Colin Leath
Fall 2006
|
San Diego, California |
|
Current Projects Midwifing the Great Turning
Creating a backyard compost pile and garden, inspired in part by Path to Freedom in Pasadena.
Creating a community garden in nearby Clay Park with the Rolando Community Council.
Helping San Diego Food Not Lawns organize a conference.
Helping the San Diego River Park Foundation extend and improve the San Diego River Trail.
Helping World Guardian Voices / San Diego Ishmael save the world.
Creating a Community Land Trust for San Diego activist collectives and for carfree people.
Planning a bioregional permaculture gathering for San Diego / Tijuana.
Academics
English and Spanish Language Literature and TESOL. San Diego State University. 2004-2006.
BS with departmental honors, Psychology. University of Washington, Seattle, Washington. 1999.
Diploma. Thomas Jefferson High School for Science and Technology, Alexandria, Virginia. 1994.
Professional Experience
|
Spring 2004-present |
Challenge Course Facilitator, Lead Facilitator, Leadership Camp Lead Ray and Joan Kroc Corps Community Center San Diego, California |
|
Fall 2006 |
Graduate Teaching Associate RWS 100: The Rhetoric of Written Argument Department of Rhetoric and Writing Studies, San Diego State University |
|
Spring 2006 |
Reader ENGL 302: Introducing Shakespeare, Dorothea Kehler, PhD Department of English and Comparative Literature, San Diego State University |
|
Fall 2005 |
Writing Tutor RWS 92A: Developmental Writing, James Hiskey, MA Department of Rhetoric and Writing Studies, San Diego State University |
|
Fall 2001-Spring 2003 |
Research Support Specialist Department of Vision Sciences State University of New York State College of Optometry, New York, New York |
|
Summer 2001 |
English Camps Counselor Associazione Culturale Linguistica Educational Folgaria, Imola, and San Pietro in Vincoli, Italy |
|
Fall 1999-Spring 2001 |
Programmer, Install Developer, Quality Assurance Analyst Greentree Systems, Inc. Pacific Grove, California |
|
Fall 1994-Spring 1995 |
Computer Instructor, Fourth and Fifth Grades Washington Union School Salinas, California |
|
Summer 1992-Summer 1994 |
Windsurfing and Sailing Instructor Mariner Sailing School and Washington Sailing Marina Alexandria, Virginia |
Research Interests
Permaculture.
The role of theory or myth in socially-constructed experience, and the process of theory composition.
Teaching Philosophy
Education should “enhance our students’ journey to wholeness” (hooks 181).
“Dominator culture has tried to keep us all afraid, to make us choose safety instead of risk, sameness instead of diversity. Moving through that fear, finding out what connects us, revelling in our differences; this is the process that brings us closer, that gives us a world of shared values, of meaningful community” (hooks 197).
bell hooks. Teaching Community: A Pedagogy of Hope. New York: Routledge, 2003.
Publications
The Carfree Universe Project: Strengthening Communities of the Carfree. April 2003 present. <http://carfreeuniverse.org/>.
A portal for the carfree community where I have published academic and creative work.
Presentations
“Nothing?” with Brad Anderson, Laura Sheppard, Michael Thayer, and William Shames of the San Diego Ishmael Group. San Diego EarthFair, Balboa Park. 23 April 2006.
“CarFree City, USA,” with Gus Yates, David Ceaser, Steven Pav, and Jim Gottlieb. San Diego EarthFair, Balboa Park. 1 May 2005.
“The Experience of Meaning in Life from a Psychological Perspective & The Effect of Participation in the Meaning in Life Forum on Participants’ Experiences of Meaning in Life.” Bridging Disciplines: The First Annual Graduate Student Board Interdisciplinary Conference. San Diego State University. 4 April 2005.
A presentation of my undergraduate theses in which I noted related literary works.
“Transitioning to Carfree Living and Environments,” with David Ceaser and Gus Yates. Green Earth Promotions’ First Annual Green Earth Festival. Veterans Memorial Building, San Luis Obispo, California. 5 June 2004.
“The Carfree Movement.” Tenth Annual Southeast Summer Permaculture Gathering. Earthaven Ecovillage, Black Mountain, North Carolina. 9 August 2003.
“Using ZOPE to Create Web Applications.” Towards Car-Free Cities III. Toulcuv Dvur, Prague, Czech Republic. 21 March 2003.
Gatherings and Affinity Groups Organized
First Annual Bioregional Permaculture Gathering for Tijuana and San Diego. Planned for 2007.
College Area Ishmael Dinners. San Diego, California. Spring 2006.
New York City Integral Transformative Practice Group. Fall 2002-Spring 2003.
The Meaning in Life Forum. Associated Students of the University of Washington Experimental College, Seattle, Washington. Spring 1998.
First Saturday of the Month Dinners. 5230 21st Ave NE, Seattle, Washington. Fall 1997-Spring 1998.
The being Group. University of Washington Registered Student Organization. Summer 1996-Fall 1997.
Gatherings Attended
San Diego Puppet Insurgency Winter Solstice Celebration and Sing-a-long. 22, 23 December 2006.
Edible San Diego Bike Tour. San Diego Food Not Lawns. 11 November 2006.
First Annual HerbDay San Diego. Sponsored by the San Diego Herb Club and the San Diego Chapter of the American Herbalists Guild. Balboa Park, San Diego, California. 14 October 2006.
Roots of Resistance: Summer Skill Share and Organizing Camp. Organic Collective, San Diego, California. 8-10 September 2006.
Permaculture Summer Gathering. Celo, North Carolina. 3-6 August 2006.
H2K2 (the fourth Hackers On Planet Earth conference). Hotel Pennsylvania, New York, New York. 12-14 July 2002.
Bioregional Gathering / Anti-GM Food Rally. At a farm near Austin, Texas. Spring 1999.
May Day Celebration (with speakers Earnest Callenbach and Dan Hamburg). Humboldt State University, Arcata, California. 2 May 1998.
Seattle’s First Activist and Media Teach-In. Sponsored by the American Friends Service Committee and the Seattle Independent Media Coalition. University Friends Meeting Hall. 21 February 1998.
Building Momentum in Character Education: A Free Conference and Curriculum Fair. Sponsored by Washington Partnership on Character Education. Stevens Elementary School, Seattle, Washington. 25 June 1997.
Affinity Group Participation
San Diego Food Not Lawns. Fall 2006-.
SDSU Environmental Business Society. Fall 2006-.
San Diego Ishmael. Spring 2005-.
San Diego Integral Meetup and AllUp. Summer 2006.
Washington, DC Ishmael. Fall 1998, Spring 2003.
New York City Ishmael. Fall 2002-Spring 2003.
New York City Integral and Integral Transformative Practice. Fall 2002-Spring 2003.
Critical Mass Bicycle Rides. Seattle; Washington, DC; New York City. 1996-2002.
Monterey Peninsula Friends Meeting. Carmel, California. Summer 1999-Fall 1999.
Friends Meeting of Austin. Austin, Texas. Spring 1999.
Friends Meeting of Washington and FMW Spiritual Friendships. Washington, DC. Fall 1998.
Union Bay Rowing Club. Seattle, Washington. Summer 1996-Fall 1996.
The Friends of the Medicinal Herb Garden. University of Washington, Seattle. Fall 1995-Summer 1997.
University of Washington Hiking Club. Fall 1995-Spring 1996.
University of Washington Sailing Club. Summer 1995-Spring 1996.
EarthCorps Invasive Plant Removal Work Parties. Seattle, Washington. Fall 1995-Spring 1996.
Intentional Communities Visited
Activist San Diego. San Diego, California. Fall 2006.
Organic Collective. San Diego, California. Summer 2006.
Celo Community Land Trust. Celo, North Carolina. Summer 2006.
Earthaven Ecovillage. Black Mountain, North Carolina. Summer 2003, Summer 2006.
Path to Freedom. Pasadena, California. Summer 2006.
Los Angeles EcoVillage. Los Angeles, California. Summer 2001, Summer 2006.
Shakti Rising. San Diego, California. Fall 2005, Spring 2006.
The Domes. Davis, California. Summer 2004.
Madre Grande Monastery. Dulzura, California. Fall 2003.
The Farm Community and Ecovillage Training Center. Summertown, Tennessee. Summer 2003.
Wildroots. Madison County, North Carolina. Summer 2003.
Freetown Cristiania. Copenhagen, Denmark. Summer 2001.
The Austin EarthFirst! House. Austin, Texas. Spring 1999.
Fossil Fuel Free Farm. Blue Lake, California. Spring 1998.
Sirius Community. Shutesbury, Massachusetts. Spring 1998.
Earthlands. Petersham, Massachusetts, North Quabbin Bioregion. Spring 1998.
Deep Springs College. Deep Springs, California. Spring 1994.
Continuing Education
Dance Place San Diego Free Day of Dance. 26 December 2006.
Master Class, Martha Graham Dance Company. SDSU, San Diego, California. 12 March 2005.
45-Hour Challenge Course Facilitator Training. The Ray and Joan Kroc Corps Community Center and The SDSU Aztec Recreation Center, San Diego, California. Spring 2004.
Classes in Kundalini Yoga, Pilates, and Qigong. Point Loma YMCA, San Diego, California. Fall 2003.
Plant Walk and Weekend with Frank Cook. Earthaven Ecovillage to the North Carolina School of Holistic Herbalism, Madison County, North Carolina. 14-16 August 2003.
Herbal Elixirs with Frank Cook. Earthaven Ecovillage, Black Mountain, North Carolina. 8 August 2003.
Classes at Dance Space and the Martha Graham Dance Company. New York, New York. Fall 2001-Spring 2002.
American Red Cross Water Safety Instructor. Monterey Sports Center, Monterey, California. Spring 2001.
Masters Synchronized Swimming. Seaside Recreation Center Pool, Seaside, California. Spring 2001.
Classes at dance studios in New York City, including Dance Space, Steps on Broadway, Broadway Dance Center, American Ballet Theater, and the New York City Parks Department; classes in Nia and in Gabrielle Roth’s 5Rhythms; and a contact improvisation jam at Judson Memorial Church. 13-27 January 2001.
Ballet and Modern. SpectorDance, CSU Monterey Bay, Fort Ord, California. Fall 2000-Spring 2001.
Ballet. Peninsula Ballet Center, Pacific Grove, California. Fall 2000-Spring 2001.
Ballet. Carmel Ballet Academy, Carmel, California. Fall 2000-Spring 2001.
Jazz, Modern, and Ballet. Monterey Peninsula College, Monterey, California. Summer 2000-Fall 2000.
Texas Master Gardener. Zilker Botanical Gardens, Travis County, Texas. Spring 1999.
Intermediate Conversational Spanish (noncredit). University of Texas, Austin, Texas. Spring 1999.
Inquirers Class. Friends Meeting of Washington. Washington, DC. Fall 1998.
Judaism 101. Hillel at UW. Seattle, Washington. Fall 1997.
Additional Experience
Solo Walk. Black Mountain to Celo, North Carolina via Mount Mitchell. Summer 2006.
Instructor for Peak Performance, Inc., for a week-long backpacking and kayaking trip for eighth graders in Big Sur, California. Summer 2006.
Staff. Hostel Obispo, San Luis Obispo, California. Summer 2004.
Solo Bicycle Tour. New York City to Manzanillo, Colima, Mexico. Spring 2003-Fall 2003.
Work Exchanger. Earthaven Ecovillage, Black Mountain, North Carolina. Summer 2003.
Volunteer Laborer. Potomac Vegetable Farms, Fairfax County, Virginia. Summer 2003.
Chorister. Volunteer Choir, Saint Bartholomew’s Church, New York, New York. Fall 2002-Spring 2003.
Chorister. Brooklyn Community Chorus, Park Slope, Brooklyn, New York. Fall 2002.
Work Study Student. Dance Space, New York, New York. Fall 2001-Spring 2002.
Solo Bicycle Tours. Monterey to San Diego, and San Remo, Italy to Malmo, Sweden. Summer 2001.
Monterey Hostel Society Volunteer. Monterey, California. Fall 1999-Spring 2001.
Crisis Line Volunteer. Community Human Services’ Community Counseling Center, Monterey, California. Spring 2001.
Assistant Teacher, South Central Yearly Meeting First and Second Grades. Union for Reform Judaism Greene Family Camp, Bruceville, Texas. Spring 1999.
ESL Citizenship Tutor. El Buen Samaritano, Austin, Texas. Spring 1999.
Sustainable Communities Initiative Volunteer. City of Austin, Austin, Texas. Spring 1999.
Gardener. South Austin Community Garden. Austin, Texas. Spring 1999.
Volunteer, Returned Peace Corps Volunteers & Amigos de las Américas of Austin Weekend Service Trip. Rio Bravo, Tamaulipas, Mexico. Spring 1999.
Intern. Libertarian National Committee. Washington, DC. Fall 1998.
Adult Leader for Boy Scouts of America National Capitol Area Council’s High Adventure Trip at Atikokan Canoe Base, Ontario, Canada. Summer 1998.
Awards
Eagle Scout, 1992.
References
|
Andrea Sanford Ray and Joan Kroc Corps Community Center
|
H. A. Sedgwick, PhD State University of New York State College of Optometry
|
Mike Strasser Greentree Systems, Inc.
|


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TODO description
Through its modular nature Arethusa can be configured for different use cases:
TODO
The new Grid layout http://localhost:8081/app/#/staging3?doc=1 A Greek document, including the SG plugin http://localhost:8081/app/#/sg?doc=athenaeus12&s=1 An empty document to play around (saving disabled) http://localhost:8081/app/#/clean?doc=clean1Arethusa is built on the AngularJS javascript web application framework and provides a back-end independent plugin infrastructure for accessing texts, annotations and linguistic services from a variety of sources. Extensibility is a guiding design goal - Arethusa includes tools for automatic generation of new plugin skeletons (Arethusa::CLI) and detailed development guides are currently in progress (TODO link?), with the hopes that others will be able to reuse and build upon the platform to add support for other annotation types, languages and back-end repositories and workflow engines.
This project has received support from the Andrew W. Mellon Foundation and the Institute of Museum and Library Services.


| cut_interval {ggplot2} | R Documentation |
cut_interval()
makes n
groups with equal range, cut_number()
makes n
groups with (approximately) equal numbers of observations;
cut_width()
makes groups of width width
.
cut_interval(x, n = NULL, length = NULL, ...) cut_number(x, n = NULL, ...) cut_width( x, width, center = NULL, boundary = NULL, closed = c("right", "left"), ... )
x |
numeric vector |
n |
number of intervals to create, OR |
length |
length of each interval |
... |
Arguments passed on to
|
width |
The bin width. |
center, boundary |
Specify either the position of edge or the center of a bin. Since all bins are aligned, specifying the position of a single bin (which doesn't need to be in the range of the data) affects the location of all bins. If not specified, uses the "tile layers algorithm", and sets the boundary to half of the binwidth. To center on integers, |
closed |
One of |
Randall Prium contributed most of the implementation of
cut_width
.
table(cut_interval(1:100, 10)) table(cut_interval(1:100, 11)) table(cut_number(runif(1000), 10)) table(cut_width(runif(1000), 0.1)) table(cut_width(runif(1000), 0.1, boundary = 0)) table(cut_width(runif(1000), 0.1, center = 0)) table(cut_width(runif(1000), 0.1, labels = FALSE))


Moon wars
Error. Please use Firefox, Chrome, Internet explorer 10 or Opera. Old IE and Safari do not support all HTML5 features.
| FPS: | |
| Connection: | no |
| Packets: | 0/0 |
Description
No more oil left on Earth, but researchers found
huge amount of Helium-3 on the moon. This non-radioactive isotope
of helium gives a chance to build Zero Point Module also known as ZPM,
which means unlimited energy. We can not miss that chance.
Unfortunately our enemies knows this. You have to protect
your base, push enemies away and save your country. Moon needs you!
There are rumors that once you acquire enough Helium-3, you will be able to create something extraordinary...
Moon wars is free online HTML5 based tank game. Main features: 9 tanks and 2 air units, 5 maps, single player, multiplayer with 4 modes, full screen support, HTML5 only, no flash.
There are rumors that once you acquire enough Helium-3, you will be able to create something extraordinary...
Moon wars is free online HTML5 based tank game. Main features: 9 tanks and 2 air units, 5 maps, single player, multiplayer with 4 modes, full screen support, HTML5 only, no flash.
Controls
| Mouse | move and target |
|---|---|
| Right click | additional movements |
| 1, 2, 3 | skills |
| TAB | live scores |
| Enter | chat |
| Shift+Enter | global chat or team chat in game |
| Delete | destroy unit |
| S | change scroll mode |
| Arrow keys | scroll map in manual scroll mode |
| Mouse scroll | scroll map up/down |
| Esc | stop and move map to your tank |
| U | change abilities upgrade mode |


Specify the path to ajc (the file aspectjtools.jar which is located in <AspectJ installation directory>\lib).
Type the path in the field, or click Browse button and select the required file in the dialog that opens.


Ocean [ac13], ocean, in Crystal Sea
Last updated Turn #146
Ocean [ac13], ocean, in Crystal Sea
------------------------------------------------------------------------
1: Canopus I [hq7s], ship, 2 hulls, 1 rowing port, 6 sails, arrived from
1: Ocean [ac12], owner:
1: Toulouse [h1q], Pen, with eight sailors
2: Canopus I [hq7s] will now be known as Sea Lion [hq7s].
2: Sea Lion [hq7s], ship, 2 hulls, 1 rowing port, 6 sails, departed for
2: Ocean [ac14].
Routes leaving Ocean:
North, to Ocean [ab13], 6 days
East, to Ocean [ac14], 6 days
South, to Ocean [ad13], 6 days
West, to Ocean [ac12], 6 days


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iOS Platform Overview
Objective
In this chapter, you will examine the concepts, features, and components that uniquely identify iOS apps. You'll look at user interface conventions, application components, and device features.
Contents
iOS stands apart from most other mobile operating systems in that both its software and hardware are controlled by Apple. For this reason, it has a tight integration of front end and back end components that is arguably unmatched. We'll look at Apple's design considerations, the Cocoa Touch framework, and various UI components that are specific to iOS. Some of the key features of the iOS platform include:
-
Crafted and consistent user interface conventions
-
Minimalist hardware design
-
Apple's Human Interface Guidelines
-
Cocoa Touch
-
Curated and closely controlled app distribution system
User interface conventions
iOS is a carefully crafted and well-designed mobile operating system. Apple has carefully considered both usability and design throughout every aspect of its design. iOS is also remarkably consistent across devices, with only a couple of minor UI differences between iPhones, iPods, and iPads, as hardware capabilities differ across those devices.
The following screen illustrates some of the common user interface components offered by iOS:
Programmers adopt one of two general approaches when creating iOS apps: adopt the conventions completely or establish their own. Game makers tend to dispense entirely with stock controls (buttons and so forth) and create custom UI controls for all aspects of their app. Programmers of business or information-oriented apps tend to adopt the standard conventions. Through the power of Titanium you are free to adopt either approach, allowing you to use the methodology that best suits the app you are creating.
Minimalist hardware design
iOS devices are famous for their one-button design. Other than a power button, volume rocker, and camera button (on some devices), iOS devices offer a single button with a consistent function – to return the user to the Springboard, or main screen. What this single-button design means to you is that your app's UI will need to include buttons and controls for every operation your app could perform. You can't rely on a hardware menu button, back button, etc. like you can on Android.
Apple's Human Interface Guidelines
In Apple's words, the Human Interface Guidelines will help you build "a superlative user interface and user experience for your iOS app." Some of the key design principles from that guide are summarized in the following image:
Cocoa Touch
Cocoa Touch is an abstraction of iOS operating system functions that is designed to help developers easily implement sophisticated app features. It is part of a layered set of APIs, as illustrated in this figure:
Cocoa Touch provides the key frameworks for developing applications on devices running iOS. Some of these key frameworks are:
-
Foundation Kit Framework
-
UIKit Framework (based on Application Kit)
-
Game Kit Framework
-
iAd Framework
-
Map Kit Framework
Titanium enables easy access to each of those functions. For example, Titanium enables access to the rich set of UI controls defined in UIKit.
Curated app distribution
We won't spend much time on it here, as there's a whole chapter on distribution later, but Apple's curated distribution model is also part of the iOS experience. By examining and approving every app in the App Store, Apple helps ensure that only useful, high quality apps are presented to users. They also carefully screen out "spam", malware, and other dangerous apps. Check out the Deployment and Distribution module for more details.
A key consideration is that you will need an iOS Developer Center account to test or publish iOS apps you create with Titanium. A basic membership is free, which gives you access to the developer tools and documentation. To test on a device or publish your app, though, you will need to upgrade to a paid membership level, which at the time of this writing is $99/year USD for individuals and businesses.
References and Further Reading
Summary
In this chapter, you examined the concepts, features, and components that make iOS apps – those for iPhone, iPod, and iPad – what they are. You looked at user interface conventions, application components, and device features. next we'll discuss some basic coding strategies for creating high quality, maintainable Titanium apps.


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[gecode-users] Modelling strategies for reconciling availabilities with scheduled shifts
Christian Schulte
cschulte at kth.se
Fri Mar 7 09:57:07 CET 2014
Hi,
This is not really a Gecode specific question, so out of scope here.
You might want to check the Constraints journal or editions of the CP and
CP-AI-OR conference proceedings published at Springer. There is quite some
material out there on rostering and time tabling.
Best
Christian
--
Christian Schulte, Professor of Computer Science, KTH,
www.ict.kth.se/~cschulte/
-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Christopher Thielen
Sent: Friday, March 07, 2014 12:43 AM
To: users at gecode.org
Subject: [gecode-users] Modelling strategies for reconciling availabilities
with scheduled shifts
Hi everyone,
I'm writing a program to help schedule student employees at our university
based on pre-defined shifts (time blocks) and student availabilities (also
time blocks).
This strikes me as similar to the Air Crew problem, except for modelling the
constraint that an employee is not simply generally available: it depends on
their schedule.
What modelling strategies can a more seasoned constraint programmer
recommend for solving this problem?
I appreciate any guidance,
Christopher Thielen
_______________________________________________
Gecode users mailing list
users at gecode.org
https://www.gecode.org/mailman/listinfo/gecode-users
More information about the users
mailing list


The Fax Mail Address Book dialog box allows you to copy names and fax numbers into the relevant text boxes in the Fax Message dialog box.
To copy a name and fax number, highlight the listing you require in the Full Name/Fax No. list. Then click the OK button to transfer the name and fax number to your fax message.
You can delete an entry from the list by highlighting it and then clicking the Delete button.


Design System : My designs are based on principles of "Design System", a term coined by Brad Frost, in his popular book Atomic Design.
Old Portfolio : Single Page portfolio website, made by me after learning to code for the first time in 2 months.
Kino Enterprise : Single Page Website and a landing page for small businesses.
Portfolio v.2(Archived) : This site is made using basic principles of design systems. Stacks Used : HTML, jQuery, SASS.
All of my other minor web design projects are listed on GitHub and CodePen
Estate Website : Website with modern web design, Progressive Web App features like app-shell caching, SEO-ready and responsiveness.
While working on team projects based on javascript frameworks, I have also gained experience in basic usage of ReactJS and AngularJS
Ciphy Bot : I began working on a Discord bot, in September of 2017, its written in NodeJS and hosted on Heroku.


Ripple Price Analysis: XRP Falls Below $0.26 But A Bullish Crossover Could Suggest A Trend Reversal
by Yaz SheikhXRP saw a small decline of around 1.42% over the past 24 hours and it currently trades at $0.2590. The cryptocurrency has seen a further drop of 10.63% over the past week and it fell below the support at $0.26.
XRP remains the third-largest cryptocurrency with a market cap of $11.35 billion.
Looking at the XRP/USD 1-Day Chart:
- Since our last analysis, XRP continued to go lower below the support at $0.2670 until reaching $0.2584.
- From above: The nearest level of resistance lies at $0.2811. Above it, resistance lies at $2880 (100-days EMA) and $0.2890. Following this, resistance is found at at $0.30, $0.308 (200-days EMA), $0.3177, and $0.3262 (bearish .382 Fib Retracement).
- From below: The nearest level of support lies at $0.2584. Beneath it, support can be found at $0.2518 and $0.25. Further support is expected at $0.24, $0.2345, $0.22, and $0.2153.
- The trading volume remains high but is diminishing slowly.
- The RSI is well beneath the 50 level which shows that the sellers are in complete control over the market momentum. However, the Stochastic RSI has been in oversold conditions for a while, as we wait for a bullish crossover signal to send the market higher.
Looking at the XRP/BTC 1-Day Chart:
- Against Bitcoin, XRP has pretty much traded sideways as it managed to remain supported above the 3000 SAT level.
- From above: The nearest level of resistance lies at 3112 SAT. Above this, resistance is found at 3200 SAT (100-days EMA), 3324 SAT, 3375 SAT, and 3500 SAT. Following this, resistance can be expected at 3568 SAT (bearish .382 Fib Retracement), 3666 SAT, and 3739 SAT.
- From below: The nearest level of support lies at 3000 SAT. Beneath this, support is found at 2904 SAT (.618 Fib Ret), 2853 SAT, 2798 SAT, 2752 SAT, 2710 SAT, and 3607 SAT.
- The trading volume is also slowly diminishing here.
- The RSI is marginally below the 50 level to show a weak bearish dominance. The Stochastic RSI is in oversold conditions as we wait for a bullish crossover signal to send the market higher.
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Disclaimer: Information found on CryptoPotato is those of writers quoted. It does not represent the opinions of CryptoPotato on whether to buy, sell, or hold any investments. You are advised to conduct your own research before making any investment decisions. Use provided information at your own risk. See Disclaimer for more information.
Cryptocurrency charts by TradingView.
Technical analysis tools by Coinigy.


--- layout: post status: publish published: true title: "(9^3) - 700" author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 906 wordpress_url: http://winterdom.com/2006/09/93700 date: '2006-09-05 23:32:50 +0000' date_gmt: '2006-09-05 23:32:50 +0000' categories: - Personal tags: [] comments: - id: 628 author: Sam Gentile author_email<EMAIL_ADDRESS>author_url: http://codebetter.com/blogs/sam.gentile date: '2006-09-06 10:22:59 +0000' date_gmt: '2006-09-06 10:22:59 +0000' content: | Happy Birthday my friend! ---
As it happens once a year, every year, today happens to be my birthday. Elevator stops on the 29th floor. Yay to me!


Gitlab
Version Control & CI
Create value faster with a single application for the whole software development and operations lifecycle.
Vault
A Tool for Managing Secrets
Vault secures, stores, and tightly controls access to tokens, passwords, certificates, API keys, and other secrets in modern computing.


class: center, middle ### W4995 Applied Machine Learning # Dimensionality Reduction ## (PCA) 03/25/19 Andreas C. Müller (Adapted and modified for CC 6021236 @ PCC/Ciencias/UCV by Eugenio Scalise, October 2019) ??? Today we're going to talk about dimensionality reduction, mostly about principal component analysis. We're also going to talk about discriminant analysis and manifold learning. These all slightly different sets of goals. But the main idea here is to take a high dimensional input dataset and produce the dimensionality for processing. It can be either before the machine learning pipeline or often for visualization. FIXME PCA components and scaling: xlabel for components 0 and 1 FIXME LDA projection slide with explanation and diagram! FIXME compare Largevis, t-SNE, UMAP FIXME print output in PCA slides: I need to know the dimenionality (29?) FIXME trim tsne animation FIXME write down math for inverse transform? (and for pca transform?) FIXME show unwhitened vs whitened plot --- class: centre,middle # Unsupervized Learning ??? --- # Unsupervized Learning - Unsupervised learning subsumes all kinds of machine learning where there is no known output, no teacher to instruct the learning algorithm. - Unsupervised learning involves tasks that operate on datasets without labeled responses or target values - The learning algorithm is just shown the input data and asked to extract knowledge from this data. - We will look into two kinds of unsupervised learning in this course: __transformations of the dataset__ (i.e. dimensionality reduction) and __clustering__. ??? --- # Applications of Unsupervized Learning - Visualize structure of a complex dataset. - Density estimation to predict probabilities of events. - Compress and summarize the data. - Extract features for supervised learning. - Discover important clusters or outliers. ??? --- # Principal Component Analysis (PCA) - PCA finds the directions of the maximum variant in the data. - PCA returns an orthogonal basis of the space where the components are ordered by how much variance of the data they cover and so we get a new basis of the original space. - This new basis corresponds to rotating the input space (in the example the first component is my X-axis and the second component is my Y-axis and this is the transformation that PCA learns). - We can use PCA for dimensionality reduction dropping some of the dimensions (they are ordered by decreasing variance). - The idea is that does a PCA projection covers as much as possible of the data set. - You can also look at PCA as a de-noising algorithm. ??? --- .center[ ![:scale 70%](images/pca-intuition.png) ] ??? Here, we have a 2D input space, there's some point scattered here. The color is supposed to show you where the data goes in the transformations. PCA finds the directions of the maximum variant in the data. So starting with this blob of data, you look at the direction that is the most elongated. And then you look for the next opponent that captures the second most various, that's orthogonal to the first component. Here in 2-dimensions, there's only one possibility to be orthogonal to the first component and so that's our second component. If you're in higher dimensions, there are obviously infinitely many different directions that could be orthogonal, and so then you would iterate. What PCA returns is basically an orthogonal basis of the space where the components are ordered by how much variance of the data they cover and so we get a new basis of the original space. So we can do this until like N dimensions many times. In this example, I could do two times, after that there are no orthogonal vectors left. And so this new basis corresponds to rotating the input space, I can rotate the input space so that the first component is my X-axis and the second component is my Y-axis and this is the transformation that PCA learns. This doesn't do any dimensionality reduction as of yet, this is just a rotation of the input space. If I want to use it for dimensionality reduction, I can now start dropping some of these dimensions. So they are ordered by decreasing variance, I could in this example drop, for example, the second component only to regain the first component. So basically, I dropped the Y-axis and projected everything to the X line. And this would be dimensionality reduction with the PCA going from two dimensions to one dimension. And the idea is that if your data lives on a lower dimensional space, or essentially lives on lower dimensional space, embedded in high dimensional space, you could think of this is mostly aligned or Gaussian blob along this direction and there's a little bit of noise in this direction. The most information about the data is sort of along this line. The idea is that does one-dimensional projection now covers as much as possible of this data set. You can also look at PCA as being sort of a de-noising algorithm, by taking this reduced representation in the rotated space and rotating it back to the original space. So this is basically transforming the data using PCA, the rotation dropping one dimension rotating back, you end up with this. And so this is through information that is retained in this projection, basically. And so, arguably, you still have a lot of information from this dataset. --- # PCA Computation - Center X (subtract mean). - In practice: Also scale. - Compute singular value decomposition (SVD): ![:scale 100%](images/pca-computation.png) ??? If I want to apply PCA to my dataset, the first thing I have to do, which is sort of part of the algorithm subtracts the mean. Any package will subtract the mean for you before it does the SVD. What you should probably also do in practice is to scale the data to unit variance. And then the PCA algorithm just computes the singular level decomposition. We decompose the data X into an orthogonal, a diagonal, and an orthogonal. V^T is number of features, U is number of samples times number of samples, D is diagonal containing singular values. Singular values correspond to the variance of each of these directions. Usually, in SVD you sort them by singular values. So the largest singular value corresponds to the first principle components. There's an additional processing step that you can do which is the most basic form of PCA. You can also use these entries of the diagonal to really scale the data in the rotated space so that the variance is the same across each of the new dimensions. --- class: split-40 # PCA for Visualization .tiny-code.left-column[```python from sklearn.decomposition import PCA print(cancer.data.shape) pca = PCA(n_components=2) X_pca = pca.fit_transform(cancer.data) print(X_pca.shape) plt.scatter(X_pca[:, 0], X_pca[:, 1], c=cancer.target) plt.xlabel("first principal component") plt.ylabel("second principal component") components = pca.components_ plt.imshow(components.T) plt.yticks(range(len(cancer.feature_names)), cancer.feature_names) plt.colorbar() ``` ![:scale 80%](images/pca-for-visualization-cancer-data.png) ] .right-column[ ![:scale 90%](images/pca-for-visualization-components-color-bar.png)] ??? I want to show you an example on real data set. So the first data set I'm going to use it on is the breast cancer data set. The way I use PCA most often is probably for visualization. I often do PCA with two components, because my monitor has two dimensions. I fit, transform the data and I scatter it and then I get the scatter plot of the first principle component versus second principal component. So this is the binary classification problem, PCA obviously is a completely unsupervised method, so it doesn't know what the class labels but I could look whether this is a hard problem to solve or is it an easy problem to solve. If I look at this plot, maybe it looks like it's a relatively easy problem to solve with the points being relatively well separated. Now I look at the principal component vectors. So there are two principal components, each of them has number of features many dimensions. So this is shown here as a heat map. And you can see that there are basically two features that dominate the principal components, which is mean area and worst area. And all the rest of the entries are approximately zero. So actually, I didn't rotate my data at all, I just looked at two features. So I didn't scale my data, if I don't scale my data and a particular feature has a much larger magnitude, this feature will basically be the first principle component because if I multiply a feature by 10,000, this feature will have the largest variance of everything. There will be no direction that has a larger variance than that. --- class:spacious # Scaling! .tiny-code[```python pca_scaled = make_pipeline(StandardScaler(), PCA(n_components=2)) X_pca_scaled = pca_scaled.fit_transform(cancer.data) plt.scatter(X_pca_scaled[:, 0], X_pca_scaled[:, 1], c=cancer.target, alpha=.9) plt.xlabel("first principal component") plt.ylabel("second principal component") ```] .center[![:scale 45%](images/scaled-pca-for-visualization-cancer-data.png)] ??? So now I scale the data. And then I get two components on the cancer data set. And now actually the data looks even better separated. Even with this unsupervised methods it very clearly shows me what separation of the classes is, I can also see things like the yellow class looks much denser than the purple class, maybe there are some outliers here, but this definitely gives me a good idea of this dataset. So this is much more compact than looking at a 30x30 scatter matrix, which I couldn't comprehend. So we can look at the components again. Imagine one feature with very large scale. Without scaling, it’s guaranteed to be the first principal component! --- class:split-40 # Inspecting components .tiny-code[```python components = pca_scaled.named_steps['pca'].components_ plt.imshow(components.T) plt.yticks(range(len(cancer.feature_names)), cancer.feature_names) plt.colorbar() ```] .smaller.left-column[ ![:scale 70%](images/inspecting-pca-scaled-components.png) ] .right-column[ ![:scale 100%](images/inspecting-pca-scaled-components-2.png)] ??? So components are stored in the components attribute of the PCA class. And you can see now all of the features contribute to the principal components. And if you're an expert in the area, and you know what these features mean, sometimes it's possible to read something in this. It's definitely helpful often to look at these component vectors. Another way to visualize the component vectors is to do a scatter plot. But that only works basically for the first two principal components. So you can basically look at the positions of the original features, each dot here is one of the original features, and you can look at how much does this feature contribute to principal component one versus principal component two. And so I can see that the second principal component is dominated by mean fractal dimension and the first personal component is dominated by the worst perimeter. And worse perimeter negatively contributes to the second principal component. And worst case point is also very strong in the first principle component but has zero in the second principal component. This was sort of the first approach trying to use PCA for 2-dimensional visualization and trying to understand what the components mean. sign of component is meaningless! --- # PCA for regularization .tiny-code[ ```python from sklearn.linear_model import LogisticRegression X_train, X_test, y_train, y_test = train_test_split(cancer.data, cancer.target, stratify=cancer.target, random_state=0) lr = LogisticRegression(C=10000).fit(X_train, y_train) print(lr.score(X_train, y_train)) print(lr.score(X_test, y_test)) ``` ``` 0.993 0.944 ``` ```python pca_lr = make_pipeline(StandardScaler(), PCA(n_components=2), LogisticRegression(C=10000)) pca_lr.fit(X_train, y_train) print(pca_lr.score(X_train, y_train)) print(pca_lr.score(X_test, y_test)) ``` ``` 0.961 0.923 ``` ] ??? One thing that PCA is often used for, in particular for statistics oriented people, is using it for regularizing a model. You can use PCA to reduce the dimensionality of your data set and then you can do a model on the on the reduced dimensional data set. Since it has fewer features, this will have less complexity, less power so you can avoid overfitting by reducing the dimensionality. I’ve given an example here on the same data set. I'm using logistic regression, and I basically turn off regularization. Instead of using L2 regularization in linear regression, I'm trying to do reduce the input space. So you can see that, if I do that, I basically overfit the data perfectly. So on the training dataset, I have 99.3% accuracy, and on test dataset I have 44.4% accuracy. Now if I use PCA with two dimensions, I reduce this down to just two features. I basically reduce overfitting a lot so I get a lower training score but I also get a lower test score. Generally, if you find that you only need 2-dimension to solve a problem, then that’s a very simple problem. But if you're shooting for accuracy, clearly you’ve regularized too much, you're restricted to the model too much by just using two components. One way to figure out a good number of components, obviously, doing grid search with cross-validation. Another way is to look at the variance that it is covered by each of the components, so this is basically the singular values. --- # Summary - PCA good for visualization, exploring correlations - PCA can sometimes help with classification as regularization or for feature extraction. - Check LDA and t-SNE: a supervised alternative to PCA. ??? PCA, I really like for visualization and for exploring correlations, you can use it together with a classification for regularization if you have lots of features. Often, I find that regularization of the classifier works better. T-SNE probably makes the nicest pictures of the bunch. And if you want a linear transformation of your data in a supervised setting Linear Discriminant Analysis is a good alternative to PCA. LDA also also yields a rotation of the input spacA --- class: center, middle # Next: Clustering


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#include <SBC.h>
Public Attributes | |
| unsigned char | bPageCode:6 |
| unsigned char | isSPF:1 |
| unsigned char | isPS:1 |
| unsigned char | bPageLength |
| unsigned char | isDCR:1 |
| unsigned char | isDTE:1 |
| unsigned char | isPER:1 |
| unsigned char | isEER:1 |
| unsigned char | isRC:1 |
| unsigned char | isTB:1 |
| unsigned char | isARRE:1 |
| unsigned char | isAWRE:1 |
| unsigned char | bReadRetryCount |
| unsigned char | pObsolete1 [3] |
| unsigned char | bReserved1 |
| unsigned char | bWriteRetryCount |
| unsigned char | bReserved2 |
| unsigned char | pRecoveryTimeLimit [2] |
| unsigned char _SBCReadWriteErrorRecovery::bPageCode |
0x01 : SBC_PAGE_READ_WRITE_ERROR_RECOVERY
| unsigned char _SBCReadWriteErrorRecovery::bPageLength |
Length of page data (0x0A)
| unsigned char _SBCReadWriteErrorRecovery::bReadRetryCount |
Number of retries when reading
| unsigned char _SBCReadWriteErrorRecovery::bReserved1 |
Reserved byte
| unsigned char _SBCReadWriteErrorRecovery::bReserved2 |
Reserved byte
| unsigned char _SBCReadWriteErrorRecovery::bWriteRetryCount |
Number of retries when writing
| unsigned char _SBCReadWriteErrorRecovery::isARRE |
Automatic read reallocation enabled bit
| unsigned char _SBCReadWriteErrorRecovery::isAWRE |
Automatic write reallocation enabled bit
| unsigned char _SBCReadWriteErrorRecovery::isDCR |
Disable correction bit
| unsigned char _SBCReadWriteErrorRecovery::isDTE |
Data terminate on error bit
| unsigned char _SBCReadWriteErrorRecovery::isEER |
Enable early recovery bit
| unsigned char _SBCReadWriteErrorRecovery::isPER |
Post error bit
| unsigned char _SBCReadWriteErrorRecovery::isPS |
Parameters savable ?
| unsigned char _SBCReadWriteErrorRecovery::isRC |
Read continuous bit
| unsigned char _SBCReadWriteErrorRecovery::isSPF |
Page or subpage data format
| unsigned char _SBCReadWriteErrorRecovery::isTB |
Transfer block bit
| unsigned char _SBCReadWriteErrorRecovery::pObsolete1[3] |
Obsolete bytes
| unsigned char _SBCReadWriteErrorRecovery::pRecoveryTimeLimit[2] |
Maximum time duration for error recovery


---
layout: page
title: Aiqi Cui
subtitle: Information Systems and Stats & ML Student
Carnegie Mellon University
use-site-title: true
---
Aiqi (Chelsea) Cui '20 is a double
Information Systems
and
Stats & Machine Learning
major at
Carnegie Mellon University.
At Carnegie Mellon, Aiqi is the co-founder and head of Talent Pool in
CMU Summit on US-China Innovation and Entrepreneurship, a research assistant at
NSF prize winning project Learning to See, Seeing to Learn,
and the Director of Communications at Mortar Board National College Senior Honor Society.
Aiqi's great passion is in creating things that make people feel "wow". Her academic interests lie in the areas splitting between Data Science/Machine Learning and Full-Stack Development.
The advanced CS/Math courses I've taken at CMU:
| Course Number | Course Name | Semester | Instructor(s) |
|---|---|---|---|
| 15-351 | Algorithms and Data Structures | S19 | Hosein Mohimani |
| 36-315 | Statistical Graphics and Visualization | S19 | Matey Neykov |
| 67-315 | Interaction Design and Accessibility Testing | S19 | Divakaran Liginlal |
| 10-601 | Introduction to Machine Learning | F18 | Matt Gormley |
| 67-327 | Web Application Security | F18 | C.F. Larry Heimann |
| 36-401 | Modern Regression | F18 | Edward H. Kennedy |
| 67-364 | Practical Data Science | S18 | Raja Sooriamurthi |
| 36-350 | Statistical Computing | S18 | Ryan Tibshirani |
| 67-272 | Application Design and Development | S18 | C.F. Larry Heimann |
| 36-226 | Introduction to Statistical Inference | S18 | Joel Greenhouse |
| 36-225 | Introduction to Probability Theory | S18 | Peter Freeman |
| 67-262 | Database Design and Development | F17 | Raja Sooriamurthi |
Programming
Data Science
Tools


I am a UX/UL Designer, I considered myself as a creative and imaginative designer. I am passionate about making 3D Modules and do editing in After Effects. I usually search some videos and tutorials on internet to try to discover and learn different skills on different sofewares.
I have done a few projects using the skills what I have already known and learned. Included Cinema 4D, After Effetcs, Illustior, Photoshop and some Programe Language. Below are some of the artworks I have created so far, Please click on the image to see more information about it.


planning.actions
Classes
ActionParserTest
AttackAction
AttackActionTest
AttackActionType
AttackActionTypeTest
BuildAction
BuildActionTest
BuildActionType
ExpandActionType
GatherAction
GatherActionType
ScoutAction
ScoutActionType
testingattackaction
TrainAction
TrainActionTest
TrainActionType
UpgradeAction
UpgradeActionType


Past three weeks
How to use essential language constructs?
- Data Types
- Recursion
- Higher-Order Functions
Next two weeks
How to implement language constructs?
- Local variables and scope
- Environments and Closures
- (skip) Type Inference
Interpreter
How do we represent and evaluate a program?
Roadmap: The Nano Language
Features of Nano:
- Arithmetic
- Variables
- Let-bindings
- Functions
- Recursion
1. Nano: Arithmetic
A “grammar” of arithmetic expressions:
| Expressions | Values | |
|---|---|---|
4 |
==> |
4 |
4 + 12 |
==> |
16 |
(4+12) - 5 |
==> |
11 |
Representing Arithmetic Expressions and Values
Lets represent arithmetic expressions as type
data Expr
= ENum Int -- ^ n
| EAdd Expr Expr -- ^ e1 + e2
| ESub Expr Expr -- ^ e1 - e2
| EMul Expr Expr -- ^ e1 * e2
Lets represent arithmetic values as a type
Evaluating Arithmetic Expressions
We can now write a Haskell function to evaluate an expression:
eval :: Expr -> Value
eval (ENum n) = n
eval (EAdd e1 e2) = eval e1 + eval e2
eval (ESub e1 e2) = eval e1 - eval e2
eval (EMul e1 e2) = eval e1 * eval e2
Alternative representation
Lets pull the operators into a separate type
data Binop = Add -- ^ `+`
| Sub -- ^ `-`
| Mul -- ^ `*`
data Expr = ENum Int -- ^ n
| EBin Binop Expr Expr -- ^ e1 `op` e2
QUIZ
Evaluator for alternative representation
What is a suitable type for evalOp
?
{- 1 -} evalOp :: BinOp -> Value
{- 2 -} evalOp :: BinOp -> Value -> Value -> Value
{- 3 -} evalOp :: BinOp -> Expr -> Expr -> Value
{- 4 -} evalOp :: BinOp -> Expr -> Expr -> Expr
{- 5 -} evalOp :: BinOp -> Expr -> Value
The Nano Language
Features of Nano:
- Arithmetic [done]
- Variables
- Let-bindings
- Functions
- Recursion
2. Nano: Variables
Let’s add variables and let
bindings!
Lets extend our datatype
QUIZ
What should the following expression evaluate to?
(A) 0
(B) 1
(C) Error
Environment
An expression is evaluated in an environment
- A phone book which maps variables to values
A type for environments
Evaluation in an Environment
We write
to mean
When expr
is evaluated in environment env
the result is value
That is, when we have variables, we modify our eval
uator to take an input environment env
in which expr
must be evaluated.
First, lets update the evaluator for the arithmetic cases ENum
and EBin
QUIZ
What is a suitable ?value
such that
(A) 0
(B) 1
(C) Error
QUIZ
What is a suitable env
such that
(A) []
(B) [x := 0, y := 9]
(C) [x := 9, y := 0]
(D) [x := 9, y := 10, z := 666]
(E) [y := 10, z := 666, x := 9]
Evaluating Variables
Using the above intuition, lets update our evaluator to handle variables i.e. the EVar
case:
Lets confirm that our eval
is ok!
envA = []
envB = ["x" := 0 , "y" := 9]
envC = ["x" := 9 , "y" := 0]
envD = ["x" := 9 , "y" := 10 , "z" := 666]
envE = ["y" := 10, "z" := 666, "x" := 9 ]
-- >>> eval envA (EBin Add (EVar "x") (ENum 1))
-- >>> eval envB (EBin Add (EVar "x") (ENum 1))
-- >>> eval envC (EBin Add (EVar "x") (ENum 1))
-- >>> eval envD (EBin Add (EVar "x") (ENum 1))
-- >>> eval envE (EBin Add (EVar "x") (ENum 1))
The Nano Language
Features of Nano:
- Arithmetic expressions [done]
- Variables [done]
- Let-bindings
- Functions
- Recursion
2. Nano: Variables
Let’s add variables and let
bindings!
Lets extend our datatype
type Id = String
data Expr
= ENum Int -- OLD
| EBin Binop Expr Expr
| EVar Id
-- NEW
| ELet Id Expr Expr
How should we extend eval
?
QUIZ
What should the following expression evaluate to?
(A) Error
(B) 1
(C) 0
QUIZ
What should the following expression evaluate to?
(A) Error
(B) 0
(C) 1
(D) 100
(E) 101
QUIZ
What should the following expression evaluate to?
(A) Error
(B) 0
(C) 1
(D) 100
(E) 101
QUIZ
What should the following expression evaluate to?
(A) Error
(B) 1
(C) 101
(D) 102
(E) 2
Principle: Static/Lexical Scoping
Every variable use gets its value from a unique definition:
- “Nearest”
let
-binder in program text
“Static” means you can tell without running the program
Great for readability and debugging
- Define local variables
- Be sure where each variable got its value
Don’t have to scratch head to figure where a variable got “assigned”
How to implement static scoping?
QUIZ
Lets re-evaluate the quizzes!
(A) env
(B) [ ]
(C) [ ("x" := 0) ]
(D) ("x" := 0) : env
(E) env ++ ["x" := 0]
QUIZ
(A) ("x" := 0) : env
(B) ("y" := 100) : env
(C) ("y" := 100) : ("x" := 0) : env
(D) ("x" := 0) : ("y" := 100) : env
(E) [("y" := 100), ("x" := 0)]
QUIZ
Lets re-evaluate the quizzes!
(A) ("x" := 0) : env
(B) ("x" := 100) : env
(C) ("x" := 100) : ("x" := 0) : env
(D) ("x" := 0) : ("x" := 100) : env
(E) [("x" := 100)]
Extending Environments
Lets fill in eval
for the let x = e1 in e2
case!
- Evaluate
e1
inenv
to get a valuev1
- Extend environment with value for
x
i.e. to(x := v1) : env
- Evaluate
e2
using extended environment.
Lets make sure our tests pass!
Run-time Errors
Haskell function to evaluate an expression:
eval :: Env -> Expr -> Value
eval env (Num n) = n
eval env (Var x) = lookup x env -- (A)
eval env (Bin op e1 e2) = evalOp op v1 v2 -- (B)
where
v1 = eval env e1 -- (C)
v2 = eval env e2 -- (C)
eval env (Let x e1 e2) = eval env1 e2
where
v1 = eval env e1
env1 = (x, v1) : env -- (D)
QUIZ
Will eval env expr
always return a value
? Or, can it crash?
(A) operation at A
may fail (B) operation at B
may fail (C) operation at C
may fail (D) operation at D
may fail (E) nah, its all good…, always returns a Value
Free vs bound variables
Undefined Variables
How do we make sure lookup
doesn’t cause a run-time error?
Bound Variables
Consider an expression let x = e1 in e2
An occurrence of
x
is bound ine2
i.e. when occurrence of form
let x = ... in ... x ...
i.e. when
x
occurs “under” alet
binding forx
.
Free Variables
An occurrence of x
is free in e
if it is not bound in e
Closed Expressions
An expression e
is closed in environment env
:
- If all free variables of
e
are defined inenv
Successful Evaluation
lookup
will never fail
- If
eval env e
is only called one
that is closed inenv
QUIZ
Which variables occur free in the expression?
(A) None
(B) x
(C) y
(D) x
and y
Exercise
Consider the function
evaluate :: Expr -> Value
evaluate e
| isOk e = eval emptyEnv e
| otherwise = error "Sorry! bad expression, it will crash `eval`!"
where
emptyEnv = [] -- has NO bindings
What should isOk
check for? (Try to implement it for nano
…)
The Nano Language
Features of Nano:
- Arithmetic expressions [done]
- Variables [done]
- Let-bindings [done]
- Functions
- Recursion
Nano: Functions
Let’s add
lambda abstraction (aka function definitions)
application (aka function calls)
e ::= n -- OLD
| e1 `op` e2
| x
| let x = e1 in e2
-- NEW
| \x -> e -- abstraction
| e1 e2 -- application
Example
Representation
data Expr
= ENum Int -- OLD
| EBin Binop Expr Expr
| EVar Id
| ELet Id Expr Expr
-- NEW
| ??? -- abstraction \x -> e
| ??? -- application (e1 e2)
Representation
data Expr
= ENum Int -- OLD
| EBin Binop Expr Expr
| EVar Id
| ELet Id Expr Expr
-- NEW
| ELam Id Expr -- abstraction \x -> e
| EApp Expr Expr -- application (e1 e2)
Example
is represented as
Functions are Values
Recall the trinity
But… what is the value of a function?
Lets build some intuition with examples.
QUIZ
What does the following expression evaluate to?
(A) Error/Undefined
(B) 10
(C) 11
(D) 0
(E) 1
What is the Value of incr
?
Is it an
Int
?Is it a
Bool
?Is it a ???
What information do we need to store (in the Env
) about incr
?
A Function’s Value is its Code
-- env
let incr = \x -> x + 1
in -- ("incr" := ) : env
incr 10 -- evaluate  with parameter := 10
What information do we store about
?
A Call’s Value
How to evaluate the “call” incr 10
?
Lookup the

i.e.<param, body>
forincr
(stored in the environment),Evaluate
body
withparam
set to10
!
Two kinds of Values
We now have two kinds of Values
- Plain
Int
(as before) - A function’s “code”: a pair of “parameter” and “body-expression”
Evaluating Lambdas and Applications
eval :: Env -> Expr -> Value
-- OLD
eval env (ENum n) = ???
eval env (EVar x) = ???
eval env (EBin op e1 e2) = ???
eval env (ELet x e1 e2) = ???
-- NEW
eval env (ELam x e) = ???
eval env (EApp e1 e2) = ???
Lets make sure our tests work properly!
exLam1 = ELet "incr" (ELam "x" (EBin Add (EVar "x") (ENum 1)))
(
EApp (EVar "incr") (ENum 10)
)
-- >>> eval [] exLam1
-- 11
QUIZ
What should the following evaluate to?
(A) Error/Undefined
(B) 10
(C) 11
(D) 0
(E) 1
exLam2 = ELet "c" (ENum 1)
(ELet "incr" (ELam "x" (EBin Add (EVar "x") (EVar "c")))
(
EApp (EVar "incr") (ENum 10)
)
)
-- >>> eval [] exLam2
-- ???
QUIZ
And what should this expression evaluate to?
(A) Error/Undefined
(B) 110
(C) 11
The “Immutability Principle”
A function’s behavior should never change
- A function must always return the same output for a given input
Why?
Oh no! How to find the bug? Is it
- In
myFunc
or - In a global variable or
- In a library somewhere else or
- …
My worst debugging nightmare
Colbert “Immutability Principle”
The Immutability Principle ?
How does our eval
work?
exLam3 = ELet "c" (ENum 1)
(
ELet "incr" (ELam "x" (EBin Add (EVar "x") (EVar "c")))
(
ELet "c" (ENum 100)
(
EApp (EVar "incr") (ENum 10)
)
)
)
-- >>> eval [] exLam3
-- ???
Oops?
-- []
let c = 1
in -- ["c" := 1]
let inc = \x -> x + c
in -- ["inc" := <x, x+c>, c := 1]
let c = 100
in -- ["c" := 100, "inc" := <x, x+c", "c" := 1] <<< env
inc 10
And so we get
Ouch.
Enforcing Immutability with Closures
How to enforce immutability principle
inc 10
always returns11
?
Key Idea: Closures
At definition: Freeze the environment the function’s value
At call: Use the frozen environment to evaluate the body
Ensures that inc 10
always evaluates to the same result!
-- []
let c = 1
in -- ["c" := 1]
let inc = \x -> x + c
in -- ["inc" := <frozenv, x, x+c>, c := 1] <<< frozenv = ["c" := 1]
let c = 100
in -- ["c" := 100, "inc" := <frozenv, x, x+c>, "c" := 1]
inc 10
Now we evaluate
eval env (inc 10)
==> eval ("x" := 10 : frozenv) (x + c) where frozenv = ["c" := 1]
==> 10 + 1
==> 1
tada!
Representing Closures
Lets change the Value
datatype to also store an Env
Evaluating Function Definitions
How should we fix the definition of eval
for ELam
?
Hint: What value should we bind incr
to in our example above?
(Recall At definition freeze the environment the function’s value)
Evaluating Function Calls
How should we fix the definition of eval
for EApp
?
(Recall At call: Use the frozen environment to evaluate the body)
Hint: What value should we evaluate incr 10
to?
- Evaluate
incr
to get<frozenv, "x", x + c>
- Evaluate
10
to get10
- Evaluate
x + c
inx:=10 : frozenv
Let’s generalize that recipe!
- Evaluate
e1
to get<frozenv, param, body>
- Evaluate
e2
to getv2
- Evaluate
body
inparam := v2 : frozenv
Immutability Achieved
Lets put our code to the test!
exLam3 = ELet "c" (ENum 1)
(
ELet "incr" (ELam "x" (EBin Add (EVar "x") (EVar "c")))
(
ELet "c" (ENum 100)
(
EApp (EVar "incr") (ENum 10)
)
)
)
-- >>> eval [] exLam3
-- ???
QUIZ
What should the following evaluate to?
let add = \x -> (\y -> x + y)
in
let add10 = add 10
in
let add20 = add 20
in
(add10 100) + (add20 1000)
TODO
Functions Returning Functions Achieved!
TODO
Practice
What should the following evaluate to?
let add = \x -> (\y -> x + y)
in
let add10 = add 10
in
let doTwice = \f -> (\x -> f (f x))
in
doTwice add10 100
Functions Accepting Functions Achieved!
The Nano Language
Features of Nano:
- Arithmetic expressions [done]
- Variables [done]
- Let-bindings [done]
- Functions [done]
- Recursion
… You figure it out Hw4 … :-)


Gecode::Set::Branch::ValRnd< inc > Class Template Reference
[Integer value selection for brancher]
Class for random value selection. More...
#include <branch.hh>
Public Types | |
| typedef SetView | View |
| View type. | |
| typedef int | Val |
| Value type. | |
| typedef ArchivedRandomGenerator | Choice |
| Choice. | |
Public Member Functions | |
| ValRnd (void) | |
| Default constructor. | |
| ValRnd (Space &home, const ValBranchOptions &vbo) | |
| Constructor for initialization. | |
| int | val (Space &home, SetView x) |
| Return minimum value of view x. | |
| ModEvent | tell (Space &home, unsigned int a, SetView x, int n) |
| Tell (a = 0) or (a = 1). | |
| Choice | choice (Space &home) |
| Return choice. | |
| Choice | choice (const Space &home, Archive &e) |
| Return choice. | |
| void | commit (Space &home, const Choice &c, unsigned a) |
| Commit to choice. | |
| void | update (Space &home, bool share, ValRnd &vs) |
| Updating during cloning. | |
| void | dispose (Space &home) |
| Delete value selection. | |
Static Public Attributes | |
| static const unsigned int | alternatives = 2 |
| Number of alternatives. | |
Protected Attributes | |
| ArchivedRandomGenerator | r |
| Random number generator. |
Detailed Description
template<bool inc>
class Gecode::Set::Branch::ValRnd< inc >
Class for random value selection.
Requires
#include <gecode/set/branch.hh>
Definition at line 130 of file branch.hh.
Member Typedef Documentation
| typedef SetView Gecode::Set::Branch::ValRnd< inc >::View |
| typedef int Gecode::Set::Branch::ValRnd< inc >::Val |
| typedef ArchivedRandomGenerator Gecode::Set::Branch::ValRnd< inc >::Choice |
Constructor & Destructor Documentation
| Gecode::Set::Branch::ValRnd< inc >::ValRnd | ( | void | ) | [inline] |
Default constructor.
Definition at line 121 of file select-val.hpp.
| Gecode::Set::Branch::ValRnd< inc >::ValRnd | ( | Space & | home, | |
| const ValBranchOptions & | vbo | |||
| ) | [inline] |
Constructor for initialization.
Definition at line 124 of file select-val.hpp.
Member Function Documentation
| int Gecode::Set::Branch::ValRnd< inc >::val | ( | Space & | home, | |
| SetView | x | |||
| ) | [inline] |
Return minimum value of view x.
Definition at line 128 of file select-val.hpp.
| ModEvent Gecode::Set::Branch::ValRnd< inc >::tell | ( | Space & | home, | |
| unsigned int | a, | |||
| SetView | x, | |||
| int | n | |||
| ) | [inline] |
Tell (a = 0) or (a = 1).
Definition at line 141 of file select-val.hpp.
| ValRnd< inc >::Choice Gecode::Set::Branch::ValRnd< inc >::choice | ( | Space & | home | ) | [inline] |
Return choice.
Definition at line 146 of file select-val.hpp.
| ValRnd< inc >::Choice Gecode::Set::Branch::ValRnd< inc >::choice | ( | const Space & | home, | |
| Archive & | e | |||
| ) | [inline] |
Return choice.
Definition at line 151 of file select-val.hpp.
| void Gecode::Set::Branch::ValRnd< inc >::commit | ( | Space & | home, | |
| const Choice & | c, | |||
| unsigned | a | |||
| ) | [inline] |
Commit to choice.
Definition at line 156 of file select-val.hpp.
| void Gecode::Set::Branch::ValRnd< inc >::update | ( | Space & | home, | |
| bool | share, | |||
| ValRnd< inc > & | vs | |||
| ) | [inline] |
Updating during cloning.
Definition at line 162 of file select-val.hpp.
| void Gecode::Set::Branch::ValRnd< inc >::dispose | ( | Space & | home | ) | [inline] |
Delete value selection.
Definition at line 167 of file select-val.hpp.
Member Data Documentation
ArchivedRandomGenerator Gecode::Set::Branch::ValRnd< inc >::r [protected] |
const unsigned int Gecode::Set::Branch::ValRnd< inc >::alternatives = 2 [static] |
Number of alternatives.
Reimplemented in Gecode::Set::Branch::AssignValRnd< inc >.
The documentation for this class was generated from the following files:
- gecode/set/branch.hh (Revision: 12001)
- gecode/set/branch/select-val.hpp (Revision: 12001)


Friday the 13th, for that matter. Not that that matters.
I’m testing out Jekyll blogging from the command line.
It gives me a nostalgic satisfaction of learning how to code Greymatter CGI for the first time, when I started blogging back in 2001 or so.
I didn’t get Jekyll to work right away. The website promised it would be easy. Not so, not for me. Yes, Mercury is retrograde.
The most satisfactory commands that worked today, separately, were:
$ rvm implode
(Me deciding rvm was absolutely worthless.)
Then, I compiled Ruby from source, and magically all my problems dissolved.
$ sudo gem install jekyll
Yess! Success!
(If the SEO bots catch on, I searched relentlessly for a fix to the zlib loaderror I kept running into using ‘gem install’.  This installed all dependencies and fixed everything.)
That is all.


The goal of vov is to wrap vov.css into functions so they can be called on when developing a shiny application. Try out the demo here or check out the original here by Vaibhav Tandon. Alternatively, you can run a local copy with vov::run_demo()
.
Install the released version of vov
from CRAN:
Or install the development version from GitHub with:
You can use vov
in a shiny app like so:
library(shiny)
library(vov)
ui <- fluidPage(
use_vov(),
swivel_vertical(
h1("hello world!")
)
)
server <- function(input, output, session) {
}
shinyApp(ui, server)
Where swivel_vertical(h1("fade_in_bottom_left"))
returns:
x <- swivel_vertical(h1("hello world!"))
print(x)
#>
hello world!

If you don’t want to load this package, go to the original repo here, download the CSS file, and write something like this in your UI code:


WARNING !
This website contains flashing images.
Note : Don't forget to enable your computer's sound. (not too high...)
Agree!


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 8-10
James Martin takes all the fuss out of this decadent showpiece dish so you have more time to spend with your guests.
Preheat the oven to 230C/210C Fan/Gas 8.
Heat half of the butter in a large frying pan over a medium heat. When the butter is foaming, add the mushrooms and fry for 4-5 minutes, or until they have released most of their water and it has evaporated from the pan. Season, to taste, with salt and freshly ground black pepper, then transfer to a plate lined with kitchen paper.
Return the frying pan to the heat, add the last of the butter and then wilt the spinach leaves and season, to taste, with salt and freshly ground black pepper. Add to the plate with the mushrooms, set aside until cool, then chill in the fridge.
Roll out both pieces of pastry onto a lightly floured work surface to create two rectangles about 5cm/2in longer and wider than the salmon fillets.
Place one sheet of pastry onto a large flat baking tray and lay one salmon fillet on top, flesh side up. Season well with salt and freshly ground black pepper.
Top the salmon fillet with the mushrooms and then the spinach, then lay the second salmon fillet on top of that, flesh side down, pressing down gently.
Brush the edges of the pastry with some of the beaten egg yolk. Carefully roll the second sheet of pastry onto the coulibiac using a rolling pin to transfer it. Press the edges of each sheet of pastry together to seal and crimp at the edges.
Brush the surface of the pastry parcel all over with the remaining beaten egg yolk. Using a sharp pair of scissors, snip the top of the pastry at intervals to make marks resembling fish scales.
Bake the salmon coulibiac for 25 minutes, then reduce the oven temperature to 200C/180C Fan/Gas 6 and bake for another 12-15 minutes, or until the salmon fillets are just cooked through and the pastry is risen and golden-brown.
Remove the salmon coulibiac from the oven and transfer it to a serving platter. Set aside to rest for 10 minutes, then carve into slices at the table and serve with buttered new potatoes and a dressed green salad.


kvision
/
pl.treksoft.kvision.form
/
Form
/
removeAll
removeAll
fun
removeAll
(
)
:
Form
<
K
>
Removes all controls from the form.
Return
current form


--- layout: page title: Sample description: "This is a sample tool page" header-img: img/bg-simple.jpg tags: hidden, tools ---


ABOUT US
When you work with us, you are part of a team of commited collaborators. All aspects of our software development process are intergrated , interactive and agile.
Our approach unifies design, development and product managent to create exceptional products.
We start each project by understanding your business goals, the users needs and the product requirements.
we help translate them into active and elegant solutions.
SERVICES
Before we sign a contract or write a line of code, our team will spend the neccessary time needed to understand your product vission.
The outcome of the scoping session a proposal or high-level statement of work.
based on your requirements, we can provide a complete offering or just the piece you need.
WHAT WE DO
DESIGN
Our design practice offers a full range of services including brand strategy, interaction and visual design and user experience testing. Throughout your project, our designers create and implement visual design and workflows, solicit user feedback and work with you to make sure what gets built is what is needed.
DEVELOPMENT
Before we sign a contract or write a line of code, our team will spend the neccessary time needed to understand your product vission. The outcome of the scoping session a proposal or high-level statement of work. based on your requirements, we can provide a complete offering or just the piece you need.
PRODUCT MANAGEMENT
All engineers are fluent in the latest enterprise, mobile and web development technologies.They collaborate with your team to write, and improve code on a daily basis, using proven practices such as test-driven development and pair programming.
PORTFOLIO
Black Studio
Ontario Security
Pyramids
Jim Carry
Have A Nice Day
Calculator
Burned
Giraffe Restaurant
CONTACT US


Messages starting from 10th of June, 2020
Hi Chris! Thanks a lot for this very useful template. Saved me a lot of time and searches on the internet.
Hi Neil, thanks for sharing your thoughts regarding Spaces. Hi Neil, thanks for sharing your thoughts regarding Spaces.
Hi Chris! Thanks a lot for this very useful template. Saved me a lot of time and searches on the internet.
Hi Chris! Thanks a lot for this very useful template. Saved me a lot of time and searches on the internet.
Hi Neil, thanks for sharing your thoughts regarding Spaces. Hi Neil, thanks for sharing your thoughts regarding Spaces.


Some draft information how to get NEOSYS Ajax implementation going in AREV backend
Partially Automated routine.
Syntax: WINDOW2HTM windowfilename windowkey outputpathandfilename
It is possible to reduce the initial grunt work of creating forms to HTML by using a NEOSYS template to HTML program in AREV. This currently results in a top down form with prompts on the left, data entry in the middle and help comments on the right. This can be edited into any look you like using an HTML editor of your choice. It might be possible to modify the conversion program to produce HTML that looks exactly like the DOS entry form but this would perhaps not exploit the new flexibility available in HTML forms. The conversion routine does not convert everything automatically ... especially it does not translate popup, pre and post routines from R/Basic to jscript. You will have to do manual work to convert these features.
Manually Create a web page in NEOSYS.NET for each template that you have. The web page will have three main sections. The dictionary and routines section can either be stored in the main web page or stored in separate files and included using any and all standard HTML programming methods and tricks. The three main logical sections of the new HTML forms are as follows:
Mostly automated routine
Syntax: MENU2HTM menufilename menukey
Handles M, W, S, E and X codes
Outputs a MENU.HTM into the NEOSYS.NET directory containing the main menu AND all subsidiary menus.
Also converts all WINDOW templates found in the menus converted.
Any S or E or X commands in the menu need converting of the subroutine and programs from R/Basic to jScript.
A collector window to collect the report parameters must be converted (see conversion of forms from templates above)
An XXXXXPROXY program must be written according to a skeleton example. XXXXX is defined in the client form as the global variable gmodule. Eg ACCOUNTSPROXY is a program that will handle a variety of requests from the client depending on the exact command.
The XXXXXPROXY program will receive the contents of the form or just a simple command from a jscript and produce an output .HTM file. NEOSYS support functions provide the path and name of the file.
A NEOSYS replacement of the standard RLIST program can output to the required .HTM file given from standard queries.
By default on saving any collector window. The contents of the window will be passed to the XXXXXPROXY program on the server and any output from XXXXXPROXY will be displayed on the client. If there is any error discovered then an error message will display, the user can correct their data on the collector window and resubmit.
The must first be converted to output to .HTM files. Preferably they should output native HTML however you can simply continue to output fixed font reports and wrap this in HTML tags.
© 2004 NEOSYS Software Ltd. All Rights Reserved.


Community, Jobs and more
Sorry, it seems you were trying to access a page that doesn't exist. Please check the spelling of the URL you were trying to access and try again.
Sorry, it seems you were trying to access a page that doesn't exist.
Please check the spelling of the URL you were trying to access and try again.
Copyright © 2007-2008 | Powered by SilverStripe Open Source CMS


{% extends "./base.html" %} {% load static %} {% block stylesheet %} {% endblock %} {% block content %}
About Me
I am a senior at SFSU, studying Computer Science. I currently work at Synopsys, Inc. where I have spent the last two and a half years as a software developer / system administrator within I.T. Before that, I had spent about two years working technical customer support within Synopsys. I have grown up in the Bay Area. I was born in Berkeley, grew up in Richmond and later Lafayette, moved to Santa Clara, and currently live in Daly City. My hobbies include cars, video games, and anime.
| Back |


It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a
About MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a
About MoreIt is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has
About More


{%- extends "base.html" %} {% set title = "Not Found" %} {% block main %}
The search and rescue crew has returned exhausted and unsuccessful.


WTF! You don't even have JavaScript enabled! You need to enable it to see all the cool stuff on this website...


{% extends "base.html" %} {% block title %}500: {% endblock%} {% block description %}{% endblock%} {% block error %}[500]{% endblock%} {% block style %}{% endblock style %} {% block main %}
The Weather-O-Meter admins get an email every time you see this page, so there's no need to contact us — we're aware of the problem, and we're going to fix it soon.
In the meantime, you can go back a page, go to the Weather-O-Meter home page, or anything, anything else.
{% endblock main %}


The EDA course is an immersive leaning experience that empowers students to learn along with their cohort the tools and skills needed to be a proficient developer.
My initial impressions are that this course will require more than just learning new technical skills and tools, it will involves a lot more soft skill development than I had expected.
I believe that this will be beneficial not only to my effectiveness as a developer but will also help in transitioning into this new profession.
I am a big believer in the self-driven learning method and can see myself thriving in an environment that requires being self-driven.
I would normally be a reluctant participant in some of the “soft skills” aspect of this course but I can see the value of these skills and will be making an effort to push myself in this area.
My expectations haven’t changed that much mostly because I didn’t really know what to expect and my expectations were pretty vague.
I am very excited to begin this course and participate in the EDA learning environment.
It does make me a bit nervous, mostly around giving up my job and launching myself into the unknown but also around how I will fit into this environment.


Note
Zend\Soap\Wsdl class is used by Zend\Soap\Server component internally to operate with WSDL documents. Nevertheless, you could also use functionality provided by this class for your own needs. The Zend\Soap\Wsdl package contains both a parser and a builder of WSDL documents.
If you don’t plan to do this, you can skip this documentation section.
Zend\Soap\Wsdl constructor takes three parameters:
addMessage($name, $parts) method adds new message description to the WSDL document (/definitions/message element).
Each message correspond to methods in terms of Zend\Soap\Server and Zend\Soap\Client functionality.
$name parameter represents the message name.
$parts parameter is an array of message parts which describes SOAP call parameters. It’s an associative array: ‘part name’ (SOAP call parameter name) => ‘part type’.
Type mapping management is performed using addTypes(), addTypes() and addComplexType() methods (see below).
Note
Messages parts can use either ‘element’ or ‘type’ attribute for typing (see http://www.w3.org/TR/wsdl#_messages).
‘element’ attribute must refer to a corresponding element of data type definition. ‘type’ attribute refers to a corresponding complexType entry.
All standard XSD types have both ‘element’ and ‘complexType’ definitions (see http://schemas.xmlsoap.org/soap/encoding/).
All non-standard types, which may be added using Zend\Soap\Wsdl::addComplexType() method, are described using ‘complexType’ node of ‘/definitions/types/schema/’ section of WSDL document.
So addMessage() method always uses ‘type’ attribute to describe types.
addPortType($name) method adds new port type to the WSDL document (/definitions/portType) with the specified port type name.
It joins a set of Web Service methods defined in terms of Zend\Soap\Server implementation.
See http://www.w3.org/TR/wsdl#_porttypes for the details.
addPortOperation($portType, $name, $input = false, $output = false, $fault = false) method adds new port operation to the specified port type of the WSDL document (/definitions/portType/operation).
Each port operation corresponds to a class method (if Web Service is based on a class) or function (if Web Service is based on a set of methods) in terms of Zend\Soap\Server implementation.
It also adds corresponding port operation messages depending on specified $input, $output and $fault parameters.
Note
Zend\Soap\Server component generates two messages for each port operation while describing service based on Zend\Soap\Server class:
- input message with name $methodName . ‘Request’.
- output message with name $methodName . ‘Response’.
See http://www.w3.org/TR/wsdl#_request-response for the details.
addBinding($name, $portType) method adds new binding to the WSDL document (/definitions/binding).
‘binding’ WSDL document node defines message format and protocol details for operations and messages defined by a particular portType (see http://www.w3.org/TR/wsdl#_bindings).
The method creates binding node and returns it. Then it may be used to fill with actual data.
Zend\Soap\Server implementation uses $serviceName . ‘Binding’ name for ‘binding’ element of WSDL document.
addBindingOperation($binding, $name, $input = false, $output = false, $fault = false) method adds an operation to a binding element (/definitions/binding/operation) with the specified name.
It takes an XML_Tree_Node object returned by addBinding() as an input ($binding parameter) to add ‘operation’ element with input/output/false entries depending on specified parameters
Zend\Soap\Server implementation adds corresponding binding entry for each Web Service method with input and output entries defining ‘soap:body’ element as ‘<soap:body use=”encoded” encodingStyle=”http://schemas.xmlsoap.org/soap/encoding/”/>
See http://www.w3.org/TR/wsdl#_bindings for the details.
addSoapBinding($binding, $style = 'document', $transport = 'http://schemas.xmlsoap.org/soap/http') method adds SOAP binding (‘soap:binding’) entry to the binding element (which is already linked to some port type) with the specified style and transport (Zend\Soap\Server implementation uses RPC style over HTTP).
‘/definitions/binding/soap:binding’ element is used to signify that the binding is bound to the SOAP protocol format.
See http://www.w3.org/TR/wsdl#_bindings for the details.
addSoapOperation($binding, $soap_action) method adds SOAP operation (‘soap:operation’) entry to the binding element with the specified action. ‘style’ attribute of the ‘soap:operation’ element is not used since programming model (RPC-oriented or document-oriented) may be using addSoapBinding() method
‘soapAction’ attribute of ‘/definitions/binding/soap:operation’ element specifies the value of the SOAPAction header for this operation. This attribute is required for SOAP over HTTP and must not be specified for other transports.
Zend\Soap\Server implementation uses $serviceUri . ‘#’ . $methodName for SOAP operation action name.
See http://www.w3.org/TR/wsdl#_soap:operation for the details.
addService($name, $port_name, $binding, $location) method adds ‘/definitions/service’ element to the WSDL document with the specified Wed Service name, port name, binding, and location.
WSDL 1.1 allows to have several port types (sets of operations) per service. This ability is not used by Zend\Soap\Server implementation and not supported by Zend\Soap\Wsdl class.
Zend\Soap\Server implementation uses:
where $name is a class name for the Web Service definition mode using class and script name for the Web Service definition mode using set of functions.
See http://www.w3.org/TR/wsdl#_services for the details.
ZendSoap WSDL accessor implementation uses the following type mapping between PHP and SOAP types:
Where xsd: is “http://www.w3.org/2001/XMLSchema” namespace, soap-enc: is a “http://schemas.xmlsoap.org/soap/encoding/” namespace, tns: is a “target namespace” for a service.
getType($type) method may be used to get mapping for a specified PHP type:
1 2 3 4 5 6 7 8 9 10 11 12 | ...
$wsdl = new Zend\Soap\Wsdl('My_Web_Service', $myWebServiceUri);
...
$soapIntType = $wsdl->getType('int');
...
class MyClass {
...
}
...
$soapMyClassType = $wsdl->getType('MyClass');
|
addComplexType($type) method is used to add complex types (PHP classes) to a WSDL document.
It’s automatically used by getType() method to add corresponding complex types of method parameters or return types.
Its detection and building algorithm is based on the currently active detection strategy for complex types. You can set the detection strategy either by specifying the class name as string or instance of a Zend\Soap\Wsdl\ComplexTypeStrategy implementation as the third parameter of the constructor or using the setComplexTypeStrategy($strategy) function of Zend\Soap\Wsdl. The following detection strategies currently exist:
addComplexType() method creates ‘/definitions/types/xsd:schema/xsd:complexType’ element for each described complex type with name of the specified PHP class.
Class property MUST have docblock section with the described PHP type to have property included into WSDL description.
addComplexType() checks if type is already described within types section of the WSDL document.
It prevents duplications if this method is called two or more times and recursion in the types definition section.
See http://www.w3.org/TR/wsdl#_types for the details.
addDocumentation($input_node, $documentation) method adds human readable documentation using optional ‘wsdl:document’ element.
‘/definitions/binding/soap:binding’ element is used to signify that the binding is bound to the SOAP protocol format.
See http://www.w3.org/TR/wsdl#_documentation for the details.
toXML(), toDomDocument() and dump($filename = false) methods may be used to get WSDL document as an XML, DOM structure or a file.
| [1] | ‘tns:’ namespace is defined as script URI (‘http://’ .$_SERVER[‘HTTP_HOST’] . $_SERVER[‘SCRIPT_NAME’]). |
| [2] | ‘http://’ .$_SERVER[‘HTTP_HOST’] . $_SERVER[‘SCRIPT_NAME’] |
| [3] | By default Zend\Soap\Wsdl will be created with the Zend\Soap\Wsdl\ComplexTypeStrategy\DefaultComplexType class as detection algorithm for complex types. The first parameter of the AutoDiscover constructor takes any complex type strategy implementing Zend\Soap\Wsdl\ComplexTypeStrategy\ComplexTypeStrategyInterface or a string with the name of the class. For backwards compatibility with $extractComplexType boolean variables are parsed the following way: If TRUE, Zend\Soap\Wsdl\ComplexTypeStrategy\DefaultComplexType, if FALSE Zend\Soap\Wsdl\ComplexTypeStrategy\AnyType. |
The source code of this file is hosted on GitHub. Everyone can update and fix errors in this document with few clicks - no downloads needed.


cs1
- Default everything
- 5 points added
cs2
- Monotonic (less curvey)
- 5 points added (same as cs1)
- Default styling
cs3
- Denser grid (0.1 instead of 1/3)
- 5 points added
- Default styling
cs4
- 4 points added
- The first and last point are xLocked
cs5
- 4 points added
- The middle point is yLocked
- The first and last points are "safe" (unremovable)
cs6
- Changed the styling
- 5 points added


Anatomy of a Web Map
You can follow along here:
goo.gl/SxIe5q. Links are in blue boxes,
green is just emphasis.
basic principles of web mapping (and some history)
plus exceptions!
100% open source Google-free stack
anatomy?
What is a web map?
skipping mobile devices
How did web maps come to be?
1996: Mapquest!
2005: And then there was Google Maps.
But what was the revolution?
The
tile.
All tiles
=
same size! 256x256 pixels
same boundaries
All these little tiles load
way faster than one big map.
This kind of map is colloquially called a
slippy map
zoom level
Zoom level 0: one tile for the world.
Zoom level 1: 4 tiles for the world.
Zoom level 2, 3, 4, 5
Zoom level 13
Tiles are rendered in advance (usually) then stored in a cache
http://tile.openstreetmap.org/4/2/6.png -- this is the name of the tile server.
http://tile.openstreetmap.org/4/2/6.png -- this is the z value, or the zoom level.
http://tile.openstreetmap.org/4/2/6.png -- This is the x/y value, or the place in the grid where the tile lives.
Google maps use Mercator projection.
A collection of raster tiles makes up what we call the map's base layer.
data layers or content layers or feature layers
vector layers (point, line, polygon)
Filetypes: GIS uses
shapefiles, but web maps prefer
KML, or more recently,
GeoJSON
Exceptions
Exception #1: Tiles are always rasters EXCEPT when they're not.
layers, geometries, and feature attributes from any datasource into individual vector tiles
Exception #2: Can’t interact with features on a raster, but...
different map projections (in the browser!)
sta.mn/jfs
Where do I start?
Do I need to make my own custom tiles?
Do I need a content layer?
No? Put all your data into the tiles, possibly using UTFGrid for interactivity
Yes? Convert a Shapefile to GeoJSON with
OGRE or write your own GeoJSON with
geojson.io
Finally,
CartoDB takes care of almost all of this for you!
Thank you and happy mapping!


Next: Type Relationships, Previous: Types, Up: Types
Information about type usage is located in the sections specified in Figure~4–1. Figure~4–7 lists some classes that are particularly relevant to the object system. Figure~9–1 lists the defined condition types.
Section Data Type Classes Object System types Slots Object System types Objects Object System types Generic Functions and Methods Object System types Condition System Concepts Condition System types Types and Classes Miscellaneous types Syntax All types—read and print syntax The Lisp Printer All types—print syntax Compilation All types—compilation issues
Figure 4–1: Cross-References to Data Type Information


This challenge is part of a tutorial track by MyCodeSchool and is accompanied by a video lesson.
You are given the pointer to the head node of a linked list and you need to print all its elements in reverse order from tail to head, one element per line. The head pointer may be null meaning that the list is empty - in that case, do not print anything!
Input Format
You have to complete the void ReversePrint(Node* head)
method which takes one argument - the head of the linked list. You should NOT read any input from stdin/console.
Output Format
Print the elements of the linked list in reverse order to stdout/console (using printf
or cout
) , one per line.
Sample Input
1 --> 2 --> NULL
2 --> 1 --> 4 --> 5 --> NULL
Sample Output
2
1
5
4
1
2
Explanation
1. First list is printed from tail to head hence 2,1
2. Similarly second list is also printed from tail to head.
Video lesson


Silence of the Klaw: Trauma and Emotional Processing
Teenage trauma may help explain Kawhi Leonard's lack of emotionality.
by Josh Gonzales M.A.Josh Gonzales M.A.
Trauma
THE BASICS
On November 20, 2019, the Los Angeles Clippers and Boston Celtics played an epic regular-season game with an intense playoff atmosphere.
 It was a great play made by an all-world talent.
Remarkably, as great as that play was, all everyone seems to want to talk about is his instant reaction.
Or more accurately, the lack thereof.
As you can see in the clip above, Leonard barely reacts after making the game-saving play. He calmly walks off the court, barely looking anyone in the eye. In his post-game interview, Kawhi remains monotone. You can’t tell if he just won a playoff atmosphere battle or just ate a decent bowl of cereal.
Media members gave a soft chuckle at his response, but this is an opportunity to look at something deeper. Let’s ask why Kawhi might have a problem emoting. To do so, let’s talk about a formative event in his teenage years.
The event
Kawhi’s father, Mark, used to own a Compton car wash. Kawhi would work there on weekends and during the summer. On January 18, 2008, Mark was shot and murdered on those very same business grounds. Kawhi was only 16 years old at the time.
NBA.com recently put out an article specifying the details of the crime. Police still haven’t solved the case. And while Kawhi decided to play basketball in a high school game barely a day after his father’s death, he’s likely still dealing with the after-effects of that trauma now.
Trauma and Emotional Processing
Research shows that childhood trauma has a lasting impact on an adult’s life. That impact can include changes to someone's ability to process emotions. A study by Marusak, Martin, Etkin and Thomason provided evidence that trauma-exposed youth were less able to regulate emotional conflict. They found evidence that:
"Aberrant amygdala response to emotional conflict was related to diminished reward sensitivity”
In other words, rewards drew less of a response.
Sound like someone you know?
Silence of the Klaw
I’m not saying this is the reason Kawhi Leonard reacts the way he does. Accounts from Leonard’s friends and family express he was always more reserved. But it’s one more data point to help us understand one of the NBA’s most mysterious megastars.
We expect NBA athletes to be showmen, especially those we recognize as perennial all-stars. Sport is an entertainment product, after all. That’s how endorsements are struck.
But this gives us reason to empathize with Kawhi's lack of emotionality, and reminds us that even though a human can be resilient and thrive after trauma, they still went through that trauma. They still have to deal with the effects.
Hopefully, we can all use this knowledge to be a little more understanding of the Klaw, and anyone else who’s suffered a traumatic event, in the future.
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This is a post. Rename the file and replace it with a real post.
Paragraph one is here! It’s a quite excited paragraph. It wants to be paragraphing.
Paragraph two is rather more sedentary. It sits happily but doesn’t get all that excited.
Another graf!
Today's color is:
Updated Tuesday, January 9, 2018


INTRODUCTION
Mind-Benders is a test of wits and logic. The event involves no syllabus or pre-requisite knowledge. The event will solely test the student’s logical
reasoning, analytical thinking abilities , problem-solving capabilities and co-ordination skills.
PUT YOUR THINKING CAP ON .
Rules:
1. This is a team event. Students should participate in teams of two members of same squad.
2. Students of different institutions can form a team but of same squad.
There are two squads:
JUNIOR SQUAD - for students of class 7 to 10.
SENIOR SQUAD - for student of class 11 and above including college student.
3. The event will be in form of pen-paper quiz. The question will have various sections like maths, puzzles, reasoning etc.
4. It will consist of single choice correct, multiple choice correct, paragraph and a very few subjective questions.
5. Each section has its own marking scheme.
6. Use of any type of electronic gadgets are strictly prohibited during the test.
QUESTIONS - 30 TIME – 1 HOUR
Venue and Timing:
Day and Date :Time :Venue :
Important Declaration:
1. Please keep checking the Celesta app, website and Celesta, IIT Patna facebook page for any future updates.
2. The rules can change without prior notification.
3. In case of any dispute, the decisions made by the organising committee and judges are final and binding.