ready_for_review
by Francis Kayiwa at 2023-02-15 15:37:52.review_requested
by Francis Kayiwa at 2023-02-15 15:38:09.review_requested
by Francis Kayiwa at 2023-02-15 15:38:17.referenced
by Robert-Anthony Lee-Faison at 2023-02-15 17:48:35.merged
by Robert-Anthony Lee-Faison at 2023-02-15 17:48:35.closed
by Robert-Anthony Lee-Faison at 2023-02-15 17:48:35.head_ref_deleted
by Robert-Anthony Lee-Faison at 2023-02-15 17:48:40.ready_for_review
by None at 2023-02-15 01:44:21.referenced
by None at 2023-02-15 11:44:01.merged
by None at 2023-02-15 11:44:01.closed
by None at 2023-02-15 11:44:01.head_ref_deleted
by None at 2023-02-15 11:44:02.@phoebeno This just finished on prod.
@regineheberlein cheers cheers cheers! you are my hero and the hero of us all!
closed
by None at 2023-02-15 01:30:24.mentioned
by None at 2023-02-15 01:30:24.subscribed
by None at 2023-02-15 01:30:24.mentioned
by None at 2023-02-15 12:45:51.subscribed
by None at 2023-02-15 12:45:52.Thanks, Regine! The results from the XPath you shared actually looks right. Not sure how I got 880.
In answer to your questions, 1. Yes 2. I'm looking to delete the entire restriction. 3. I'm looking to delete restrictions with type "Restricted," which is what the XPath you shared seems to have located.
No, the XPath above merely looks for the presence of an accessrestrict element. When controlling for the value of the rights-restriction attribute, I get to 867 components:
//c[@id="aspace_C1491_c1"]//c[not(c)]/accessrestrict[@rights-restriction="Restricted"]
Are these the ones you want to delete?
head_ref_deleted
by Christina Chortaria at 2023-02-15 11:43:53.head_ref_deleted
by Christina Chortaria at 2023-02-15 11:43:54.With the latest update and per @mzelesky we want to submit a separate record for each item.
mentioned
by None at 2023-02-15 21:40:37.subscribed
by None at 2023-02-15 21:40:37.This has been advanced beyond the SN@P ticket, as the parties involved in configuring the Cognos reports which generate the report for the existing Samba/CIFS file share are in direct communication with me using e-mail messages.
@kelea99 Can you help us track down the keystrokes needed to replicate this issue? I.e. "Allah" in Arabic.
mentioned
by Kim Leaman at 2023-02-15 16:24:19.subscribed
by Kim Leaman at 2023-02-15 16:24:19.labeled
by Eliot Jordan at 2023-02-15 16:25:42.PR Updated:
head_ref_force_pushed
by Eliot Jordan at 2023-02-15 15:58:22.head_ref_force_pushed
by Eliot Jordan at 2023-02-15 18:22:34.head_ref_force_pushed
by Eliot Jordan at 2023-02-15 19:01:38.ready_for_review
by Eliot Jordan at 2023-02-15 19:01:45.assigned
by Eliot Jordan at 2023-02-15 19:19:49.unlabeled
by Eliot Jordan at 2023-02-15 19:19:57.closed
by Robert-Anthony Lee-Faison at 2023-02-15 14:50:05.referenced
by None at 2023-02-15 14:49:26.merged
by None at 2023-02-15 14:49:26.closed
by None at 2023-02-15 14:49:27.head_ref_deleted
by None at 2023-02-15 14:51:45.referenced
by Christina Chortaria at 2023-02-14 23:15:01.merged
by Christina Chortaria at 2023-02-14 23:15:01.closed
by Christina Chortaria at 2023-02-14 23:15:02.head_ref_deleted
by Christina Chortaria at 2023-02-14 23:15:03.labeled
by Jane Sandberg at 2023-02-14 23:27:26.ready_for_review
by None at 2023-02-15 14:36:51.deployed
by None at 2023-02-15 21:11:59.assigned
by Max Kadel at 2023-02-15 16:30:16.Think we got one this @kayiwa. I'll close it.
closed
by Kevin Reiss at 2023-02-15 21:50:41.mentioned
by Francis Kayiwa at 2023-02-15 21:50:42.subscribed
by Francis Kayiwa at 2023-02-15 21:50:42.review_requested
by Vickie Karasic at 2023-02-15 17:51:22.renamed
by Vickie Karasic at 2023-02-15 17:51:54.referenced
by Francis Kayiwa at 2023-02-16 00:50:50.merged
by Francis Kayiwa at 2023-02-16 00:50:50.closed
by Francis Kayiwa at 2023-02-16 00:50:50.head_ref_deleted
by Francis Kayiwa at 2023-02-16 00:50:56.labeled
by Christina Chortaria at 2023-02-15 11:21:53.I think at this point we can safely merge this branch into main (pending review, of course)
Coverage: 94.405% (+0.01%) from 94.393% when pulling 018b0753dc2c53a075d29088daeed142c013ef8c on i3392stackmapjavascript into 7ee7a9af98cb7a3e839b9f373c4713b57971ee8d on main.
ready_for_review
by Max Kadel at 2023-02-15 13:56:39.deployed
by None at 2023-02-15 13:57:14.deployed
by None at 2023-02-15 14:07:08.assigned
by None at 2023-02-15 14:50:01.Coverage: 94.393%. Remained the same when pulling a8ade8d30c83e7667e2865c00f9248d3e774006e on 3359-requests-with-manually-entered-volume into 7ee7a9af98cb7a3e839b9f373c4713b57971ee8d on main.
closed
by Bess Sadler at 2023-02-15 21:31:33.Here is a potential capistrano solution; no sudoers changes needed: https://github.com/pulibrary/pul_library_drupal/pull/1967. How does this look?
head_ref_force_pushed
by None at 2023-02-15 17:52:26.I don't think I wanna kill long running queries, but more info sounds awesome to me.
yeah I agree that would be bad. I'll add the 2 recommendations as checkboxes in the description.
mentioned
by Francis Kayiwa at 2023-02-15 16:58:55.subscribed
by Francis Kayiwa at 2023-02-15 16:58:55.mentioned
by Trey Pendragon at 2023-02-15 16:58:55.subscribed
by Trey Pendragon at 2023-02-15 16:58:55.renamed
by None at 2023-02-15 22:15:37.Failing idempotence when the TASK [update cache]
in the ruby_s role reports changed on the second run.
head_ref_force_pushed
by None at 2023-02-15 17:38:14.head_ref_force_pushed
by None at 2023-02-15 17:54:53.head_ref_force_pushed
by None at 2023-02-15 17:59:46.I think it definitely would if the root user is able to run the command on mysql.
head_ref_force_pushed
by Jane Sandberg at 2023-02-15 16:59:13.head_ref_force_pushed
by Jane Sandberg at 2023-02-15 17:37:25.ready_for_review
by Kevin Reiss at 2023-02-15 21:22:28.referenced
by Kevin Reiss at 2023-02-15 21:22:39.merged
by Kevin Reiss at 2023-02-15 21:22:39.closed
by Kevin Reiss at 2023-02-15 21:22:39.head_ref_deleted
by Kevin Reiss at 2023-02-15 21:22:40.labeled
by Jane Sandberg at 2023-02-15 16:36:36.labeled
by Jane Sandberg at 2023-02-15 16:36:36.assigned
by Jane Sandberg at 2023-02-15 16:36:36.closed
by Kevin Reiss at 2023-02-15 21:22:41.labeled
by Eliot Jordan at 2023-02-15 16:29:55.labeled
by Eliot Jordan at 2023-02-15 16:37:51.referenced
by Bess Sadler at 2023-02-15 13:57:21.merged
by Bess Sadler at 2023-02-15 13:57:21.closed
by Bess Sadler at 2023-02-15 13:57:21.head_ref_deleted
by Bess Sadler at 2023-02-15 13:57:23.referenced
by Chuck McCallum at 2023-02-15 14:27:18.merged
by Chuck McCallum at 2023-02-15 14:27:18.closed
by Chuck McCallum at 2023-02-15 14:27:18.head_ref_deleted
by Chuck McCallum at 2023-02-15 14:27:20.closed
by Chuck McCallum at 2023-02-15 14:27:20.closed
by Kate Lynch at 2023-02-15 14:45:00.ready_for_review
by Chuck McCallum at 2023-02-15 21:28:59.labeled
by Chuck McCallum at 2023-02-15 21:32:47.assigned
by Chuck McCallum at 2023-02-16 01:26:26.assigned
by Chuck McCallum at 2023-02-16 01:26:45.assigned
by Chuck McCallum at 2023-02-16 01:26:52.assigned
by Chuck McCallum at 2023-02-16 01:27:03.


{% extends 'plans/base.html' %} {% load i18n %} {% block body %}
{% blocktrans %} Please contact our sales for an exclusive customised offer tailored to your needs. {% endblocktrans %}


THE MOD SQUAD A film review by Matt Williams
RATING: * out of * * * *
The Hollywood creative rut of recycling old TV show reruns has finally gotten deep enough to reach The Mod Squad. A ridiculous show to start with, should we be surprised that it has spawned an even more ridiculous movie?
It seems that the qualifications to work as a cop are completely optional. At least that is what Detective Greer (Dennis Farnia) decides when he recruits three young criminals to form an elite, though weaponless, undercover squad...the Mod Squad. Whose great idea was this?!? The film conveniently starts in media res, so we never get to hear Greer's arguments for turning the justice system on its head.
In any event, the Squad is composed of Julie (Claire Danes), Linc (Omar Epps) and Pete (Giovanni Ribisi), guilty respectively of assault, arson and robbery. Their mission in the movie is to infiltrate a high class prostitution ring. Oh, and to look cool while doing it.
But things quickly go wrong. Soon, The Mod Squad are embroiled in a web of murder, deceit, drug deals and police corruption. Before you jump to the conclusion that this sounds interesting, let me assure you that any life and excitement that may have one time inhabited this plot has long since fled the scene.
The Mod Squad's best attribute, nay, its only positive attribute, is its sense of style, and even that is troublingly forced. Shot with moody colored lighting, and the occasional wild angle, The Mod Squad is less of a film that an extended length music video...without the entertainment factor.
There are a few good actors buried under the moldy plot and pointless dialogue. The film tries to give each of the Mod Members a poignant scene or two. Julie runs afoul of an old flame (Josh Brolin), Pete tries to reconcile with his parents, and Linc...well, Linc really likes his car.
But then, there's the plot. Ugh...what a plot! The whole thing relies on the bad guys clearly stating their evil intentions in a loud enough voice to make any James Bond villain proud. I guess since policework is this easy, it's no wonder any random criminal can be a cop.
And don't go to see The Mod Squad expecting any excitement. The characters themselves even remark how incredibly boring it is, sitting around in cars.  Even the few "action" scenes are dull and lifeless.
The Mod Squad is the type of film that is best enjoyed merely from watching its commercials. Subject yourself to this mindless movie in quantities larger than 30 seconds, and you'll certainly regret it.
Copyright 1999 Matt Williams
- Matt Williams<EMAIL_ADDRESS>Reviewer for Cinematter: http://www.cinematter.com Home of nearly 700 reviews, and information on over 750 upcoming releases
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


TokenList
component offers a simplified way of working with lists: instance names are listed vertically
or horizontally, adding is done using drop-down list, removal - using the buttons located near each instance.
In this example, we have defined two collection data sources: orderItemsDc
nested datasource, which
includes a collection of order lines within an order, and allItemsDc
datasource containing a collection
of all order lines available in the database. The TokenList
component displays the content of the
orderItemsDc
datasource and allows changing the collection by adding instances from allItemsDc
.
tokenList
elements:
lookup
- values selection component descriptor.button
- descriptor of the button for adding items. Can contain caption
and
icon
attributes.
clearButton
- descriptor of the button for removing items. Can contain caption
and
icon
attributes.


Punishment Assistant
A simple tool teachers would love to use!
What is does? It uses machine learning models to detect wether a student who is pushished to do a hands-up, is he doing it properly or just faking it.
The model starts a beep sound when the student puts the hands half way down or completely puts it down.


Leading up to this trip, not to lie, I was scared. I heard some pretty intense stuff about DMT and I wasn't sure what to expect. After preparing the D. cabrerana and putting the syrian rue into capsule form, my roomate and I took the capsules. We did it about a half hour before drinking the potion. After drinking the potion I began to voluntarily meditate. It did upset my stomach, so I used the meditation to help calm myself. About 35 mins. later I puked.  The trip began just before I vomited. The next three hours were amazing. The trip set on fast, not like drinking tea made from San Pedro. I was tripping before my friend who had eaten shrooms at the same time I drank the potion was tripping. The next 2 hours consisted of AMAZING color visuals.
When my roomate and I felt that we hit our peak, we decided to smoke some salvia. We did it in a completely dark room. for the next 10 mins, I tripped harder than I ever had before, and I am a pretty experienced tripper. Color visuals gave way to hallucinations. My roomates laser printer turned into a large monstrous frog. I was so scared of this frog eating my leg that I sat indian style hunched over at the waist to protect them from its venomous bite. I began to come down. The salvia sort of killed the D. cabrerana buzz, because it was so intense that the D. cabrerana seemed to do nothin to me. I passed out a midnight about 3.5 hours after the initial consumption.
The next day I slept for about 14 hours, I was totally drained from the night before. For the price and ease of preparation this was better that anything done before (including LSD and PCP). Next time however, we are going to experiment with more syrian rue to prolong the tripping experience.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


We value the input of our users, so we are always happy to receive feedback from you or attend to any enquiries about our Safe Route and plans for it in the future. Don't feel shy to leave a message for us.


Reasoning¶
The part in which we describe why we chose what we chose.
Technology stack¶
Our technology stack is mainly focused on flexibility and ease-of-use:
- Flask was used over django because it is definitely more lightweight, and is more flexible.
- SQLAlchemy was used because of its, again, flexibility and speed of development. SQLAlchemy uses data-mapper model instead of Django’s familiar Active Record, and it allows for some interesting features such as association proxies.
- Itsdangerous is a small library with ‘good’ cryptography. It is a common knowledge that you shouldn’t implement cryptography by yourself, and this library contains a lot of neat things to help with that.
- PostgreSQL was chosen for backend because it is feature-rich, stable, and easy to use. SQLite didn’t have ARRAY builtin type and full index support for JSON. MySQL just tends to fall apart randomly (from my experience). Other SQL (MS SQL, Oracle) are too much enterprise for such project.


FileOperation COM Object
The IFileOperation COM object has a method that we can use to copy files to our secure location as the operation will auto-elevate and able to do a privilege copy. To exploit we can in inject our malicious DLL in a medium integrity process to carry out the operation. Since the COM object is set to auto-elevate the injected process does not need to be marked for auto-elevation in its manifest.
On Windows 7 injected processes that have copied successfully are
C:\Windows\explorer.exe
C:\Windows\System32\wuauclt.exe
C:\Windows\System32\taskhost.exe
During tests taskhost.exe only happens to work once after boot and wuauclt.exe doesn’t always work which leaves explorer.exe is only the reliable process to use.
On Windows 8 injected processes that have copied successfully are
C:\Windows\explorer.exe
C:\Windows\System32\wuauclt.exe
C:\Windows\System32\RuntimeBroker.exe
Again explorer.exe is only the reliable process to use I found during my tests and the only one that worked on Windows 8.1


* . * _.---._ ___ . ___.' '. * . _____[LLL]______________[LLL]_____ \ / [LLL] [LLL] \ | /____________________________________\ | . )==================================( / . * '|I .-. I .-. I .--. I .-. I .-. I|' .' * |I |+| I |+| I |. | I |+| I |+| I|-'` * |I_|+|_I_|+|_I_|__|_I_|+|_I_|+|_I| . . /_I_____I_____I______I_____I_____I_\ )================================( * * _ |I .-. I .-. I .--. I .-. I .-.
"Hell is empty and all the devils are here"
- The Tempest
You have died. Resuscitate from first breath?
His face looked like a man's. An older man in his 40s. Plain. Ordinary. I knew him though. I knew the creature that hid behind the mask of a man. And I knew why he was standing in the cold rain, staring in the direction of my window.
I began to tremble knowing what I had to do...
I move closer to the window. For a moment, I think I see him there. But A cold emptiness stands where I thought 'he' was. The street is deserted. Wet concrete shining indifferently. A shiver goes through me as I turn from the window. It's then that I see it. Just below the sliver of space between my bedroom door and the floor a barely visible shadow standing perfectly still. Inhumanly still.
I lie in bed with the covers pulled tight to my chin. I know he's still outside though. I know I lacked the courage to meet his gaze. A part of me has died.
You have lost a loved one who believed in you.Hear door broken down by an axe. You wait until the man goes into your bedroom.


Weeks:
Teams:
Courses:
Holes Per Course:
Start Date:
Multiple Teams Per Hole on Extra:
Smart Sort:
Dup Check:
team
scheduler
Schedules
Course By Team
Hole By Team
Team vs. Team
Load Data
Save Data
Paste previously copied saved data in this box to import existing schedule.
Import
Copy data in this box and save somewhere save. You can load this data back in later.


{% if false %} # # This is an example template to embed our email signup form into the website. # More information on customization here: # https://help.actionnetwork.org/hc/en-us/articles/203112529-Customizing-widgets-with-javascript # {% endif %}


|
Someday
(Sugar Ray) |
|
Someday,
when my life has passed me by
I'll lay around and wonder why you were always there for me One way, in the eyes of a passer-by I'll look around for another try, and fade away Just close your eyes and I'll take you there This place is warm without a care We'll take a swim in the deep blue sea I go to leave as you reach for me Some say, better things will come our way No matter what they try to say you were always there for me Some way, when the sun begins to shine I'll hear a song from another time, and fade away Just close your eyes and I'll take you there This place is warm without a care. We'll take a swim in the deep blue sea I go to leave as you reach for me Ohhhh..cmon Someone says you tried to hard (don't pass me by) Someone says we got it all (I wonder why) Someone says we tried to long (don't pass me by) We never see the writing on the wall So far, so long, so far away So far, so long, so far away (Various Vocal Lines) Someday, when my life has passed me by I'll lay around and wonder why you were always there for me One way, in the eyes of a passer-by I'll look around for another try, and fade away and fade away --(repeats numerous times) |


OptiFine is a Minecraft optimization mod.
It allows Minecraft to run faster and look better with full support for HD textures and many configuration options.
The official OptiFine description is on the Minecraft Forums.
Resources:
Translation, Documentation, Issue Tracker.
Social
media: Discord, Twitter, Reddit.
Privacy | Refund | Copyright | Contact
Website Remake by Kxffie#1444
FPS Boost
- Doubling the FPS is common
- Decreases lag spikes and smooths gameplay
Support for HD Textures
- HD textures and HD fonts (MCPatcher not needed)
- Custom terrain and item textures
- Animated terrain and item textures
- Custom HD Font character widths
- Custom colors
-
Custom block color palettes
- Custom lighting
- Unlimited texture size
Support for Shaders
- Based on the Shaders Mod by Karyonix
Dynamic Lights
- Allows handheld and dropped light emitting items to illuminate the objects around them
- Similar, but not related to the Dynamic Lights mod
Variable Render Distance
- From Tiny to Extreme (2 x Far) in 16m steps
- Sun, Moon and Stars are visible in Tiny and Short distance
Configurable Smooth Lighting
- From 1% - smooth lighting without shadows
- To 100% - smooth lighting with full shadows
Performance: VSync
- Synchronizes framerate with monitor refresh rate to remove split frames and smooth gameplay
Smart Advanced OpenGL
- More efficient, less artifacts
- Fast - Faster, some artifacts still visible
- Fancy - Slower, avoids visual artifacts
Fog control
- Fog: Fancy, Fast, OFF
- Fog start: Near, Far
Mipmaps>
- Visual effect which makes distant objects look better by smoothing the texture details
- Mipmap level - OFF, 1, 2, 3, Max
- Mipmap type - Nearest, Linear
Anisotropic Filtering
- Restores details in mipmapped textures
- AF level - OFF, 2, 4, 8, 16 (depends on hardware support)
Antialiasing
- Smooths jagged lines and sharp color transitions
- AA level - OFF, 2, 4, 6, 8, 12, 16 (depends on hardware support)
- Better Grass
- Fixes grass blocks side texture to match surrounding grass
terrain
Better Snow
- Fixes transparent blocks textures to match surrounding snow terrain
Clear Water
- Clear, transparent water with good visibility underwater
- Random Mobs
- Use random mob textures if available in the texture pack.
Connected Textures
- Connects textures for glass, glass panes, sandstone and bookshelf blocks which are next to each other.
Natural Textures
- Removes the gridlike pattern created by repeating blocks of the same type.
- Uses rotated and flipped variants of the base block texture.
FPS control
- Smooth FPS - stabilizes FPS by flushing the graphics driver buffers (examples)
- Smooth Input - fixes stuck keys, slow input and sound lag by setting correct thread priorities
Chunk Loading Control
- Load Far - loads the world chunks at distance Far, allows fast render distance switching
- Preloaded Chunks - defines an area in which no new chunks will be loaded
- Chunk Updates per
Frame - allows for faster world loading
- Dynamic Updates - loads more chunks per frame when the player is standing still
Configurable Details
- Clouds - Default, Fast, Fancy
- Cloud Height - from 0% to 100%
- Trees - Default, Fast, Fancy
- Grass - Default, Fast, Fancy
- Water - Default, Fast, Fancy
- Rain and Snow -
Default, Fast, Fancy
- Sky - ON, OFF
- Stars - ON, OFF
- Sun & Moon - ON, OFF
- Depth Fog - ON, OFF
- Weather - ON, OFF
- Swamp Colors - ON, OFF
- Smooth Biomes - ON, OFF
- Custom Fonts - ON, OFF
- Custom
Colors - ON, OFF
- Show Capes - ON, OFF (supports HD capes)
Configurable animations
- Water Animated - OFF, Dynamic, ON
- Lava Animated - OFF, Dynamic, ON
- Fire Animated - OFF, ON
- Portal Animated - OFF, ON
- Redstone Animated - OFF, ON
- Explosion Animated - OFF, ON
- Flame Animated - OFF, ON
- Smoke Animated - OFF, ON
- Void Particles - OFF, ON
- Water Particles - OFF, ON
- Rain Splash - OFF, ON
- Portal Particles
- OFF, ON
- Dripping Water/Lava - OFF, ON
- Terrain Animated - OFF, ON
- Items Animated - OFF, ON
Fast Texturepack Switching
- Switch the current Texturepack without leaving the world
Fullscreen Resolution
- Configurable fullscreen resolution
Debug
- Fast Debug Info - removes lagometer from debug screen
- Debug Profiler - removes profiler from debug screen
Time Control
- Default, Day Only or Night Only - works in only in Creative mode
Autosave
- Configurable Autosave interval
- A fix for the famous Lag Spike of Death


You need to provide the data and complete this form:
-
If you use any data generated over the course of your
NM EPSCoR
project in a publication, you need to provide the data
and complete this form.
-
If you installed instrumentation in the field for ongoing
data collection, such as a weather station or well monitoring
equipment, you need to provide that data.
-
If you performed model simulations that were or will be
used in a publication, you need to provide the model outputs
referenced in that publication. If you'd like, you can also
provide the model inputs.
-
If you performed a survey, please make sure that you
are providing anonymized data for inclusion in the
public data portal.
If you have data such as:
- text files from a logger
- text files from a piece of lab equipment
- raster outputs from a model
- spreadsheets from anonymized survey data
- proprietary data files from a piece of equipment
- a database from a geologic survey
This list is not exhaustive. If you are not sure if you need
to deliver data to NM EPSCoR, please contact
NM EPSCoR
or
EDAC for more information.
Learn more
Begin Authoring


serialver(1) serialver(1) Name serialver - The Serial Version Command The serialver command returns the serialVersionUID. SYNOPSIS serialver [ options ] [ classnames ] options Command-line options, as specified in this document. classnames One or more class names DESCRIPTION serialver returns the serialVersionUID for one or more classes in a form suitable for copying into an evolving class. When invoked with no argu‐ ments it prints a usage line. OPTIONS -classpath <directories and zip/jar files separated by :> Set search path for application classes and resources. -show Displays a simple user interface. Enter the full class name and press either the Enter key or the Show button to display the seri‐ alVersionUID. -Joption Pass option to the Java virtual machine, where option is one of the options described on the reference page for the java(1). For exam‐ ple, -J-Xms48m sets the startup memory to 48 megabytes. NOTES The serialver command loads and initializes the specified classes in its virtual machine, and by default, it does not set a security manager. If serialver is to be run with untrusted classes, a security manager can be set with the following option: -J-Djava.security.manager and, if necessary, a security policy can be specified with the following option: -J-Djava.security.policy=<policy file> SEE ALSO java.io.ObjectStreamClass @ http://docs.oracle.com/javase/7/docs/api/java/io/ObjectStreamClass.html 16 Mar 2012 serialver(1)


Computer Science graduate student at NJIT with software development experience in Java, JavaScript, Python. Highly organized and efficient in fast paced multitasking environments, able to prioritize effectively to accomplish objectives with creativity and enthusiasm. Looking forward to apply my skills and knowledge to a position where diligence, problem solving, hard working and result-based focus are valued.
Get Started!Web Tier Intern
Office Assistant


{%extends "neighbourhood/base.html"%} {% block content %}
Some Information Might be Incorrect
Are you sure you want to delete "{{object.title}}"


View frontman Kyle Falconer sells prized guitar as he starts new life abroad
The Scottish rock star has revealed he is offloading his beloved 1967 Gretsch Country Gentlemen guitar which he regularly played on stage.
by Stephen Stewart, https://www.dailyrecord.co.uk/authors/stephen-stewart/Scots rock star Kyle Falconer has revealed he is flogging one of his favourite guitars as he heads off to start a new life abroad.
The tousle-haired frontman of The View tweeted that he was selling his beloved 1967 Gretsch Country Gentlemen guitar that he played on stage with the band.
He said he was keen to see her go to a good home as he prepared to move overseas although he hasn't yet revealed where he plans to relocate to.
His tweet read: “Selling this 1967 Gretsch Country Gentlemen, in its original case, can be signed, played live with The View and solo also on Ropewalk and No Thank You albums.
“Had for 6 years, moving overseas so want her to go to a good home!!! PM for details”
Kyle and his band have a devoted following of indie rock fans.
Since bursting onto the music scene with The View’s debut album, ‘Hat’s Off to The Buskers’ in 2007, Kyle and The View have written and released five studio albums, a handful of EPs and smash hit singles including ‘Same Jeans’ and ‘Wasted Little DJs’.
More recently, he’s released his first solo album, ‘No, Thank You’ and his ‘Almost Pleasant’ EP dropped earlier this year.
He has been compared to the Gallagher brothers. Recently, he said: “I still get a bit of a judder when I see Liam or Noel Gallagher.
"We’re pals but it’s still weird talking to them. They’re just geniuses, the figureheads for an entire generation.”


You will be given a random number at the start of the game.
There are four crystals below. By clicking on a crystal you will add a specific ammount of points to
your total score.
You win the game by matching your total score to the random number; you lose the game if your total
score goes above the random number.
The value of each crystal is hidden from you until you click on it.
Each time the games starts, the values of the crystals will change.


Welcome to Random Number Guesser
I am thinking of number between 1 and 1000
Can you guess it in least amount of tries!
Try


You will be logged in again after
every 3 hours.
P.S.- If you liked the extention please show your support
by marking a star to the
repository
.
Fill form


The magnetic north pole is situated west of true north and it is currently shifting westwards. This means that magnetic declination is increasing.
Magnetic declination information is displayed at the bottom of all South African topographic map sheets. We require this information in order to calculate present-day magnetic declination and to determine magnetic bearing.
Follow these simple steps in order to determine current magnetic declination:
Step 1: Determine the difference in years between the time of measurement and the current year.
Step 2: Calculate the total annual change.
Step 3: If migration is westwards, add the total change to the original declination. If migration is eastwards, subtract the total change from the original declination.
Determine the current magnetic declination for Kruisfontein 2015.
Step 1: 2015 – 2011 = 4 years
Step 2: 6' × 4 = 24'W
Step 3: 26°58'W + 24'W = 26°82'W = 27°22'W


Triangle Tracker
First side
Second side
Third side
Submit!
The type of triangle you would have is a
!


--- layout: null permalink: /puz/ ---
Simply drag & drop a .puz file here, and I'll make you a crossword. No files will be sent to the server, this is entirely done using your modern Web browser. Note that this only currently works with the following HTML5-compatible browsers:
Note 2021-09-04: The original web app used to live at Derek Slager's site, but at some point it stopped working. I (Leo Stein) grabbed a static archived version from the Internet Archive and am mirroring it here for personal convenience. All credit goes to Derek Slager for originally developing and hosting the page.


SHAC Engine¶
The core algorithm from the paper Parallel Architecture and Hyperparameter Search via Successive Halving and Classification.
This engine provides an interface similar to Scikit-Learn, with two methods - fit
and predict
which training and parameter sampling respectively.
The data for the classifiers is generated via rejection sampling, using Joblib for parallel batch generation and evaluation. It even allows for halted training - such that training can resume from the previous stage without any issue.
Two important user inputs to this class are :
- Evaluation function
- Hyper Parameter list
Note¶
The engine will generate samples at each epoch of training, and supply them to the evaluation function which will also be executed in parallel. Therefore, all stages of sample generation, training, evaluation must be thread safe.
While the training algorithm can manage thread safety of the generator and training modules, the evaluation module is for the user to write.
Therefore, we provide wrappers such as TensorflowSHAC
, KerasSHAC
and TorchSHAC
to allow safer evaluation. However, this comes
at significant cost of execution, as a new Tensorflow Graph and likewise, a new Keras Session must be built for each evaluator thread.
Serial Evaluation
If parallel evaluation is not preferred, please refer the Serial Evaluation page.
Class Information¶
SHAC¶
pyshac.core.engine.SHAC(hyperparameter_list, total_budget, num_batches, objective='max', max_classifiers=18, save_dir='shac')
The default and generic implementation of the SHAC algorithm. It is a wrapper over the abstract class, and performs no additional maintenance over the evaluation function.
It is fastest engine, but assumes that the evaluation function is thread safe and the system has sufficient memory to run several copies of the evaluation function at the same time.
This engine is suitable for Numpy / PyTorch based work. Both numpy and PyTorch dynamically allocate memory, and therefore, as long as the system has enough memory to run multiple copies of the evaluation model, there is no additional memory management to be done.
Still, for PyTorch, the number of evaluation processes should be carefully set, so as not to exhaust all CPU / GPU memory during execution.
Arguments:
- evaluation_function ((int, list) -> float): The evaluation function is passed only the integer id (of the worker) and the sampled hyper parameters in an OrderedDict. The evaluation function is expected to pass a python floating point number representing the evaluated value.
- hyperparameter_list (hp.HyperParameterList | None): A list of parameters (or a HyperParameterList) that are passed to define the search space. Can be None, so that it is loaded from disk instead.
- total_budget (int):
N
. Defines the total number of models to evaluate. - num_batches (int):
M
. Defines the number of batches the work is distributed to. Must be set such thattotal budget
is divisible bybatch size
. - objective (str): Can be
max
ormin
. Whether to maximise the evaluation measure or minimize it. - max_classifiers (int): Maximum number of classifiers that are trained. Default (18) is according to the paper.
- save_dir (str): The base directory where the data of the engine will be stored.
References:
Raises:
- ValueError: If
total budget
is not divisible bybatch size
.
SHAC methods¶
fit¶
fit(eval_fn, skip_cv_checks=False, early_stop=False, relax_checks=False, callbacks=None)
Generated batches of samples, trains total_classifiers
number of XGBoost models
and evaluates each batch with the supplied function in parallel.
Allows manually changing the number of processes that are used to generate samples or to evaluate them. While the defaults generally work well, further performance gains can be had by trying different values according to the limits of the system.
>>> eval = lambda id, params: np.exp(params['x']) >>> shac = SHAC(params, total_budget=100, num_batches=10) >>> shac.set_num_parallel_generators(20) # change the number of generator process >>> shac.set_num_parallel_evaluators(1) # change the number of evaluator processes >>> shac.generator_backend = 'multiprocessing' # change the backend for the generator (default is `multiprocessing`) >>> shac.concurrent_evaluators() # change the backend of the evaluator to use `threading`
Has an adaptive behaviour based on what epoch it is on, since later epochs require far more number of samples to generate a single batch of samples. When the epoch number increases beyond 10, it doubles the number of generator processes.
This adaptivity can be removed by setting the parameter limit_memory
to True.
>>> shac.limit_memory = True
Arguments:
- evaluation_function ((int, list) -> float): The evaluation function is passed only the integer id (of the worker) and the sampled hyper parameters in an OrderedDict. The evaluation function is expected to pass a python floating point number representing the evaluated value.
- skip_cv_checks (bool): If set, will not perform 5 fold cross validation check on the models before adding them to the classifer list. Useful when the batch size is small.
- early_stop (bool): Stop running if fail to find a classifier that beats the last stage of evaluations.
- relax_checks (bool): If set, will allow samples who do not pass all of the checks from all classifiers. Can be useful when large number of models are present and remaining search space is not big enough to allow sample to pass through all checks.
- callbacks (list | None): Optional list of callbacks that are executed when
the engine is being trained.
History
callback is automatically added for all calls tofit
.
Returns:
A History
object which tracks all the important information
during training, and can be accessed using history.history
as a dictionary.
fit_dataset¶
fit_dataset(dataset_path, skip_cv_checks=False, early_stop=False, presort=True, callbacks=None)
Uses the provided dataset file to train the engine, instead of using the sequentual halving and classification algorithm directly. The data provided in the path must strictly follow the format of the dataset maintained by the engine.
Standard format of datasets:
Each dataset csv file must contain an integer id column named "id" as its 1st column, followed by several columns describing the values taken by the hyper parameters, and the final column must be for the the objective criterion, and must be named "scores".
The csv file must contain a header, following the above format.
Example:
id,hp1,hp2,scores 0,1,h1,1.0 1,1,h2,0.2 2,0,h1,0.0 3,0,h3,0.5 ...
Arguments:
- dataset_path (str): The full or relative path to a csv file containing the values of the dataset.
- skip_cv_checks (bool): If set, will not perform 5 fold cross validation check on the models before adding them to the classifer list. Useful when the batch size is small.
- early_stop (bool): Stop running if fail to find a classifier that beats the last stage of evaluations.
- presort (bool): Boolean flag to determine whether to sort the values of the dataset prior to loading. Ascending or descending sort is selected based on whether the engine is maximizing or minimizing the objective. It is preferable to set this always, to train better classifiers.
- callbacks (list | None): Optional list of callbacks that are executed when
the engine is being trained.
History
callback is automatically added for all calls tofit_dataset
.
Raises:
- ValueError: If the number of hyper parameters in the file are not the same as the number of hyper parameters that are available to the engine or if the number of samples in the provided dataset are less than the required number of samples by the engine.
- FileNotFoundError: If the dataset is not available at the provided filepath.
Returns:
A History
object which tracks all the important information
during training, and can be accessed using history.history
as a dictionary.
predict¶
predict(num_samples=None, num_batches=None, num_workers_per_batch=None, relax_checks=False, max_classfiers=None)
Using trained classifiers, sample the search space and predict which samples can successfully pass through the cascade of classifiers.
When using a full cascade of 18 classifiers, a vast amount of time to sample a single sample.
Sample mode vs Batch mode
Parameters can be generated in either sample mode or batch mode or any combination of the two.
num_samples
is on a per sample basis (1 sample generated per count). Can be None
or an int >= 0.
num_batches
is on a per batch basis (M samples generated per count). Can be None
or an integer >= 0.
The two are combined to produce a total number of samples which are provided in a list.
Arguments:
- num_samples (None | int): Number of samples to be generated.
- num_batches (None | int): Number of batches of samples to be generated.
- num_workers_per_batch (int): Determines how many parallel threads / processes
are created to generate the batches. For small batches, it is best to use 1.
If left as
None
, defaults tonum_parallel_generators
. - relax_checks (bool): If set, will allow samples who do not pass all of the checks from all classifiers. Can be useful when large number of models are present and remaining search space is not big enough to allow sample to pass through all checks.
- max_classfiers (int | None): Number of classifiers to use for sampling. If set to None, will use all classifiers.
Raises:
- ValueError: If
max_classifiers
is larger than the number of available classifiers. - RuntimeError: If
classifiers
are not available, either due to not being trained or not being loaded into the engine.
Returns:
batches of samples in the form of an OrderedDict
save_data¶
save_data()
Serialize the class objects by serializing the dataset and the trained models.
restore_data¶
restore_data()
Recover the serialized class objects by loading the dataset and the trained models from the default save directories.
set_num_parallel_generators¶
set_num_parallel_generators(n)
Check and sets the number of parallel generators. If None, checks if the number of workers exceeds the number of virtual cores. If it does, it warns about it and sets the max parallel generators to be the number of cores.
Arguments:
- n (int | None): The number of parallel generators required.
set_num_parallel_evaluators¶
set_num_parallel_evaluators(n)
Check and sets the number of parallel evaluators. If None, checks if the number of workers exceeds the number of virtual cores. If it does, it warns about it and sets the max parallel generators to be the number of cores.
Arguments:
- n (int | None): The number of parallel evaluators required.
parallel_evaluators¶
parallel_evaluators()
Sets the evaluators to use the loky
backend.
The user must take the responsibility of thread safety and memory management.
concurrent_evaluators¶
concurrent_evaluators()
Sets the evaluators to use the threading backend, and therefore be locked by Python's GIL.
While technically still "parallel", it is in fact concurrent execution rather than parallel execution of the evaluators.
set_seed¶
set_seed(seed)
Sets the seed of the parameters and the engine.
Arguments:
- seed (int | None): Seed value of the random state.
as_deterministic¶
as_deterministic()
Context manager that sets the seed of the parameters and the engine only inside the context block.
Arguments:
- seed (int | None): Seed value of the random state.


Javascript Data Types
Defination
The data type is a basic type of data that can be used in a program. JavaScript provides different data types to hold different types of values.
The different types of data types in JavaScript are shown below:
Primitive Data Types
- Number: It represents numeric Value
- String:Is a sequence of Characters
- Boolean:Represent Boolean value either True or False
- Undefined: It represents an undefined value
- Null: Represents no value


The current page is idle due to lack of activity. You can try to reload this page or log out of the website.


This
chapter explains how to start using i2G software and describes the I2G basic
functionality.
Learning Objectives:
· Managing your account
· A quick-start guide to the I2G user interface
· A brief description of the data structure
Step 1. Go to https://wi.i2g.cloud/
Step 2. At the Sign In the dialog, enter your Username and Password.
Figure 2‑1 Sign In dialog
Tip: Select Remember me option then i2G will
remember you for a long time and the website won’t ask you for a password
again.
Step 3. Click Sign In.
If you’re having trouble logging in, please contact your administrator
or contact us via i2g.cloud/contact-us
Step 1. Click Log Out ( ) icon at the top right of i2G page
Step 2. Click Ok at the Log Out dialog that appears
Figure 2‑2 Log Out dialog
To change your password on i2G if you're already logged in:
Step 1. Click on your account name in the top right corner (the left side of Log Out button), Change Password dialog pops up
Step 2. Enter your Old Password, New Password and Confirm Password.
Figure 2‑3 Change Password dialog
Note:
-
The New Password must contain at least 8
characters
-
The New Password and the Confirm Password must be the same
Step 3. Click Ok.
Figure 2‑4 Primary components of i2G
I2G consists
of the following primary components which are described in the section below:
·
Menu Bar for
accessing domain menus
·
The Toolbar allows you to
quickly access tools under Menu Bar
·
Pop-out windows:
§
Project Browser– Listing all
project data in the hierarchical Data tree
§
Properties Editor window – Listing
all properties of the selected object
§
Output window: Displays
messages from the system
·
Display area: Area where
all objects display such as log-plot, cross-plot, histogram, workflow, task…
The i2G Menu
Bar is located at the top of the window. Including:
·
Home
·
Data
·
Plot
·
Data Processing
·
Petrophysics
·
Geomechanics
·
Reservoir Analysis
·
Machine Learning
·
Help
Click a menu name with the left mouse button
to display the Tool Bar.
The icons at the right end of Menu Bar allow you to manage your i2G’s
account
Tip: click ( ) to
hide the Tool Bar
These icons allow you to quickly access i2G tools under the Menu Bar. You can launch modules such as Pre-Computation, Clastic, Fracture Basement, Geomechanics, FPress, SHM, ML, and others.
Figure 2‑5 Tool Bar in i2G
From Menu
Bar, click the Home tab and
choose the Project Browser. The Project Browser dock window will be
displayed on the left side of the i2G window.
The Project
Browser functionality allows the user to interpret an i2G project in a
graphical tree view interface. The view is hierarchical, similar to a typical Windows
browser.
The Project Browser displays all the data
in the project in a set of hierarchical folders. Similar or related data is
grouped together in one of several main folders. These main folders can contain
subfolders where the details for each type of data are stored.
There
are 5 areas: Wells, Log-Plot, Cross-Plot,
Histogram, and Workflow.
Figure 2‑6 Project Browser window
The Project Browse allows the user to apply
numerous actions such as data importing, data filtering, tagging at:
·
The Well level
·
The Dataset level
·
The Zone Set level
·
The Marker Set level
·
The Image Set level
·
The Variable level
The available actions in the context menu
depend on the object you select
Figure 2‑7 Context menu of the objects on data tree
From Menu
Bar, click the Home tab and
choose the Project Browser. The Properties Editor window will be displayed right under the Project Browser.
Properties Editor window displays all parameters of the selected object. Its structure may vary depending on the object being selected at that moment. Most i2G objects can be retrieved, modified, and configured from this window, including the units of a variable and parameters.
Figure 2‑8 Properties Editor window
In addition, users can also modify properties of an object from Properties dialog by double-clicking on the desired object. In this dialog, every option and setting will be displayed including advanced, complicated ones. With this, every object in the log view is fully customizable
Figure 2‑9 Track Properties dialog
Figure 2‑10 Curve properties dialog
From Menu
Bar, click the Home tab and
choose Output. The Output window will be displayed right
under the Properties Editor window.
The output window displays messages from the system including information, errors, and warnings. It allows you to diagnose issues when working in i2G
Display area: Area where all objects display such as log-plot, cross-plot, histogram, workflow, task…
Figure 2‑11 Display Area
The windows
in i2G can be moved around at your convenience. If more than one window is put
in the same location, the windows are placed on top of each other and tabs will
be shown.
If
data extends beyond the visible area, you can move it into view using the
scroll bars. The window remains open until you close the window. The dashed
double line, called a “handle”, at the top of the window indicates that the window
can be “torn off”, opening a separate window that can be placed somewhere else
on the screen.
Tip: The icons at the top right of each window
can be used to close ( ) the window or maximize ( ) the
size of that one


AMAZING PEOPLE, MAKING AMAZING DESIGNS, IN A FUN ENVIRONMENT
When you work with us, you are a part of a team of committed collaborators. All aspects of our software development process are integrated, interactive and agile.
Our approach unifies design, development and product management, to create exceptional products.
We make sure to start each project by first understanding your business goals, the users needs and the product requirements, then we help trans;ate them into effective and elegant solutions.
Before we sign a contract or write a line of code, our team will spend the necessary time needed to understand your product vision.
The outcome of this scoping session is proposals on high-level statement of work.
Based on your requirements, we can provide a complete offering, at the prices you need.
Our design practice offers a full range of services including brand strategy, interaction and visual design and user experience testing.
Throughout your project, our designers create and implement visual design and workflows, solicit user feedback and work with you to make sure what gets built is what is needed.
All engineers are fluent in the latest enterprise, mobile and web development technologies.
They collaborate with your team to write, and improve code on a daily basis, using proven practices such as test-driven development and pair programming.
Planning and development is iterative. Because we are constantly coding and testing, the products we build are always ready to go live.
This iterative process allows for changes as business requirements evolve.
(c) Delani Studio, 2020.


Question no 1
Program to take a number from user and check whether the number is even or odd
Assign the variable and log it in the console


If you disagree with your Personal Independence Payment (PIP) decision:
Discuss the decision with the Personal Independence Payment team.
Explain why you do not agree - include if you think something has been overlooked or if your circumstances have changed. The contact details will be on your decision letter.
Make a formal request to have the decision looked at again (known as ‘mandatory reconsideration’) if you still disagree.
Explain why you’re asking for a reconsideration and include more information if necessary. The contact details will be on your decision letter. You must make the request within 1 month of your decision.
Fill in a ‘Notice of appeal against a decision of the Department of Work and Pensions’ if you disagree with the mandatory reconsideration.
You must send this within 1 month of your mandatory reconsideration decision.


Help on Topics Explorer
About
This application is designed to introduce topic modeling particularly gently (e.g. for educational purpose). If you have a very large text corpus, you may wish to use more powerful tools like MALLET, which is written in Java and can be completely controlled from the command-line. The topic modeling algorithm used in this application, latent Dirichlet allocation, was implemented by Allen B. Riddell using collapsed Gibbs sampling as described in Pritchard et al. (2000).
You might want to check out some Jupyter notebooks for topic modeling in Python – experimenting with an example corpus on Binder does not require any software on your local machine.
Issues
Please use the project’s issue tracker on GitHub, but consider first checking out the troubleshooting section on the application’s website.
What is topic modeling?
- David M. Blei, Probabilisitic Topic Models, in: Communications of the ACM 55 (2012).
- Megan R. Brett, Topic Modeling, A Basic Introduction, in: Journal of Digital Humanities 2 (2012).
- Matthew Jockers and David Mimno, Significant Themes in 19th-Century Literature, in: Poetics 41 (2013).
- Steffen Pielström, Severin Simmler, Thorsten Vitt and Fotis Jannidis, A Graphical User Interface for LDA Topic Modeling, in: Proceedings of the 28th Digital Humanities Conference (2018).
What is DARIAH-DE?
DARIAH-DE supports research in the humanities and cultural sciences with digital methods and procedures. The research infrastructure of DARIAH-DE consists of four pillars: teaching, research, research data and technical components. As a partner in DARIAH-EU, DARIAH-DE helps to bundle and network state-of-the-art activities of the digital humanities. Scientists use DARIAH, for example, to make research data available across Europe. The exchange of knowledge and expertise is thus promoted across disciplines and the possibility of discovering new scientific discourses is encouraged.
This application is developed with support from the DARIAH-DE initiative, the German branch of DARIAH-EU, the European Digital Research Infrastructure for the Arts and Humanities consortium. Funding has been provided by the German Federal Ministry for Research and Education (BMBF) under the identifier 01UG1610A to J.
License
This application is licensed under Apache 2.0. You can do what you like with the source code, as long as you include the original copyright, the full text of the Apache 2.0 license, and state significant changes. You cannot charge DARIAH-DE for damages, or use any of its trademarks like name or logos.


Pong
An age-old classic.
Player 1:
0
Player 2:
0
Current Difficulty:
5
Press Space to Start. Arrow Keys to Move. R to Restart.


#include <laser_objects.hpp>
| laser_object_t::laser_object_t |
( |
std::pair< float, float > |
pos_com, |
|
|
std::pair< float, float > |
vel_com |
|
) |
| |
| laser_object_t::~laser_object_t |
( |
| ) |
|
| float laser_object_t::distance |
( |
std::pair< float, float > |
coords_to | ) |
|
| bool laser_object_t::get_is_mobile |
( |
| ) |
|
| ros::Time laser_object_t::get_last_active |
( |
| ) |
|
| std::pair< float, float > laser_object_t::get_pos_centerofmass |
( |
| ) |
|
| std::pair< float, float > laser_object_t::get_vel_centerofmass |
( |
| ) |
|
| void laser_object_t::run_kalman_filter |
( |
std::pair< float, float > |
new_pos, |
|
|
float |
dt |
|
) |
| |
| bool laser_object_t::test_mobile |
( |
| ) |
|
|
private |
| float laser_object_t::immobile_time |
|
private |
| bool laser_object_t::is_mobile |
|
private |
| arma::fmat laser_object_t::K |
|
private |
| ros::Time laser_object_t::last_active |
|
private |
| arma::fmat laser_object_t::P |
|
private |
| std::pair<float, float> laser_object_t::pos_centerofmass |
|
private |
| std::pair<float, float> laser_object_t::vel_centerofmass |
|
private |
| arma::fmat laser_object_t::X |
|
private |
The documentation for this class was generated from the following files:


Fabric Terminal is the first ever B2B mobile application that connects the fabric suppliers & garment manufacturers across the country. It is a one-stop sourcing platform where suppliers & manufacturers can directly communicate, exchange information about the rate, availability of fabric & get detailed statistics of all the activities performed. The app resolves all the hurdles in the textile industry. It provides the suppliers and manufacturers with insights into real active trends & brings them the power of technology to develop their business without being a mediator.
For more info and support, contact us!


Welcome to Mamute!
Mamute
is a website for asking and answering objective questions.
Learn more about Mamute and its rules.


R/Backfillz-Class.R
backfillz-class.Rd
An S4 class to represent a the backfillz plot object.
theme_name
Name of current theme
theme_text_family
Text family theme option for plots
theme_text_font
Text font theme option for plots
theme_text_font_colour
Text font colour theme option for plots
theme_text_cex_title
Text size title for plots
theme_text_cex_main
Text size main for plots
theme_text_cex_axis
Text size axis for plots
theme_text_col_title
Text colour title for plots
theme_text_col_main
Text colour main for plots
theme_text_col_axis
Text colour axis for plots
theme_bg_colour
Background colour theme option for plots
theme_mg_colour
Middleground colour theme option for plots
theme_fg_colour
Foregound colour option for plots
theme_alpha
Transparency option for plots
theme_palette
List of hexdecimal colours for use in plots
mcmc_samples
MCMC samples from a bayesian model fit
mcmc_model
Text definition of MCMC model
plot_history
Data frame with overall plot history
plot_store
List containing stored plots
df_slice_histogram
Slot containing data from plot_slice_histrogram function
df_trace_dial
Slot containing data from plot_slice_dial function
df_spiral_stream
Slow containing data from plot_spiral_stream function


Did Jhené Aiko Shade Ariana Grande On "None Of Your Concern" Featuring Big Sean?
by Yohance Kyles (@HUEYmixwitRILEY)Check out the Def Jam singer's collab with her ex.
(AllHipHop News) R&B vocalist Jhené Aiko has some listeners wondering if she took a subliminal shot at Pop star Ariana Grande on her new single. The speculation stems from the fact that both women once dated Big Sean.
Aiko's "None Of Your Concern" includes a line where she says, "Of course you on the scene with little miss thing, and trust me she really don't want beef." Less than four months after Sean and Jhené reportedly broke up in late 2018, he was photographed in a car with Grande.
Before that moment, Grande mentioned Sean on her #1 smash "Thank U, Next" which came out last November. The record is all about the former Nickelodeon actress' past relationships. Ariana and Sean dated for about 8 months from 2014 to 2015.
Big Sean shows up in the video for "None Of Your Concern" to croon his own verse about a lost lover. The Detroit rapper and Jhené Aiko have collaborated numerous times throughout their respective careers, including 2016's Twenty88 joint album.


Hello,I am Sishir Pokhrel. I am a junior Computer Science student currently enrolled in University of Monroe. My main center of interests lies in Cyber Security and Machine Learning. I have done few projects in those fields, and if you are interested, you can click on "My Projects" option on menu above. You can view my resume on by clicking on Online resume option on menu above which is at Second page.Please feel free to leave any comments and suggestions on Feedback page.
ABOUT ME !!!
I am from Nepal.
Do you know where it is?
It lies in the South-Eastern part of Asia on the globle.
My Achievements Includes:
Sucessfully completed ethical hacking course and passed CEH exam. My team was declared winners of Phishing Contest at ULM's InfoSec Boot Camp 2019.
Developed a program that uses a collection of existing movie reviews to assign sentiment scores to additional reviews provided as input. The program is an example of Machine Learning, a branch of computer science that studies algorithms that build models from sample inputs and use those models to make predictions or decisions. The data that the algorithm is going to “learn” from is a set of movie reviews extracted from the Rotten Tomatoes database, in which the sentiment of each review has been manually rated on a scale from 0 to 4.
(Collaborated group research in the Systems Thinking, Lean Startup, and Entrepreneurial Cognition
using mainly the seminal work and the
literature review using the google databases and online library EBSCO
databases)
(01/2017 – 05/2017)
Got included in dean's list.
(08/2016 – 08/2017)
I am currently the member of the following organizations:
- Association of Computer Machinary.
- Neplease Student Association at ULM.
- Global Ambassadors at ULM
- Rotract club of San Francisco.
Also please feel free to leave a comment/feedback on what you feel about my page.
Your feedbacks are greatly appriciated. Thank you !!!
You can join me on the social media, here.


All content provided is for informational purposes only. The articles and posts on this website are my own and don't necessarily represent the positions, strategies, or opinions of my employer or its subsidiaries. I make no representations as to the accuracy or completeness of any information found here or by following any links. I will not be liable for any errors or omissions in this information nor for the availability of this information. I will not be liable for any losses, injuries, or damages from the display or use of this information.
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JEE Mains: Everything You Need to Know
If you're planning to pursue a career in engineering, the Joint Entrance Examination (JEE) Mains is a must-take exam. Conducted by the National Testing Agency (NTA), JEE Mains is a computer-based exam that assesses a candidate's knowledge in physics, chemistry, and mathematics.
The JEE Mains exam is conducted twice a year, in January and April, and candidates can choose to appear for either or both exams. The exam is divided into two papers – Paper 1 for engineering aspirants and Paper 2 for architecture and planning aspirants.
The JEE Mains exam is a highly competitive exam, with lakhs of candidates appearing for it every year. To crack the exam, candidates need to have a strong foundation in the subjects covered and should be well-versed in problem-solving and time management skills.
JEE Mains Syllabus
The JEE Mains syllabus is based on the NCERT curriculum for classes 11 and 12. The topics covered in the exam include:
- Physics - Mechanics, Thermodynamics, Electromagnetism, Optics, and Modern PhysicsMore Details
- Chemistry - Physical Chemistry, Organic Chemistry, and Inorganic ChemistryMore Details
- Mathematics - Algebra, Trigonometry, Coordinate Geometry, Calculus, and VectorsMore Details
New JEE Mains Exam Pattern
- Section A: (Marking Scheme: Correct +4, Incorrect -1, Unanswered: 0)
Question Type: MCQs
Total Questions: 20
Questions to be Attempted: 20 - Section B: (Marking Scheme: Correct +4, Incorrect -1, Unanswered: 0)
Question Type: Numerical Value
Total Questions: 10
Questions to be Attempted: 5
Note: The total time for the paper is 3 hours.
For more information about the JEE Mains exam, please visit the official website.
JEE Mains Preparation Tips
Preparing for the JEE Mains exam requires dedication and hard work. Here are some tips that can help you crack the exam:
- Have a clear understanding of the syllabus and exam pattern
- Make a study plan and stick to it
- Practice as many sample papers and mock tests as possible
- Revise regularly and focus on your weak areas
- Stay calm and focused during the exam


vignettes/colocalize.Rmd
colocalize.Rmd
library(catalogueR)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
Here, we aim to more robustly test whether the genetic signals underlying two dataset (e.g. GWAS vs. eQTL in the same locus)are indeed the same, using a methodology called colocalization.
Specifically, we will use coloc
, which infers the probability that each SNP is causal in a given locus in each of the datasets. It then tests the hypothesis that those signals show substantially similar association distributions.
We have previously queried eQTL Catalogue using several Parkinson’s disease GWAS loci (with eQTL_Catalogue.query()
).
Let’s first gather those files and save them to disk as csv files.
query_res <- list("BST1"=catalogueR::BST1__Alasoo_2018.macrophage_IFNg,
"LRRK2"=catalogueR::LRRK2__Alasoo_2018.macrophage_IFNg,
"MEX3C"=catalogueR::MEX3C__Alasoo_2018.macrophage_IFNg
)
# select where you want to store them
storage_dir <- "catalogueR_queries/Nalls23andMe_2019"
gwas.qtl_paths <- lapply(names(query_res), function(x){
storage_path <- file.path(storage_dir,
"Alasoo_2018.macrophage_IFNg",
paste0(x,"__Alasoo_2018.macrophage_IFNg.tsv.gz"))
dir.create(dirname(storage_path), showWarnings = F, recursive = T)
data.table::fwrite(query_res[[x]], storage_path)
return(storage_path)
}) %>%unlist() %>% `names<-`(names(query_res))
coloc
has been updated so that it can now model multiple causal variants within a given dataset (see the paper), whereas previously it could assume one causal variants. Thus, it may be able to better estimate the colocalization probability between two datasets.
coloc_QTLs <- run_coloc(gwas.qtl_paths,
save_path="./coloc_results.tsv.gz",
nThread=4,
top_snp_only=T,
split_by_group=F,
method = "abf")
#> + QTL Group = Alasoo_2018.macrophage_IFNg
First, let’s plot only the results with >80% colocalization probability. This is a colocalization threshold commonly used in the field.
coloc_plot <- plot_coloc_summary(coloc_QTLs = coloc_QTLs,
PP_thresh = .8)
#> Error in plot_coloc_summary(coloc_QTLs = coloc_QTLs, PP_thresh = 0.8):
#>
#> ** No coloc tests reached the PPH4 threshold (0.8).Try lowering `PP_thresh`. **
Uh oh! Looks like there were no colocalizations at 80% probability. Let’s explore the data a bit and lower the threshold.
Indeed, two loci show mild colocalization at 50% probability. As a general rule, the more tests you do to higher your probability threshold should be, since Bayesian methods don’t calculate P-values (and this cannot used multiple-testing correction methods like FDR).
For example, if you ran many thousands of coloc test across many GWAS-eQTL pairs, it’s advisable to raise your PP threshold to .90 or even .99. This also has the benefit of narrowing down your (sometimes many!) results so that you may focus on only the strongest colocalizations.
coloc_plot <- plot_coloc_summary(coloc_QTLs = coloc_QTLs,
PP_thresh = .5)
utils::sessionInfo()
#> R version 4.0.3 (2020-10-10)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] dplyr_1.0.4 catalogueR_0.1.0
#>
#> loaded via a namespace (and not attached):
#> [1] highr_0.8 compiler_4.0.3 pillar_1.4.7 tools_4.0.3
#> [5] digest_0.6.27 evaluate_0.14 memoise_2.0.0 lifecycle_1.0.0
#> [9] tibble_3.0.6 gtable_0.3.0 pkgconfig_2.0.3 rlang_0.4.10
#> [13] DBI_1.1.1 parallel_4.0.3 yaml_2.2.1 pkgdown_1.6.1
#> [17] xfun_0.21 fastmap_1.1.0 stringr_1.4.0 knitr_1.31
#> [21] generics_0.1.0 desc_1.2.0 fs_1.5.0 vctrs_0.3.6
#> [25] systemfonts_1.0.1 rprojroot_2.0.2 grid_4.0.3 tidyselect_1.1.0
#> [29] glue_1.4.2 data.table_1.13.6 R6_2.5.0 textshaping_0.3.0
#> [33] rmarkdown_2.6 farver_2.0.3 tidyr_1.1.2 purrr_0.3.4
#> [37] ggplot2_3.3.3 magrittr_2.0.1 scales_1.1.1 htmltools_<IP_ADDRESS>
#> [41] ellipsis_0.3.1 assertthat_0.2.1 colorspace_2.0-0 labeling_0.4.2
#> [45] ragg_1.1.0 stringi_1.5.3 munsell_0.5.0 cachem_1.0.3
#> [49] crayon_1.4.1


😤 You're an employee thinking about leaving
🤯 You're a manager dealing with the person above
🤥 You're trying to skip work but still charge hours
31.5%
22.4%
Up to 50% of millennials say they would accept an offer out of the blue that offers better pay or benefits20.2%
16.5%
7.7%
1.7%
Revenue loss
Productivity loss
Creating bottlenecks
Lower employee morale
Remember that it is each of our individual responsibilites to create a strong, inclusive culture that...


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Don't worry about trying to remember every homework
assignment, project, or test—use that brainpower to
ace your classes and let Helium whip your schedule into
shape! Easily organize and color-coordinate your
schedule and schoolwork, capture details about every
assignment, and plan your study schedule. Keep track of
the details of your class, put together your necessary
supplies, and catalog things like teacher
contact info and class location.
|
|
|
|
|
|
Tired of always wondering how you're doing in a class?
Frustrated by trying to calculate your own grades?
Record grades as you get them, and Helium takes care of
the rest! A full workup of your progress is always just
a click away, with constantly up-to-date details about
your grades in every class, a breakdown of your
progression through the term, and insight into which
classes you're acing and what could use improvement.
We'll crunch the numbers for you!
|
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Remove an app setting from the .NET machine.config file.
Remove-DotNetAppSetting [-Name] <String> [-Framework] [-Framework64] [-Clr2] [-Clr4] [-WhatIf] [-Confirm] [<CommonParameters>]
The Remove-DotNetAppSetting
removes an app setting from one or more of the .NET machine.config file. The app setting can be removed from up to four different machine.config files:
Any combination of Framework and Clr switch can be used, but you MUST supply one of each.
If the app setting doesn't exist in the machine.config, nothing happens.
Remove-DotNetAppSetting
was added in Carbon 2.2.0.
| Name | Type | Description | Required? | Pipeline Input | Default Value |
|---|---|---|---|---|---|
| Name | String | The name of the app setting to remove. |
true | false | |
| Framework | SwitchParameter | Remove the app setting from a 32-bit machine.config. Must be used with one or both of the |
false | false | False |
| Framework64 | SwitchParameter | Remove the app setting from a 64-bit machine.config. Ignored if running on a 32-bit operating system. Must be used with one or both of the |
false | false | False |
| Clr2 | SwitchParameter | Remove the app setting from a .NET 2.0 machine.config. Must be used with one or both of the |
false | false | False |
| Clr4 | SwitchParameter | Remove the app setting from a .NET 4.0 machine.config. Must be used with one or both of the |
false | false | False |
| WhatIf | SwitchParameter | false | false | ||
| Confirm | SwitchParameter | false | false | ||
| CommonParameters | This cmdlet supports common parameters. For more information type Get-Help about_CommonParameters . |
Remove-DotNetAppSetting -Name ExampleUrl -Framework -Framework64 -Clr2 -Clr4
Remvoes the ExampleUrl
app setting from the following machine.config files:
%SYSTEMROOT%\Microsoft.NET\Framework\v2.0.50727\CONFIG\machine.config
%SYSTEMROOT%\Microsoft.NET\Framework64\v2.0.50727\CONFIG\machine.config
%SYSTEMROOT%\Microsoft.NET\Framework\v4.0.30319\CONFIG\machine.config
%SYSTEMROOT%\Microsoft.NET\Framework64\v4.0.30319\CONFIG\machine.config
Remove-DotNetAppSetting -Name ExampleUrl -Framework64 -Clr4
Sets the ExampleUrl app setting in the following machine.config file:
%SYSTEMROOT%\Microsoft.NET\Framework64\v4.0.30319\CONFIG\machine.config


Type Function Library media.* Return value none Revision Current Public Release (2013.2076) Keywords media, video, playback, remote video Sample code /CoronaSDK/SampleCode/media/StreamingVideo See also native.newVideo()
Plays the video at the specified path (both local and remote) in a device-specific popup Video media player.
During video playback, the media player interface takes over. If showControls
is true
(function argument), then the user can adjust playback, e.g. start, stop, seek, etc. Pass a listener to get notified when the video has ended. Note this function is asynchronous: any code that follows will be executed. After that, the application code will continue to run on iOS devices, but on Android devices the application will be suspended until the video playback is complete.
Supported video formats are platform- and version-dependent. The iPhone video player supports playback of movie files with the .mov, .mp4, .m4v, and .3gp filename extensions and using the following compression standards:
This API is not available on the Windows version of the Corona Simulator.
If the path to the video is a URL, then you must set the following permission in the "build.settings" file in order to play the video on Android.
settings =
{
android =
{
usesPermissions =
{
"android.permission.INTERNET",
},
},
}
media.playVideo( path [, baseSource ], showControls, listener )
String. The local filename or a remote URL for the video.
Constant. Optional parameter that controls how the local filename path is interpreted. It can either be one of the system-defined directory constants, or media.RemoteSource
(use this to access video on a remote server).
Boolean. If true
, then the user can adjust playback, e.g. start, stop, seek, etc.
Listener. Listener to notify when the video has ended. The listener can be either a function listener or a table listener. If listener is a table, it must have a completion method. The event dispatched to the listener will be a completion event.
local onComplete = function(event)
print( "video session ended" )
end
media.playVideo( "Movie.m4v", true, onComplete )


An extension of
paFormControl
adding functionalities for native html fields
paNativeTextField
is designed to be a base class of custom form controls.
It manages a ViewChild input or textarea html element and it
- provides controls on placeholder
- provides controls on maxLength html attribute
- allows to enable / disable browser autofill
- provides hint and error messages to the user
- focus the input programmatically
- fixes iOS issues with caret positioning
- gives access keyup event
- gives access keyup.enter event
- gives access to focus event
- gives access to blur event
- allows to 'sanitize' user input, removing html tags


6. Modeling Object Layer
6.1 Modeling ObjEntities
Java object layer in Cayenne is modeled as a set of ObjEntities
with relationships between them. Each ObjEntity consists of a reference to a
DbEntity (table). It also specifies the Java class for a business
object and a set of attributes of this class.
A default set of ObjEntities is created during reverse engineering the database.
It can be modified manually. E.g. certain entities may be excluded,
certain attributes deleted if they are not a part of object layer. Some relationships
can be "flattened" as described later in this chapter.
Modeler has a useful function that allows to update an ObjEntity after the changes were made to
an underlying DbEntity. E.g. if a new database table called PAINTING_INFO was added, and a DbEntity
created for this table, the following steps
can be taken to quickly create a corresponding ObjEntity.
- Create a new ObjEntity. Rename it to "PaintingInfo", specify the Java class.
- From the dropdown of DbEntities select "PAINTING_INFO".
- While the new entity is selected, from the "Project" menu select "Sync ObjEntity
with DbEntity" item.
- Inspect PaintingInfo attributes and relationships. A set of values matching
the underlying DbEntity should've been created.
6.1.1 ObjEntity Qualifier
ObjEntities can hold a qualifier expression that is automatically appended to all
SelectQueries rooted in a given ObjEntity. Entity qualifier can be viewed as
a global data filter for a given entity. One area where this feature is used is inheritance mapping,
however by itself it has nothing to do with inheritance as such and can be used
standalone. To set an entity qualifier, type a Cayenne expression into the "Qualifier" field of the
ObjEntity editor panel. Valid expressions grammar is described here.
|


| fkSession reference pages | |
for_each_epoch
synopsis
execute function for each epoch
syntax
result=FOR_EACH_EPOCH(rootdir,fcn)
description
result=FOR_EACH_EPOCH(rootdir,fcn) executes the specified function for
each epoch defined in rootdir/epochs/epochs.def. The signature of the
function is: result=fcn(epoch_info, ...), where epoch_info is a
structure with the name and start and end times of the epoch. The
output is a cell array with the results of the function for each
epoch.
| import_waveform | Toolbox page | import_sources_and_signals |


--- title: Grammar of Graphics (ggplot2) [Part 1] date: '2017-03-02' slug: grammar-of-graphics-ggplot2 categories: - R output: blogdown::html_page: toc: true ---
ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and none of the bad parts.
Fuel economy data from 1999 and 2008 for 38 popular models of car., see ?mpg
for details.
What is the relationship between an engine size displ
and mileage on highway hwy
?
ggplot(data = mpg) +
geom_point(aes(x = displ, y = hwy))
Aesthetic mappings aes
connect data space and visual spaces.
What is a difference between those two graphs? First guess, then try.
# Graph 1: color is in aes
ggplot(data = mpg) +
geom_point(aes(x = displ, y = hwy, color = "green"))
# Graph 2: color is out of aes
ggplot(data = mpg) +
geom_point(aes(x = displ, y = hwy), color = "green")
Why is that?
There are two functions for facets: facet_grid
(= 2D grid) and facet_wrap
(= 1D ribbon wrapped into 2D).
What will be the arrangement of the following four graphs. First guess, then try.
p <- ggplot(data = mpg) + geom_point(aes(x=displ, y=hwy))
p + facet_grid(. ~ cyl)
p + facet_grid(. ~ cyl)
p + facet_grid(drv ~ cyl)
p + facet_wrap(~ class)
Download ggplot2 Cheat Sheet to see many geoms of ggplot2.
There are many ways how to capture dependence between a car type class
and mileage hwy
.
ggplot(data = mpg, aes(x = class, y = hwy))
Try to add different geoms from cheat sheet to get different visualization. For example, adding geom_boxplot
will look like
ggplot(data = mpg, aes(x = class, y = hwy)) +
geom_boxplot()
What happens if you try to add multiple geoms? First guess, then try.
ggplot(mpg, aes(x = displ, y = hwy)) +
geom_point() +
geom_smooth()
Automatically draws a geom for each group, for example
ggplot(data = mpg, aes(x = displ, y = hwy, color = drv)) +
geom_point() +
geom_smooth(se = FALSE) # se = std. error bars
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
Try to create the following plot.
A dataset containing the prices and other attributes of almost 54,000 diamonds. Try ?diamonds
and ?View(diamonds)
.
Many geoms display not raw data but values derived from the raw data. The process that calculates the values is called stat
.
Guess what ggplot2 puts on the y axis? Try and see.
ggplot(diamonds, aes(x=cut)) +
geom_bar()
What do each of these adjustment do? (run the code and interpret)
p <- ggplot(diamonds, aes(x = cut, fill = clarity))
p + geom_bar(position = "stack")
p + geom_bar(position = "dodge")
p + geom_bar(position = "identity")
p + geom_bar(position = "fill")
Another frequent use of position argument is jittering, that is moving each point a bit in a random direction to avoid overplotting.
Compare the following two plots. The are 236 data points on the second one, but only 126 data points on the first one.
p <- ggplot(mpg, aes(displ, hwy))
p + geom_point() + ggtitle("No jittering")
p + geom_point(position = "jitter") + ggtitle("Jittered")
A pie chart is just a bar chart in polar coordinates.
ggplot(diamonds, aes(x = factor(1), fill = cut)) +
geom_bar(width = 1) +
coord_polar(theta="y") +
theme_void() # to remove grey backgroud
Read about coordinate systems on ggplot2 cheat sheet. How to you switch x and y axis to get the following graph?
There is more that one approach to ggplot2. It might be viewed as a magic set of powerful spells that you discover on StackExchange or Kaggle, memorize and later use on your dataset.
However, if your understand how ggplot2 magic works, you can become much more powerful magician.
Next time we will learn how to make ggplot2 output not to look like (grey ugly) ggplot2 output but rather something like this.


Maybe it's just me, but I reckon DSLs are the next (ok ok, they've been around for ages) big (ok, hipster) thing. I know I'm by no means the first to say so it's just that I'm increasingly bemused at seeing things squeezed into data structures they've outgrown.
In general, as everyone's finally warming to the idea that you can use code to describe not just your application but also how it's deployed, we're reaching a state where that code needs to be newbie-friendly - by which I mean that it ought to be easily understandable by humans. If it isn't, it's prone to mistakes.
A few months ago, I experimented with creating a DSL for writing web pages and I was fairly happy with the result (though there's lots more work to be done). I'm thinking of applying the same ideas to CloudFormation.
resources:
db:
type: rds
engine: mysql
size: c3.xlarge
app:
type: ec2
ami: my-app-image
size: t2.micro
scale:
min: 1
max: 10
expose: 80
security:
db: app
app: <IP_ADDRESS>:80
Obviously I've put little to no thought into the above but it shouldn't be too hard to come up with something useful.
Maybe some day soon ;)


{% extends 'index.html' %} {% block body %}
A platform for SF State students to buy and sell items
SFSU Software Engineering Project CSC 648-848 Team 02, Fall 2019. For Demonstration Only


Restart
randomized DFS
(backtracks if blocked, but usually pushes forward)
Randomized DFS with stack shaking
(you can notice it "teleporting" back and restarting
from already visited location erraticly)


Cat app
This is a app for all cat-lovers.
Play/Stop
Delay in seconds
→
The image informations are in the file
data.json


Flanked by the Nilgiris on the East and the Arabian Sea on the West, Malappuram is a district rich with evergreen forests, pristine valleys, meandering rivers and breathtaking beaches. Situated 50 km southeast of Kozhikode, Malappuram has four great rivers flowing through it, namely, the Chaliyar, the Kadalundi, the Thirurpuzha and the Bharathapuzha. The district that has a rich heritage has several examples of Indo-European architecture.
This district was the venue for many of the Mappila revolts (uprisings against the British East India Company in Kerala) between 1792 and 1921. It was also a famous centre for Hindu - Vedic learning and Islamic philosophy. The temples and mosques of this district are well known for their spectacular festivals. Along with historic monuments and diverse natural attractions, Malappuram is also famous for its cultural and ritual arts.
The region also has a network of inland waterways. The midland region is fertile with thick coconut groves while the hilly tract has dense forests and extensive teak plantations apart from the innumerable streams and rivers.
Situated 40 km from Malappur, Nilambur is famous for its teak plantations. Tourists often stop here on their way to Ooty. The oldest teak plantation of the world, the Connolly’s Plot is just 2 Kms from Nilambur town. The town also has Kannimaree, the oldest and tallest teak tree of the world. Nilambur is also home to the world’s first teak museum. The museum has information on all aspects of teak, exhibits, articles and details of the historic, aesthetic and scientific value of teak wood.
It is in Ponnani that the Nila River ends her journey by emptying out into the Arabian Sea. This scenic coastal town is counted as one of the most important fishing centres along the Malappuram Coast. One can go river rafting on the Thootha River on a raft made of wild bamboo fastened with coir ropes. Boating in the Tirur Puzha and Kootai, where you can spot migratory birds is also an enchanting experience.
Tanur was one of the oldest Portuguese settlements. St. Francis Xavier visited the place in 1546. Tanur Beach is the small fishing town of Tanur. The nearby attraction is the Keraladeshpuram temple, dedicated to Lord Vishnu. It is the oldest temple of Kerala.
The Kadalundi Bird Sanctuary is spread over a cluster of islands in a scenic area surrounded by hillocks where the Kadalundi River flows into the Arabian Sea. The place is locally known as Kadalundi Nagaram. This land is the abode of a hundred species of native birds and over 60 varieties of migratory birds that flock here in large numbers during February-March. A hillock nearby, which is 200 m above sea level, offers a splendid view of the river mouth and the sea. Kadalundi is also known for a wide variety of fish, mussels and crabs.
Padinharekara Beach is close to Ponnani and at the end of the Tipu Sulthan Road. It offers a breath taking view of the confluence of the River Bharathapuzha and Tirurpuzha with the Arabian Sea.
Kadampuzha is situated 3 km north of Vettichira on NH-17 connecting Calicut and Trissur. The temple is in Melmuri village of Tirur taluk and is famous for its Bhagavathi temple, said to have been set up by Jagadguru Sankaracharya.
This ancient temple on the banks of River Bharathapuzha is dedicated to Lord Shiva. This temple was the venue of the Mamankam festival where people adept in the martial art of Kalaripayattu used to come to fight it out.
This ancient Shiva temple with an idol is said to have been installed by Parasurama. It is situated close to the town of Tirur, and attracts devotees from far and wide.
Located 13 km from Malappuram, the small town of Kottakkal is home to Kottakkal Arya Vaidyasala, one of the best institutions of Ayurveda in the country. The institution was founded by Vaidyaratnam P.S. Warrier in 1902. The Vaidyasala runs an Ayurveda research center, a nursing home, a hospital, an Ayurveda college and a medicinal herbal garden.


Kinetic Web Page
How to:
-- Triple click to enter "Kinetic" mode then simply click and drag to move around
-- Once in "Kinetic" mode, use the scroll function from your mouse to zoom in or out
-- Triple click again to exit "Kinetic" mode
-- Triple click to enter "Kinetic" mode then simply click and drag to move around
-- Once in "Kinetic" mode, use the scroll function from your mouse to zoom in or out
-- Triple click again to exit "Kinetic" mode


Uses of Class
org.bukkit.StructureType
Package
Description
The root package of the Bukkit API, contains generalized API classes.
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Uses of StructureType in io.papermc.paper.event.world
Modifier and TypeMethodDescriptionStructureLocateEvent.getType()
Deprecated, for removal: This API element is subject to removal in a future version.Gets theStructureType
that is to be located.Modifier and TypeMethodDescriptionvoid
StructureLocateEvent.setType
(@NotNull StructureType type) Deprecated, for removal: This API element is subject to removal in a future version.Sets theStructureType
that is to be located.ModifierConstructorDescriptionStructureLocateEvent
(@NotNull World world, @NotNull Location origin, @NotNull StructureType structureType, int radius, boolean findUnexplored) Deprecated, for removal: This API element is subject to removal in a future version. -
Uses of StructureType in io.papermc.paper.world.structure
Modifier and TypeMethodDescriptionConfiguredStructure.getStructureType()
Gets the structure type for this configure structure. -
Uses of StructureType in org.bukkit
Modifier and TypeFieldDescriptionstatic final StructureType
StructureType.BASTION_REMNANT
Deprecated.Bastion remnant.static final StructureType
StructureType.BURIED_TREASURE
Deprecated.Buried treasure consists of a single chest buried in the beach sand or gravel, with random loot in it.static final StructureType
StructureType.DESERT_PYRAMID
Deprecated.Desert pyramids (also known as desert temples) are found in deserts.static final StructureType
StructureType.END_CITY
Deprecated.End Cities are tall castle-like structures that generate in the outer island of the End dimension.static final StructureType
StructureType.IGLOO
Deprecated.Igloos are structures that generate in snowy biomes.static final StructureType
StructureType.JUNGLE_PYRAMID
Deprecated.Jungle pyramids (also known as jungle temples) are found in jungles.static final StructureType
StructureType.MINESHAFT
Deprecated.Mineshafts are underground structures which consist of branching mining tunnels with wooden supports and broken rails.static final StructureType
StructureType.NETHER_FORTRESS
Deprecated.Nether fortresses are very large complexes that mainly consist of netherbricks.static final StructureType
StructureType.NETHER_FOSSIL
Deprecated.Nether fossils.static final StructureType
StructureType.OCEAN_MONUMENT
Deprecated.Ocean monuments are underwater structures.static final StructureType
StructureType.OCEAN_RUIN
Deprecated.Ocean ruins are clusters of many different blocks that generate underwater in ocean biomes (as well as on the surface of beaches).static final StructureType
StructureType.PILLAGER_OUTPOST
Deprecated.Pillager outposts may contain crossbows.static final StructureType
StructureType.RUINED_PORTAL
Deprecated.Ruined portal.static final StructureType
StructureType.SHIPWRECK
Deprecated.Shipwrecks are structures that generate on the floor of oceans or beaches.static final StructureType
StructureType.STRONGHOLD
Deprecated.Strongholds are underground structures that consist of many rooms, libraries, and an end portal room.static final StructureType
StructureType.SWAMP_HUT
Deprecated.Swamp huts (also known as witch huts) generate in swamp biomes and have the ability to spawn witches.static final StructureType
StructureType.VILLAGE
Deprecated.Villages are naturally generating structures that form above ground.static final StructureType
StructureType.WOODLAND_MANSION
Deprecated.Mansions (also known as woodland mansions) are massive house structures that generate in dark forests, containing a wide variety of rooms.Modifier and TypeMethodDescriptionstatic @NotNull Map<String,
StructureType> StructureType.getStructureTypes()
Deprecated.Get all registeredStructureType
s.Modifier and TypeMethodDescriptionBukkit.createExplorerMap
(@NotNull World world, @NotNull Location location, @NotNull StructureType structureType) Create a new explorer map targeting the closest nearby structure of a givenStructureType
.Bukkit.createExplorerMap
(@NotNull World world, @NotNull Location location, @NotNull StructureType structureType, int radius, boolean findUnexplored) Create a new explorer map targeting the closest nearby structure of a givenStructureType
.Server.createExplorerMap
(@NotNull World world, @NotNull Location location, @NotNull StructureType structureType) Create a new explorer map targeting the closest nearby structure of a givenStructureType
.Server.createExplorerMap
(@NotNull World world, @NotNull Location location, @NotNull StructureType structureType, int radius, boolean findUnexplored) Create a new explorer map targeting the closest nearby structure of a givenStructureType
.World.locateNearestStructure
(@NotNull Location origin, StructureType structureType, int radius, boolean findUnexplored) Deprecated.
World.locateNearestStructure(Location, Structure, int, boolean)
orWorld.locateNearestStructure(Location, StructureType, int, boolean)
instead.


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Map operators
Syntax:
#include <map> TYPE& operator[]( const key_type& key ); map operator=(const map& c2); bool operator==(const map& c1, const map& c2); bool operator!=(const map& c1, const map& c2); bool operator<(const map& c1, const map& c2); bool operator>(const map& c1, const map& c2); bool operator<=(const map& c1, const map& c2); bool operator>=(const map& c1, const map& c2); Maps can be compared and assigned with the standard comparison operators: ==, !=, <=, >=, <, >, and =. Individual elements of a map can be examined with the [] operator. Performing a comparison or assigning one map to another takes linear time. Two maps are equal if:
Comparisons among maps are done lexicographically. For example, the following code defines a map between strings and integers and loads values into the map using the [] operator: struct strCmp { bool operator()( const char* s1, const char* s2 ) const { return strcmp( s1, s2 ) < 0; } }; map<const char*, int, strCmp> ages; ages["Homer"] = 38; ages["Marge"] = 37; ages["Lisa"] = 8; ages["Maggie"] = 1; ages["Bart"] = 11; cout << "Bart is " << ages["Bart"] << " years old" << endl; cout << "In alphabetical order: " << endl; for( map<const char*, int, strCmp>::iterator iter = ages.begin(); iter != ages.end(); iter++ ) { cout << (*iter).first << " is " << (*iter).second << " years old" << endl; } When run, the above code displays this output: Bart is 11 years old In alphabetical order: Bart is 11 years old Homer is 38 years old Lisa is 8 years old Maggie is 1 years old Marge is 37 years old |