Table of Contents
This section will guide you though the most basic features of Boost.Build V2. We will start with the “Hello, world” example, learn how to use libraries, and finish with testing and installing features.
The simplest project that Boost.Build can construct is
stored in example/hello/
directory. The
project is described by a file
called Jamroot
that contains:
exe hello : hello.cpp ;
Even with this simple setup, you can do some interesting
things. First of all, just invoking bjam will
build the hello
executable by compiling and
linking hello.cpp
. By default, debug variant
is built. Now, to build the
release variant of hello
, invoke
bjam release
Note that debug and release variants are created in different
directories, so you can switch between variants or even build
multiple variants at once, without any unnecessary
recompilation. Let's extend the example by adding another line
to our project's Jamroot
:
exe hello2 : hello.cpp ;
Now let us build both the debug and release variants of our project again:
bjam debug release
Note that two variants of hello2
are linked.
Since we have already built both variants
of hello
, hello.cpp won't be recompiled;
instead the existing object files will just be linked into the
corresponding variants of hello2
. Now
let's remove all the built products:
bjam --clean debug release
It's also possible to build or clean specific targets. The
following two commands, respectively, build or clean only the
debug version of hello2
.
bjam hello2 bjam --clean hello2


{% load static%} {% extends 'home/base_home.html' %} {% block title %} Password Changed {% endblock %} {% block content %}
Your password has been changed successfully !


--- layout: post-update current: post-update cover: assets/images/covers/wizardcompass.jpg navigation: True title: Wizard date: 2022-01-15 10:00:00 class: post-template tags: [Mobile App, Android] author: raul subclass: 'post' category: apps ---
First screens can be helpful when opening an app, both to inform you about which permits the app will require to properly work and to show you the shortcuts to use its full potenital.
The following wizard is meant to do that job, reducing the number of steps to the minimum, and informing you at its maximum. And available in the new light/dark theme trend!
This project has been developed for a specific client. All images in this concept come from a free stock source. All icons have been designed only for this app´s usage.


About
The Impermanent Marker is a (temporary) home for writing about ephemeral and obsolescent things—a place to embrace and celebrate impermanence. It is an archiveless blog, hosting one article at a time. With each new article that is published, the previous article is deleted, never to be read again.
Anyone interested in contributing to the Impermanent Marker is encouraged to contact us by writing to<EMAIL_ADDRESS>.
The Impermanent Marker was created by Seth Mabbott .


GOLUM - Software Information
Server & Main application logic written in Typescript
Arduino Code written in C++
Github: https://github.com/Kevoot/GOLUM


Availability: ALL, but usage in a MDI environment can be problematic as the higher level debugger is not aware of breakpoints set here.
The BSH (Breakpoint Set Hardware) command sets a hardware breakpoint with an optional pass count and an optional command list.
Usage
BSH options [ size ] [ asid ] arange [ # mask ]
[ = vrange [ # mask ]] [ , [ - ]number ] [ “{“ cmd_list “}” ]
Arguments
Flag word consisting of one or more of the following letters:
I - Break on matching instruction fetch
R - Break on Data Read
W - Break on Data Write
S - Size qualifier present, break only if access matches
A - ASID qualifier present, break only if access matches
T - Generate a Tracepoint signal without stopping.
B - Break on Tracepoint (redundant unless T also given)
Description
If no pass count is specified, a value of one is assumed. If a negative pass count is specified, the breakpoint is temporary: it will be removed automatically when it is taken. The program will be interrupted each time the break address is reached number times. At that time, the command list will be executed. The actual number of hardware breakpoints available and the options which can actually be used to condition them, is dependent on the target CPU's capabilities.


IIIF Applications
IIIF Discovery in JAPAN
Subject
View
Map
View
Cesium
View
People
View
Timeline
View
iiif-universe
View


dddmp.h
dddmpInt.h
dddmpBinary.c
dddmpConvert.c
dddmpDbg.c
dddmpDdNode.c
dddmpDump.c
By: Gianpiero Cabodi & Stefano Quer
By: Gianpiero Cabodi & Stefano Quer
By: Gianpiero Cabodi and Stefano Quer
Input and output BDD codes and integers from/to file
in binary mode.
DD node codes are written as one byte. Integers of any length are written as
sequences of "linked" bytes.
For each byte 7 bits are used for data and one (MSBit) as link with
a further byte (MSB = 1 means one more byte).
Low level read/write of bytes filter filter
By: Gianpiero Cabodi and Stefano Quer
Conversion between ASCII and binary formats is presently
supported by loading a BDD in the source format and storing it
in the target one. We plan to introduce ad hoc procedures
avoiding explicit BDD node generation.
By: Gianpiero Cabodi
Functions to display BDD files in binary format
By: Gianpiero Cabodi
Functions to handle BDD node infos and numbering
By: Gianpiero Cabodi & Stefano Quer
Functions to read in and write out bdds to file. BDDs
are represended on file either in text or binary format under the
following rules. A file contains a forest of BDDs (a vector of
Boolean functions). BDD nodes are numbered with contiguous numbers,
from 1 to NNodes (total number of nodes on a file). 0 is not used to
allow negative node indexes for complemented edges. A file contains
a header, including information about variables and roots to BDD
functions, followed by the list of nodes. BDD nodes are listed
according to their numbering, and in the present implementation
numbering follows a post-order strategy, in such a way that a node
is never listed before its Then/Else children.
DddmpWriteCode()
DddmpReadCode()
DddmpWriteInt()
DddmpReadInt()
WriteByteBinary()
ReadByteBinary()
dddmpConvert.c
Conversion between ASCII and binary formats
Dddmp_Text2Bin()
Dddmp_Bin2Text()
dddmpDbg.c
Functions to display BDD files
Dddmp_cuddBddDisplayBinary()
dddmpDdNode.c
Functions to handle BDD node infos and numbering
DddmpNumberDdNodes()
DddmpUnnumberDdNodes()
DddmpWriteNodeIndex()
DddmpReadNodeIndex()
DddmpVisited()
DddmpSetVisited()
DddmpClearVisited()
NumberNodeRecur()
RemoveFromUniqueRecur()
RestoreInUniqueRecur()
dddmpDump.c
Functions to read in and write out bdds to file
Dddmp_cuddBddStore()
Dddmp_cuddBddArrayStore()
Dddmp_cuddBddLoad()
Dddmp_cuddBddArrayLoad()
StoreNodeRecur()
QsortStrcmp()
FindVarname()
Last updated on 1031103 12h03


Home
About
Blog
Contact Us
Login
Searching Number:
Khulna Ha-11-3354
Insurence date:
Expired with in (12-may-18)
Status:
Black Listed Car
Road Permit:
All over Bangladesh.
Others Document's:
Clear
Tax Remain with in date:
1200/= (12-may-18)
Apply For Case
For Details
woner of the car
Driver of the car
×
Apply For a Case
Cuse of Case
Accident
Helmet Missing
Insurence Date Expired
Road Pemit Expired
Tax Date Expired
Add to Black List
Create Case


Introduction
The app is connected with Laravel 5.5 based CMS using REST APIs, the following documentation will guide you through the process to connect the app with your backend. This guide assumes you have some experience in setting up PHP based web applications and Laravel Framework 5.5.
Setting up the server
-
Server Requirement
The server on which you are going to deploy the backend must fulfill the following requirements:
- PHP >= 7.0.0
- Mysql 5.7
- OpenSSL PHP Extension
- PDO PHP Extension
- Mbstring PHP Extension
- Tokenizer PHP Extension
- XML PHP Extension
-
Deploying Backend
Follow these steps:
- Extract the
bustracking.zip
on your server - For example if your domain is http://bustracking.com then you will be able to access the backend as http://bustracking.com/bustracking/public
- Extract the
-
Database
In accompanied source code you will find a sql file named
bustracking_multi_production.sql
. Create the database and then import the file in your database. -
Cron Job
In order to send pickup/drop reminder to parent when bus is near to location, you will need to setup a cron job on your server. Add the following line to your cron jobs list:
* * * * * php /path-to-your-project/artisan schedule:run >> /dev/null 2>&1
-
Configuration
All the major configuration values you will need to set in .env file which is present in root folder of the accompanied source code. Following are the most important values, you may set other values in .env as well if you have experience and requirment to do so:
- App related:
- APP_NAME: Title of your app
- APP_URL: Url of your backend
- Database related:
- DB_HOST: Database host, usually it’s localhost
- DB_PORT: Database port, incase of mysql it’s usually 3306
- DB_DATABASE: Database Name
- DB_USERNAME: Database username
- DB_PASSWORD: Database password
- Push Notification related:
- FCM_SERVER_KEY
- FCM_SENDER_ID
- Email Related:
Email integration is provided with Mailgun, Amazon SES, SMTP. For more details refer to https://laravel.com/docs/5.5/mail.
If you are integrating with mailgun, you can simply set following values in .env
- MAILGUN_DOMAIN
- MAILGUN_SECRET
If you need more configuration or advance setting, you can look for keys starting with MAIL_ in .env
- Logo:
- APP_LOGO: Enter the url of your logo, this logo will be displayed in backend panel
- Firebase and Google Services:
- FIREBASE_ISS: Sample value: https://securetoken.google.com/
- FIREBASE_DATABASE_URI: Sample value: https://
.firebaseio.com/ - FIREBASE_API_KEY: Sample value: AIzaSyBQgDBgxgMLaf2Xp173VIhuKVzAw_vPXSCyY
- FIREBASE_AUTH_DOMAIN: Sample value:
.firebaseapp.com - FIREBASE_PROJECT_ID: Sample value:
- FIREBASE_STORAGE_BUCKET: Sample value:
.appspot.com - FIREBASE_SENDER_ID: Sample value:<PHONE_NUMBER>82
- FIREBASE_ISS: Sample value: https://securetoken.google.com/
Mobile App
-
Setup Firebase and Api keys
- Login to http://console.firebase.google.com
- Click on “Add project” to add new project -> provide project name as you like and hit Create Project.
- Now you have to Register apps in this project. Click “Add app” -> choose platform Android
- Each app has its unique ID known as “Package name” or “ApplicationId”. For more info on how to name one visit https://developer.android.com/studio/build/application-id
- Enter package name as asked on firebase console(once for Parent’s app and Driver’s app. ps:-sequence doesnt matter).
- Set a nickname(optional, but we’ll add total of three apps so..)
- Enter your app signing certificate(Optional but important in order to make otp verification work. here is how to have one -> https://developers.google.com/android/guides/client-auth)
- Click Register app. Upon succesful registration of app you’ll be provided with your configuration file(google-services.json) for that app.
- Next click continue or skip to proceed and Repeat this step 1 more times to register app for Driver’s application
- Upon registering 2 applications in your firebase project you should have 2 applicationIds and 2 configuration files(google-services.json).
- Navigate to Database section from side menu and choose Real Time Database -> start in test mode -> Enter any dummy value so that the selection stays.
- Next click on Storage and enable it.
- Now for api keys visit https://console.cloud.google.com/cloud-resource-manager
- Select the project you just created in firebase
- Navigate to “Api and Services” section and click “ENABLE APIS AND SERVICES”
- Now Search and Enable 3 apis -> maps sdk for android, places sdk for android and directions api.
- Go to credentails and copy “Android key” and “Browser key”
-
Download/Setup Java and Android Studio
- Download Java here: https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html
- Download Android Studio here: https://developer.android.com/studio/
- Install and restart.
-
Verify installation
- Easy steps: https://www.java.com/en/download/help/path.xml
-
Running project
- Add configuration files(google-services.json) aquired from step 1 into respective project’s app folder.
- Open Android studio -> Click on “Open an existing Android Studio project” to navigate and select project.
- Open and edit app level build.gradle file (app/build.gradle)
- Set respective applicationId also aquired from firebase console in step 1.
- Enter Directions api key(Browser key) and Geo/Maps api key(Android key)
- Lastly app’s name and colors can be changed by changing variables “app_name” and colorPrimary, colorPrimaryDark and colorAccent respectively.
- Change application’s BASE_URL with your’s in file app/src/main/java/com/project/verbosetech/bustracker/network/ApiUtils.java
- Android studio will be asking you to Sync project files since build.gradle is modified. Hit “Sync now”
- Done, now you can build apk from build section in navigation menu.


Annotation results
Export JSON
Charts
Percentage of genes with annotations
Percentage of genes annotated with GSAn
Gene set similarity (GS²)
Synthetic annotation
Table
Combined tree visualization


CreatableFromJSON
protocol CreatableFromJSON
Adopted by a type that can be instantiated from JSON data.
-
Attempts to configure a new instance of the conforming type with values from a JSON dictionary.
Declaration
Swift
init?(json: [String: Any])
-
init(json:key:)
Extension methodAttempts to configure a new instance using a JSON dictionary selected by the
key
argument.Declaration
Swift
init?(json: [String: Any], key: String)
-
createRequiredInstances(from:arrayKey:)
Extension methodAttempts to produce an array of instances of the conforming type based on an array in the JSON dictionary.
Declaration
Swift
static func createRequiredInstances(from json: [String: Any], arrayKey: String) -> [Self]?
Return Value
nil
if the JSON array is missing or if there is an invalid/null element in the JSON array. -
createRequiredInstances(from:)
Extension methodAttempts to produce an array of instances of the conforming type based on an array of JSON dictionaries.
Declaration
Swift
static func createRequiredInstances(from jsonDictionaries: [[String: Any]]) -> [Self]?
Return Value
nil
if there is an invalid/null element in the JSON array. -
createOptionalInstances(from:arrayKey:)
Extension methodAttempts to produce an array of instances of the conforming type, or
nil
, based on an array in the JSON dictionary.Declaration
Swift
static func createOptionalInstances(from json: [String: Any], arrayKey: String) -> [Self?]?
Return Value
nil
if the JSON array is missing, or an array withnil
for each invalid/null element in the JSON array. -
createOptionalInstances(from:)
Extension methodAttempts to produce an array of instances of the conforming type, or
nil
, based on an array.Declaration
Swift
static func createOptionalInstances(from array: [Any]) -> [Self?]
Return Value
An array of instances of the conforming type and
nil
for each invalid/null element in the source array.


Cloud Vision V1 API - Class Google::Cloud::Vision::V1::ImageAnnotator::Client::Configuration (v0.6.4)
Reference documentation and code samples for the Cloud Vision V1 API class Google::Cloud::Vision::V1::ImageAnnotator::Client::Configuration.
Configuration class for the ImageAnnotator API.
This class represents the configuration for ImageAnnotator, providing control over timeouts, retry behavior, logging, transport parameters, and other low-level controls. Certain parameters can also be applied individually to specific RPCs. See Rpcs for a list of RPCs that can be configured independently.
Configuration can be applied globally to all clients, or to a single client on construction.
Inherits
- Object
Extended By
- Gapic::Config
Example
# Modify the global config, setting the timeout for # batch_annotate_images to 20 seconds, # and all remaining timeouts to 10 seconds. ::Google::Cloud::Vision::V1::ImageAnnotator::Client.configure do |config| config.timeout = 10.0 config.rpcs.batch_annotate_images.timeout = 20.0 end # Apply the above configuration only to a new client. client = ::Google::Cloud::Vision::V1::ImageAnnotator::Client.new do |config| config.timeout = 10.0 config.rpcs.batch_annotate_images.timeout = 20.0 end
Methods
#channel_args
def channel_args() -> ::Hash
Extra parameters passed to the gRPC channel. Note: this is ignored if a
GRPC::Core::Channel
object is provided as the credential.
- (::Hash)
#channel_args=
def channel_args=(value) -> ::Hash
Extra parameters passed to the gRPC channel. Note: this is ignored if a
GRPC::Core::Channel
object is provided as the credential.
- value (::Hash)
- (::Hash)
#credentials
def credentials() -> ::Object
Credentials to send with calls. You may provide any of the following types:
- (
String
) The path to a service account key file in JSON format - (
Hash
) A service account key as a Hash - (
Google::Auth::Credentials
) A googleauth credentials object (see the googleauth docs) - (
Signet::OAuth2::Client
) A signet oauth2 client object (see the signet docs) - (
GRPC::Core::Channel
) a gRPC channel with included credentials - (
GRPC::Core::ChannelCredentials
) a gRPC credentails object - (
nil
) indicating no credentials
- (::Object)
#credentials=
def credentials=(value) -> ::Object
Credentials to send with calls. You may provide any of the following types:
- (
String
) The path to a service account key file in JSON format - (
Hash
) A service account key as a Hash - (
Google::Auth::Credentials
) A googleauth credentials object (see the googleauth docs) - (
Signet::OAuth2::Client
) A signet oauth2 client object (see the signet docs) - (
GRPC::Core::Channel
) a gRPC channel with included credentials - (
GRPC::Core::ChannelCredentials
) a gRPC credentails object - (
nil
) indicating no credentials
- value (::Object)
- (::Object)
#endpoint
def endpoint() -> ::String
The hostname or hostname:port of the service endpoint.
Defaults to "vision.googleapis.com"
.
- (::String)
#endpoint=
def endpoint=(value) -> ::String
The hostname or hostname:port of the service endpoint.
Defaults to "vision.googleapis.com"
.
- value (::String)
- (::String)
#interceptors
def interceptors() -> ::Array<::GRPC::ClientInterceptor>
An array of interceptors that are run before calls are executed.
- (::Array<::GRPC::ClientInterceptor>)
#interceptors=
def interceptors=(value) -> ::Array<::GRPC::ClientInterceptor>
An array of interceptors that are run before calls are executed.
- value (::Array<::GRPC::ClientInterceptor>)
- (::Array<::GRPC::ClientInterceptor>)
#lib_name
def lib_name() -> ::String
The library name as recorded in instrumentation and logging
- (::String)
#lib_name=
def lib_name=(value) -> ::String
The library name as recorded in instrumentation and logging
- value (::String)
- (::String)
#lib_version
def lib_version() -> ::String
The library version as recorded in instrumentation and logging
- (::String)
#lib_version=
def lib_version=(value) -> ::String
The library version as recorded in instrumentation and logging
- value (::String)
- (::String)
#metadata
def metadata() -> ::Hash{::Symbol=>::String}
Additional gRPC headers to be sent with the call.
- (::Hash{::Symbol=>::String})
#metadata=
def metadata=(value) -> ::Hash{::Symbol=>::String}
Additional gRPC headers to be sent with the call.
- value (::Hash{::Symbol=>::String})
- (::Hash{::Symbol=>::String})
#quota_project
def quota_project() -> ::String
A separate project against which to charge quota.
- (::String)
#quota_project=
def quota_project=(value) -> ::String
A separate project against which to charge quota.
- value (::String)
- (::String)
#retry_policy
def retry_policy() -> ::Hash
The retry policy. The value is a hash with the following keys:
-
:initial_delay
(type:Numeric
) - The initial delay in seconds. -
:max_delay
(type:Numeric
) - The max delay in seconds. -
:multiplier
(type:Numeric
) - The incremental backoff multiplier. -
:retry_codes
(type:Array<String>
) - The error codes that should trigger a retry.
- (::Hash)
#retry_policy=
def retry_policy=(value) -> ::Hash
The retry policy. The value is a hash with the following keys:
-
:initial_delay
(type:Numeric
) - The initial delay in seconds. -
:max_delay
(type:Numeric
) - The max delay in seconds. -
:multiplier
(type:Numeric
) - The incremental backoff multiplier. -
:retry_codes
(type:Array<String>
) - The error codes that should trigger a retry.
- value (::Hash)
- (::Hash)
#rpcs
def rpcs() -> Rpcs
Configurations for individual RPCs
- (Rpcs)
#scope
def scope() -> ::Array<::String>
The OAuth scopes
- (::Array<::String>)
#scope=
def scope=(value) -> ::Array<::String>
The OAuth scopes
- value (::Array<::String>)
- (::Array<::String>)
#timeout
def timeout() -> ::Numeric
The call timeout in seconds.
- (::Numeric)
#timeout=
def timeout=(value) -> ::Numeric
The call timeout in seconds.
- value (::Numeric)
- (::Numeric)


unbescape is Open Source Software created in his spare time by a Spanish Software Engineer called Daniel Fernández, who's also the author of other popular java libraries like thymeleaf, attoparser, jasypt, op4j or javatuples.
It is neither made nor backed by any software (or any other type of) company, and it is offered to the public totally free of charge, both in binary and in source code forms, under the Apache License 2.0.
No, it does not. Commercial support is not offered at the moment, but there is an issue tracking system at your disposal.
Yes, all stable (non-beta) releases can be considered production-ready.
In many ways:
If you want to contribute some code to unbescape, please read first the page on Contributing to unbescape.
From time to time, unbescape will produce a snapshot release that will allow you to test new or being-developed features. These are non production ready releases, but will be stable enough for most testing purposes, and will enable you to try new features before they are generally available.
In order to use snapshot releases, you need to add the Sonatype OSS Snapshots repository in your Maven pom.xml file, like this:
<repositories> <repository> <id>sonatype-nexus-snapshots</id> <name>Sonatype Nexus Snapshots</name> <url>https://oss.sonatype.org/content/repositories/snapshots</url> <snapshots> <enabled>true</enabled> </snapshots> </repository> </repositories>
Also, you will have to modify your unbescape dependency/ies to use a snapshot version, which usually consists of the version number of the next release (not the current one), followed by -SNAPSHOT. For example, meanwhile 1.1.5.RELEASE is the latest published stable release, snapshots will probably appear under the 1.1.5-SNAPSHOT or maybe 1.2.0-SNAPSHOT version numbers:
<dependency> <groupId>org.unbescape</groupId> <artifactId>unbescape</artifactId> <version>1.1.6-SNAPSHOT</version> <scope>compile</scope> </dependency>


--- layout: %%PATH_TO_VIEWS%%/layouts/demo-project.html --- {{##content:
{{= page.request.originalUrl }}


DESFingerprint()
Syntax
Result$ = DESFingerprint(Password$, Key$)Description
Returns a DES encrypted version of the given Password$.
Parameters
Password$ The password to encrypt. It can be up to 8 characters long (all further characters are simply ignored). StringFingerprint() can be used to hash a bigger buffer. Key$ The Key$ is also known as the 'Salt' parameter, well know from Linux/Unix/BSD users. When using a 2 characters long Key$, this function returns a 'Salt2' string, compatible which any standard Linux hash password (/etc/passwd). This function is based on the open source crypt() function.
Return value
Returns the encrypted password.
Remarks
This algorithm is based on the DES (Data Encryption Standard) crypt method to generates a 13 characters string. This string is mean to be unique and non-reversible implying a strong encryption, hardly crackable when the password is correctly chosen.
Example
Debug DESFingerprint("Password", "Key007") Debug DESFingerprint("NewPass", "Key007")
See Also
StringFingerprint(), Fingerprint()
Supported OS
All


Going the Distance
During the fourth week of this program, your major task is to finish programming your player, which may go on to the finals!
By the end of this week, you should:
- Have reviewed the results of the practice Regional Competition
- Understand and be able to describe your final game strategy
- Complete your computer program and select a single entry from your whole group for submission to the Regional Competition
- Be able to work in teams to solve problems related to your game strategy and coding
Now, let's prepare your ZR game player, and explore some of the STEM content you've learned about.
Programming in Space is STEMulating!
Engage in some of these online activities to explore and reinforce the connections between programming and the STEM content you have learned about in ZR.
-
To learn more about coordinates, grids, and graphing, check out:


Analysis Report
Analysis Report - AVG dep
Analysis Report - total revenue dep
Analysis Report - total count lecturer
Analysis Report - research categories
Back to home


Vendor Name:
APPRENTISSAGE CONTINUUM LEARNING
Reference Number:
6015676
Contract Date:
2014-11-04
Description of Work:
446 Training Consultants
Contract Period:
2014-11-04 to 2014-30-09
Delivery Date:
2014-30-09
Original Contract Value:
$18,984.00
Current Contract Value:
$18,984.00
Comments:
This contract was sole-sourced.
Additional Comments:
Exam correction services related to professional development (human resources)
Former Public Servant in Receipt of a Pension under the Public Service Superannuation Act:
No


Sydney, Australia
Badu Mangroves
A boardwalk winds through this sliver of coastal nature hidden within Sydney.
The Badu Mangroves are found within the Sydney Olympic Park complex adjacent to Homebush Bay. The mangroves are surrounded by parkland and a water bird refuge, where you can see variety of shorebirds, ducks, pelicans, and small songbirds. Several shipwrecks are also present a few meters off the shore from the refuge, including the SS Ayrfield.
Before the 1990s, the mangroves were largely overlooked, as they were considered irrelevant. Industrial factories and chemical plants dumped pollution into the area, causing lasting damage. Fortunately, recent research has led people to realize how important they are for the local marine ecosystem.
There is an excellent elevated boardwalk system that’ll take you through the center of the mangroves, allowing you to experience the ecosystem without damaging the vegetation. The walkways are in excellent condition and would be accessible for both wheelchairs and strollers. To the south of the mangroves are a number of picnic areas, which include bathrooms.
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forum Visit our forums.


BREAKING: Five die in Kogi tanker fire - The Nation Newspaper
by https://www.facebook.com/CheerfulpraiseNo fewer than five people have perished in a tanker crash around the Felele axis, along the Abuja-Lokoja highway.
A petrol laden tanker coming from the Lagos end, apparently with a failed brake, crashed into five other vehicles by the NNPC Mega Station in Felele, Lokoja, Kogi State.
The incident has resulted in a protest by youths around the area.
Details shortly…


Buy the hardware, flash the firmware and connect your board to a VGA monitor and PS/2 keyboard.
Turn on the board and follow instructions on the monitor.
Use a dice or a card deck to create the needed entropy.
Copy the mnemonic generate and store it in a safe place.
You will need an ESP32 module with a VGA and PS/2 connectors. You can find on AliExpress for around 15$.
Open trentanove/trentanove.ino with Arduino IDE, configure for ESP32 board, select port and flash the firmware.
Connect a VGA monitor and PS/2 keyboard. Turn on the board and follow instructions on the monitor.


--- title: Personal website. By Pankesh Bamotra layout: page homepage: true image: src: /assets/images/location/fulfillment.jpg width: 1600 height: 1289 layout_options: hide_page_title: true class: homepage --- Hi there, I'm Pankesh. A computer vision research engineer spending the majority of time reading other people's writing. I (not often) write about computer science, life, politics, history, and public policy. Elsewhere Technical Blog – because one website is not enough Recent Articles {% include page/post-list.html limit=5 collection=site.posts %} View all posts
A computer vision research engineer spending the majority of time reading other people's writing. I (not often) write about computer science, life, politics, history, and public policy.
Technical Blog – because one website is not enough


Copyright © 2012, Oracle and/or its affiliates. All rights reserved.
821-1841-15
April 2012
500 Oracle Parkway
Redwood City, CA 94065
U.S.A.
This tutorial is a guide to developing enterprise applications for the Java Platform, Enterprise Edition 6 (Java EE 6) using GlassFish Server Open Source Edition.
Copyright and License: The Java EE 6 Tutorial
This tutorial is a guide to developing applications for the Java Platform, Enterprise Edition and contains documentation ("Tutorial") and sample code. The "sample code" made available with this Tutorial is licensed separately to you by Oracle under the Berkeley license. If you download any such sample code, you agree to the terms of the Berkeley license.
This Tutorial is provided to you by Oracle under the following license terms containing restrictions on use and disclosure and is protected by intellectual property laws. Oracle grants to you a limited, non-exclusive license to use this Tutorial for information purposes only, as an aid to learning about the Java EE platform. Except as expressly permitted in these license terms, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means this Tutorial. Reverse engineering, disassembly, or decompilation of this Tutorial is prohibited.
The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing.
If the Tutorial is licensed on behalf of the U.S. Government, the following notice is applicable:
U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. Government customers are "commercial computer software" or "commercial technical data" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, duplication, disclosure, modification, and adaptation shall be subject to the restrictions and license terms set forth in the applicable Government contract, and, to the extent applicable by the terms of the Government contract, the additional rights set forth in FAR 52.227-19, Commercial Computer Software License (December 2007). Oracle USA, Inc., 500 Oracle Parkway, Redwood City, CA 94065.
This Tutorial is not developed or intended for use in any inherently dangerous applications, including applications which may create a risk of personal injury. If you use this Tutorial in dangerous applications, then you shall be responsible to take all appropriate fail-safe, backup, redundancy, and other measures to ensure the safe use.
THE TUTORIAL IS PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND.
IN NO EVENT SHALL ORACLE BE LIABLE FOR ANY INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE OR CONSEQUENTIAL DAMAGES, OR DAMAGES FOR LOSS OF PROFITS, REVENUE, DATA OR DATA USE, INCURRED BY YOU OR ANY THIRD PARTY, WHETHER IN AN ACTION IN CONTRACT OR TORT, EVEN IF ORACLE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. ORACLE'S ENTIRE LIABILITY FOR DAMAGES HEREUNDER SHALL IN NO EVENT EXCEED ONE THOUSAND DOLLARS (U.S. $1,000).
No Technical Support
Oracle's technical support organization will not provide technical support, phone support, or updates to you.
Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners.
The sample code and Tutorial may provide access to or information on content, products, and services from third parties. Oracle Corporation and its affiliates are not responsible for and expressly disclaim all warranties of any kind with respect to third-party content, products, and services. Oracle Corporation and its affiliates will not be responsible for any loss, costs, or damages incurred due to your access to or use of third-party content, products, or services.


Opp calls APC on Nov 26
by News DeskThe joint opposition has called an all-party conference on Nov 26 to chalk out a future strategy against the ruling Pakistan Tehreek-e-Insaf (PTI).
According to media reports, Jamiat Ulema-e-Islam-Fazl (JUI-F) chief Fazlur Rehman telephoned Pakistan People’s Party (PPP) Chairman Bilawal Bhutto-Zardari and Pakistan Muslim League-Nawaz (PML-N) senior leader Ahsan Iqbal to discuss the political situation in the country, especially after the Azadi March and the departure of former prime minister Nawaz Sharif.
The two leaders agreed to set up contacts with the opposition parties to strengthen the anti-government Rehbar Committee and chalk up ‘Plan C’.
Maulana Fazlur Rehman had led a two-week protest against the government in Islamabad which began in Karachi on Oct 27 but was later called off. It was followed by a ‘Plan B’ that included blocking key roads and highways across the country but that too was called off by the opposition’s Rehbar Committee on Tuesday.


C Data Visualizations
Project Indicators by COO Community
How to Read these Plots
The following plots display a large amount of data in a visually-dense format. The indicators for each COO Community are arranged in a column; within those columns, each grid square contains the following information:
- the indicator values for each census tract (represented by a thin yellow line)
- the indicator values for all census tracts (represented by a light gray histogram chart in the grid’s background)
- the indicator value for King County (represented by a thick blue line)
- for percent indicators only: the indicator value of all of the tracts in the COO community combined (represented by a thick dashed yellow line)
Reading the plot from top to bottom, one column at a time, the viewer can see how the tracts of each community compare to each other; to the community as a whole; to the county as a whole; and to the distribution of values amongst all King County census tracts.


The Base Control chart visualizes Larva Spawning for Hatcheries and energy usage of Nexus and Orbital Commands.
Chrono Boosts
are visualized in case of
Nexus
grouped by the target building they are used on (each building has its own row) ,
Calldown: MULEs
,
Scanner Sweeps
and
Calldown: Extra Supplies
in case of
Orbital Commands
.
For
Hatcheries
the chart visualizes
larva injections
(
Spawn Larva
commands; each targeted
Hatchery
has its own row), and also calculates 2 very important metrics from the injections: the
Average Spawning Ratio
and the
Average Injection Gap
(for each
Hatchery
which is injected at least once, and a global value for all injected
Hatcheries
).
The Average Spawning Ratio is the ratio of the time a Hatchery is spawning larva compared to the time between its
first injection till the end of its last injection. The greater the better.
The Average Injection Gap is the average
time gap between time windows a Hatchery is spawning larva. The smaller the better.
${#/hu/scelight/r/html/help/fragment/event-box-tip.html}


basf
Businessmodel of BASF
Customer Segments
BASF serves more a customer base of more than 300,000, comprising businesses of all sizes, ranging from major multinational groups to independent local workshops. The Company’s five operating segments provide services targeted primarily at customers operating within the following industries:
- Agriculture, providing biotechnology and crop care products to large agricultural companies, as well as industrial and domestic urban and rural pest control products;
- Automotive and Transportation, including products for aviation and aerospace, automotive, logistics, and mass transport companies;
- Chemicals, including products for textile, cosmetics, oilfield, and construction companies;
- Energy and Resources, including products for mining, refining, metal treatment, and renewable energy companies;
- Paints and Coatings, providing chemical products for producers of industrial, architectural and decorative coatings;
- Plastics and Rubber, providing products to plastics processors. BASF includes among its customers a number of well-known brands, such as Shell, Honda, Yamaha, Sibur, and ABB.
BASF’s principal market is Europe, which accounts for around half of the Company’s sales. Europe. The Company also does significant business with customers in North America and Asia Pacific, as well more limited business with customers across South America, Africa, and Middle East.
Value Propositions
BASF provides value to its customers in the following ways:
- Its reputation and industry standing, with the Company having an established brand name in its industry, serving a number of high-profile clients such as Tesla Motors, ABB, and Honda;
- Its broad selection of products and industry reach, with the Company offering a wide range of chemicals products for companies operating across multiple sectors, including the automotive, agricultural and energy industries;
- Its global presence and sales reach, with the Company serving customers across Europe, the Americas, Asia, Africa, and the Middle East through its own facilities and its partners; and
- Its commitment to innovation and development, with the Company committing substantial financial and personnel resources to research and development activities. ### Channels
BASF operates a website at www.basf.com, through which it provides information to customers on its various services, products, and target markets. The Company also operates its own WorldAccount webshop, through which customers can access product literature, place orders and track order status.
BASF makes the majority of its sales through its own in-house direct sales teams, which are organised both by operating segment and geographic region. The Company operates through facilities across its operating regions in Europe, the Americas, Asia, Africa, and the Middle East, including offices and sites in Mexico, Canada, the US, Kazakhstan, Japan and New Zealand.
BASF also serves customers through a number of joint venture companies that typically operate on a regional basis, including co-owned entities such as Kolon Plastics in Korea and Avantim in the Netherlands.
Customer Relationships
BASF provides certain products to customers on a self-service basis through its webshop service, which allows for online ordering and account management without the need for direct interaction with BASF staff.
BASF makes its sales primarily through its own direct sales personnel, who interact closely with clients to ensure their individual requirements are met. BASF maintains close relationships with companies operating within its target industries, and positions itself globally in order that it can directly supply customers in all regions.
BASF provides personal assistance to customer throughout the sales process. It also provides product information, news and media resources, and various business publications on its website, and is able to interact with customers through its social media accounts, including with mainstream networks Facebook, Twitter and LinkedIn, as well as with Flickr and Slideshare.
Key Activities
BASF is a chemicals company. Its operations are split into five operating segments: Chemicals, comprising the Company’s consists of the Petrochemicals, Monomers and Intermediates divisions; Performance Products, comprising the Company’s the Dispersions and Pigments, Care Chemicals, Nutrition and Health, and Performance Chemicals divisions; Functional Materials and Solutions, comprising the Company’s Construction Chemicals, Coatings and Performance Materials divisions; Agricultural Solutions, comprising the Company’s Crop Protection division; and Oil & Gas, comprising the Company’s Exploration and Production division.
BASF’s product portfolio includes solvents, plasticisers, glues, and electronic chemicals, as well as materials for use in the production of detergents, plastics, textiles and paints.
Key Partners
BASF collaborates with a number of companies that support and supplement its business operations. The Company’s partners can be categorised as follows:
- Supplier Partners, comprising suppliers of resources, materials and services;
- Joint Venture Partners, with which the Company collaborates on various operations through co-owned entities; and
- Strategic and Alliance Partners, comprising a range of industrial and chemical companies, as well as academic and research organisations, with which the Company shares resources, and collaborates on joint projects. BASF has a partnership with North America Center for Research in Advanced Materials to research innovative materials for the automotive, building and construction, and energy sectors; with The California Research Alliance to develop new inorganic materials; with Meiji Seika to develop and insecticide to control biting insect pests; and with the US Department of Energy to deliver advanced battery materials.
Key Resources
BASF’s key resources are its technologies and intellectual properties, its manufacturing facilities and physical infrastructure, its supply chain, its various strategic and joint-venture partnerships, and its personnel.
BASF operates 338 production sites worldwide that are key to the Company’s operations. The Company also has a number of patents in place to protect its proprietary technologies, that are an important component of the Company’s business. In 2015 BASF filed 1,000 new patents worldwide, heading the Patent Asset Index in 2015 – which compares patent portfolios industry-wide – for the year.
Searches of records published by the US Patent and Trademark Office identified numerous applications filed in BASF’s name, including applications entitled ‘Method for producing amino acids’, Process for preparing formic acid’ and ‘Carrier system for fragrances’.
Cost Structure
BASF incurs costs in relation to its research and development activities, the operation of its production facilities – including the acquisition of supplies and consumables, the maintenance and operation of its physical infrastructure – including logistics and warehousing, the management of its partnerships and the retention of its personnel.
In 2015 BASF’s cost of materials and merchandise amounted to €37.32 billion, while its expenses for services purchased and energy costs amounted to €14.79 billion. The Company’s personnel expenses – comprising the payment of salaries and benefits to the Company’s 110,000 employees – amounted to €9.98 billion, and research and development costs were recorded at €1.95 billion.
Revenue Streams
BASF generates revenue through the sale of its portfolio of chemicals products – including intermediates, monomers, pigments, catalysts, conversions and performance chemicals – across its five operating segments.
In 2015 BASF recorded annual sales revenue of €70.45 billion, down almost €4 billion on the €74.33 billion generated by the Company in 2014. The Company’s Functional Materials and Solutions segment generated the largest portion of the Company’s sales revenue, recording annual sales of €18.52 billion. This was followed by the Performance Products, Chemicals, and Oil and Gas segments, each of which recorded more than €12 billion in sales revenue for the year.


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Super Mario Bros. is a 1985 platform video game internally developed by Nintendo EAD and published by Nintendo as a pseudo-sequel to the 1983 game Mario Bros. It was originally released in Japan for the Family Computer on September 13, 1985, and later for the Nintendo Entertainment System in North America in 1985, Europe on May 15, 1987 and Australia in 1987. It is the first of the Super Mario series of games. In Super Mario Bros., the player controls Mario and in a two-player game, a second player controls Mario's brother Luigi as he travels through the Mushroom Kingdom in order to rescue Princess Toadstool from the antagonist Bowser.
The player takes on the role of the main protagonist of the series, Mario. Mario's younger brother, Luigi, is only playable by the second player in the game's multiplayer mode, and assumes the same plot role and functionality as Mario. The objective is to race through the Mushroom Kingdom, survive the main antagonist Bowser's forces, and save Princess Toadstool. The player moves from the left side of the screen to the right side in order to reach the flag pole at the end of each level.
The game has been highly influential, popularizing the side-scrolling genre. In 2005, IGN's poll named it as The Greatest Game Of All Time. The game also sold enormously well, and was the best-selling game of all time for approximately three decades, until Wii Sports took that title. The commercial success of Super Mario Bros. has caused it to be ported to almost every one of Nintendo's major gaming consoles. Nintendo released special red variants of the Wii and Nintendo DSi XL consoles in re-packaged, Mario-themed, limited edition bundles in late 2010 as part of the 25th anniversary of the game's release.


---
layout: about
---
About me
I am a student at International Institute of Information Technology Bangalore. Currently, I am pursuing M. Tech. in Data Science.
During my academics I gained experience in Android Development, Full Stack Web-App Development, Software Development along with advance knowledge of Java, C, C++ and beginner level knowledge in python, nodejs.
I like to contribute to open source projects & I aspire to solve problems for differently able & make their life better.


NATType
and NATTypeDetection
.PortPreservingStrategy
.NATTypeDetection
object to ping the
given relay peer in order to find out the NATType
of this
Peer
.Peer
in order to find out the NAT
port assignment behavior.ChannelFuture
s
and calls the associated FutureDone
as soon as they're done.RelayUtils.encodeMessage(Message, SignatureFactory)
}.MessageUtils#decodeMessage(Buffer, InetSocketAddress, InetSocketAddress, SignatureFactory)
, but
in addition checks that the relay peers of the decoded message are set correctlyExternalAddressRequestMessage
.Dispatcher
and handles the reverse
connection at each step.HolePStrategy
.Thread
specifically for the
HolePStrategy
.MapRequestMessage
.PeerConnection
to an unreachable (behind a
NAT) peer using an active relay of the unreachable peer.HolePScheduler
.Copyright © 2016. All rights reserved.


The best way to not feel hopeless is to get up and do something. Don’t wait for good things to happen to you.
- Barack Obama
No account yet? Click me.


Default JupyterHub authenticates via Unix username/password.
from tornado import gen
from IPython.lib.security import passwd_check
from traitlets import Dict
from jupyterhub.auth import Authenticator
class DictionaryAuthenticator(Authenticator):
users = Dict(config=True, help="Map from username -> password hash.")
@gen.coroutine
def authenticate(self, handler, data):
username, password = data['username'], data['password']
try:
password_hash = self.users[username]
except KeyError:
return None
if passwd_check(password_hash, password):
return username
else:
return None
Slightly more complex:
quantopian.com/authorize
.
/authorize
HUB/oauth_callback
with "OAuth Code"./oauth_callback
quantopian.com/oauth/token
.
/oauth/token
replies with an "Access Token".
quantopian.com/api/get_resource_id/
.
/api/get_resource_id/
replies with the user's ID.
Jupyter Notebook provides a filesystem interface for storing notebooks.
Filesystem manipulation is abstracted behind by the Contents API.
Notebook server implements the Contents REST API.
Translates HTTP verbs into filesystem operations.
| Verb | Action |
|---|---|
| GET | Load Notebook |
| POST | Save Notebook |
| DELETE | Delete Notebook |
...a few extra endpoints for saving/restoring checkpoints.
{
'content': {
'metadata': {},
'nbformat': 4,
'nbformat_minor': 0,
'cells': [
{'cell_type': 'markdown',
'metadata': {},
'source': 'Some **Markdown**'},
],
},
'created': datetime(2015, 7, 25, 19, 50, 19, 19865),
'format': 'json',
'last_modified': datetime(2015, 7, 25, 19, 50, 19, 19865),
'mimetype': None,
'name': 'a.ipynb',
'path': 'foo/a.ipynb',
'type': 'notebook',
'writable': True,
}
Contents HTTP handlers dispatch to a ContentsManager
.
Default FileContentsManager
translates
requests into reads/writes to/from a local directory.
The ContentsManager
class used by the notebook application is configurable!
ContentsManager.get (path[, content, type, ...]) |
Get a model. |
ContentsManager.save (model, path) |
Save a model to path. |
ContentsManager.delete_file (path) |
Delete the file at path. |
ContentsManager.rename_file (old_path, new_path) |
Rename a file. |
ContentsManager.file_exists ([path]) |
Does a file exist at the given path? |
ContentsManager.dir_exists (path) |
Does a directory exist at the given path? |
ContentsManager.is_hidden (path) |
Is path hidden? |
PGContents
is drop-in replacement for the default FileContentsManager
.
It stores notebooks in a PostgreSQL database instead of on the filesystem.
cryptography
Package
HybridContentsManager
.
Surprisingly few...Postgres is awesome!
Most significant issue was running out of database connections.
Fixed by adding transparent connection pooling with pgbouncer.
Jupyter projects are series of increasingly-elaborate lies.
They present the illusion of talking directly to a kernel, but add layers of indirection.
We want the illusion of having a single JupyterHub, but with multiple real hubs.
We also want to embed the Hub in another web page.
We render the hub in an iframe to kill two birds with one stone.
We subclass the base JupyterHub
class to add
additional logic for registering/heartbeating with discovery:
class QuantopianJupyterHub(JupyterHub):
@gen.coroutine
def initialize(self, *args, **kwargs):
yield super().initialize(*args, **kwargs)
yield self.do_discovery_start()
# Heartbeat immediately, then register a callback to poll.
yield self.do_discovery_heartbeat()
PeriodicCallback(
self.do_discovery_heartbeat,
1e3 * self.discovery_heartbeat_interval,
).start()
@gen.coroutine
def do_discovery_heartbeat(self):
try:
yield self._make_discovery_request('heartbeat')
self.consecutive_failed_heartbeats = 0
except HTTPError as e:
self.consecutive_failed_heartbeats += 1
self.log.exception(
"Heartbeat %d failed",
self.consecutive_failed_heartbeats
)
if self.consecutive_failed_heartbeats >= \
self.consecutive_failed_heartbeats_before_shutdown:
self.log.error("Too many failed heartbeats. Shutting Down.")
self.trigger_graceful_shutdown()
raise
Quantopian is a community of authors and researchers.
Users need to be able to share and discuss their findings.
Notebooks are an ideal format for sharing exploratory research.
Two Parts:
NBExtension + Server Extension combo makes it relatively easy to add arbitrarily powerful functionality to the notebook.
Server-side APIs are generally more robust and stable.
Part of the motivation behind JupyterLab is adding more well-defined APIS for frontend extensions.
Jupyter Applications are amazingly extensible and customizable.
Extensions I didn't have time to talk about:
State is the enemy of robustness and scalability.
Lots of problems become way easier if we don't have to worry about state.
Jupyter is built on a throne of lies.
Appropriate use of indirection allows us to compose complex applications from simple parts.


Phone Directory
Add Contact
Search contact by Mobile No:
Contacts Summary
Name
Mobile
Email
Data Not Found


Single Logout will sign the user out of all Azure Active Directory sessions and not just Jenkins.
This is a security hardening that some organisations may want to enable, but is a poor user experience.
Users using applications like teams or outlook in the browser will be logged out and won't continue receiving emails and messages.


- w - Variable in class com.vividsolutions.jts.algorithm.HCoordinate
-
- warning(SAXParseException) - Method in class com.vividsolutions.jts.io.gml2.GMLHandler
-
- weightedSum(Vector2D, double) - Method in class com.vividsolutions.jts.math.Vector2D
-
Computes the weighted sum of this vector
with another vector,
with this vector contributing a fraction
of frac to the total.
- within(Geometry) - Method in class com.vividsolutions.jts.geom.Geometry
-
Tests whether this geometry is within the
specified geometry.
- within(Geometry) - Method in interface com.vividsolutions.jts.geom.prep.PreparedGeometry
-
Tests whether the base
Geometry
is within a given geometry.
- WKBConstants - Interface in com.vividsolutions.jts.io
-
Constant values used by the WKB format
- wkbGeometryCollection - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- WKBHexFileReader - Class in com.vividsolutions.jts.io
-
Reads a sequence of
Geometry
s in WKBHex format
from a text file.
- WKBHexFileReader(File, WKBReader) - Constructor for class com.vividsolutions.jts.io.WKBHexFileReader
-
Creates a new WKBHexFileReader given the File to read from
and a WKTReader to use to parse the geometries.
- WKBHexFileReader(String, WKBReader) - Constructor for class com.vividsolutions.jts.io.WKBHexFileReader
-
Creates a new WKBHexFileReader, given the name of the file to read from.
- WKBHexFileReader(Reader, WKBReader) - Constructor for class com.vividsolutions.jts.io.WKBHexFileReader
-
Creates a new WKBHexFileReader, given a Reader
to read from.
- wkbLineString - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- wkbMultiLineString - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- wkbMultiPoint - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- wkbMultiPolygon - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- wkbNDR - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- wkbPoint - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- wkbPolygon - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- WKBReader - Class in com.vividsolutions.jts.io
-
Reads a
Geometry
from a byte stream in Well-Known Binary format.
- WKBReader() - Constructor for class com.vividsolutions.jts.io.WKBReader
-
- WKBReader(GeometryFactory) - Constructor for class com.vividsolutions.jts.io.WKBReader
-
- WKBWriter - Class in com.vividsolutions.jts.io
-
Writes a
Geometry
into Well-Known Binary format.
- WKBWriter() - Constructor for class com.vividsolutions.jts.io.WKBWriter
-
Creates a writer that writes
Geometry
s with
output dimension = 2 and BIG_ENDIAN byte order
- WKBWriter(int) - Constructor for class com.vividsolutions.jts.io.WKBWriter
-
- WKBWriter(int, boolean) - Constructor for class com.vividsolutions.jts.io.WKBWriter
-
- WKBWriter(int, int) - Constructor for class com.vividsolutions.jts.io.WKBWriter
-
Creates a writer that writes
Geometry
s with
the given dimension (2 or 3) for output coordinates
and byte order
If the input geometry has a small coordinate dimension,
coordinates will be padded with
Coordinate.NULL_ORDINATE
.
- WKBWriter(int, int, boolean) - Constructor for class com.vividsolutions.jts.io.WKBWriter
-
Creates a writer that writes
Geometry
s with
the given dimension (2 or 3) for output coordinates
and byte order.
- wkbXDR - Static variable in interface com.vividsolutions.jts.io.WKBConstants
-
- WKTFileReader - Class in com.vividsolutions.jts.io
-
Reads a sequence of
Geometry
s in WKT format
from a text file.
- WKTFileReader(File, WKTReader) - Constructor for class com.vividsolutions.jts.io.WKTFileReader
-
Creates a new WKTFileReader given the File to read from
and a WKTReader to use to parse the geometries.
- WKTFileReader(String, WKTReader) - Constructor for class com.vividsolutions.jts.io.WKTFileReader
-
Creates a new WKTFileReader, given the name of the file to read from.
- WKTFileReader(Reader, WKTReader) - Constructor for class com.vividsolutions.jts.io.WKTFileReader
-
Creates a new WKTFileReader, given a Reader
to read from.
- WKTReader - Class in com.vividsolutions.jts.io
-
Converts a geometry in Well-Known Text format to a
Geometry
.
- WKTReader() - Constructor for class com.vividsolutions.jts.io.WKTReader
-
- WKTReader(GeometryFactory) - Constructor for class com.vividsolutions.jts.io.WKTReader
-
- WKTWriter - Class in com.vividsolutions.jts.io
-
Writes the Well-Known Text representation of a
Geometry
.
- WKTWriter() - Constructor for class com.vividsolutions.jts.io.WKTWriter
-
Creates a new WKTWriter with default settings
- WKTWriter(int) - Constructor for class com.vividsolutions.jts.io.WKTWriter
-
Creates a writer that writes
Geometry
s with
the given output dimension (2 or 3).
- wrap(int, int) - Static method in class com.vividsolutions.jts.math.MathUtil
-
Computes an index which wraps around a given maximum value.
- write(Geometry) - Method in class com.vividsolutions.jts.io.gml2.GMLWriter
-
Writes a
Geometry
in GML2 format to a String.
- write(Geometry, Writer) - Method in class com.vividsolutions.jts.io.gml2.GMLWriter
-
Writes a
Geometry
in GML2 format into a
Writer
.
- write(Geometry) - Method in class com.vividsolutions.jts.io.kml.KMLWriter
-
Writes a
Geometry
in KML format as a string.
- write(Geometry, Writer) - Method in class com.vividsolutions.jts.io.kml.KMLWriter
-
Writes the KML representation of a
Geometry
to a
Writer
.
- write(Geometry, StringBuffer) - Method in class com.vividsolutions.jts.io.kml.KMLWriter
-
Appends the KML representation of a
Geometry
to a
StringBuffer
.
- write(byte[], int) - Method in class com.vividsolutions.jts.io.OutputStreamOutStream
-
- write(byte[], int) - Method in interface com.vividsolutions.jts.io.OutStream
-
- write(Geometry) - Method in class com.vividsolutions.jts.io.WKBWriter
-
- write(Geometry, OutStream) - Method in class com.vividsolutions.jts.io.WKBWriter
-
- write(Geometry) - Method in class com.vividsolutions.jts.io.WKTWriter
-
Converts a Geometry
to its Well-known Text representation.
- write(Geometry, Writer) - Method in class com.vividsolutions.jts.io.WKTWriter
-
Converts a Geometry
to its Well-known Text representation.
- writeFormatted(Geometry) - Method in class com.vividsolutions.jts.io.WKTWriter
-
Same as write
, but with newlines and spaces to make the
well-known text more readable.
- writeFormatted(Geometry, Writer) - Method in class com.vividsolutions.jts.io.WKTWriter
-
Same as write
, but with newlines and spaces to make the
well-known text more readable.
- writeGeometry(Geometry, double) - Static method in class com.vividsolutions.jts.io.kml.KMLWriter
-
Writes a Geometry as KML to a string, using
a specified Z value.
- writeGeometry(Geometry, double, int, boolean, String) - Static method in class com.vividsolutions.jts.io.kml.KMLWriter
-
Writes a Geometry as KML to a string, using
a specified Z value, precision, extrude flag,
and altitude mode code.


Faceted logistic regression¶
seaborn components used: set_theme()
, load_dataset()
, lmplot()
import seaborn as sns
sns.set_theme(style="darkgrid")
# Load the example Titanic dataset
df = sns.load_dataset("titanic")
# Make a custom palette with gendered colors
pal = dict(male="#6495ED", female="#F08080")
# Show the survival probability as a function of age and sex
g = sns.lmplot(x="age", y="survived", col="sex", hue="sex", data=df,
palette=pal, y_jitter=.02, logistic=True, truncate=False)
g.set(xlim=(0, 80), ylim=(-.05, 1.05))


The DroidScript App contains a scripting engine which allows anyone with a bit of JavaScript knowledge to easily write Apps for their mobile phone or tablet. You can write very simple Apps with just a few buttons, or more complex ones which include dynamic graphical interfaces such as the DroidScript application itself, which is written using the very same engine.
As well as creating graphical interfaces, you have access to Sensors like the Accelerometer, Compass, Light meter or other device components like Wifi, Bluetooth, Camera, GPS, SD Card, SMS, Emails, Internet and more. We're always adding new functionality to the engine, so if you want something added just let us know via email or leave a comment on the forum.
When you first start DroidScript, you will see a series of icons used to run your JavaScript Apps. There will initially be a simple 'Hello World' example App here for you try. You can launch the App by simply touching the icon. After you have finished with an App, press the phone's 'back' button to return to the main screen. Long press an App's icon to see other available actions.
You can edit Apps right here on your phone or tablet using the built-in script editor by long pressing on the App's icon and selecting the 'Edit' option.
You can also edit your Apps on a PC or Mac in a browser using the built in Wifi editor, by touching the small arrow button at the top and following the instructions shown. Editing with a full size keyboard is much easier and we recommend that you use the WiFi editing for long coding sessions, especially for larger projects. The Wifi editor also allows you to easily upload image and sound resources to your App.
DroidScript comes with many sample Apps, ranging from very simple "Hello World" type Apps which show a single button to more complex ones which involve Web pages, Wifi and Phone-PC communication. It's a good idea to copy the script in one of these samples as a starting point for your own Apps. Try to find the one which best matches your requirements. Have a look at them right now!
In order to maintain the scale of graphical objects in devices with different screen resolutions and orientations, all positioning and sizing values are given as a decimal fraction of the screen width or height. For example creating a button with a width of 0.5 would make the button half the screen width and using a height of 0.1 would make the button one tenth of screen height. You can however specify -1 or leave out the width and height parameters completely on many controls if you want the control to size according to its contents.
Before starting to write your own Apps it's a good idea to read the documentation explaining 'Layouts' as these are a fundamental part of every DroidScript App.


| p: | |
| q: | |
| r: | |
| s: | |
| t: |
~A
for $\lnot{}A$[]A
for $\Box{}A$<>A
for $\Diamond{}A$(A & B)
for $(A\land{}B)$(A | B)
for $(A\lor{}B)$(A -> B)
for $(A\rightarrow{}B)$(A <-> B)
for $(A\leftrightarrow{}B)$Modal logic is a type of symbolic logic for capturing inferences about necessity and possibility. As with other logical systems, the theory lies at the intersection of mathematics and philosophy, while important applications are found within computer science and linguistics.
This app is a graphical semantic calculator for a specific kind of modal logic, modal propositional logic, which extends propositional logic but lacks quantifiers (∀ and ∃). Let's take a whirlwind tour.
To start out, let's briefly recall the language and semantics of propositional logic, i.e., connectives and truth tables.[1]
The usual connectives are the following:
| Symbol | Read as | Operation | Natural language example[2] |
|---|---|---|---|
| $\lnot$ | 'not' | negation | It is not raining. |
| $\land$ | 'and' | conjunction | It is snowing and it is cold. |
| $\lor$ | 'or' | disjunction | It is raining or it is cold. |
| $\rightarrow$ | 'if...(then)' | implication | If it is snowing, (then) it is cold. |
| $\leftrightarrow$ | 'iff' | equivalence | 3 × 2 = 6 if and only if 3 + 3 = 6. |
A typical (long-form) truth table would look something like this (using 0 for false and 1 for true):
| $p$ | $q$ | $(q\rightarrow{}p)$ | $(p\rightarrow{}(q\rightarrow{}p))$ |
|---|---|---|---|
| 0 | 0 | 1 | 1 |
| 0 | 1 | 0 | 1 |
| 1 | 0 | 1 | 1 |
| 1 | 1 | 1 | 1 |
So once we've fixed a truth value for each of the propositional variables, the truth value of any formula using those variables is deterministic.
Now, in modal logic, we add two new unary connectives to our familiar language:
| Symbol | Read as | Operation | Natural language example[2] |
|---|---|---|---|
| $\Box$ | 'box' | necessity | It must be cold outside. |
| $\Diamond$ | 'diamond' | possibility | It may be snowing. |
Semantically, these modal connectives are interpreted with respect to possible worlds. We can conceive of possible worlds in various ways, depending on what we're interested in modelling. On the one hand, possible worlds might be hypothetical 'alternate universes': there is the 'actual world', the way things really are at the present moment, as well as an infinity of other 'worlds' which differ in ways both subtle (such as a world where my pen is simply on the opposite side of my desk) and dramatic (such as a world in which dinosaurs still roam Earth in 2013 CE). Alternatively, possible worlds might be the various states of a computer, a computer program, or another system which evolves over time.
Regardless, if we have a proposition $p$ and current world $w$:
What does it mean for a world to be 'accessible'? The clearest example is surely that of a computer: an 'accessible' state is simply a successor state, one that is immediately reachable from the current state. As such, the set of all possible worlds isn't just an unstructured mess, but is ordered by an accessibility relation that says which worlds we can get to from which others.
Let's illustrate this further with an example from linguistics. When one speaks of what may or must be so, we can view this as talking about what is true in some or all possible worlds. Yet we're seldom concerned with every single possible world at once: when conversing about the current weather, things like pens and dinosaurs are typically far from one's mind. Rather, we're only concerned with a relevant subset of these possibilities—just those worlds which are accessible from the actual world via some implicit relation.
The English sentences below show three kinds of accessibility relations at work:
| Example sentence | Modality type | Accessible worlds |
|---|---|---|
| It must have rained overnight. | epistemic | worlds consistent with one's knowledge |
| You must arrive before noon. | deontic | worlds consistent with one's obligations |
| A triangle must have three vertices. | alethic | worlds consistent with logic (= all worlds) |
These sentences might be represented as $\Box{}p$, $\Box{}q$, and $\Box{}r$, but the box operator has a noticeably different interpretation in each case.
In the first case, we can imagine someone who, upon leaving their house in the morning, notices that the sidewalk is wet. Based on this observation, they conclude that it has rained overnight. Here, the worlds under consideration are just those which are consistent with the speaker's knowledge, in particular, their observation of the sidewalk. Thus the box means something like, 'Given what is known, it must be the case that...'. This 'knowledge-based' interpretation of the modal operators is known as epistemic modality.
The second sentence might be uttered by airport staff to inform a passenger of the time that their flight boards. In this case, the relevant worlds are those consistent with the passenger's obligations, namely, to get to their airplane punctually. The box here means, 'Given what is obligated, it must be the case that...'. This 'obligation-based' interpretation of the modal operators is known as deontic modality.
Finally, suppose that we remove all restrictions and let the modal operators range over every single possible world at once. But we've talked about the infinity of possible worlds—what could they possibly all have in common? One thing only: logical consistency. Under this so-called alethic modality, the box now means, 'It is logically necessary that...'. This interpretation may not be commonplace in daily conversation, but is useful for discussing mathematics, as in the third sentence: by definition, a triangle has three vertices, otherwise it wouldn't be a triangle!
Conveniently, we can view possible world semantics as an extension of truth tables. In propositional logic, we only had to fix a truth value for each propositional variable once, but in modal logic, each propositional variable can take a different truth value at each possible world. Even when two worlds have the same truth assignment, formulas with $\Box$ or $\Diamond$ might have a different truth value in each world, since the worlds accessible from each may not be the same. Thus we might say that each possible world "has its own truth table". A complete assignment of truth values to each variable at each world is known as a valuation.
Altogether, a set of possible worlds, an accessibility relation, and a valuation form a semantic model for modal logic, known as a Kripke model. A Kripke model can be visualized as a directed graph, where nodes represent worlds, the set of edges represents the accessibility relation, and the valuation is indicated by annotating each node with its truth assignment.
As a culminating example, let's take a look at the following graph, which happens to be the initial model for the app:
Using the computer program metaphor, imagine a scenario where $p$ stands for 'the program is running' and $q$ stands for 'the program has terminated'. Then state 0 of our model represents the state where the program is about to launch (neither running nor terminated), state 1 is the running (and non-terminated) state, and state 2 is the terminated (and no longer running) state. As for the accessibility relation: from the ready-to-launch state, the only option is to transition to the running state; at the running state, the program can either continue to run (the reflexive edge is indicated by a bold circle) or terminate; and the terminated state is the end of the line, so to speak.
We can then evaluate formulas based on this model. For instance, $\Diamond(p\land\lnot{}q)$ says 'there is a transition to a running-and-not-terminated state (i.e., to state 1)', or more naturally, that the program is able to run (or keep running). This formula is true at states 0 and 1 but false at state 2, which can be expressed in the following notation (the 'double turnstile' $\models$ can be read as 'satisfies' or 'makes...true'):
To see this in action, try using the app to evaluate <>(p & ~q)
at each state!
This whirlwind tour has only scratched the surface of modal logic—if you're curious to learn more, here are a few useful resources:
A freely-available, broad-scope introduction to symbolic logic. Chapters 5-7 deal with modal logic and some of its applications.
A lively Flash presentation aimed at computer scientists.
Copy the following URL to save your model for later or to share it with others:


4.10. Dynamic Programming¶
4.10.1. Dynamic Programming¶
Dynamic programming is an algorithm design technique that can improve the efficiency of any inherently recursive algorithm that repeatedly re-solves the same subproblems. Using dynamic programming requires two steps:
You find a recursive solution to a problem where subproblems are redundantly solved many times.
Optimize the recursive algorithm to eliminate re-solving subproblems. The resulting algorithm may be recursive or iterative. The iterative form is commonly referred to by the term dynamic programming.
We will see first how to remove redundancy with a simple problem, computing Fibonacci numbers. Then we introduce the knapsack problem, and show how it can be solved efficiently with dynamic programming.
4.10.2. Computing Fibonacci Numbers¶
Consider the recursive function for computing the \(n\)’th Fibonacci number.
/** Recursively generate and return the n'th Fibonacci
number */
static long fibr(int n) {
// fibr(91) is the largest value that fits in a long
if ((n <= 0) || (n > 91)) { return -1; }
if ((n == 1) || (n == 2)) { return 1; } // Base case
return fibr(n-1) + fibr(n-2); // Recursive call
}
The cost of this recursive algorithm (in terms of function calls) is the size of the \(n\)’th Fibonacci number itself, which is exponential on \(n\) (approximately \(1.62^n\) ). Why is this so expensive? Primarily because two recursive calls are made by the function, and the work that they do is largely redundant. That is, each of the two calls is recomputing most of the series, as is each sub-call, and so on. Thus, the smaller values of the function are being recomputed a huge number of times. If we could eliminate this redundancy, the cost would be greatly reduced. The approach that we will use can also improve any algorithm that spends most of its time recomputing common subproblems.
The following slideshow explains the redundancy problem.
Looking at the final tree, we see that there are only seven unique subproblems to solve (for Fibonacci values 0 through 6). The graphical representation below is called a dependency graph, and shows the dependencies for the subproblems.
Note that the dependency graph was laid out on in a one dimensional table of size seven, corresponding to the unique subproblems invoked by the algorithm. This table can simply store the value of each subproblem. In this way, redundant calls can be avoided because the value of a subproblem which was previously computed can be read from its corresponding cell in the table without the need to recompute it again.
The table can be used to derive two alternative, but efficient, algorithms. One way to accomplish this goal is to keep a table of values, and first check the table to see if the computation can be avoided. This technique is called memoization. Here is a straightforward example of doing so. Note that it mirrors the original version of the Fibonacci recursive algorithm.
static int fibrt(int n) {
// Assume Values has at least n slots, and all
// slots are initialized to 0
if ((n <= 0) || (n > 91)) { return -1; }
if (n <= 2) { return 1; } // Base case
if (Values[n] == 0) {
Values[n] = fibrt(n-1) + fibrt(n-2);
}
return Values[n];
}
This version of the algorithm will not compute a value more than once, so its cost is linear. The corresponding recursion tree is shown below. Note that the first occurrence of each recursive call invokes two recursive calls. However, subsequent occurrences of such a call do not produce additional calls because they just read the contents of its corresponding cell.
A second technique is called tabulation. The dependency graph must be analyzed to infer an alternative computation order for the subproblems. The only restriction is that a subproblem can only be computed when the subproblems it depends on have been computed. In addition, the value of each subproblem must be stored in the table. In the case of computing a value in the Fibonacci series, we reverse the order to calculate the series from the starting point, and implement this by a simple loop. Unfortunately, since it does not have any similarity to the original recursive algorithm, there is no mechanical way to get from the original recursive form to the dynamic programming form.
An additional optimization can be made. Of course, we didn’t actually need to use a table storing all of the values, since future computations do not need access to all prior subproblems. Instead, we could build the value by working from 0 and 1 up to \(n\) rather than backwards from \(n\) down to 0 and 1. Going up from the bottom we only need to store the previous two values of the function, as is done by our iterative version.
/** Iteratively generate and return the n'th Fibonacci
number */
static long fibi(int n) {
// fibr(91) is the largest value that fits in a long
if ((n <= 0) || (n > 91)) { return -1; }
long curr, prev, past;
if ((n == 1) || (n == 2)) { return 1; }
curr = prev = 1; // curr holds current Fib value
for (int i=3; i<=n; i++) { // Compute next value
past = prev; // past holds fibi(i-2)
prev = curr; // prev holds fibi(i-1)
curr = past + prev; // curr now holds fibi(i)
}
return curr;
}
Recomputing of subproblems comes up in many algorithms.
It is not so common that we can store only a few prior results as we
did for fibi
.
Thus, there are many times where storing a complete table of
subresults will be useful.
The approach shown above to designing an algorithm that works by
storing a table of results for subproblems is called
dynamic programming when it is applied to optimization
algorithms.
The name is somewhat arcane, because it doesn’t bear much obvious
similarity to the process that is taking place when storing subproblems
in a table.
However, it comes originally from the field of dynamic control
systems, which got its start before what we think of as computer
programming.
The act of storing precomputed values in a table for later reuse is
referred to as “programming” in that field.
Dynamic programming algorithms are usually implemented with the
tabulation technique described above.
Thus, fibi
better represents the most common form of dynamic
programming than does fibrt
, even though it doesn’t use the
complete table.
4.10.3. The Knapsack Problem¶
We will next consider a problem that appears with many variations in a variety of commercial settings. Many businesses need to package items with the greatest efficiency. One way to describe this basic idea is in terms of packing items into a knapsack, and so we will refer to this as the Knapsack Problem. We will first define a particular formulation of the knapsack problem, and then we will discuss an algorithm to solve it based on dynamic programming. There are many other versions for the problem. Some versions ask for the greatest amount that will fit, others introduce values to the items along with size. We will look at a fairly easy to understand variation.
Assume that we have a knapsack with a certain amount of space that we will define using integer value \(K\). We also have \(n\) items each with a certain size such that that item \(i\) has integer size \(k_i\). The problem is to find a subset of the \(n\) items whose sizes exactly sum to \(K\), if one exists. For example, if our knapsack has capacity \(K = 5\) and the two items are of size \(k_1 = 2\) and \(k_2 = 4\), then no such subset exists. But if we add a third item of size \(k_3 = 1\), then we can fill the knapsack exactly with the second and third items. We can define the problem more formally as: Find \(S \subset \{1, 2, ..., n\}\) such that
Example 4.11.1
Assume that we are given a knapsack of size \(K = 163\) and 10 items of sizes 4, 9, 15, 19, 27, 44, 54, 68, 73, 101. Can we find a subset of the items that exactly fills the knapsack? You should take a few minutes and try to do this before reading on and looking at the answer.
One solution to the problem is: 19, 27, 44, 73.
Example 4.11.2
Having solved the previous example for knapsack of size 163, how hard is it now to solve for a knapsack of size 164? Try it.
Unfortunately, knowing the answer for 163 is of almost no use at all when solving for 164. One solution is: 9, 54, 101.
If you tried solving these examples, you probably found yourself doing a lot of trial-and-error and a lot of backtracking. To come up with an algorithm, we want an organized way to go through the possible subsets. Is there a way to make the problem smaller, so that we can apply recursion? We essentially have two parts to the input: The knapsack size \(K\) and the \(n\) items. It probably will not do us much good to try and break the knapsack into pieces and solve the sub-pieces (since we already saw that knowing the answer for a knapsack of size 163 did nothing to help us solve the problem for a knapsack of size 164).
So, what can we say about solving the problem with or without the \(n\)’th item? This seems to lead to a way to break down the problem. If the \(n\)’th item is not needed for a solution (that is, if we can solve the problem with the first \(n-1\) items) then we can also solve the problem when the \(n\)’th item is available (we just ignore it). On the other hand, if we do include the \(n\)’th item as a member of the solution subset, then we now would need to solve the problem with the first \(n-1\) items and a knapsack of size \(K - k_n\) (since the \(n\)’th item is taking up \(k_n\) space in the knapsack).
To organize this process, we can define the problem in terms of two parameters: the knapsack size \(K\) and the number of items \(n\). Denote a given instance of the problem as \(P(n, K)\). Now we can say that \(P(n, K)\) has a solution if and only if there exists a solution for either \(P(n-1, K)\) or \(P(n-1, K-k_n)\). That is, we can solve \(P(n, K)\) only if we can solve one of the sub problems where we use or do not use the \(n\) th item. Of course, the ordering of the items is arbitrary. We just need to give them some order to keep things straight.
Continuing this idea, to solve any subproblem of size \(n-1\), we need only to solve two subproblems of size \(n-2\). And so on, until we are down to only one item that either fills the knapsack or not.
Continuing this idea, to solve any subproblem of size \(n-1\), we need only to solve two subproblems of size \(n-2\). And so on, until we are down to only one item that either fits the knapsack or not. Assuming that \(P(i, S)\) represents the problem for object i and after, and with size s still free in the knapsack, the following algorithm expresses the ideas.
Although this algorithm is correct, it naturally leads to a cost expressed by the recurrence relation \(\mathbf{T}(n) = 2\mathbf{T}(n-1) + c = \Theta(2^n)\). That can be pretty expensive!
But… we should quickly realize that there are only \(n(K+1)\) subproblems to solve! Clearly, there is the possibility that many subproblems are being solved repeatedly. This is a natural opportunity to apply dynamic programming. If we draw the recursion tree of this naive recursive algorithm and derive its corresponding dependency graph, we notice that all the recursive calls can be laid out on an array of size \(n \times K+1\) to contain the solutions for all subproblems \(P(i, k), 0 \leq i \leq n-1, 0 \leq k \leq K\).
Example 4.11.3
Consider the instance of the Knapsack Problem for \(K=10\) and five items with sizes 9, 2, 7, 4, 1. The recursion tree generated by the recursive algorithm follows, where each node contains the index of the object under consideration (from 0 to 4) and the size available of the knapsack.
The dependency graph for this problem instance, laid out in a table of size \(n × K + 1\), follows:
As mentioned above, there are two approaches to actually solving the problem. One is memoization, that is, to start with our problem of size \(P(n, K)\) and make recursive calls to solve the subproblems, each time checking the array to see if a subproblem has been solved, and filling in the corresponding cell in the array whenever we get a new subproblem solution. The other is tabulation. Conceivably we could adopt one of several computation orders, although the most “natural” is to start filling the array for row 0 (which indicates a successful solution only for a knapsack of size \(k_0\)). We then fill in the succeeding rows from \(i=1\) to \(n\).
In other words, a new slot in the array gets its solution by looking at most at two slots in the preceding row. Since filling each slot in the array takes constant time, the total cost of the algorithm is \(\Theta(nK)\).
Example 4.11.4
Consider again the instance of the Knapsack Problem for K=10 and five items with sizes 9, 2, 7, 4, 1. A tabulation algorithm will fill a table of size n×K+1 starting from object i=0 up to object i=4, filling all the cells in the table in a top-down fashion.
For example, \(P(2, 9)\) stores value I/O. It contains O because \(P(1, 9)\) has a solution (so, this item is not needed along that path). It contains I because \(P(1,2) = P(1, 9-7)\) has a solution (so, this item is needed along that path). Since \(P(4, 10)\) is marked with I, it has a solution. We can determine what that solution actually is by recognizing that it includes \(k_4\) (of size 1), which then leads us to look at the solution for \(P(3, 9)\). This in turn has a solution that omits \(k_3\) (of size 4), leading us to \(P(2, 9)\). At this point, we can either use item \(k_2\) or not. We can find a solution by taking one valid path through the table. We can find all solutions by following all branches when there is a choice.
Note that the table is first filled with the values of the different subproblems, and later we inferred the sequence of decisions that allows computing an optimal solution from the values stored in the table. This last phase of the algorithm precludes the possibility of actually reducing the size of the table. Otherwise, the table for the knapsack problem could have been reduced to a one dimensional array.
4.10.4. Chained Matrix Multiplication¶
Many engineering problems require multiplying a lot of matrices. Sometimes really large matrices. It turns out to make a big difference in which order we do the computation.
First, let’s recall the basics. If we have two matrices (on of \(r\) rows and \(s\) columns, and the other of \(s\) rows and \(t\) columns), then the result will be a matrix of \(r\) rows and \(t\) columns. What we really care about is that the cost of the matrix multiplication is dominated by the number of terms that have to be multipled together. Here, it would be a total cost of \(r \times s \times t\) multiplications (plus some additions that we will ignore since the time is dominated by the multiplications).
The other thing to realize is this: Of course it matters whether we multiply \(A \times B\) or \(B \times A\). But let’s assume that we already have determined the order that they go in (that it should be \(A \times B\) But we still have choices to make if there are many matrices to multiply together The thing that we need to consider is this: If we want to multiply three matrices, and we know the order, we still have a choice of how to group them. In other words, we can multiply three matrices as either \(A(BC)\) or \((AB)C\), and the answer will be the same in the end. However, as we see below, it can matter a lot which way we do this in terms of the cost of getting that answer.
To solve this problem efficiently (of how to group the order of the multiplications), we should notice that there are a lot of duplicate nodes in the recursion tree. But there are only a relatively limited number of actual subproblems to solve. For instance, we repeatedly need to decide the best order to multiply ABC. And to solve that, we repeatedly compute AB’s cost, and BC’s cost. One way to speed this up is simply to remember the answers whenever we compute them. This is called memoization. Whenever we ask the question again, we simply use the stored result. This implies that we have a good way to remember where to store them, that is, how to organize the subproblems to easily check if the problem has already been solved.
So, how do we organize the subproblems when there are \(n\) matrices to multiply, labeled 1 to \(n\)? One way is to use a table of size \(n \times n\). In this table, the entry at \([i, j]\) is the cost for the best solution of multiplying matrices \(i\) to \(j\). So, the upper left corner (entry \([1, n]\)) is the full solution. Entries on the main diagonal are simply a single matrix (no multiplication). Only the upper left triangle has entries (since there is no meaning to the cost for multiplying matrix 5 through matrix 3, only for multiplying matrix 3 through matrix 5).
Now, when we need to compute a series of matrices from \(i\) to \(j\), we just look in position \([i, j]\) in the table. If there is an answer there, we use it. Otherwise, we do the computation, and note it in the table.


An American actress and singer.
Johansson is the world's highest-paid actress, has made multiple appearances in the Forbes Celebrity 100, and has a star on the Hollywood Walk of Fame.
She aspired to be an actress from a young age, and first appeared on stage in an Off-Broadway play as a child.
生于1984年的她是当今好莱坞最具潜力的女明星之一。
1994年，主演了她的第一部影片《北》。
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Pick a Stock
Select a company of interest from one on the sites database.
Learn about the POV alg.
Learn about the Percentage of Volume algorithm.
Look at the Code
Check out the Code that powers the site and take a copy.
Dictionary
Half the battle is knowing the Jargon. Side step the technical terms.
Learn the TWAP algorithm
Learn about the Time Weighted Average Price algorithm.
Upload your Algorithm
Upload your own Algorithm via the sites exposed API.
}


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used for the purpose of targeting ads and measuring ad effectiveness on behalf of our advertisers.
Information All-Star Puzzles Collects
To enable All-Star Puzzles and its advertising agents to provide better targeting
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agents collects several types of non-personally-identifiable information about consumers who
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The type of information that All-Star Puzzles and its advertising agents can
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Your domain: e.g., .com, .net, or .edu. This is standard information that is available with all communication sent on the Internet.
Other information that All-Star Puzzles and its advertising agents can infer consists of:
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Operating system: e.g., Windows, DOS, Macintosh, or UNIX;
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Browser version and type: e.g., Netscape Navigator or Internet Explorer;
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Internet Service Provider (ISP): e.g., MindSpring or AOL;
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Clickstream information: All-Star Puzzles and its advertising agents can infer how you use the
sites and pages on the internet, and can infer your local time.
In some cases, you may voluntarily provide personal information in response to a specific ad
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If this does occur, All-Star Puzzles or its advertising agents may collect this information on behalf of an advertiser.
This information is used by an advertiser to respond to your request.
In addition, All-Star Puzzles or its agents may combine this information
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the type of individuals who view a specific type of ad or visit a particular kind of website.
Data Collection
All-Star Puzzles or its advertising agents may use "cookies" to enhance your experience on the web.
All-Star Puzzles cannot use these cookies to personally identify you in any way.
Google, as a third party vendor, uses cookies to serve ads on your site. Google's use of the DART
cookie enables it to serve ads to your users based on their visit to your sites and other sites on the Internet.
Users may opt out of the use of the DART cookie by visiting the
Google ad and content network privacy policy.
What are cookies and why do we use them?
A cookie is a unique number that is provided to you the first time a
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advertising agent utilising this technology serves you an ad. Cookies can help advertisers target ads
to you, reducing multiple ad views. While we believe cookies enhance your Internet experience
by limiting the number of times you see the same ad and delivering more relevant content to
you, they are not required for All-Star Puzzles to deliver advertising banners to you.
If you do not want the benefit of the advertiser's network cookie, there is a simple procedure to manually delete your cookies. Please consult your web browser's Help documentation for more information.
Note that All-Star Puzzles also uses cookies for implementation of the Save button.
If you have any additional questions about All-Star Puzzles dedication to consumer privacy, please contact us at
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All-Star Puzzles WORKS WITH THIRD PARTIES THAT SERVE ADS TO THIS SITE. TO FIND OUT MORE ABOUT HOW OUR ADVERTISERS MANAGE THE PRIVACY OF INFORMATION IN CONJUNCTION WITH SERVING ADS ON THIS SITE, PLEASE EMAIL US AND WE CAN PROVIDE YOU WITH THE NAMES OF OUR ADVERTISING AGENCIES.
Specific privacy information regarding our advertising with MaxOnline:
Third Party Advertising
We use MaxOnline and other third-party advertising companies to serve ads when you visit our Web site. These companies may use information (not including your name, address, email address or telephone number) about your visits to this and other Web sites in order to provide advertisements on this site and other sites about goods and services that may be of interest to you. If you would like more information about this practice and to know your choices about not having this information used by these companies, please click here
http://www.maxonline.com/privacy_policy/index.php
Third Party Cookies
In the course of serving advertisements to this site, our third-party advertiser may place or recognize a unique "cookie" on your browser.
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[
questions from twitter
]
nóva answers questions from twitter about anything. each episode is 30ish minutes long, and she will answer a question. if you have a question, ask on twitter with the hashtag #NóvaQuestions


TypeScript stands in an unusual relationship to JavaScript. TypeScript offers all of JavaScript’s features, and an additional layer on top of these: TypeScript’s type system. For example, JavaScript provides language primitives like string, number, and object, but it doesn’t check that you’ve consistently assigned these. TypeScript does. This means that your existing working JavaScript code is also TypeScript code. The main benefit of TypeScript is that it can highlight unexpected behavior in your code, lowering the chance of bugs.


Sprint Planning Poker
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Norrland Military Program
Important notice: This program was updated on 24 December 2016. If you made any calculations before this time, you will need to do them again. Sorry for any inconvenience.
List of the changes:
- The budget equation was updated to minimize the extremities.
- Some prices were updated to be more realistic.
- Blank fields when allocating funds automatically turn to 0.
- Research funding has been added.
- You can now view different countries' militaries.
Options for your nation:
- Calculate Budget
- Allocate Funds
- View Military
- Simulate Battle (coming soon!)