CONFIG_DATA(1) Perl Programmers Reference Guide CONFIG_DATA(1) NAME config_data - Query or change configuration of Perl modules SYNOPSIS # Get config/feature values config_data --module Foo::Bar --feature bazzable config_data --module Foo::Bar --config magic_number # Set config/feature values config_data --module Foo::Bar --set_feature bazzable=1 config_data --module Foo::Bar --set_config magic_number=42 # Print a usage message config_data --help DESCRIPTION The "config_data" tool provides a command-line interface to the configuration of Perl modules. By "configuration", we mean something akin to "user preferences" or "local settings". This is a formalization and abstraction of the systems that people like Andreas Koenig ("CPAN::Config"), Jon Swartz ("HTML::Mason::Config"), Andy Wardley ("Template::Config"), and Larry Wall (perl's own Config.pm) have developed independently. The configuration system emplyed here was developed in the context of "Module::Build". Under this system, configuration information for a module "Foo", for example, is stored in a module called "Foo::ConfigData") (I would have called it "Foo::Config", but that was taken by all those other systems mentioned in the previous paragraph...). These "...::ConfigData" modules contain the configuration data, as well as publically accessible methods for querying and setting (yes, actually re-writing) the configuration data. The "config_data" script (whose docs you are currently reading) is merely a front-end for those methods. If you wish, you may create alternate front-ends. The two types of data that may be stored are called "config" values and "feature" values. A "config" value may be any perl scalar, including references to complex data structures. It must, however, be serializable using "Data::Dumper". A "feature" is a boolean (1 or 0) value. USAGE This script functions as a basic getter/setter wrapper around the configuration of a single module. On the command line, specify which module's configuration you're interested in, and pass options to get or set "config" or "feature" values. The following options are supported: module Specifies the name of the module to configure (required). feature When passed the name of a "feature", shows its value. The value will be 1 if the feature is enabled, 0 if the feature is not enabled, or empty if the feature is unknown. When no feature name is supplied, the names and values of all known features will be shown. config When passed the name of a "config" entry, shows its value. The value will be displayed using "Data::Dumper" (or similar) as perl code. When no config name is supplied, the names and values of all known config entries will be shown. set_feature Sets the given "feature" to the given boolean value. Specify the value as either 1 or 0. set_config Sets the given "config" entry to the given value. eval If the "--eval" option is used, the values in "set_config" will be evaluated as perl code before being stored. This allows moderately complicated data structures to be stored. For really complicated structures, you probably shouldn't use this command-line interface, just use the Perl API instead. help Prints a help message, including a few examples, and exits. AUTHOR Ken Williams<EMAIL_ADDRESS>COPYRIGHT Copyright (c) 1999, Ken Williams. All rights reserved. This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself. SEE ALSO Module::Build(3), perl(1). perl v5.14.2 2014-09-30 CONFIG_DATA(1)


Plot ground tracks and orbits for any number of Earth satellites simultaneously in either "Mission Control" or spherical format. Sunlit side shows colored relief profile, night side shows light sources viewed from space. Get up-to-date TLE parameter sets with one click from celestrak.com or other web sites.


Functions | |
| int | sqlo_get_oci_handle (int sqloh, void *ocihp, sqlo_oci_handle_types_e type) |
| Get the specified OCI handle. | |
| int | sqlo_get_db_handle (sqlo_stmt_handle_t sth) |
| Return the database handle of a statement handle. | |
| int | sqlo_set_blocking (sqlo_db_handle_t dbh, unsigned int on) |
| Set OCI blocking mode on/off. | |
| int | sqlo_get_blocking (sqlo_db_handle_t dbh, unsigned int *blocking) |
| Get OCI blocking mode. | |
| int | sqlo_break (sqlo_db_handle_t dbh) |
| Abort all operations in non-blocking mode. | |
| int | sqlo_set_prefetch_rows (sqlo_stmt_handle_t sth, unsigned int nrows) |
| Set the prefetch row attribute for a statement. | |
| int | sqlo_server_version (sqlo_db_handle_t dbh, char *bufp, unsigned int buflen) |
| Get the server version string. | |
| int | sqlo_get_stmt_state (sqlo_stmt_handle_t sth) |
| Get the state of the statement. | |
| const char * | sqlo_get_stmt (sqlo_stmt_handle_t sth) |
| Get the sql statement text for the statement handle. | |
| int | sqlo_get_ocol_dtype (sqlo_stmt_handle_t sth, unsigned int pos) |
| Get the datatype of a column in the select list. | |
| int | sqlo_trace (sqlo_db_handle_t dbh, int on) |
| Switches Oracle trace on/off. | |
| int | sqlo_print (sqlo_stmt_handle_t sth) |
| Print info about the statement to stdout. | |
| int | sqlo_register_int_handler (int *handle, sqlo_signal_handler_t signal_handler) |
| Register a signal handler for interrupts. | |
| int | sqlo_clear_int_handler (int handle) |
| Clear an interrupt handler. |
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Abort all operations in non-blocking mode. This call performs an immediate (asynchronous) abort of any currently executing OCI function that is associated with a connection. If the connection is in blocking mode, SQLO_SUCCESS is returned without doing an abort. The cursor in "SQLO_STILL_EXECUTING" status is closed.
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Clear an interrupt handler.
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Get OCI blocking mode. Returns the the blocking mode.
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Return the database handle of a statement handle.
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Get the specified OCI handle. You can get the oci handles here, if you want to call other OCI functions.
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Get the datatype of a column in the select list.
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Get the sql statement text for the statement handle.
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Get the state of the statement.
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Print info about the statement to stdout.
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Register a signal handler for interrupts. Because oracle catches SIGINT, you can register here a handler, which is called by oracle, when SIGINT is catched.
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Get the server version string. Returns the server version string which might look like this: Oracle8i Enterprise Edition Release <IP_ADDRESS>.0 - Production With the Partitioning and Java options PL/SQL Release <IP_ADDRESS>.0 - Production.
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Set OCI blocking mode on/off. By default a database connection is in blocking mode. This means the call does not return until the task is finished. With this function you can change to non-blocking mode. In this case some functions can return SQLO_STILL_EXECUTING. The functions are:
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Set the prefetch row attribute for a statement. This functions sets the oci attribute OCI_ATTR_PREFETCH_ROWS to the given value.
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Switches Oracle trace on/off. Use this to switch the Oracle trace facility (tkprof) on or off.
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First Avenue & 7th Street Entry
701 North 1st Avenue
Minneapolis, MN 55403
Probably the best venue of all time in the history of time and I'm not biased at all**I'm totally biased
Nicollet Mall
1010 Nicollet Mall
Minneapolis, MN 55403
This is just speculation, but if you are going to run into Prince in downtown Minneapolis it's probably going to be here.111 North 5th St
Minneapolis, MN 55403
Booooooooooo, Mill City Nights is owned by AEG Live (Anschutz Entertainment Group) the bajillion dollar LA corporation that also runs such venues as the Target Center (charming). Basically Mill City Nights is their "down-home" rock club, competing with locally-owned business. Also, funny story, when Mill City Nights opened in 2012 it was called The Brick.  I'm not a one to shush people, but this acoustically challenged space brings out the worst in me. They have good fries though.416 Cedar Avenue
Minneapolis, MN 55454
The Cedar is a very chill venue. So chill that it is staffed by volunteers, how chill is that, people just work there for free. The space is a little bit like standing in a highschool gym but we don't hold that against them. As a short and perpetually tired person, the Cedar's seated shows are my favorite thing since staying home and watching nextflix.917 Cedar Avenue
Minneapolis, MN 55404
One time I saw Andrew WK there and there was free Dos XX all night long, a contortionist performed and a man held his breath in water tank for a really long time. (this is a true story, not a dream I had)


This page gives the API for the custom Sphinx extensions used in Astropy.
This sphinx extension adds a tools to simplify generating the API documentationfor Astropy packages and affiliated packages.
This directive takes a single argument that must be module or package. Itwill produce a Documentation section named “Reference/API” that includes the docstring for the package, an automodsumm directive, and an automod-diagram if there are any classes in the module.
It accepts the following options:
- :no-inheritance-diagram:
If present, the inheritance diagram will not be shown even if the module/package has classes.
- :skip: str
This option results in the specified object being skipped, that is the object will not be included in the generated documentation. This option may appear any number of times to skip multiple objects.
- :no-main-docstr:
If present, the docstring for the module/package will not be generated. The function and class tables will still be used, however.
- :headings: str
Specifies the characters (in one string) used as the heading levels used for the generated section. This must have at least 2 characters (any after 2 will be ignored). This also must match the rest of the documentation on this page for sphinx to be happy. Defaults to “-^”, which matches the convention used for Python’s documentation, assuming the automodapi call is inside a top-level section (which usually uses ‘=’).
This extension also adds a sphinx configuration option automodapi_toctreedirnm. It must be a string that specifies the name of the directory the automodsumm generated documentation ends up in. This directory path should be relative to the documentation root (e.g., same place as index.rst). It defaults to ‘_generated’
This sphinx extension adds two directives for summarizing the public members of a module or package.
These directives are primarily for use with the automodapi extension, but can be used independently.
This directive will produce an “autosummary”-style table for public attributes of a specified module. See the sphinx.ext.autosummary extension for details on this process. The main difference from the autosummary directive is that autosummary requires manually inputting all attributes that appear in the table, while this captures the entries automatically.
This directive requires a single argument that must be a module or package.
It also accepts any options supported by the autosummary directive- see sphinx.ext.autosummary for details. It also accepts two additional options:
- :classes-only:
If present, the autosummary table will only contain entries for classes. This cannot be used at the same time with :functions-only: .
- :functions-only:
If present, the autosummary table will only contain entries for functions. This cannot be used at the same time with :classes-only: .
- :skip: obj1, [obj2, obj3, ...]
If present, specifies that the listed objects should be skipped and not have their documentation generated, nor be includded in the summary table.
This directive will produce an inheritance diagram like that of the sphinx.ext.inheritance_diagram extension.
This directive requires a single argument that must be a module or package. It accepts no options.
Note
Like ‘inheritance-diagram’, ‘automod-diagram’ requires graphviz to generate the inheritance diagram.


# File test/unit/standard_user_test.rb, line 20 def test_accessible_bodysize_records user = users(:standarduser) records = user.accessible_bodysize_records assert_equal 2, records.length, "Fixture contain two records this user should be able to access" records.each do |record| assert((record.creator == user || record.approved), "User is record's creator, or record is approved") end end


|
Log4j 1.2.11 | ||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
See:
Description
| Class Summary | |
| ListVsVector | Compares the performance of looping through a list versus a Vector. |
| NewVsSetLen | This program compares the cost of creating a new StringBuffer and converting it to a String versus keeping the same StringBuffer, setting its size to zero and then converting it to String. |
| NOPWriter | Extends Writer with methods that return immediately
without doing anything. |
| NullAppender | A bogus appender which calls the format method of its layout object but does not write the result anywhere. |
| SystemTime | Measures the time required to make a System.currentTimeMillis() and Thread.currentThread().getName() calls. |
Package to measure the performance of the different log4j components.
The
org.apache.log4j.performance
package is intended
for internal use only. Consequently, the classes in this
package are not included in the log4j.jar file.
|
Log4j 1.2.11 | ||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


This initial version of the widget illustrates how a self-contained AngularJS widget can be added to an existing web page.
The only integration points are:
In this version of the widget, the locations for which we are displaying the weather are hard-coded in the widget code.
For the next version, we would like to allow these locations to be specified in the HTML template.


To gather insights for our new project, we needed to research different areas and topics related to or taken out of the context of the project. With these insights we can create How Might We questions during the ideation phase of the project.
As we split out to investigate individually a topic or focus, which we discussed with the group. Mine was the 2D print house my dad works at. It is one of the largest 2D print houses in the benelux, so with this knowledge, I am assuming that they know what they are doing!
I made a research document where I documented the process of the research. Within this is the approach of the interview that was conducted.
I interviewed my dad one evening. We sat down and I started the 'interview' but it felt more as a conversation about his work at the company. Within this conversation, all of the desired questions were asked that were written down inside of the research document. It felt very natural talking to him this way. I think that was because of the amount of times that I have already conducted a similar kind of interview.
From this research, I gathered insights that are also relevant for the 3D metal printing businesses. Some key insights from the research are the following:
Once I did the interview, I received feedback in the following weeks to better this research(document). From the execution to the conclusion was not so much of a bridge, so there was no reasoning on why some of the conclusions were made. With the gathered feedback, I added a step between the execution and conclusion called results. Here I analyze the answers given and try to answer the research question which I was set out to answer.
The technique of interviewing has already been very much in my system as I am an ICT & Media Design student. So on that front, I didn't learn too much. I did learn a lot of my dad and the processes that are happening at print houses. This is good for the project as these insights will help in later stages of the project.
Through this research, which started out with the group, I defined useful research questions to be answered. One such question was answered with the conclusion of this interview wherein I independently selected the method and executed it to gather insights for the group project.
I created the research document and conducted the interview myself.


With great power comes great responsibility
Go web! Fly! Up, up, and away web! Shazaam! Go! Go! Go web go! Tally ho.
The itsy bitsy spider climbed up the water spout. Down came the Goblin and took the spider out.
Green Goblin We are who we choose to be... now, CHOOSE.
- You have a knack for getting in trouble.
- You have a knack for saving my life. I think I have a superhero stalker.
- I was in the neighborhood.
Spider Man will always have enemies. I can't let you take that risk.
Whatever life holds in store for me, I will never forget these words: "With great power comes great responsibility."
This is my gift, my curse.
Who am I? I'm Spiderman.


I am a MS student at Mechanical Engineering, Massachusetts Institute of Technology, with my interest focusing on robotics, wearable devices and computational mechanics. Before that, I did my bachelor at Department of Engineering Mechanics, Tsinghua University.
Email  /  Google Scholar
I have a mixed background including mechanics, electronic devices, robotics and intelligent systems. The fowllowings are some projects I have done in recent years.
This project was supervised by Prof. Sheng Xu at UC San Diego and the main cooperators are Hongjie Hu, Hao Huang and Mohan Li. My main contributions were developing the post-processing code for elastography, optimizing the probe design by simulation and experiment, and conducted demontrative experiments. A real-time wearable ultrasound system was demonstrated with ability to map the strain/modulous distribution of tissue 4-5 cm under the skin.
This project was supervised by Prof. Xue Feng and Prof. Yinji Ma at Tsinghua University. We Proposed a theoretical model to study the impact of arterial wall on the measured blood pressur, which was in accordance with our the simulation results of ABAQUS and the experiment results from liturature. The paper revealed that the blood pressure of arteriosclerostic patients cound be overestimated, which may help to improve the accuracy of cuff-based blood pressure measurement in future.
This project was a simple practice using an Arduino board, a logitech camera and a stepper motor. I and Zhuyou Hu designed and completed the project. We realized face recognition using Python, with which we further control the motor to follow the movement of face and make the face stay in the center of footage.
This project was supervised by Prof. Gangtie Zheng at Tsinghua University and the main cooperators are Yupu Lu, Yijie Wu and Shijie Zhu. Based on a 32-channel automatic harp, we designed a layered modular framework integrating both hardware and software for implementing real-time control protocol and machine learning algorithms, which may bring more expressiveness for human-machine collaborative music performances.
This project aims to optimize the neck mechanism of a robot to realize a high degree of freedeom and a high speed as well as visulizing/simulating the movement of the neck mechanism in real time. The project was done at Purdue Univerisity under the supervision of Prof. Voyles.


Telluride Film Festival 1994 (Part 2 of 2) Film reviews by Wayne Citrin Copyright 1994 Wayne Citrin
MONDAY, SEPTEMBER 5
AN UNFORGETTABLE SUMMER (Romania/France, 1994, 80m)
Although the festival went all the way through Monday evening, and was an opportunity to catch some of the films we has missed, we really only had time for one film since Deborah had work the next day and we wanted to get home at a decent hour. We chose the film AN UNFORGETTABLE SUMMER, which was described by one of the festival staff as "one of the jewels of the festival." He was also enthusiastic about the short, which I'll describe later. AN UNFORGETTABLE SUMMER is an historical piece about a Romanian army captain and his wife in the 1920s. In order to protect his wife from the advances of his commanding officer, the captain, a staff officer at the time, requests a transfer, and is transferred to a bleak border post in the Romanian east. He and his wife adapt, but they eventually find themselves in a situation where the moral solution is the one that will destroy them. The film shows how two decent, honest people can find themselves in a no-win situation. The film is presented on a small scale and, ironically, is told through the eyes of the young son, who simply remembers this as "an unforgettable summer," possibly the best summer he ever had. I'd say that this is one of the four best things we saw: ONCE WERE WARRIORS was the best, then LADYBIRD, LADYBIRD, and then a toss-up between this and MURIEL'S WEDDING.
Before AN UNFORGETTABLE SUMMER, we were shown the hilarious and wonderfully strange English short "Franz Kafka's IT'S A WONDERFUL LIFE" (England, 1994, 25m). In the film, we see Kafka, in his room at the top of a castle, attempting to write "Metamorphosis" on Christmas Eve, while dealing with disturbances by his various neighbors. Kafka wrestles with the decision of exactly what Gregor Samsa is transformed into ("a banana?"), and eventually learns that he has friends who love him. I chuckle just thinking about it.
Here's a quick list of the other things that played at Telluride this year.
TRIBUTE TO JUDY DAVIS
This included a showing of THE NEW AGE (described in part 1), plus a compilation of Davis clips. I heard that Davis seemed quite shy, and was relieved to get her medallion and disappear. Apparently she doesn't like a lot of her early work.
 Selected by John Simon, the 1994 Guest Director of the festival.
LONESOME (USA, 1928, 69m)
Apparently the most requested film of the festival, although I didn't speak to anyone who had seen it. A silent movie, and a love story.
WRITING FOR HITCH
Live conversations with two screenwriters who worked for Hitchcock, along with excerpts.
TRIBUTE TO KEN BURNS
A tribute to Ken Burns, director of the PBS documentary THE CIVIL WAR, and the new 18-hour documentary BASEBALL. Everyone who saw him said how wonderful he was. The tribute included the fifth part of the nine-part series (it concentrates on the Negro leagues and is apparently the part he's most proud of) and the rest of the documentary premiered on local Telluride cable TV in 4-hour segments over the course of the festival. I caught the fourth part (on Babe Ruth and the 1920s) and it was pretty good. This will appear on PBS later this month.
VANYA ON 42ND STREET (USA, 1994, 115m)
A new film by Louis Malle, with Andre Gregory and Wally Shawn. A sequel to MY DINNER WITH ANDRE? Not quite - it's a film about the rehearsals of a production of Uncle Vanya on Broadway. It sounded intriguing, but I couldn't work it in.
THE EASY LIFE (Italy, 1962, 105m)
Another choice of John Simon. Didn't see it, and didn't speak to anyone who did.
TRIBUTE TO HARRIET ANDERSON
A tribute to the Swedish actress who worked with Ingmar Bergman. Included a compilation and a "rare screening of the uncut, uncensored MONIKA." Didn't hear anything about it.
 Included a showing of the film AVENTURERA (1949, 95m). Didn't hear anything about it.
SILENCES OF THE PALACE (Tunisia/France. 1994, 127m)
A film about the lives of female servants in a privileged Tunisian family. I wanted to see it but couldn't fit it in. Heard it was good.
"Black Daisies for the Bride" (England, 1993, 50m)
TV film by British poet Tony Harrison. Shown with another short film "A Maybe Day in Kazakhstan" (England, 1994, 26m). Didn't hear anything about it.
FILMMAKERS OF TOMORROW: STUDENTS FILMMAKERS OF TOMORROW: RESUMES
A forum for films by aspiring directors - in the former case, film students, and in the later case, people from other positions. People seemed to like the program.
"Music for the Movies: Toru Takemitsu" (USA/France/Japan, 1994, 58m)
A documentary about the film music composer.
MONTAND (France, 1994)
A film biography of the actor.
ED WOOD MOVIES
Mini-retrospective of Ed Wood films, in conjunction with the showing of Tim Burton's ED WOOD. Films shown were GLEN OR GLENDA (USA, 1953, 61m) and PLAN 9 FROM OUTER SPACE (USA, 1959, 79m).
THE TRANSFORMATION OF THE WORLD INTO MUSIC (Germany 1994, 90m)
A new documentary by Werner Herzog on the Wagner festival in Bayreuth, Germany.
CROWS (Poland, 1994, 65m)
Film about a young neglected girl who kidnaps another girl in order to be the mother she never had. Heard good thing about it.
"The Parrot" (USA, 1994, 20m)
New film by director Errol Morris (THE THIN BLUE LINE) about a parrot that may have witnessed a murder. Shown with CROWS. Supposed to be good. Morris also demonstrated his INTERROTRON system, a new system to improve interviews by projecting the interviewer's image on the camera lens, thus causing the subjects to look directly into the camera rather than off-camera.
THE BUDDY FACTOR (USA, 1994, 98m)
A comedy about a film grad who becomes an assistant to a studio executive. I wanted to see it but couldn't fit it in. People liked it, and were impressed by the fact that it was shot in 18 days, but some said that it was too much like THE PLAYER. I hope it gets theatrical release, so I can see it.
"Flat" (Mexico, 1994, 14m)
Short film shown with THE BUDDY FACTOR.
MEMORIES AND DREAMS (Australia, 1994, 58m)
Animated reflection on the life of a Czech journalist who emigrates to Australia.
 For a long time, nobody knew who was writing the word, which became a cultural icon. It sounded interesting.
DUST OF LIFE (France, 1994, 87m)
A story about Amerasian orphans in Vietnam, by Rachid Bouchareb (dir. BATON ROUGE and CHEB). I heard good things about it, and wanted to see it, but couldn't fit it in.
WE, CHILDREN OF THE 20TH CENTURY (Russia, 1994, 85m)
A documentary on marginal children in St. Petersburg by Vitali Kanevski, director of FREEZE DIE COME TO LIFE. Sounded interesting but I couldn't fit it in.
"Zinky Boys Go Underground" (England, 1994, 25m)
Showed with WE, CHILDREN OF THE 20TH CENTURY.
ONE FINE DAY (Italy, 1969, 105m)
Another selection by John Simon. More interesting was the short that showed with it:
"Bris Ads" (Sweden, 1951, 9m)
"Ingmar Bergman directed these TV soap commercials, never before seen in the US."
ARIZONA DREAM (France/USA, 1993, 120m)
Supposedly a big hit in Europe, this is the first American film by Yugoslavian director Emir Kusturica (WHEN FATHER WAS AWAY ON BUSINESS, TIME OF THE GYPSIES). People liked it, but said that it was very strange. What would you expect with a cast that includes Johnny Depp, Jerry Lewis, Faye Dunaway, and Lili Taylor? I wanted to see it, but couldn't fit it in. It'll probably play in art theaters, so I'll get a chance to see it.
"Texan" (USA, 1994, 30m)
Shown with ARIZONA DREAMS. Treat Williams' directorial debut.
DEDEE D'ANVERS (France, 1947, 95m)
Part of a Simone Signoret retrospective. A new print.
CASQUE D'OR (France, 1952, 96m)
Another Signoret film. I heard that the new print looked great. Popular enough to merit a repeat showing.
ROOM AT THE TOP (England, 1959, 117m)
Signoret won a Best Actress Oscar for her English-speaking role in this film.
BULLETS OVER BROADWAY (USA, 1994)
The world premiere of Woody Allen's new film; a surprise entry not in the original program. I didn't see it since I figured I'd have the chance to see it shortly. I heard mixed things about it. Some people thought it was very funny, while other people thought that the joke was kind of thin for a full-length movie. About the Mafia financing a Broadway musical in the 1920s.
ED WOOD (USA, 1994)
Another surprise entry, the world premiere of Tim Burton's new film on the cult director, starring Johnny Depp. Again, I didn't bother to see it, since it will be playing theaters shortly, and since it showed fairly late in the festival, I didn't get a chance to talk to anybody who had seen it.
-- Wayne Citrin<EMAIL_ADDRESS><EMAIL_ADDRESS>.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Weather
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--- layout: post title: LET BOYS BE BOYS - BUT LET THEM BE GENTLEMAN TOO date: 2009-12-06 10:04:44.000000000 -08:00 type: post parent_id: '0' published: true pd: '' status: publish categories: - Early Childhood Issues - Middle School Issues tags: - behavior management - early childhood - manners author: login: k email: k@k display_name: mcary first_name: '' last_name: '' ---
I am the mother of three boys, ages three, five and eight. They are constantly pushing each other around and fighting to be first at whatever they do. I feel like I’m a general in the army that has to go around shouting orders all the time. Any ideas to help me get some peace of mind?
Are your sons gentlemen? It’s a word that we don’t use too often these days. The way we raise our boys today will determine the types of men that we have in our society in a decade or so. With more equality for woman and girls, we are now asking less of our young men and boys. Each day I see boys, and girls too for that matter, that are not held accountable for their actions. The older I get the more it scares me. All parents need to teach courtesy, manners and respect for others as a life skill.
Some might argue that, "ladies first," is a phrase from the past. Maybe so, but as a parent and teacher, nothing pleases me more than seeing a boy with manners. Proper courtesy to others is a reflection of a family’s values. Teaching manners instills both a respect for others (including siblings), and respect for oneself, which in turn will help alleviate the impetuous behavior you describe. Do your sons practice the behaviors listed below? If not, perhaps it’s time to teach them these:
1. Open the door for others, especially women, mothers with strollers and older people;
2. Shake hands and look people in the eye when greeting them;
3. Assist seniors (grandparents, etc.) with getting in or out of the car and carrying groceries;
4. Take off hats during the National Anthem (any country’s) and Pledge of Allegiance;
5. Know not to interrupt adults or peers when they are talking and instead listen and have respect for what others have to say, even if they have a different point of view;
6. Accept responsibility for actions, good and bad, and;
7. Use "please," "thank you," and "excuse me" as appropriate.
Good manners should be an unconditional parental expectation. The best way to teach manners is to model them daily yourself. Although children often learn best by emulating what they see, it’s also important to make clear what your expectations are. Don’t wait for misbehavior to tell your boys what you expect, tell them when things are calm, tell them when they are alone, and tell them as a group. Without "nagging," tell them often, and praise them when they exhibit good manners. Children want attention and will strive to get it. As you notice and praise one of the boys when you catch them doing the right thing, the others will catch on. If they get more attention when they are praised than when they are corrected, the good behavior will become the norm.
Of course all of the above goes for girls too. Although when they get older they’ll appreciate, "ladies first." You can count on it!


--- title: CEIC Design System description: A design system for the Cannabis Equity Illinois Coalition, created by Code for Chicago layout: default home: true ---


Write a function to detect palindrome. A palindrome is a string that is spelled the same both forwards and backwards, usually without considering punctuation or word breaks and return true or false.
For example:
palindromes('racecar') // true
palindromes(‘jungle') // false
Enter the text or word you want to check if it's palindrome or not:


GANSynth is a deep neural network that synthesizes audio of musical instrument notes.
GANSynth
Time for 1 sample:
Log Magnitude
Instantaneous Frequency Start Stop Total Leaked Memory:
Total Leaked Memory:


Innovative software engineer offering 8+ years of experience in the full software development lifecycle, from concept through delivery of web and mobile oriented solutions. Expert in advanced methodologies, tools and processes contributing to the design and rollout of software applications
I have skills on backend applications, user experience, user interface and Dev Ops. I have experience with HTML, CSS (Sass, Less), Javascript, AngularJS, Node.JS, C# (ASP.NET) and AWS.
I focus on solving problems and provide strongly structured projects applying SOLID principles and the best practices for each technology. Passionate working on projects focused on new technologies
Provide object-oriented software design; developing and supporting a CMS web solution. Autoweb is an automotive media and marketing services company leader in North America.
Successfully delivered a high-performed web solution that provides the employees manage their resources communication in a easy and efficient way
Lead front end developer designing and implementing mobile and desktop web solutions. Completed eight major projects, working closely with agile development team to develop, test and maintain Web and mobile-based software applications.
Desktop applications and Front-end websites development using Java, Javascript, PHP, and many other web technologies.
Teach about web design using HTML5/CSS3 and Javascript
Advanced Node.js Basics React.js Practical Design Patterns in Javascript Javascript Best Practices C# Fundamentals Understanding Machine Learning Asynchronous Programming in .NET Developer to Architect Mastering Flux and Redux Building Offline Web Apps with Service Worker Progressive Web App Fundamentals Google Analytics for Creative Professionals
Universidad Mariano Gálvez de Guatemala
Universidad Mariano Gálvez de Guatemala
Colegio Mixto Centroamericano


What's new in 0.7 ?
use latest official ant (no more a patched version)
refactor antcontrib usage, antcontrib is now considered as a dependency of easyant-core
add the capabilty to override target/phases defined in module.ivy (override.module.ant)
enhanced multimodule support
full support for all standard build phases
full support for Ivy descriptor "extends"
build-scoped repository should allow overwrites (#74)
meta-build: better support for custom ivysettings.xml (#75)
use two cache instance (one for easyant plugins/buildtypes, one for project)
use cache by default instead of retrieving in lib directory
simplify version management : uses revision attribute in module.ivy instead of a specific property (#81)
simplify syntax of easyant tags, plugins/buildtypes now support two ways to be imported (#84):
using mrid
using exploded style
support Shortcut on buildtypes / plugins / skeletons in mrid style (#73)
make the help more helpful (#13) introduce new useful command line lines switches (listTargets, listPlugins, listPhases, listProps, describe)
add validation on easyant config files
refactor the repository structure : default plugins/buildtypes are now shipped in easyant-core.jar, additional plugins are now shipped in easyant-extra-plugins.jar (#80)
add support for provided artifacts (#83)
performance improvement
javadoc/scaladoc are no more imported in default buildtypes
enhanced clean cache mechanism (can now clean easyant-cache or project cache) (#79, #80)
add default skeleton for :
standard java application
standard java webapplication
add new plugins
a small webstart plugins (Thanks to Nicolas Gapaillard for the contrib !)
docbook plugin (#62)
cobertura coverage plugin / "abstract-coverage" support (#67)
a new build type for easyant plugin (simplify easyant plugin development) #85
improve skeleton plugin (#86)
add support for LICENSE/NOTICE files in package-jar / package-war plugins (#87)
support executable jar attributes in manifest plugin (#76)
several bugfix on
emma
cobertura
junit (#78)
javadoc (#77)
xooki / eadoc


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--- layout: registration permalink: /post_incorporation_services/ tab: registration title: Services sub_heading: POST INCORPORATION SERVICES ---
Vinod Kannan & Associates., Cost Accountant Firm assists startups in all statutory registration, licenses and permission necessary for starting a business in India such as Goods and Service Tax Registration, PAN registration, TAN Registration, MSME Registration, Profession Tax Registration, Deed registration, Import Export Code (IEC), ESI, PF, etc.
We also undertake complete compliance management advising on business setup and establishing systems and controls, accounting, auditing, statutory compliances.
We provide services relating to cancellation or modification of above registrations.


1.9 The math Module
The math module implements a number of mathematical operations for
floating-point numbers. The functions are generally thin wrappers
around the platform C library functions of the same name, so results
may vary slightly across platforms in normal cases, or vary a lot in
exceptional cases. Example 1-60 demonstrates the use of the math module.
Example 1-60. Using the math Module
File: math-example-1.py
import math
print "e", "=>", math.e
print "pi", "=>", math.pi
print "hypot", "=>", math.hypot(3.0, 4.0)
# and many others...
e => 2.71828182846
pi => 3.14159265359
hypot => 5.0
See the Python
Library Reference for a full list of functions.
|


The Digital Visualization Group is a regular meeting of UVA faculty, historians, graduate students, and others intererested in digital visualization using the tools developed at UVA's SHANTI Interactive. We meet in person in Alderman Library or you can join us via a Zoom video conference.
Zoom video conference
or call<PHONE_NUMBER> ID: 565 903 617


John Doe
Web designer at MDBootstrap
Warsaw, Poland
Some quick example text to build on the card title and make up the bulk of the card's content.
John's Achievements
John's Contributions
-
Questions 14
-
Answers 14
-
Submited projects 14
-
Pull requests 14
John's projects
Project name
Some quick example text to build on the card title and make up the bulk of the card's content.
Project name
Some quick example text to build on the card title and make up the bulk of the card's content.
Project name
Some quick example text to build on the card title and make up the bulk of the card's content.
Project name
Some quick example text to build on the card title and make up the bulk of the card's content.


{% extends 'base.html' %} {% block subtitle %}- Registration{% endblock %} {% block content %}
Web-based registration has been locked by the sysops. Please contact them for help or further information.


Source Code¶
Server¶
| Module: | server |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
pysotdashboard.
onMsgRun
(msg)¶ Runs the PySOT experiment and sends the result to client
Once the client send the parameters for the experiment to the server. All the required instance are initialized and the experiment begins. At the end of each evaluation the results are sent to the client.
While initializing the experiment if any exceptions is raised, by the dashboard. The error is sent to the client instead of crashing the server.
Parameters: msg (json) – Input parameter sent form client
Variables: - parsed_json – Parsed input message.
- new_obj – Instance of PySOTObject.
- pySOTObj – Dictionary containing the PySOT objects. Required to initialize the experiment.
- new_controller_object – Instance of ControllerObject
- controller – Instace of POAP Controller.
-
pysotdashboard.
render_homepage
()¶ Render the homepage of pySOT Web Dashboard
-
pysotdashboard.
sendingDict
(msg)¶ Sends the dictionary generated by PySOTDictionary :para msg: Not used :type msg: string
PySOT Dictionary¶
| Module: | pySOT_dictionary |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
class
pySOT_dictionary.
PySOTDictionary
¶ Generates a dictionary continuing all the methods/classes of PySOT
Each method in the class parses a different file in pySOT directory and extracts all the methods or classes from that file along with their default values. Then appends all of the extracted data to a dictionary with a unique key.
The names of methods or classes extracted are appended to the dictionary, instead of the objects. This is done because the final dictionary obtained is meant to be converted to json and objects can not be converted to json. The eval() method can be used to call objects using their string names stored in the dictionary.
Variables: - kernel_list – List of all kernel classes.
- tail_list – List of all tail classes.
- projection_list – List of user defined projection functions.
- delay_list – List of user defined delay functions.
- optimization_problem_dict – Dictionary of Optimization Problems.
- experimental_design_dict – Dictionary of Experimental Designs.
- surrogate_model_dict – Dictionary of Surrogate Models.
- adaptive_sampling_dict – Dictionary of Adaptive Sampling.
- strategy_dict – Dictionary of PySOT strategies.
- controller_dict – Dictionary of POAP controllers.
- obj – An instance of GetModuleClass used to extract all the information required to initialize the dictionaries.
-
adaptive_sampling_generate_dict
()¶ Initialize surrogate_model_dict with surrogate model in rbf.py file in pySOT directory.
By using the GetModuleClass instance, we obtain the dictionary of surrogate model’s. Then we fetches all the input arguments and their defaults values for each of the model object in a loop. The objects arguments and default values are then appended to the dictionary, with the model’s name attribute as the key.
-
controller_generate_dict
()¶ Initialize controller_dict with strategies in controller.py in POAP.
By using the GetModuleClass instance, we obtain the dictionary of controllers. It has to noted that there are classes in controller.py that are not controllers. Therefore they have to be removed from the dictionary. An assumption is made that all controllers will have the key work controller in their name and therefore all objects were filter based on this assumption.
Then all the input arguments and their defaults values for each of the controller object are fetched in a loop and appended to the dictionary, with the controller’s name attribute as the key.
-
delay_generate_list
()¶ Initializes delay_list with user defined delay function. By using the GetModuleClass instance, it feteches the list of all delay function in delay_function.py file.
-
experimental_design_generate_dict
()¶ Initialize experimental_design_dict with all experimental design in experimental_design.py file in pySOT directory.
By using the GetModuleClass instance, we obtain the dictionary of all optimization problems. Then we fetches all the input arguments and their defaults values for each of the design object in a loop. The objects arguments and default values are then appended to the dictionary, with the design’s name attribute as the key.
-
generate_dictionaries
()¶ Uses GetModuleClass class to initialize all dictionaries.
-
get_dict
()¶ Request the PySOT Dictionary
Returns: dict
-
kernel_generate_list
()¶ Initialize kernel_list with all kernels objects in PySOT. By using the GetModuleClass instance, it fetches the list of all kernel objects in kernels.py file.
-
optimization_problem_generate_dict
()¶ Initialize optimization_problem_dict with all optimization problems in test_problems in pySOT directory.
By using the GetModuleClass instance, we obtain the dictionary of all optimization problems. Then we fetches all the input arguments and their defaults values for each of the problem objects in a loop. The objects arguments and default values are then appended to the dictionary, with the problem’s name attribute as the key.
-
projection_generate_list
()¶ Initializes projection_list with user defined projection functions. By using the GetModuleClass instance, it fetches the list of all projection function in projection_function.py file.
-
strategy_generate_dict
()¶ Initialize strategy_dict with strategies in sot_sync_strategies.py in pySOT directory.
By using the GetModuleClass instance, we obtain the dictionary of strategies. Then we fetches all the input arguments and their defaults values for each of the strategy object in a loop. The objects arguments and default values are then appended to the dictionary, with the strategy’s name attribute as the key.
-
surrogate_model_generate_dict
()¶ Initialize surrogate_model_dict with surrogate model in rbf.py file in pySOT directory.
By using the GetModuleClass instance, we obtain the dictionary of surrogate model’s. Then we fetches all the input arguments and their defaults values for each of the model object in a loop. The objects arguments and default values are then appended to the dictionary, with the model’s name attribute as the key.
-
tail_generate_list
()¶ Initialize tail_list with all tail objects in PySOT By using the GetModuleClass instance, it fetches the list of all tail objects in tails.py file.
PySOT Object¶
| Module: | pySOT_object |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
class
pySOT_object.
PySOTObject
(parsed_json, class_dict=None)¶ Creates all object needed to initialize the PySOT experiment.
This class will generate Optimization Problem, Experimental Design, Surrogate Model and Adaptive Sampling. required to perform PySOT experiment.
Parameters: - parsed_json (dict) – All the object and their arguments that need to be initialized.
- class_dict (dict) – Dictionary produced by PySOTDictionary
Variables: - data – Instance of Optimization Problem
- exp_des – Instance of Experimental Design
- surrogate – Instance of Surrogate Model
- adapt_samp – Instance of Adaptive Sampling
- maxeval – Number of max evaluations
-
init_adaptive_sampling
(as_arguments)¶ Initialize Adaptive Sampling
This module receives a dictionary containing the name arguments of the adaptive sampling to be initialized. After confirming that the input adaptive sampling indeed exists in PySOT. It will initialize the adaptive sampling using the arguments provided and store the resulting object in self.adapt_samp.
Parameters: as_arguments (dict) – Name of and arguments of adaptive sampling. Raises: ValueError – If the adaptive sampling specified in input do not exist in current PySOT version.
-
init_experimental_design
(ed_arguments, dim)¶ Initialize Experimental Design
This module receives a dictionary containing the name arguments of the experimental design to be initialized. After confirming that the input experimental design indeed exists in PySOT. It will initialize the experimental design using the arguments provided and store the resulting object in self.exp_des.
Parameters: - ed_arguments (dict) – Name of and arguments of experimental design.
- dim (int) – Dimensions of optimization problem data set.
Raises: ValueError – If the experimental design specified in input do not exist.
-
init_optimization_problem
(op_arguments)¶ Initialize Optimization Problem
This module receives a dictionary containing the name of problem to be initialized along with its arguments. After confirming that the input problem indeed exists in PySOT. It will initialize the problem using the arguments provided and store the resulting problem in self.data.
Parameters: op_arguments (dict) – Name of and arguments of Optimization Problem. Raises: ValueError – If the optimization problem specified in input do not exist in current PySOT version.
-
init_surrogate_model
(sm_arguments)¶ Initialize Surrogate Model
This module receives a dictionary containing the name arguments of the surrogate model to be initialized. After confirming that the input surrogate model indeed exists in PySOT. It will initialize the surrogate model using the arguments provided and store the resulting object in self.surrogate.
Parameters: sm_arguments (dict) – Name of and arguments of Surrogate Model. Raises: ValueError – If the Surrogate Model specified in input do not exist.
-
return_values
()¶ Request the PySOT object. The method will return a dictionary containing the objects required to initialize the strategy for the Experiment.
Returns: dict
Controller Object¶
| Module: | controller_object |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
class
controller_object.
ControllerObject
(input_argument, pysot_object, pysot_dict=None)¶ Initialize a POAP controller using user’s input parameters
This class receives parameters for the controller in the form of a dictionary. The dictionary contains all the data needed, including the types of controller and strategy to be used and all of their required input arguments.
Parameters: - input_argument (dict) – Parameters needed for setting up the controller and strategy
- pysot_object (dict) – Optimization Problem, Adaptive Sampling, Surrogate Model and Experimental Design objects
- pysot_dict (dict) – Categorised List of all classes in PySOT
Raises: ValueError – If any of the controller or strategy picked does not exit
Variables: - monitor – Instance of MonitorSubClass
- input_argument – Parameter for setting up controller object
- pySOT_Object – PySOT objects needed for the problem
- PySOT_dict – Categorised List of all classes in PySOT
- strategy – Instance of PySOT strategy
- controller – Instance of POAP controller
-
get_controller
()¶ Request the initialized controller object
Returns: Controller Object
-
init_controller
(controller_argument)¶ Initialize the Controller using input arguments.
If the controller specified by the user exists in POAP then the arguments name for the controller and their values are extracted from PySOT_dict and controller_argument respectively. These arguments are then used to initialize the controller object.
The eval() method is used to execute the controller, as the user only provides the server with the strings containing the controllers name.
Parameters: controller_argument (dict) – Information required to initialize controller
-
init_strategy
(strategy_argument)¶ Initializes the Strategy using input arguments.
If the strategy specified by the user exists in PySOT then the arguments name for the strategy and their values are extracted from PySOT_dict and controller_argument respectively. These arguments are then used to initialize the strategy object.
The eval() function is used to execute the strategy, as the user only provides the server with the strings containing the controllers name.
Parameters: strategy_argument (dict) – Information required to initialize strategy
-
class
controller_object.
MonitorSubClass
(controller)¶ Captures and sends the values of each evaluation.
MoniterSubClass inherits from the Monitor class. It hooks into the controller and monitors it’s progress. every time the controller registers a record completion event after appending the value of the current evaluation EvalRecord.value. The on_complete method is invoked, sending the value of the latest evaluation to the client.
Parameters: controller (controller) – The controller object to be monitored -
on_complete
(record)¶ Send the value of the recently completed evaluation to the client
Parameters: record (EvalRecord) – Data structure containing information about the completed evaluation
-
on_terminate
()¶ Handle terminates
-
Module Scraper¶
| Module: | module_scraper |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
class
module_scraper.
GetModuleClass
¶ Extracts specific class information from request modules. Like class names and their arguments.
-
get_arguments_and_default_values
(val)¶ Retrives the arguments for the __init__ function and their default values for the specified object
Parameters: val (Object) – The class object to extract inforamtion from Returns: list
-
get_class_names
(mod_name)¶ Compiles a dictionary containing class __name__ attributes as keys and the class objects as values.
Parameters: mod_name – The module from which the information is extracted Returns: dict
-
get_fun_names
(mod_name)¶ Compiles a dictionary containing module __name__ attributes as keys and the objects as values.
Parameters: mod_name – The module from which the information is extracted Returns: list
-
is_in_current_module
(method, mod_name_str)¶ A helper method or class to check if the a object exists in a given file
Parameters: - method (Object) – The object under question
- mod_name_str (String) – The __name__ attribute of the parent file
Returns: bool
-
Projection Function¶
| Module: | projection_function |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
projection_function.
projection
(x)¶ Sample Projection Function
Parameters: x (int) – Input list Returns: Norm form of input list
Delay Functions¶
| Module: | delay_function |
|---|---|
| Author: | Israr Mahmood<EMAIL_ADDRESS>|
-
delay_function.
delay
(records)¶ Sample Delay Function
Parameters: records (EvalRecord) – Completed Evaluation Record Returns: int
Client Page
| Module: | Index.html |
|---|---|
| Author: | Peiyu Shi<EMAIL_ADDRESS>|
-
index.
showHide
(shID) Toggle shows and hides the section with given ID.
Given a section ID, shows and hide the section by a button.
Parameters: shID (json) – Section ID
-
index.
make_json
(form) Generate JSON file upon user clicked submit button.
The function is currently displaying JSON on client page for verification. Future work would be required to resolve the conflict between client side and server side.
This fuction takes in a form and make json file that is parseable on server side.
Parameters: form (json) – form for a section in html.
-
index.
set_val
(json) Parse the JSON file given from backend, and fill in the default values. Currently using the sample.json file, should be changed to taking input JSON file from server.
Image Display
| Module: | Index.html |
|---|---|
| Author: | Peiyu Shi<EMAIL_ADDRESS>|
-
image.
run
(dataList) This function takes in a dataList from server side and construct an image for display. It returns the script and div for javascript use.
Parameters: dataList (dataList) – result sent from server side.
-
bokeh_display.
display_image
(json) Given the json file representing the image of the result, display the image using bokeh.
Parameters: json (json) – json file representing the image


Attending a trade show can be a very effective method of promoting your company and its products. And one of the most effective ways to optimize your trade show display and increase traffic to your booth is through the use of banner stands.
Attending a trade show can be a very effective method of promoting your company and its products. And one of the most effective ways to optimize your trade show display and increase traffic to your booth is through the use of banner stands.
Classified advertising is a form of advertising that is particularly common in newspapers and
other periodicals. A classified is usually textually based and can consist of as little as the type of
item being sold, and a contact number to call for more information
If you are considering purchasing a new grill, or barbecue, you will be faced with a multitude of options to choose between. However, there is one choice which you will need to make fairly quickly in your quest for the perfect grill for you. That decision is whether to buy a charcoal or gas grill.

Classified advertising is a form of advertising that is particularly common in newspapers and other periodicals. A classified is usually textually based and can consist
If you are considering purchasing a new grill, or barbecue, you will be faced with a multitude of options to choose between. However, there is one choice which you will need.
Chopped, sliced or wedged, hard-cooked eggs are the basis of egg salad and add protein and a happy glow to tossed and composed salads and casseroles.
Chopped, sliced or wedged, hard-cooked eggs are the basis of egg salad and add protein and a happy glow to tossed and composed salads and casseroles.


STSMSGErrorCode
enum STSMSGErrorCode {}
StraaS.io messaging SDK error code
-
Network error, underlying error object is included in the user info dictionary.
Declaration
Objective-C
STSMSGErrorCodeNetwork = 0
-
Channel code should not be an empty string.
Declaration
Objective-C
STSMSGErrorCodeChannelCodeLength = 1
-
Auto create chat requires member authorization(a member JWT is needed).
Declaration
Objective-C
STSMSGErrorCodeGuestCreateChatNotSupported = 2
-
Can not perform operation(disconnect from channel, send message, get users, etc.) because channel is not connected.
Declaration
Objective-C
STSMSGErrorCodeChannelNotConnected = 3
-
Can not connect to channel because channel is already connected.
 Can not change member name via StraaS.io messaging service.
Declaration
Objective-C
STSMSGErrorCodeMemberNicknameUpdateNotSupported = 5
-
Nickname length must be between 1~20 characters.
Declaration
Objective-C
STSMSGErrorCodeNicknameLength = 6
-
Message length must be between 1~300 characters.
Declaration
Objective-C
STSMSGErrorCodeMessageLength = 7
-
The role to be updated can only be NORMAL or MODERATER.
Declaration
Objective-C
STSMSGErrorCodeUserRole = 8
-
Member JWT is invalid or expired. Please try again with a new member JWT.
Declaration
Objective-C
STSMSGErrorCodeUnauthorized = 9
-
This task is not permitted by server since what you want to do is not allowed or the identity of current user has no permission to execute the task.
Declaration
Objective-C
STSMSGErrorCodePermission = 10
-
Can not connect to chatroom since it is not found on our server. Please make sure you’ve created this chatroom before trying to connect it.
Declaration
Objective-C
STSMSGErrorCodeChatroomNotfound = 11
-
Can not update role since member id is not found. Please make sure you’ve created this member id before trying to update role.
Declaration
Objective-C
STSMSGErrorCodeMemberIdNotFound = 12
-
Archive Id cannot be found, please check if the archive id existed.
Declaration
Objective-C
STSMSGErrorCodeArchiveIdNotFound = 13
-
Input value is invalid, please check the error’s userInfo[NSLocalizedDescriptionKey] to get more informations.
Declaration
Objective-C
STSMSGErrorCodeInputValueInvalid = 14
-
Server side error happened, please try again later or contact with service provider.
Declaration
Objective-C
STSMSGErrorCodeServer = 15
-
SDK internal error happened, please try again or report issue.
Declaration
Objective-C
STSMSGErrorCodeInternal = 16
-
Aggregate data length must be between 1~100 characters.
Declaration
Objective-C
STSMSGErrorCodeAggregatedDataLength = 17
-
Raw data must be an object which can be converted to JSON object.
Declaration
Objective-C
STSMSGErrorCodeRawDataFormatNotAllowed = 18
-
Requests over the rate limit.
Declaration
Objective-C
STSMSGErrorCodeTooManyRequests = 19


3/26 email
From: Faculty<EMAIL_ADDRESS>on behalf of Michael Mandiberg<EMAIL_ADDRESS>Sent: Thursday, March 26, 2020 11:45 AM
To<EMAIL_ADDRESS>Cc<EMAIL_ADDRESS><EMAIL_ADDRESS>Subject: [Faculty] CUNY Distance Learning Archive / Request for Contributions
Hello All,
I hope you are holding together in this upside down time. I know we are all overwhelmed with emails, and pauses and recalibrations – so I'm actually writing about those destabilizing disruptions and disorienting new conditions:
I'm writing to share some information about the CUNY Distance Learning Archive project: http://cuny.is/cdla. And to ask you to 1) share this info widely 2) share materials with the archive – especially materials that document your experience over the past three weeks.
I am particularly keen on ensuring that programs like ours document the specific challenges that we have faced as we have confronted the challenge of moving media + production courses online.
Created over the week following the move to distance learning, by a group led collaboratively by the Ph.D. Program in English’s Knowledge Infrastructure class and the Interactive Technology & Pedagogy certificate program (ITP), the project aims to make space to build an archive documenting the ways that members of the CUNY community are responding to the rapid pedagogical shift to remote learning in response to the Novel Coronavirus (COVID-19). The group is working on several fronts, including archiving social media and official emails from each college administration, capturing the changes to college websites, and writing reflective texts.
My co-teacher this semester Sonia K. González and I are working with current students from the ITP class, to collect writings from students, instructors, and staff, including specifically HEOs and CLTs, about this moment. We seek responses that reflect on the planning, implementation, and impact of rapidly moving courses to online forums throughout the CUNY system.
Our request:
We are asking for your written contribution. We have drafted a set of writing prompts: You may choose to write short responses to all of these, or focus on just one. We welcome all approaches. We have no word count expectations; write as much or as little as you feel is appropriate.
Please send this to everyone you know at CUNY. We welcome contributions from students, faculty, and staff, including specifically HEOs and CLTs.
Please signal boost on social: @cunyarchive has accounts on Insta, FB, and Tw: https://twitter.com/cunyarchive/status/1238971426905915398
We are interested in written contributions — short and long — from all members of the CUNY community. Contributions from students, faculty, and staff, including HEOs and CLTs are all welcome.
Please submit your text as a word document via the submission form on the CDLA commons site: https://cdla.commons.gc.cuny.edu/ Look for “Upload your file here.”
Sonia and I are happy to answer any questions.
Thank you! Michael
Do not feel obligated to respond to all of these. Feel free to submit another written reflection about how COVID-19 has impacted your CUNY courses. For example, if you have emailed students, staff, or faculty since this public health crisis began, please submit that, or include it in your response.
Who are you (questions for all)?
Are you a student, staff, faculty, or more than one?
At which CUNY campus(es) do you teach or learn?
What academic discipline(s) are you in?
At what level do you teach, work, or learn: community college, four-year college, graduate school, etc...?
What is your position: adjunct, administration, undergraduate student, etc...?
Questions for all:
We want to understand your plans for your classes as they move to online platforms. From your perspective, how much did the courses you are taking, teaching, or supporting have to change in order to move to a remote learning environment? Are they still the same courses?
What do you anticipate are the potential advantages and limitations of an online class in your discipline? If your discipline has specific experiential learning, can it be recreated in an online environment? What might be possible with online learning that was not possible in your traditional classroom?  If you are administrative or instructional staff, how is this impacting the work you are doing or the courses you are working with? How are you being called upon to adapt in this moment? As a student, how has your course changed, and how will you have to change your study habits, work schedule, and other life responsibilities?
How will this process affect access and accessibility of higher education?  If you are staff managing a lab, how is your program supporting access to this infrastructure? If you are an instructor, how have you made accommodations for students’ different degrees of technological access to avoid exacerbating these inequities? How will this experiment impact the accessibility needs of students with disabilities?
Questions for all:
From your perspective as a student, staff, and/or instructor, do you feel prepared for online learning? How has this abrupt shift to online learning affected the kind of work you do, and how much you are doing? Is it an increase or decrease in: studying, teaching, preparation, intellectual labor, emotional labor, physical labor, etc...? How has your definition of educational success/failure shifted as a result of the unexpected transition to online learning? How have course expectations shifted in a remote learning environment? Do you think these expectations are different for students, faculty, and staff?
Questions for all:
How and where are you seeking, teaching, and learning support as classes move to online platforms?
How have you supported others as courses move to online platforms?
How are you addressing the possible changes in the health and wellbeing of those around you? How do you translate this into your communications with others: students, staff, faculty, etc…?
Where and when are you engaging with your online class? How does that environment enable you or prevent you from engaging, in comparison to the face to face environment?
How do you think this experience will change education overall, and how society views traditional and online education?
Do you think this will result in more or less online courses in the future?
As a teacher or staff member, have you found that you need to engage online with students’ emotional responses to the changes — personal and educational — wrought by the COVID-19 crisis? As a student, have you found that faculty and staff are engaging with you in this way, and if so, is it welcome or unwelcome?


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PLUNKETT & MACLEANE A film review by Steve Rhodes Copyright 1999 Steve Rhodes RATING (0 TO ****): **
PLUNKETT & MACLEANE, a lavish costume drama set in London in 1748, has it all: huge, powdered wigs, men with lipstick, rock music, fast edits, squalor and decadence. In short it's the perfect movie for those people who think the main problem with the cinema today is that it lacks an MTV video gloss.
First-time film director Jake Scott has an extensive resume of -- surprise! -- rock videos. PLUNKETT & MACLEANE is a hyperactive movie that is a treat for the eyes but offers little for the mind. Billed as a comedy, it doesn't contain a single funny scene with the possible exception of a remark about halitosis. When someone uses bad breath as an insult and that elicits a film's only laugh, you know the movie is in trouble.
Loosely based on the tale of a real-life robber known as the "Gentleman Highwayman," the movie is BONNIE AND CLYDE meets BARRY LYNDON, all scored with a rock sensibility.
A typical scene, filmed through a golden filter, is set at a lavish costume ball in which the decorations appear to be leftover floats from the Main Street Parade at Disneyland. The floor looks like an Escher print, and the heavy rock beat is as topical as the music from your local radio station. Did I mention the crazy costumes?
The setup for the plot is that two working-class criminals develop a scam whereby one, Macleane (Jonny Lee Miller), will impersonate a gentleman in order to find who is carrying the most money and valuables. Plunkett (Robert Carlyle) will act like he is Macleane's servant. Together they will rob the coaches of the richest of the aristocracy. This life of crime has predictable twists and turns, right down to the ending, which is lifted out of a hundred similar movies.
Liv Tyler, as the story's love interest, Lady Rebecca, continues in her tradition of delivering lifeless performances to characters that are already badly underwritten. At the party in which she is introduced, she is inexplicably the only person, male or female, without a wig.
The best supporting character is played by Alan Cumming, as Lord Rochester, a bisexual dandy who sports the show's most outlandish wardrobes, with his large purple hat and accompanying crimson and lavender jacket being perhaps the most wonderfully silly.
Visually attractive like VELVET GOLDMINE, the movie suffers the same problem. It's a good-looking picture, but it's never more than just a good-looking picture. The characters are poorly drawn, the script is DOA and the director only knows how to create flash. Boiled down to its three-minute rock video essence, it might prove diverting. At a full-movie length, it tests the viewer's stamina.
PLUNKETT & MACLEANE runs 1:33. It is rated R for some strong violence, sexuality and language and would be acceptable for older teenagers.
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| Bio1 |
Annual mean temperature |
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Mean diurnal range |
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Temperature seasonality |
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Reports unused named patterns ("define") in a RELAX-NG file (XML or Compact Syntax). A define will not be marked as unused if it is used through an include in another file.


This chapter provides an overview of injection in Java EE and describes the two injection mechanisms provided by the platform: resource injection and dependency injection.
Java EE provides injection mechanisms that enable your objects to obtain references to resources and other dependencies without having to instantiate them directly. You declare the required resources and other dependencies in your classes by decorating fields or methods with one of the annotations that mark the field as an injection point. The container then provides the required instances at runtime. Injection simplifies your code and decouples it from the implementations of its dependencies.
The following topics are addressed here:
Resource injection enables you to inject any resource available in the JNDI namespace into any container-managed object, such as a servlet, an enterprise bean, or a managed bean. For example, you can use resource injection to inject data sources, connectors, or custom resources available in the JNDI namespace.
The type you use for the reference to the injected instance is usually an interface, which decouples your code from the implementation of the resource.
For example, the following code injects a data source object that provides connections to the default Java DB database shipped with GlassFish Server:
public class MyServlet extends HttpServlet { @Resource(name="java:comp/DefaultDataSource") private javax.sql.DataSource dsc; ... }
In addition to field-based injection as in the preceding example, you can inject resources using method-based injection:
public class MyServlet extends HttpServlet { private javax.sql.DataSource dsc; ... @Resource(name="java:comp/DefaultDataSource") public void setDsc(java.sql.DataSource ds) { dsc = ds; } }
To use method-based injection, the setter method must follow the JavaBeans conventions for property names: The method name must begin with set
, have a void
return type, and have only one parameter.
The @Resource
annotation is in the javax.annotation
package and is defined in JSR 250 (Common Annotations for the Java Platform). Resource injection resolves by name, so it is not typesafe: the type of the resource object is not known at compile time, so you can get runtime errors if the types of the object and its reference do not match.
Dependency injection enables you to turn regular Java classes into managed objects and to inject them into any other managed object. Using dependency injection, your code can declare dependencies on any managed object. The container automatically provides instances of these dependencies at the injection points at runtime, and it also manages the lifecycle of these instances for you.
Dependency injection in Java EE defines scopes, which determine the lifecycle of the objects that the container instantiates and injects. For example, a managed object that is only needed to respond to a single client request (such as a currency converter) has a different scope than a managed object that is needed to process multiple client requests within a session (such as a shopping cart).
You can define managed objects (also called managed beans) that you can later inject by assigning a scope to a regular class:
@javax.enterprise.context.RequestScoped public class CurrencyConverter { ... }
Use the javax.inject.Inject
annotation to inject managed beans; for example:
public class MyServlet extends HttpServlet { @Inject CurrencyConverter cc; ... }
As opposed to resource injection, dependency injection is typesafe because it resolves by type. To decouple your code from the implementation of the managed bean, you can reference the injected instances using an interface type and have your managed bean implement that interface.
For more information about dependency injection, see Chapter 23, "Introduction to Contexts and Dependency Injection for Java EE" and JSR 299 (Contexts and Dependency Injection for the Java EE Platform).
Table 4-1 lists the main differences between resource injection and dependency injection.


Welcome to my Wonderous Questionaire!
Test your expertise at facebook stalking against this entirely related set of random facts.
Let's begin!
q1
q2
q3
q4
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The Iris Flower Dataset is a standard machine learning data set dating back to the 1930s. It contains measurements from 150 flowers.
If we wanted to learn these underlying species’ measurements, we would
use these real valued measurements and make assumptions about the
structure of the data. We could assume that conditioned on assignment to species
, the measurement data
follwed a multivariate normal
In this case, the data comes from three species of flowers:
Plotting the data shows that indiviudal species exhibit a typical range of measurements
The dimensionality of a clustering model is equal to the number of clusters in the model. Bayesian clustering algorithms often rely of the Dirichlet Distribution to encode prior information about these cluster assignments. The Dirichlet distribution (DD) can be considered a distribution of distributions. Each sample from the DD is a categorial distribution over \(K\) categories. It is parameterized \(G_0\), a distribution over \(K\) categories and \(\alpha\), a scale factor.
The expected value of the DD is \(G_0\). The variance of the DD is a function of the scale factor. When \(\alpha\) is large, samples from \(DD(\alpha\cdot G_0)\) will be very close to \(G_0\). When \(\alpha\) is small, samples will vary more widely.
Most clustering algorithms require the number of clusters to be given in advance. If we don’t know the number of species in the data, how would we be able to classify these flowers?
The Dirichlet Process is a stochastic process used in Bayesian nonparametrics to cluster data without specifying the number of clusters in advance. The Dirichlet Process Prior is used to mathematically descirbe prior information about the number of clusters in the data.
The Dirichlet Process Prior is nonparametric because its dimensionality is infinite. This characteristic is advantageous in clustering because it allows us to recognize new clusters when we observe new data.
The Dirichlet Process can be considered a way to generalize the Dirichlet distribution. While the Dirichlet distribution is parameterized by a discrete distribution \(G_0\) and generates samples that are similar discrete distributions, the Dirichlet process is parameterized by a generic distribution \(H_0\) and generates samples which are distributions similar to \(H_0\). The Dirichlet process also has a parameter \(\alpha\) that determines how similar how widely samples will vary from \(H_0\).
When learning a clustering using a Dirichlet Process Prior, observations are probabilistically assigned to clusters based on the number of observations in that cluster \(n_k\).
Probability of new clusters are paramteterized by \(\alpha\)
In other words, these culsters exhbit a rich get richer property.
The expected number of clusters in a dataset clustered with the Dirichlet Process is \(O(\alpha\log(N))\)
The expected number of clusters with \(m\) observations (Arratia et al., 2003) is \(\frac{\alpha}{m}\)
We can construct a sample \(H\) (recall that \(H\) is a probability distribution) from a Dirichlet process \(\text{DP}(\alpha H_0)\) by drawing a countably infinite number of samples \(\theta_k\) from \(H_0\)) and setting:
where the \(\pi_k\) are carefully chosen weights (more later) that sum to 1. (\(\delta\) is the Dirac delta function.)
\(H\), a sample from \(DP(\alpha H_0)\), is a probability distribution that looks similar to \(H_0\) (also a distribution). In particular, \(H\) is a discrete distribution that takes the value \(\theta_k\) with probability \(\pi_k\). This sampled distribution \(H\) is a discrete distribution even if \(H_0\) has continuous support; the support of \(H\) is a countably infinite subset of the support \(H_0\).
The weights (\(\pi_k\) values) of a Dirichlet process sample related the Dirichlet process back to the Dirichlet distribution.
Gregor Heinrich writes:
The defining property of the DP is that its samples have weights \(\pi_k\) and locations \(\theta_k\) distributed in such a way that when partitioning \(S(H)\) into finitely many arbitrary disjoint subsets \(S_1, \ldots, S_j\) \(J<\infty\), the sums of the weights \(\pi_k\) in each of these \(J\) subsets are distributed according to a Dirichlet distribution that is parameterized by \(\alpha\) and a discrete base distribution (like \(G_0\)) whose weights are equal to the integrals of the base distribution \(H_0\) over the subsets \(S_n\).
As an example, Heinrich imagines a DP with a standard normal base measure \(H_0\sim \mathcal{N}(0,1)\). Let \(H\) be a sample from \(DP(H_0)\) and partition the real line (the support of a normal distribution) as \(S_1=(-\infty, -1]\), \(S_2=(-1, 1]\), and \(S_3=(1, \infty]\) then
where \(H(S_n)\) be the sum of the \(\pi_k\) values whose \(\theta_k\) lie in \(S_n\).
These \(S_n\) subsets are chosen for convenience, however similar results would hold for any choice of \(S_n\). For any sample from a Dirichlet process, we can construct a sample from a Dirichlet distribution by partitioning the support of the sample into a finite number of bins.
There are several equivalent ways to choose the \(\pi_k\) so that this property is satisfied: the Chinese restaurant process, the stick-breaking process, and the Pólya urn scheme.
To generate \(\left\{\pi_k\right\}\) according to a stick-breaking process we define \(\beta_k\) to be a sample from \(\text{Beta}(1,\alpha)\). \(\pi_1\) is equal to \(\beta_1\). Successive values are defined recursively as
Thus, if we want to draw a sample from a Dirichlet process, we could, in theory, sample an infinite number of \(\theta_k\) values from the base distribution \(H_0\), an infinite number of \(\beta_k\) values from the Beta distribution. Of course, sampling an infinite number of values is easier in theory than in practice.
However, by noting that the \(\pi_k\) values are positive values summing to 1, we note that, in expectation, they must get increasingly small as \(k\rightarrow\infty\). Thus, we can reasonably approximate a sample \(H\sim DP(\alpha H_0)\) by drawing enough samples such that \(\sum_{k=1}^K \pi_k\approx 1\).
We use this method below to draw approximate samples from several Dirichlet processes with a standard normal (\(\mathcal{N}(0,1)\)) base distribution but varying \(\alpha\) values.
Recall that a single sample from a Dirichlet process is a probability distribution over a countably infinite subset of the support of the base measure.
The blue line is the PDF for a standard normal. The black lines represent the \(\theta_k\) and \(\pi_k\) values; \(\theta_k\) is indicated by the position of the black line on the \(x\)-axis; \(\pi_k\) is proportional to the height of each line.
We generate enough \(\pi_k\) values are generated so their sum is greater than 0.99. When \(\alpha\) is small, very few \(\theta_k\)‘s will have corresponding \(\pi_k\) values larger than \(0.01\). However, as \(\alpha\) grows large, the sample becomes a more accurate (though still discrete) approximation of \(\mathcal{N}(0,1)\).
Often we want to draw samples from a distribution sampled from a Dirichlet Process instead of from the Dirichlet process itself. Much of the literature on the topic unhelpful refers to this as sampling from a Dirichlet process.
Fortunately, we don’t have to draw an infinite number of samples from the base distribution and stick breaking process to do this. Instead, we can draw these samples as they are needed.
Suppose, for example, we know a finite number of the \(\theta_k\) and \(\pi_k\) values for a sample \(H\sim \text{Dir}(\alpha H_0)\). For example, we know
To sample from \(H\), we can generate a uniform random \(u\) number between 0 and 1. If \(u\) is less than 0.5, our sample is \(0.1\). If \(0.5<=u<0.8\), our sample is \(-0.5\). If \(u>=0.8\), our sample (from \(H\) will be a new sample \(\theta_3\) from \(H_0\). At the same time, we should also sample and store \(\pi_3\). When we draw our next sample, we will again draw \(u\sim\text{Uniform}(0,1)\) but will compare against \(\pi_1, \pi_2\), AND \(\pi_3\).
The class below will take a base distribution \(H_0\) and \(\alpha\) as arguments to its constructor. The class instance can then be called to generate samples from \(H\sim \text{DP}(\alpha H_0)\).
from numpy.random import choice
class DirichletProcessSample():
def __init__(self, base_measure, alpha):
self.base_measure = base_measure
self.alpha = alpha
self.cache = []
self.weights = []
self.total_stick_used = 0.
def __call__(self):
remaining = 1.0 - self.total_stick_used
i = DirichletProcessSample.roll_die(self.weights + [remaining])
if i is not None and i < len(self.weights) :
return self.cache[i]
else:
stick_piece = beta(1, self.alpha).rvs() * remaining
self.total_stick_used += stick_piece
self.weights.append(stick_piece)
new_value = self.base_measure()
self.cache.append(new_value)
return new_value
@staticmethod
def roll_die(weights):
if weights:
return choice(range(len(weights)), p=weights)
else:
return None
This Dirichlet process class could be called stochastic memoization. This idea was first articulated in somewhat abstruse terms by Daniel Roy, et al.
Below are histograms of 10000 samples drawn from samples drawn from Dirichlet processes with standard normal base distribution and varying \(\alpha\) values.
import pandas as pd
base_measure = lambda: norm().rvs()
n_samples = 10000
samples = {}
for alpha in [1, 10, 100, 1000]:
dirichlet_norm = DirichletProcessSample(base_measure=base_measure, alpha=alpha)
plt.figure(figsize=(9,6))
pd.Series([dirichlet_norm() for _ in range(n_samples)]).hist()
plt.title('Alpha: %s' % alpha)
plt.savefig('Alpha_Hist_%s.png')
Note that these histograms look very similar to the corresponding plots of sampled distributions above. However, these histograms are plotting points sampled from a distribution sampled from a Dirichlet process while the plots above were showing approximate distributions samples from the Dirichlet process. Of course, as the number of samples from each \(H\) grows large, we would expect the histogram to be a very good empirical approximation of \(H\).
For more information on the Dirichlet Process, please see our developer Tim Hopper’s additional notebooks.


The Search Tool is driven by an index that contains multiple sub indexes. When using the tool for basic search, only 2 of these indexes are used: the context index, and the content index. The content index contains a stored and tokenized full text index of a digested form of the content. This means that a Word document uploaded to Resources will have had all its text extracted and indexed, whereas a video package may have had only the metadata indexed. When the search results are returned, it is this content that is shown with the matching terms highlighted.
The context index provides a keyword index of the source of the content. This is the worksite or course which contains the content. When the search tool performes a basic search, it adds a search term of +content:<currentsiteid> where <currentsiteid> is the context or site id where the search is being performed. This can be translated as "results must come from the current site".
You can search for terms within any of the indexes. For example to search only in announcements, you can use the search terms +tool:announcement +content:cowslip which will only return announcements containing the word cowslip.
The index currently contains the following named indexes.
The Query Engine is based on Apache Lucene. For completeness the Apache Query documentation is included below. More information can be found at http://lucene.apache.org/java/docs/queryparsersyntax.html
A query is broken up into terms and operators. There are two types of terms: Single Terms and Phrases.
A Single Term is a single word such as "test" or "hello".
A Phrase is a group of words surrounded by double quotes such as "hello dolly".
Multiple terms can be combined together with Boolean operators to form a more complex query (see below).
Note: The analyzer used to create the index will be used on the terms and phrases in the query string. So it is important to choose an analyzer that will not interfere with the terms used in the query string.
Lucene supports fielded data. When performing a search you can either specify a field, or use the default field. The field names and default field is implementation specific.
You can search any field by typing the field name followed by a colon ":" and then the term you are looking for.
As an example, let's assume a Lucene index contains two fields, title and text and text is the default field. If you want to find the document entitled "The Right Way" which contains the text "don't go this way", you can enter:
title:"The Right Way" AND text:go
or
title:"Do it right" AND right
Since text is the default field, the field indicator is not required.
Note: The field is only valid for the term that it directly precedes, so the query
title:Do it right
Will only find "Do" in the title field. It will find "it" and "right" in the default field (in this case the text field).
Lucene supports modifying query terms to provide a wide range of searching options.
Lucene supports single and multiple character wildcard searches.
To perform a single character wildcard search use the "?" symbol.
To perform a multiple character wildcard search use the "*" symbol.
The single character wildcard search looks for terms that match that with the single character replaced. For example, to search for "text" or "test" you can use the search:
te?t
Multiple character wildcard searches looks for 0 or more characters. For example, to search for test, tests or tester, you can use the search:
test*
You can also use the wildcard searches in the middle of a term.
te*t
Note: You cannot use a * or ? symbol as the first character of a search.
Lucene supports fuzzy searches based on the Levenshtein Distance, or Edit Distance algorithm. To do a fuzzy search use the tilde, "~", symbol at the end of a Single word Term. For example to search for a term similar in spelling to "roam" use the fuzzy search:
roam~
This search will find terms like foam and roams.
Starting with Lucene 1.9 an additional (optional) parameter can specify the required similarity. The value is between 0 and 1, with a value closer to 1 only terms with a higher similarity will be matched. For example:
roam~0.8
The default that is used if the parameter is not given is 0.5.
Lucene supports finding words are a within a specific distance away. To do a proximity search use the tilde, "~", symbol at the end of a Phrase. For example to search for a "apache" and "jakarta" within 10 words of each other in a document use the search:
"jakarta apache"~10
Range Queries allow one to match documents whose field(s) values are between the lower and upper bound specified by the Range Query. Range Queries can be inclusive or exclusive of the upper and lower bounds. Sorting is done lexicographically.
mod_date:[20020101 TO 20030101]
This will find documents whose mod_date fields have values between 20020101 and 20030101, inclusive. Note that Range Queries are not reserved for date fields. You could also use range queries with non-date fields:
title:{Aida TO Carmen}
This will find all documents whose titles are between Aida and Carmen, but not including Aida and Carmen.
Inclusive range queries are denoted by square brackets. Exclusive range queries are denoted by curly brackets.
Lucene provides the relevance level of matching documents based on the terms found. To boost a term use the caret, "^", symbol with a boost factor (a number) at the end of the term you are searching. The higher the boost factor, the more relevant the term will be.
Boosting allows you to control the relevance of a document by boosting its term. For example, if you are searching for
jakarta apache
and you want the term "jakarta" to be more relevant boost it using the ^ symbol along with the boost factor next to the term. You would type:
jakarta^4 apache
This will make documents with the term jakarta appear more relevant. You can also boost Phrase Terms as in the example:
"jakarta apache"^4 "Apache Lucene"
By default, the boost factor is 1. Although the boost factor must be positive, it can be less than 1 (e.g. 0.2)
Boolean operators allow terms to be combined through logic operators. Lucene supports AND, "+", OR, NOT and "-" as Boolean operators(Note: Boolean operators must be ALL CAPS). OR
The OR operator is the default conjunction operator. This means that if there is no Boolean operator between two terms, the OR operator is used. The OR operator links two terms and finds a matching document if either of the terms exist in a document. This is equivalent to a union using sets. The symbol || can be used in place of the word OR.
To search for documents that contain either "jakarta apache" or just "jakarta" use the query:
"jakarta apache" jakarta
or
"jakarta apache" OR jakarta
AND
The AND operator matches documents where both terms exist anywhere in the text of a single document. This is equivalent to an intersection using sets. The symbol && can be used in place of the word AND.
To search for documents that contain "jakarta apache" and "Apache Lucene" use the query:
"jakarta apache" AND "Apache Lucene"
+
The "+" or required operator requires that the term after the "+" symbol exist somewhere in a the field of a single document.
To search for documents that must contain "jakarta" and may contain "lucene" use the query:
+jakarta apache
NOT
The NOT operator excludes documents that contain the term after NOT. This is equivalent to a difference using sets. The symbol ! can be used in place of the word NOT.
To search for documents that contain "jakarta apache" but not "Apache Lucene" use the query:
"jakarta apache" NOT "Apache Lucene"
Note: The NOT operator cannot be used with just one term. For example, the following search will return no results:
NOT "jakarta apache"
The "-" or prohibit operator excludes documents that contain the term after the "-" symbol.
To search for documents that contain "jakarta apache" but not "Apache Lucene" use the query:
"jakarta apache" -"Apache Lucene"
Lucene supports using parentheses to group clauses to form sub queries. This can be very useful if you want to control the boolean logic for a query.
To search for either "jakarta" or "apache" and "website" use the query:
(jakarta OR apache) AND website
This eliminates any confusion and makes sure you that website must exist and either term jakarta or apache may exist.
Lucene supports using parentheses to group multiple clauses to a single field.
To search for a title that contains both the word "return" and the phrase "pink panther" use the query:
title:(+return +"pink panther")
Lucene supports escaping special characters that are part of the query syntax. The current list special characters are
+ - && || ! ( ) { } [ ] ^ " ~ * ? : \
To escape these character use the \ before the character. For example to search for (1+1):2 use the query:
\(1\+1\)\:2