sum(V). |
void |
timesAssign(double[] V,
double v)
Element-wise multiplication and assignment operation. |
void |
timesAssign(double[] V1,
double[] V2)
Element-wise multiplication and assignment operation. |
void |
train()
Inference the basic HMM with scaling. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
int[][] Os
int[][] Qs
int N
int M
double[] pi
double[][] A
double[][] B
double epsilon
int maxIter
| Constructor Detail |
|---|
public HMM()
public HMM(int N, int M, double epsilon, int maxIter)
N
- number of states in the modelM
- number of distinct observation symbols per stateepsilon
- convergence precisionmaxIter
- maximal number of iterationspublic HMM(int N, int M)
N
- number of states in the modelM
- number of distinct observation symbols per state| Method Detail |
|---|
public static void main(java.lang.String[] args)
args
- public void feedData(int[][] Os)
Os
- observation sequencespublic void feedLabels(int[][] Qs)
Qs
- state sequencespublic double evaluate2(int[] O)
O
- an observation sequence
public double evaluate(int[] O)
O
- an observation sequence
public int argmax(double[] V)
V
- a double
array
public int[] predict2(int[] O)
O
- an observation sequence
public int[] predict(int[] O)
O
- an observation sequence
public void train()
public double[] genDiscreteDistribution(int n)
n
- sample size
private double[][] initializeB()
private double[][] initializeA()
private double[] initializePi()
public void assignVector(double[] V, double v)
double
array by a real scalar.
V
- a 1D double
arrayv
- a real scalarpublic void clearVector(double[] V)
double
array to zero.
V
- a double
arraypublic void clearMatrix(double[][] M)
double
array to zero.
M
- a 2D double
arraypublic double[] allocateVector(int n)
double
array.
n
- number of elements to be allocated
double
array of length npublic double[][] allocateMatrix(int nRows, int nCols)
double
array.
nRows
- number of rowsnCols
- number of columns
double
arraypublic void divideAssign(double[] V, double v)
V
- a 1D double
arrayv
- a real scalarpublic void timesAssign(double[] V, double v)
V
- a 1D double
arrayv
- a real scalarpublic void timesAssign(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic double sum(double[] V)
double
array.
V
- a 1D double
array
public void sum2one(double[] V)
double
array to one, i.e., V[i] = V[i] / sum(V).
V
- a 1D double
arraypublic void plusAssign(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic void assignVector(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic void saveModel(java.lang.String filePath)
filePath
- file path to save the modelpublic void loadModel(java.lang.String filePath)
filePath
- file Path to load an HMM model frompublic void setQs(int[][] Qs)
public void setOs(int[][] Os)
public void setPi(double[] pi)
public void setA(double[][] A)
public void setB(double[][] B)
public double[] getPi()
public double[][] getA()
public double[][] getB()
public void showStateSequence(int[] Q)
Q
- a state sequence represented by a 1D
int
arraypublic void showObservationSequence(int[] O)
O
- an observation sequence represented by a 1D
int
arraypublic static int[][][] generateDataSequences(int D, int T_min, int T_max, double[] pi, double[][] A, double[][] B)
D
- number of data sequences to be generatedT_min
- minimal sequence lengthT_max
- maximal sequence lengthpi
- initial state distributionA
- state transition probability matrixB
- observation probability matrix
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


hunch_net hunch_net-2012 knowledge-graph by maker-knowledge-mining
1 hunch net-2012-12-29-Simons Institute Big Data Program
Introduction: Michael Jordan sends the below: The new Simons Institute for the Theory of Computing will begin organizing semester-long programs starting in 2013. One of our first programs, set for Fall 2013, will be on the “Theoretical Foundations of Big Data Analysis”. The organizers of this program are Michael Jordan (chair), Stephen Boyd, Peter Buehlmann, Ravi Kannan, Michael Mahoney, and Muthu Muthukrishnan. See http://simons.berkeley.edu/program_bigdata2013.html for more information on the program. The Simons Institute has created a number of “Research Fellowships” for young researchers (within at most six years of the award of their PhD) who wish to participate in Institute programs, including the Big Data program. Individuals who already hold postdoctoral positions or who are junior faculty are welcome to apply, as are finishing PhDs. Please note that the application deadline is January 15, 2013. Further details are available at http://simons.berkeley.edu/fellows.h
2 hunch net-2012-10-26-ML Symposium and Strata-Hadoop World
Introduction: The New York ML symposium was last Friday. There were 303 registrations, up a bit from last year . I particularly enjoyed talks by Bill Freeman on vision and ML, Jon Lenchner on strategy in Jeopardy, and Tara N. Sainath and Brian Kingsbury on deep learning for speech recognition . If anyone has suggestions or thoughts for next year, please speak up. I also attended Strata + Hadoop World for the first time. This is primarily a trade conference rather than an academic conference, but I found it pretty interesting as a first time attendee. This is ground zero for the Big data buzzword, and I see now why. It’s about data, and the word “big” is so ambiguous that everyone can lay claim to it. There were essentially zero academic talks. Instead, the focus was on war stories, product announcements, and education. The general level of education is much lower—explaining Machine Learning to the SQL educated is the primary operating point. Nevertheless that’s happening, a
3 hunch net-2012-10-18-7th Annual Machine Learning Symposium
Introduction: A reminder that the New York Academy of Sciences will be hosting the 7th Annual Machine Learning Symposium tomorrow from 9:30am. The main program will feature invited talks from Peter Bartlett , William Freeman , and Vladimir Vapnik , along with numerous spotlight talks and a poster session. Following the main program, hackNY and Microsoft Research are sponsoring a networking hour with talks from machine learning practitioners at NYC startups (specifically bit.ly , Buzzfeed , Chartbeat , and Sense Networks , Visual Revenue ). This should be of great interest to everyone considering working in machine learning.
4 hunch net-2012-09-29-Vowpal Wabbit, version 7.0
Introduction: A new version of VW is out . The primary changes are: Learning Reductions : I’ve wanted to get learning reductions working and we’ve finally done it. Not everything is implemented yet, but VW now supports direct: Multiclass Classification –oaa or –ect . Cost Sensitive Multiclass Classification –csoaa or –wap . Contextual Bandit Classification –cb . Sequential Structured Prediction –searn or –dagger In addition, it is now easy to build your own custom learning reductions for various plausible uses: feature diddling, custom structured prediction problems, or alternate learning reductions. This effort is far from done, but it is now in a generally useful state. Note that all learning reductions inherit the ability to do cluster parallel learning. Library interface : VW now has a basic library interface. The library provides most of the functionality of VW, with the limitation that it is monolithic and nonreentrant. These will be improved over
5 hunch net-2012-08-27-NYAS ML 2012 and ICML 2013
Introduction: The New York Machine Learning Symposium is October 19 with a 2 page abstract deadline due September 13 via email with subject “Machine Learning Poster Submission” sent to<EMAIL_ADDRESS>Everyone is welcome to submit. Last year’s attendance was 246 and I expect more this year. The primary experiment for ICML 2013 is multiple paper submission deadlines with rolling review cycles. The key dates are October 1, December 15, and February 15. This is an attempt to shift ICML further towards a journal style review process and reduce peak load. The “not for proceedings” experiment from this year’s ICML is not continuing. Edit: Fixed second ICML deadline.
6 hunch net-2012-08-24-Patterns for research in machine learning
Introduction: There are a handful of basic code patterns that I wish I was more aware of when I started research in machine learning. Each on its own may seem pointless, but collectively they go a long way towards making the typical research workflow more efficient. Here they are: Separate code from data. Separate input data, working data and output data. Save everything to disk frequently. Separate options from parameters. Do not use global variables. Record the options used to generate each run of the algorithm. Make it easy to sweep options. Make it easy to execute only portions of the code. Use checkpointing. Write demos and tests. Click here for discussion and examples for each item. Also see Charles Sutton’s and HackerNews’ thoughts on the same topic. My guess is that these patterns will not only be useful for machine learning, but also any other computational work that involves either a) processing large amounts of data, or b) algorithms that take a signif
7 hunch net-2012-07-17-MUCMD and BayLearn
Introduction: The workshop on the Meaningful Use of Complex Medical Data is happening again, August 9-12 in LA, near UAI on Catalina Island August 15-17. I enjoyed my visit last year, and expect this year to be interesting also. The first Bay Area Machine Learning Symposium is August 30 at Google . Abstracts are due July 30.
8 hunch net-2012-07-09-Videolectures
Introduction: Yaser points out some nicely videotaped machine learning lectures at Caltech . Yaser taught me machine learning, and I always found the lectures clear and interesting, so I expect many people can benefit from watching. Relative to Andrew Ng â€˜s ML class there are somewhat different areas of emphasis but the topic is the same, so picking and choosing the union may be helpful.
9 hunch net-2012-06-29-ICML survey and comments
Introduction: Just about nothing could keep me from attending ICML , except for Dora who arrived on Monday. Consequently, I have only secondhand reports that the conference is going well. For those who are remote (like me) or after the conference (like everyone), Mark Reid has setup the ICML discussion site where you can comment on any paper or subscribe to papers. Authors are automatically subscribed to their own papers, so it should be possible to have a discussion significantly after the fact, as people desire. We also conducted a survey before the conference and have the survey results now. This can be compared with the ICML 2010 survey results . Looking at the comparable questions, we can sometimes order the answers to have scores ranging from 0 to 3 or 0 to 4 with 3 or 4 being best and 0 worst, then compute the average difference between 2012 and 2010. Glancing through them, I see: Most people found the papers they reviewed a good fit for their expertise (-.037 w.r.t 20
10 hunch net-2012-06-15-Normal Deviate and the UCSC Machine Learning Summer School
Introduction: Larry Wasserman has started the Normal Deviate blog which I added to the blogroll on the right. Manfred Warmuth points out the UCSC machine learning summer school running July 9-20 which may be of particular interest to those in silicon valley.
11 hunch net-2012-06-05-ICML acceptance statistics
Introduction: People are naturally interested in slicing the ICML acceptance statistics in various ways. Here’s a rundown for the top categories. 18/66 = 0.27 in (0.18,0.36) Reinforcement Learning 10/52 = 0.19 in (0.17,0.37) Supervised Learning 9/51 = 0.18 not in (0.18, 0.37) Clustering 12/46 = 0.26 in (0.17, 0.37) Kernel Methods 11/40 = 0.28 in (0.15, 0.4) Optimization Algorithms 8/33 = 0.24 in (0.15, 0.39) Learning Theory 14/33 = 0.42 not in (0.15, 0.39) Graphical Models 10/32 = 0.31 in (0.15, 0.41) Applications (+5 invited) 8/29 = 0.28 in (0.14, 0.41]) Probabilistic Models 13/29 = 0.45 not in (0.14, 0.41) NN & Deep Learning 8/26 = 0.31 in (0.12, 0.42) Transfer and Multi-Task Learning 13/25 = 0.52 not in (0.12, 0.44) Online Learning 5/25 = 0.20 in (0.12, 0.44) Active Learning 6/22 = 0.27 in (0.14, 0.41) Semi-Superv
12 hunch net-2012-05-12-ICML accepted papers and early registration
Introduction: The accepted papers are up in full detail. We are still struggling with the precise program itself, but thatâ€™s coming along. Also note the May 13 deadline for early registration and room booking.
13 hunch net-2012-05-03-Microsoft Research, New York City
Introduction: Yahoo! laid off people . Unlike every previous time there have been layoffs, this is serious for Yahoo! Research . We had advanced warning from Prabhakar through the simple act of leaving . Yahoo! Research was a world class organization that Prabhakar recruited much of personally, so it is deeply implausible that he would spontaneously decide to leave. My first thought when I saw the news was “Uhoh, Rob said that he knew it was serious when the head of ATnT Research left.” In this case it was even more significant, because Prabhakar recruited me on the premise that Y!R was an experiment in how research should be done: via a combination of high quality people and high engagement with the company. Prabhakar’s departure is a clear end to that experiment. The result is ambiguous from a business perspective. Y!R clearly was not capable of saving the company from its illnesses. I’m not privy to the internal accounting of impact and this is the kind of subject where there c
14 hunch net-2012-05-02-ICML: Behind the Scenes
Introduction: This is a rather long post, detailing the ICML 2012 review process. The goal is to make the process more transparent, help authors understand how we came to a decision, and discuss the strengths and weaknesses of this process for future conference organizers. Microsoft’s Conference Management Toolkit (CMT) We chose to use CMT over other conference management software mainly because of its rich toolkit. The interface is sub-optimal (to say the least!) but it has extensive capabilities (to handle bids, author response, resubmissions, etc.), good import/export mechanisms (to process the data elsewhere), excellent technical support (to answer late night emails, add new functionalities). Overall, it was the right choice, although we hope a designer will look at that interface sometime soon! Toronto Matching System (TMS) TMS is now being used by many major conferences in our field (including NIPS and UAI). It is an automated system (developed by Laurent Charlin and Rich Ze
15 hunch net-2012-04-20-Both new: STOC workshops and NEML
Introduction: May 16 in Cambridge , is the New England Machine Learning Day , a first regional workshop/symposium on machine learning. To present a poster, submit an abstract by May 5 . May 19 in New York , STOC is coming to town and rather surprisingly having workshops which should be quite a bit of fun. Iâ€™ll be speaking at Algorithms for Distributed and Streaming Data .
16 hunch net-2012-04-09-ICML author feedback is open
Introduction: as of last night, late. When the reviewing deadline passed Wednesday night 15% of reviews were still missing, much higher than I expected. Between late reviews coming in, ACs working overtime through the weekend, and people willing to help in the pinch another ~390 reviews came in, reducing the missing mass to 0.2%. Nailing that last bit and a similar quantity of papers with uniformly low confidence reviews is what remains to be done in terms of basic reviews. We are trying to make all of those happen this week so authors have some chance to respond. I was surprised by the quantity of late reviews, and I think that’s an area where ICML needs to improve in future years. Good reviews are not done in a rush—they are done by setting aside time (like an afternoon), and carefully reading the paper while thinking about implications. Many reviewers do this well but a significant minority aren’t good at scheduling their personal time. In this situation there are several ways to fail:
17 hunch net-2012-03-24-David Waltz
Introduction: has died . He lived a full life. I know him personally as a founder of the Center for Computational Learning Systems and the New York Machine Learning Symposium , both of which have sheltered and promoted the advancement of machine learning. I expect much of the New York area machine learning community will miss him, as well as many others around the world.
18 hunch net-2012-03-13-The Submodularity workshop and Lucca Professorship
Introduction: Nina points out the Submodularity Workshop March 19-20 next week at Georgia Tech . Many people want to make Submodularity the new Convexity in machine learning, and it certainly seems worth exploring. Sara Olson also points out a tenured faculty position at IMT Lucca with a deadline of May 15th . Lucca happens to be the ancestral home of 1/4 of my heritage
19 hunch net-2012-03-06-COLT-ICML Open Questions and ICML Instructions
Introduction: Sasha is the open problems chair for both COLT and ICML . Open problems will be presented in a joint session in the evening of the COLT/ICML overlap day. COLT has a history of open sessions, but this is new for ICML. If you have a difficult theoretically definable problem in machine learning, consider submitting it for review, due March 16 . You’ll benefit three ways: The effort of writing down a precise formulation of what you want often helps you understand the nature of the problem. Your problem will be officially published and citable. You might have it solved by some very intelligent bored people. The general idea could easily be applied to any problem which can be crisply stated with an easily verifiable solution, and we may consider expanding this in later years, but for this year all problems need to be of a theoretical variety. Joelle and I (and Mahdi , and Laurent ) finished an initial assignment of Program Committee and Area Chairs to pap
20 hunch net-2012-02-29-Key Scientific Challenges and the Franklin Symposium
Introduction: For graduate students, the Yahoo! Key Scientific Challenges program including in machine learning is on again, due March 9 . The application is easy and the $5K award is high quality “no strings attached” funding. Consider submitting. Those in Washington DC, Philadelphia, and New York, may consider attending the Franklin Institute Symposium April 25 which has several speakers and an award for V . Attendance is free with an RSVP.
21 hunch net-2012-02-24-ICML+50%
22 hunch net-2012-02-20-Berkeley Streaming Data Workshop
23 hunch net-2012-01-30-ICML Posters and Scope
24 hunch net-2012-01-28-Why COLT?
25 hunch net-2012-01-04-Why ICML? and the summer conferences


A No Sidewalk label should be placed if there is a missing sidewalk where there
should be one.
Where and how should I place a No Sidewalk label?
@Html(Messages("labeling.guide.no.sidewalk.summary"))
You should not place No Sidewalk labels in narrow side streets or alleys.


This approach is useful if you want to have more than one instance of `uc-zoom-component` on the same page but with different appearance.
On the component:
On the general styles.css file of the application:
On the component css:
On the component:
On the component:
On the component:
On the component:
On the component:


Toggleable Button JS Library
Toggleable Button Demos
Normal
Include the below code snippet within the form element of your page:
Size x2
Include the below code snippet within the form element of your page:
Size x3
Include the below code snippet within the form element of your page:


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Forests Catalog
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January 15, 2002
Osama costume results in serious beatdown
New Zealand Stuff | Submitted by: Jon Blast
It is still too early to bring out that Bin Laden costume:
"Cops were called to the party by neighbours who reported a brawl.
When they arrived at the Glengarry Rd, Glen Eden, address, Ben's
attackers had fled, leaving him lying in a pool of blood in the
back yard." The price of Ben's faux pas is 17 stitches.
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Read article...
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Idahoans may drive stoned
Denver Channel | Submitted by: La Singe
"A three-judge panel of the San Francisco-based court wrote that Idaho's
impaired driving law makes it illegal to drive under the influence of alcohol
and narcotics. But Idaho doesn't list marijuana as a narcotic."
[Note: Narcotic is normally a medical term, describing a genre of drugs of
which marijuana and THC are not. But opium is.] "The court said that
because marijuana is not listed as a narcotic, Matthew Patzer could not
automatically be presumed impaired, like motorists who have been
drinking alcohol."
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Read article...
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Child "needs" $600K per month
Associated Press | Submitted by: Ross
"In court documents, [Lisa] Kerkorian lists monthly expenses for daughter
Kira including $144,000 for travel, $14,000 for parties and play dates and
$7,000 for charity." According to Lisa, "the word 'needs' never meant basic
needs, but what was required to maintain her in the station of life and
with all the things and benefits befitting the daughter of Kirk Kerkorian."
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Read article...
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National ID cards coming
Washington Post | Submitted by: Justin
Apparently some people continue to believe that a national I.D. card system
could have prevented September 11th, never minding that the attackers had
legitimate passports, visas, and driver's licenses. Now they're asking
Congress for $100 million funding to study an end run, coercing the states
into this under the pretext of driver's license databases, rather than the
furor over a federal law. Spokesman: "The whole issue comes down to
improving public safety, protecting national security and preventing
identity fraud." ID cards do none of this.
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References back to ToC
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R. Agarwal, D. G. Fernandez, T. Elsaleh, A. Gyrard, J. Lanza, L. Sanchez, N.Georgantas, and V. Issarny. 2016. Unified IoT Ontology to Enable Interoperability and Federation of Testbeds. In 3rd IEEE World Forum on Internet of Things. IEEE, Reston, USA, pp. 70-75


SQL Query
Sometimes it is useful to not use entity beans or dto beans but instead execute sql queries
producing SqlRow
objects or reading directly from JDBC ResultSet.
In typical recent applications around 2%
of queries were SqlQuery type queries.
SqlQuery and SqlRow
Note that with SqlQuery we can get Ebean to add limit/offset
clause appropriate
to the database platform and we can bind parameters using all the mapped types
(Enums, java.time, array types etc).
For more information goto docs / query / sqlquery
String sql = "select id, name, when_active from customer where status = ?";
List<SqlRow> rows = DB.sqlQuery(sql)
.setParameter(1, "NEW")
.setMaxRows(100)
.findList();
for (SqlRow sqlRow : rows) {
Long id = row.getLong("id")
String name = row.getString("name")
Timestamp whenActivated = row.getTimestamp("when_activated")
}
val sql = """
select id, name, when_activated
from customer
where name like ?
""".trimIndent()
val rows = DB.sqlQuery(sql)
.setParameter(1, "Rob%")
.setMaxRows(100)
.findList()
for (row in rows) {
val id = row.getLong("id")
val name = row.getString("name")
val whenActivated = row.getTimestamp("when_activated")
}
SqlQuery and RowMapper
Alternatively we can use a RowMapper to read from the JDBC ResultSet.
String sql = "select id, name, status from customer order by name desc";
DB.sqlQuery(sql)
.findEachRow((resultSet, rowNum) -> {
// read directly from ResultSet
long id = resultSet.getLong(1);
String name = resultSet.getString(2);
// do something interesting with the data
});
val sql = "select id, name, status from customer order by name desc"
DB.sqlQuery(sql)
.findEachRow { resultSet, rowNum ->
// read directly from ResultSet
val id = resultSet.getLong(1)
val name = resultSet.getString(2)
// do something interesting with the data
}


| To be completed by: | {% if objective.end_year and objective.end_month %} {% set 'end_date' objective.end_month|month_name|concat:' '|concat:objective.end_year %} {% endif %}{% include "exportplan/includes/pdf/pdf_blank.html" with data=end_date tag="strong" lines=1 %} |
| Owner: | {% include "exportplan/includes/pdf/pdf_blank.html" with data=objective.owner tag="strong" lines=1 %} |


{% include "menu.html" %}
Random Track
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{% if success == 0 %}
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{% elif success == 1 %}
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Handling of Personal Information of Customers
The governing language of this statement shall be Japanese.
1. Definition of Personal Information
"Personal Information" means information that can help identify specific individuals as defined by the "Act on Protection of Personal Information", including but not limited to the name, age, telephone number, email address, address and employer of an individual as well as information on products or services purchased by an individual, information on inquiries made by an individual and ID numbers.
2. Basic Policy on Personal Information Protection and Management
- OMRON SINIC X Corporation will collect, obtain, use and provide Personal Information in an appropriate manner.
- OMRON SINIC X Corporation will make best efforts to ensure personal data to be precise and up-to-date.
- OMRON SINIC X Corporation will take necessary and appropriate measures to manage personal data including protecting personal data against unauthorized access, loss, leak and damage.
- OMRON SINIC X Corporation will comply with laws, regulations and the guidelines for them as well as internal rules on Personal Information.
- When contracting the handling of personal data to a third party, OMRON SINIC X Corporation will only entrust to a contractor who meets the requirements based on OMRON SINIC X Corporation's internal rules. OMRON SINIC X Corporation will manage such contractors in an appropriate manner.
- OMRON SINIC X Corporation will continue to try improving protection of Personal Information.
3. Name of Business Operator handling Personal Information
OMRON SINIC X Corporation Corporation
4. Purpose of Use of Personal Information
OMRON SINIC X Corporation will ensure that, in the process of providing its products and services, it will obtain Personal Information necessary to carry out its business through the OMRON SINIC X Corporation business entities (as described in 4(1) below) for the purposes of use (as described in 4(2) below), and that it will handle Personal Information within the scope of the purposes.
For details of the purposes of use of Personal Information by each OMRON SINIC X Corporation business entity, please go to the website of the respective business entity.
The purposes of use of Personal Information obtained from shareholders are as described in 4(3) below.
- OMRON SINIC X Corporation's Businesses
- Planning, development, manufacturing, sales, installation and maintenance of machines and equipment.
- Information communication and information processing services.
- Collecting, analyzing and providing information on themes related to people, culture, life style and health. Managing and operating sports and cultural facilities.
- Planning and producing advertisement and acting as an advertising agent. Manpower services, for-fee job placement services, leasing business, non-life insurance agency business, credit card business, freight services, security services, construction business and real estate management services.
- Sales of foods, beverages and general merchandises.
- Purposes of Use of Personal Information
- Providing customers with products and services that OMRON SINIC X Corporation and its subsidiaries and partners offer ("Products") and maintenance of them.
- Planning, development, manufacturing, sales and installation of Products.
- Providing and distributing information such as information on Products.
- Managing contractual relationship related to providing Products and other business activities
- Advertising and holding campaigns, exhibits and other events to promote Products.
- Providing and distributing brochures, CD-ROMs, materials and samples of Products.
- Conducting surveys on Products and analysis of the results.
- Ensuring the security of OMRON SINIC X Corporation's business bases.
- Providing information, contacting and notifying applicants seeking employment with OMRON SINIC X Corporation and OMRON SINIC X Corporation Group companies. Carrying out selection processes.
- Purposes of Use of Personal Information obtained from Shareholders
- Exercising rights and fulfilling obligations provided by and required by laws and regulations.
- Facilitating understanding of the business of OMRON SINIC X Corporation. Carrying out measures and initiatives that facilitate a good relationship between OMRON SINIC X Corporation and its shareholders.
- Collection, preparation and statistical processing of data in accordance with the prescribed standards required by laws and regulations.
5. Joint Use
OMRON SINIC X Corporation uses personal information (names, date of birth, place of employment, image, development data etc.) which OMRON SINIC X Corporation obtained when products are purchased, developed or services are provided etc. within the purposes described in 4 above, jointly with OMRON SINIC X Corporation Group Companies, joint research partners, dealers and agents. OMRON SINIC X Corporation is responsible for the management of such Personal Information.
6. Providing Personal Information to Third Parties
OMRON SINIC X Corporation will not disclose or provide personal data to third parties without consent of the Persons in Question, except in the following cases. However, even in the cases of (5), (6) and (7) below, OMRON SINIC X Corporation will obtain consent of the Persons in Question before personal data is provided to third parties in foreign countries.
- When required by laws and regulations.
- When necessary to protect life, well being or property of the Persons in Question, and when it is difficult to obtain the consent of them.
- When necessary particularly for improving public health or promoting healthy growth of children, and when it is difficult to obtain the consent of the Persons in Question.
- When necessary to provide cooperation to national agencies, municipalities, or entities which are entrusted by such governmental organizations in the performance of their tasks required by laws and regulations, and when obtaining consent from the Persons in Question can hinder the proper execution of such tasks.
- When contracting out a part of or the entire operations to a contractor for facilitating smooth operations.
In this case, OMRON SINIC X Corporation will conclude an agreement with the contractor on the handling and protecting of Personal Information and manage such information in an appropriate manner. - When the consent of Persons in Question has been obtained in advance.
- When Personal Information is jointly used as described in 5 above.
- When a business is transferred and succeeded.
7. Information needed for Requesting Disclosure, etc.
OMRON SINIC X Corporation will promptly respond to requests, within a reasonable scope, for disclosure of stored personal data, revision, addition or deletion of the contents, suspension of use or deletion of such data ("Request for Disclosure, etc."). The procedures for such requests are as follows.
- Where to send requests for disclosure, etc.
Please mail your request to OMRON SINIC X Corporation Corporation. Please mark the envelop with "Request for Disclosure, etc." in red.
Request form (download) <PDF 60kb>
- Documents (forms) to be submitted with "Request for Disclosure, etc."
When sending a "Request for Disclosure, etc.", please download the request form as described in (a) below and fill in all the spaces provided. Please enclose the ID documents described in (b) below and a return envelop with the address of the Person in Question (the same address as on the ID) and mail them to the address provided in 7(1) above.
When notifying the purpose of use or requesting disclosure, please return an addressed and stamped return envelop as described in (c) below.
- Request form prescribed by OMRON SINIC X Corporation
- ID document
One of the following documents and a seal registration certificate (when a seal is affixed on the request form)- Copy of driver's license
- Copy of passport
- Copy of alien registration card
- Copy of residence card
- Copy of special permanent resident certificate
- Copy of either health insurance card or pension book;
and - Copy of family register or resident register
[When a request is made by an agent:]
- An agent with power of attorney: Power of attorney (affixed with a registered seal) and each of the following documents:
- Seal registration certificate for the seal affixed on power of attorney
- Documents to prove the agent's identity
(the same ID documents as required for the Person in Question above)
- When a request is made by a legal representative: One copy of each of the following:
- For a minor
- Copy of family resister of the Person in Question or copy of health insurance card with the names of dependents.
- For an adult ward
- Documents to prove registration as prescribed in Section 10 of the Act on Guardianship Registration, etc.
- Document to prove the right for legal representation for a minor or an adult ward.
- ID documents of the legal representative.
(the same ID documents as required for the Person in Question above)
- For a minor
- Addressed and stamped return envelope
- Please write down the address of the Person in Question on the envelope.
(the address on the ID documents for the Person in Question or his/her agent) - When notifying the purpose of use or requesting disclosure, please affix a stamp that covers the cost of certified registered mail.
- Please write down the address of the Person in Question on the envelope.
- Reply to Request for Disclosure, etc.
A reply will made in writing and sent using the return envelop.
8. When Request for Disclosure, etc. cannot be granted:
A Request for Disclosure, etc. will not be granted when laws and regulations present the grounds and when there are flaws in the information presented in accordance with 7 above.
Please fill out the form below and click To Confirmation button to transmit your inquiry.
Inquiry FormRevised: May 30, 2017