CreditInterest_TierBandMethod
- CalculationMethod : String
Methods of calculating interest
- Enum:
- Compound
- SimpleInterest
- Destination : String
Describes whether accrued interest is payable only to the BCA or to another bank account
- Enum:
- PayAway
- SelfCredit
- Notes : List
Optional additional notes to supplement the Tier Band Set details


Interface for all containers (vectors and matrices). More...
#include <dune/xt/la/container/container-interface.hh>
Public Types | |
| typedef ScalarImp | ScalarType |
| typedef Traits::RealType | RealType |
Public Member Functions | |
| virtual | ~ContainerInterface () |
Have to be implemented by a derived class! | |
| derived_type | copy () const |
| Creates a (deep) copy of the underlying resource. More... | |
| void | scal (const ScalarType &alpha) |
| BLAS SCAL operation (in-place sclar multiplication). More... | |
| void | axpy (const ScalarType &alpha, const derived_type &xx) |
| BLAS AXPY operation. More... | |
| bool | has_equal_shape (const derived_type &other) const |
| Test for equal sizes. More... | |
| void | ensure_uniqueness () |
Are provided by the interface for convenience! | |
| |
| virtual derived_type & | operator*= (const ScalarType &alpha) |
| static std::string | type_this () |
Interface for all containers (vectors and matrices).
| typedef Traits::RealType Dune::XT::LA::ContainerInterface< Traits, ScalarImp >::RealType |
| typedef ScalarImp Dune::XT::LA::ContainerInterface< Traits, ScalarImp >::ScalarType |
|
inlinevirtual |
|
inline |
BLAS AXPY operation.
| alpha | The scalar coefficient with which each element of the container is multiplied |
| xx | Container that is to be elementwise added. |
Referenced by Dune::XT::LA::ContainerInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::axpy().
|
inline |
Creates a (deep) copy of the underlying resource.
Referenced by Dune::XT::LA::VectorInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::add(), Dune::XT::LA::ContainerInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::copy(), Dune::XT::LA::VectorInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::operator*(), and Dune::XT::LA::VectorInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::sub().
|
inlineprotected |
|
inline |
Test for equal sizes.
| other | Container the sizes of which this is to be compared to. |
Referenced by Dune::XT::LA::ContainerInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::has_equal_shape().
|
inlinevirtual |
|
inline |
BLAS SCAL operation (in-place sclar multiplication).
| alpha | The scalar coefficient with which each element of the container is multiplied. |
Referenced by Dune::XT::LA::ContainerInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::operator*=(), and Dune::XT::LA::ContainerInterface< internal::CommonDenseVectorTraits< ScalarImp >, ScalarImp >::scal().
|
inlinestatic |


The JellySWT Library is a Jelly Library for creating Rich User Interfaces using SWT via XML markup (a Jelly script)


Linked Data is data that has been structured and published in such a way that it may be interlinked as part of the Semantic Web. In contrast to the traditional web, which is aimed at human readers, the semantic web is designed to be machine readable. It is built upon standard web technologies – HTTP, RDF, and URIs.
I’ve been working with Manchester-based Linked Data pioneers Swirrl to convert open data to linked data format. This experience has opened my eyes to the immense power of linked data. I thought it was simply a good, extensible structure with some nice web-oriented features. What I’ve actually found is some pretty fundamental differences that require quite a change in mind set.
Introduction to Linked Data
If you’re already familiar with linked-data then jump down to read about the changes in perspective it’s led me to see. If you’re new to the topic or a bit rusty then you might want to read about the basic principles first.
The recently updated RDF Primer 1.1 provides an excellent introduction to RDF. A brief summary follows.
Everything is a graph
Graphs, in the mathematical sense, are collections of nodes joined by edges. In linked-data this is described in terms of triples – statements which relate a subject to an object via a predicate:
<subject> <predicate> <object>
<Bob> <is a> <person>
<Bob> <is a friend of> <Alice>
<Bob> <is born on> <the 4th of July 1990>
These statements are typically grouped together into graphs or contexts. A quad statement has a subject, predicate, object, and context (or graph).
URIs and Literal
The subjects and predicates are all identifiers symbolic representations that a supposed to be globally unique, called uniform resource identifiers (URIs). URIs are much like URLs (Uniform Resource Locators) that you may be familiar with using to find web pages (this “finding” process – requesting a URL in your browser to get a web page in response – is more technically known as “dereferencing”). URIs are a superset of URLs which also include URNs (Uniform Resource Names) such as ISBNs (International Standard Book Numbers).
The objects can also be URIs or they can take the form of literal values (like strings, numbers and dates).
Turtle and SPARQL
There are a number of serialisation formats for RDF. By far the most readable is Turtle.
BASE <http://example.org/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX schema: <http://schema.org/>
<bob#me>
a foaf:Person ;
foaf:knows <alice#me> ;
schema:birthDate "1990-07-04"^^xsd:date ;
SPAQRL is a query language for RDF. The query below selects Bob.
SELECT ?person WHERE { ?person foaf:knows <http://example.org/alice#me> }
Thinking with a Linked Data Mindset
Now that we’ve established the basics, we can go on to consider how this perspective can lead to a different mindset.
There’s no distinction between data and metadata
Metadata is data that describes data. For example, the date a dataset was published. In traditional spreadsheets there’s not always an obvious place to put this information. It’s recorded in the filename or on a “miscellanous details” sheet. This isn’t ideal as a) it’s not generally referenceable, and b) it is easily lost if it’s not copied around with the data itself.
In RDF, metadata is stored in essentially the same way as data. It’s triples all the way down! Certainly there are some vocabularies that are designed for metadata purposes (Dublin Core, VOID, etc) but the content is described using the same structures and is amenable to the same sorts of interrogation techniques.
This makes a lot of sense when you think about it. Metadata serves two purposes: to enable discovery and to allow the recording of facts that wouldn’t otherwise fit.
Discovery is the process of finding data relevant to your interests. Metadata summarises the scope of a dataset so that we can make requests like: “show me all of the datasets published since XXXX about YYYY available on a neighbourhood level”. But this question could be answered with the data itself. The distinction between metadata and data exists in large part, because of the way we package data. That is to say we typically present data in spreadsheets where the content and scope cannot be accessed without the user first acquiring and then interpreting the data. Obviously this can’t be done in bulk unless the spreadsheets follow a common schema (some human interaction is otherwise necessary to prepare the data). If we remove the data from these packages, and allow deep inspection of it’s content, then discovery can be acheived without resorting to a separate metadata index (although metadata descriptions can still make the process more efficient).
The recording of facts that don’t fit is usually a problem for metadata because it doesn’t vary along the dimensions of the dataset in the traditional (tabular) way it’s usually present. This isn’t a problem for linked data.
The entity-relationship model doesn’t (always) fit
The capacity of entity-relationship models is demonstrated by the popularity of object-oriented programming and relational-databases. Linked-data too can represent entity-relationship very naturally. The typically problem with the ER approach is that there’s so often an exception to the rule. A given entity doesn’t fit with the others and has a few odd properties that don’t apply to everything else. Different relationships between instances of the same two types (typically recorded with primary/ foreign keys) are qualitatively different. Since in ER, information about an object is stored within it, the data model can become brittle. In linked-data, properties can be defined quite apart from objects.
There’s no schema: arbitrary data can be added anywhere
In a traditional table representation, it’s awkward to add arbitrary data. If you want to add a datum that doesn’t fit into the schema then the schema must be modified. Adding new columns for a single datum is wasteful, and quickly leads to a bloated and confusing list of seldom-used fields.
In part, this frustration gave rise to the Schemaless/ NoSQL databases. These systems sit at the other end of the scale. Without any structure it can be complex to make queries and maintain data integrity. These problems are shifted from the database to the application layer.
In a graph representation, anything can be added anywhere. The schema is in the data itself and we can decide how much structure (like constraints and datatypes) we want to add.
The data is self-describing
This flexibility – the ability to add arbitrary facts without the constriction of a schema – can certainly seem daunting. Without a schema what is going to prevent errors, provide guarantees, or ensure consistency? In fact linked-data does have a schema of sorts. Vocabularies are used to describe the data. A few popular ontologies are worth mentioning:
- RDFS: the RDF Schema extends the basic RDF vocabulary to include a class and property system.
- OWL: the Web Ontology Language is designed to represent rich and complex knowledge about things, groups of things, and relations between things
- SKOS: provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, and other similar types of controlled vocabulary.
There’s no one right way to do things
The flexibility of the data format means that there are often several ways to model the same dataset. This can lead to a sort of options-paralysis! It often pays to make a choice for the sake of progress, then review it later once more of the pieces of the puzzle are in place. Realising that it doesn’t need to be perfect first time is certainly liberating.
Naming is hard
Naming is one of the hardest problems in programming. Linked data modelling is 90% naming. The Linked Data Patterns book provides some useful suggestions for how to approach naming (URI design) in a range of contexts.
Identifiers have value: clarifying ambiguity, promoting consensus, providing reliability, ensuring stability, and facilitating integration.
Vocabularies aren’t settled
When developing a linked-data model, it’s vital to understand the work done by others before you. After all, you need to adopt other vocabularies and URIs in order to link your data to the rest of the semantic web. There are lots of alternatives. The Linked Open Vocabularies site provides a way to search and compare vocabularies to help you decide which to use.
The Linked-Data Mind Set
In summary:
- Metadata can be data too, don’t treat it as a second class citizen
- Use entities if it helps, but don’t get too hung-up on them
- Let your schema grow and change over time as you learn more about the domain
- Use the core vocabularies to bring commonly understood structure to your data
- Experiment with different models to see what works best for your data and applications
- Create identifiers – it might be hard to start with, but everybody benefits in the long-term
- Stand on the shoulders of giants – follow patterns and adopt vocabularies


sealed class ViewState<out T>
This class hold data for ViewStateStore. The data could be a Success, an Error, a Loading or None
T
- the type of the Success data
Author
Davide Giuseppe Farella
Error |
A class that represents a failure and will contains the relative throwable. Inherit from ViewState open class Error : ViewState<Nothing> |
Loading |
A class that represents the loading state and will contains Nothing Inherit from ViewState object Loading : ViewState<Nothing> |
None |
A class that represents the unknown state and will contains Nothing Inherit from ViewState object None : ViewState<Nothing> |
Success |
A class that represents the success and will contains the data Inherit from ViewState data class Success<out T> : ViewState<T> |
data |
An instance of T that will be available in case of Success, else it will be null open val data: T? |


Underline
Create a sketchy underline below an element.
Box
This style draws a box around the element.
Circle
Draw a circle around the element.
Highlight
Creates a highlight effect as if marked by a highlighter.
Strike-Through
Draw a hand-drawn line through an element creating a stroke-through effect.
Crossed-Off
To symbolize rejection, use a crossed-off effect on an element.
Brackets
Create a hand-drawn bracket around a block (like a paragraph of text) on one or multiple sides of the block.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed accumsan nisi hendrerit augue molestie tempus. Phasellus purus quam, aliquet nec commodo quis, pharetra ut orci. Donec laoreet ligula nisl, placerat molestie mauris luctus id. Fusce dapibus non libero nec lobortis. Nullam iaculis nisl ac eros consequat, sit amet placerat massa vulputate.
Multiple lines
Ability to annotate inline content that can span multiple lines
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed accumsan nisi hendrerit augue molestie tempus. Phasellus purus quam, aliquet nec commodo quis, pharetra ut orci. Donec laoreet ligula nisl, placerat molestie mauris luctus id. Fusce dapibus non libero nec lobortis. Nullam iaculis nisl ac eros consequat, sit amet placerat massa vulputate. Maecenas euismod volutpat ultrices. Pellentesque felis ex, ullamcorper in felis finibus, feugiat dignissim augue. Integer malesuada non eros consectetur interdum. Mauris mollis non urna in porta.
Annotation Group
Rough Notation provides a way to order the animation of annotations by creating an annotation-group. Pass the list of annotations to create a group. When show is called on the group, the annotations are animated in order.
Annotation Styling
Various properties of the annotation can be configured, like color, strokeWidth, animation duration.
No Animation
Of course you don't have to animate the annotation, it just shows up when show is called.


|
QuantLib: a free/open-source library for quantitative finance
Fully annotated sources - version 1.30
|
time grid class More...
#include <ql/timegrid.hpp>
Public Member Functions | |
Constructors | |
| TimeGrid ()=default | |
| TimeGrid (Time end, Size steps) | |
| Regularly spaced time-grid. More... | |
| template<class Iterator > | |
| TimeGrid (Iterator begin, Iterator end) | |
| Time grid with mandatory time points. More... | |
| template<class Iterator > | |
| TimeGrid (Iterator begin, Iterator end, Size steps) | |
| Time grid with mandatory time points. More... | |
| TimeGrid (std::initializer_list< Time > times) | |
| TimeGrid (std::initializer_list< Time > times, Size steps) | |
Time grid interface | |
| Size | index (Time t) const |
| returns the index i such that grid[i] = t More... | |
| Size | closestIndex (Time t) const |
| returns the index i such that grid[i] is closest to t More... | |
| Time | closestTime (Time t) const |
| returns the time on the grid closest to the given t More... | |
| const std::vector< Time > & | mandatoryTimes () const |
| Time | dt (Size i) const |
sequence interface | |
| typedef std::vector< Time >::const_iterator | const_iterator |
| typedef std::vector< Time >::const_reverse_iterator | const_reverse_iterator |
| std::vector< Time > | times_ |
| std::vector< Time > | dt_ |
| std::vector< Time > | mandatoryTimes_ |
| Time | operator[] (Size i) const |
| Time | at (Size i) const |
| Size | size () const |
| bool | empty () const |
| const_iterator | begin () const |
| const_iterator | end () const |
| const_reverse_iterator | rbegin () const |
| const_reverse_iterator | rend () const |
| Time | front () const |
| Time | back () const |
| typedef std::vector<Time>::const_iterator const_iterator |
Definition at line 158 of file timegrid.hpp.
| typedef std::vector<Time>::const_reverse_iterator const_reverse_iterator |
Definition at line 160 of file timegrid.hpp.
|
default |
Regularly spaced time-grid.
Definition at line 26 of file timegrid.cpp.
| TimeGrid | ( | Iterator | begin, |
| Iterator | end | ||
| ) |
Time grid with mandatory time points.
Mandatory points are guaranteed to belong to the grid. No additional points are added.
Definition at line 55 of file timegrid.hpp.
Time grid with mandatory time points.
Mandatory points are guaranteed to belong to the grid. Additional points are then added with regular spacing between pairs of mandatory times in order to reach the desired number of steps.
Definition at line 86 of file timegrid.hpp.
Definition at line 136 of file timegrid.hpp.
Definition at line 138 of file timegrid.hpp.
returns the index i such that grid[i] = t
Definition at line 43 of file timegrid.cpp.
returns the index i such that grid[i] is closest to t
Definition at line 80 of file timegrid.cpp.
returns the time on the grid closest to the given t
Definition at line 148 of file timegrid.hpp.
| const std::vector< Time > & mandatoryTimes | ( | ) | const |
Definition at line 162 of file timegrid.hpp.
| Size size | ( | ) | const |
| bool empty | ( | ) | const |
| const_iterator begin | ( | ) | const |
| const_iterator end | ( | ) | const |
| const_reverse_iterator rbegin | ( | ) | const |
Definition at line 168 of file timegrid.hpp.
| const_reverse_iterator rend | ( | ) | const |
Definition at line 169 of file timegrid.hpp.
| Time front | ( | ) | const |
| Time back | ( | ) | const |
|
private |
Definition at line 174 of file timegrid.hpp.
|
private |
Definition at line 175 of file timegrid.hpp.
|
private |
Definition at line 176 of file timegrid.hpp.


Go to the source code of this file.
◆ ACK
◆ main()
For writing underline (_) on the slaves LCD
Receive end character from master device.
Signifies end of game.
Definition at line 48 of file slave2.c.
◆ buffer
Row in which is placed everything that comes over Soft Uart.
Definition at line 34 of file slave2.c.
◆ down
◆ duzina
Length of the given word.
Definition at line 30 of file slave2.c.
◆ end
◆ error1
Auxiliary variable for Soft UART initialization.
Definition at line 36 of file slave2.c.
◆ keydata
| unsigned short keydata = 0 |
Variable in which is placed integer value of the length.
Definition at line 44 of file slave2.c.
◆ P0_0_bit
| sbit PS2_DATA at P0_0_bit |
PS2 module connections.
Definition at line 16 of file slave2.c.
◆ P0_1_bit
| sbit PS2_CLOCK at P0_1_bit |
◆ P1_0_bit
| sbit Soft_Uart_RX at P1_0_bit |
Define pin 1.0 as receiver for Soft UART.
Definition at line 8 of file slave2.c.
◆ P1_1_bit
| sbit Soft_Uart_TX at P1_1_bit |
Define pin 1.1 as transceiver for Soft UART.
Definition at line 12 of file slave2.c.
◆ P2_0_bit
LCD pinout settings.
Definition at line 21 of file slave2.c.
◆ P2_1_bit
◆ P2_2_bit
◆ P2_3_bit
◆ P2_4_bit
◆ P2_5_bit
◆ player
◆ special
| unsigned short special = 0 |


search for the speaker icon on the chat
stemmIt: @damian14443
the name "krystyna", "krycha", was created by @carrioner
Offchain Krycha V0.3


To whom it may concern at TripAdvisor,
My name is Craig Bryan, and I'm currently studying software engineering at the University of Ottawa. I recently saw TripAdvisor's booth at the High Tech Career fair at uOttawa. After hearing about the positions you have available, I began to think how awesome it would be to work at TripAdvisor — it is a globally recognizable brand that I have seen all over the world, and that I have personally used many times. It is an exciting prospect to work on a product that I have an interest in as a user.
At the career fair, I learned that you are looking for developers with skills in Java and the standard front-end web tools (HTML, CSS, and Javascript). I believe these technologies to be some of my strongest technical skills. Java, in addition to being the very first language I taught myself, is uOttawa's primary teaching language. I've had more exposure and practice with Java than any other language. I have worked and hacked on many web-based projects, so I've used those front-end tools extensively. My most recent work (other than this website) has been on UmpleOnline — a website that runs tons of Javascript.
In lieu of a standard paper CV, I've opted to share with you my new online resume. Most job applications are now done remotely via the internet and leave the applicant with almost no opportunity to showcase their personality. This website is my attempt to make my application more personal, and, at the same time, show you some of my work. You can see all the source for this website here.
I would absolutely love the chance to talk further about working at TripAdvisor with you. Please, click here or use the menu to the left to see the rest of my resume.
Sincerely,
Craig Bryan.
Just a head's up, there's no link back to this page from my main website. If you want to read this again, you'll have to use the link I sent you to get here.


title = "Add actors" url = "/add-actors" layout = "default" is_hidden = 0 [actorform] [session] security = "user" redirect = "login" ==


public interface RebuildingContext
| Modifier and Type | Method and Description |
|---|---|
boolean |
containsUpdated(Node node)
Checks if the context contains already an updated version of the given node.
|
java.util.Map<Node,Node> |
getRebuildingMap()
Returns a map of instruction nodes to instruction nodes, which contains the nodes to be replaced as key and the
nodes which shall replace the old nodes as values.
|
<T extends Node> |
getUpdated(T node)
Returns resolved node of type T or null if is not yet resolved.
|
<T extends Node> |
getUpdatedOrSame(T node)
Returns updated or same(given) node from context.
|
<T extends Node> |
put(T oldNode,
T newNode)
Holds relation between old node and new node
|
<T extends Node> T getUpdatedOrSame(T node)
T
- the type of Node
node
- to be see if updated.<T extends Node> T getUpdated(T node)
T
- the type of Node
node
- to get the update fromboolean containsUpdated(Node node)
node
- the instruction node for which it shall be checked if an updated version exists for ittrue
if the context contains an updated version, false
if not.java.util.Map<Node,Node> getRebuildingMap()


You can now directly communicate with the Seller of this package.
Customisable itineraries where you may choose transport, stay & sightseeing as per your taste & comfort
Delhi - 2 Nights
Agra - 1 Night
Jaipur - 2 Nights
Favourite of 1 people | Add to your list!
A tour spanning the cities of Delhi, Agra and Jaipur having grandeur found in their monuments, glory and history. These cities exude heritage every step of the way. Delhi is the capital city of India and effortlessly entwines old-school charm and modernity. Agra is the world-famous city and home to the beautiful Taj Mahal. Jaipur, commonly known as the Pink City, is a famous shopping hub, with its prints famous nationwide.
CHECK IN FOR 2 NIGHTS
CHECK IN FOR 2 NIGHTS
CHECK IN FOR 2 NIGHTS
Advance Booking Fee
Important: The booking stands liable to be cancelled if 100% payment is not received less than 20 days before date of departure.
If you Cancel your Holiday
You or any member of your party may cancel their travel arrangements at any time. Written notification or an e-mail to that effect from the person who made the booking must be received at our office. The cancellation charges applicable are as per the published cancellation policy below:
Cancellation charges per person
If we change or cancel your holiday
Day 1 - Arrival in Delhi | Delhi to Agra
Soon after your arrival in Delhi, proceed towards Agra.
Situated on the banks of Yamuna River, Agra is a treasure trove for travellers who wish for a dream vacation. Agra attracts hordes of visitors from all over the world for its alluring attraction – the Taj Mahal. Known as the symbol of love, Taj Mahal is an architectural wonder. Apart from housing one of the Seven Wonders of the World, this city is also known for several other notable attractions, which include Fatehpur Sikri, Agra Fort and Jama Masjid.
Day 2 - Agra to Bharatpur
Soon after your arrival in Delhi, proceed towards Agra.
Situated on the banks of Yamuna River, Agra is a treasure trove for travellers who wish for a dream vacation. Agra attracts hordes of visitors from all over the world for its alluring attraction – the Taj Mahal. Known as the symbol of love, Taj Mahal is an architectural wonder. Apart from housing one of the Seven Wonders of the World, this city is also known for several other notable attractions, which include Fatehpur Sikri, Agra Fort and Jama Masjid.
On reaching Agra, check-in at the hotel and relax yourself. Afterwards, you can move out of the hotel to explore the attractions of the city.
Later, come back to the hotel for an overnight stay.
Located in the north east of Rajasthan, state capital Jaipur is India' s tenth largest city, and one of its most popular tourist destinations. It is part of what is known as the country' s golden triangle of tourism that includes Delhi (260 km away) and Agra (240 km away). Known as the 'Pink City' it is also the gateway to the splendours of Rajasthan. Tourists arrive here and then make their way to the various historical cities around the state. It is the city of forts and palaces and was founded in 1727 by Maharaja Sawai Jai Singh II, the ruler of Amber, after whom it is named. Jai Singh had deep interests in sciences like astronomy, mathematics and astrophysics, and he had the city built on the principles of Shilpa Shastra, the ancient Indian science of architecture. It divided the city into nine blocks, two of which contain the state buildings and palaces, with the remaining seven


Jesse Erickson
About Me
Work
Contact Me
About
Me
I'm a curious soul who likes to stop and see the wonders and read that plaques. I enjoy a challenge. I love wonder and awe. I cherish those days that leave you feeling like you just stood on the edge of the Grand Canyon for the first time.
Work
Weather App
GitHub
Work Day Scheduler
GitHub
Quiz Game
GitHub
Bingo Group Project
GitHub
Concert Goer
Twisted Fire Starter
Elkhound Lover


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Yash Naik
John Hammond.
|Settings
|Log Out
|Your Events
|About Us
Categories.
Sports
Food
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Arts
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Festivals
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Sensor Data Modelling For Sports
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Silent DJ!
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Food Truck Festival
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Beach Party
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Book fair
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Vintage Film Screening
Load more? :Do.


Tomatar is a Pomodoro Technique tool to help you stay mega productive.
Hit the big button to start a pomodoro session. The time will wind down. You can hit it again to pause, in case you get interrupted.
All of your pomodori are saved so you can track your progress.


Raspberry Pi Computer
-
Description
I want to build a fully functional Raspberry Pi computer to use for developing electronics such as image detection, sound recording, and robotics. I hope that you will support my goals! Thank you for your time! -
What I Need
- Raspberry Pi
- Mouse
- Keyboard
- HDMI Cable
-
Why I Need It
I'm going to hook this Pi up to a monitor, keyboard, mouse and whatever other component to make it as fully functional as a personal computer as possible. I will be able to learn Computer Science and program applications on it. -
Location


Tips for Formula Input
You may have noticed some unexpected behavior in Math Expression problems. The system we use is very reliable, but like any system it has its quirks. Here are a few things to watch out for:
- You must use explicit multiplication, with as asterisk (*) as the multiplication symbol. For instance, for "a times b" you cannot write "ab" or "axb". You must write "a*b".
- Sometimes these problems are case-sensitive. For instance, if the answer is "D*E*f", you cannot type "D*E*F", or you will get an error that says "Invalid input: F not permitted in answer."
- That same error appears any time you use a variable that is not allowed in the answer. In some problems, it will be possible to simplify the answer so that the variable you used does not appear in the answer. Other times, you may have typed the wrong letter by mistake.
- Squares of trigonometric expressions are typically written by hand as \(\sin^2(x)\). However, this system requires very specific notation. Writing "(sin(x))^2" will get you the right answer, as will "sin(x)^2".
- Greek letters like \(\theta\) and \(\alpha\) must be written in English. (If you are using a Greek keyboard, pressing the \(\theta\) key will not work for this.) If you are uncertain of how to spell a particular Greek letter in English, Wikipedia has a list of greek letters that you can use for reference.


Day 4
Interactivity.
Interactive examples
BBC Dynasties
BBC A Perfect Planet
TOMS glow in the dark
Playdate’s Interactive animation
@lynnandtonic responsive illustration
Interactive emails on Really Good Emails
Image swap on
:hover
📝
Live coding an image swap on CodePen
Can I email…
display:none
and
:hover
Interactive quiz with
:checked
Punched card coding
—
Mark Robbins
Bulletin quiz example
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Live coding an Interactive quiz on CodePen
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Rotation 6: Lamination, Vacuum Forming, Molding & Casting
For Rotation 6:
Assignment Part 1- Molding From A Negative
1. Design an 3D ORIGINAL .stl file to use in the MDX40A.
2. Mill the part using subtractive manufacturing using the MDX40A. You will mill in wax.
3. Create a mold using Smooth-Sil 960.
4. Cast a chocolate part.


max branches per node:
P of spawning a new branch (0-1):
P decay (new branches how much less probable at each node?):
max tree depth:
branch angle range in degrees:
min:
max:
new:
branch length:
new:
length multiplier (new branches length of prev x this):
tree color:
silvery w/ green nodes
silvery w/ black nodes
blackish w/ silver nodes
blackish w/ green nodes
make it so
Fixed the click-stealing.
It's still true though that if your changes make the tree too thick this page will get real slow ¯\_(ツ)_/¯
drag to spin / mousewheel to zoom


PNA
DOMESTIC
INTERNATIONAL
ENTERTAINMENT
TECHNOLOGY
SCIENCE
BUSINESS AND FINANCE
SPORT
FACTS AND OPINION


@(urlForm: Form[String]) @main(Messages("application.name")) {
The URL Shortener
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In this video I tried to capture how to play poker via gui, for more details please check here: https://github.com/sg777/bet. Please join CHIPS discord for a...
Alright19-May-19 10:34 PM
what is bitcoinj?
Anthony19-May-19 10:35 PM
BitcoinJ is Bitcoin java library
Alright19-May-19 10:35 PM
needs to turn his mic up
1
can't hear this at all
Anthony19-May-19 10:37 PM
Ok register then join?
Alright19-May-19 10:37 PM
do you have the TUI up?
you need a balance first
Anthony19-May-19 10:37 PM
Yes
What
always something
Alright19-May-19 10:37 PM
you can either do setgenerate true 4 or post an address here and I'll send
Anthony19-May-19 10:38 PM
REeCcLfpiMPC6XGzm6PLzZiuvCBxDnw4BD
Maximum number of retries exceeded!
packet_write_wait: Connection to <IP_ADDRESS> port 22: Broken pipe
ASCs-iMac:~ asc$
looks like it took the vps out
I shoulda picked 5$ instead of 2.5$
Alright19-May-19 10:39 PM
min specs are like 8gb 4 core, you can get by with 4gb with a bunch of swap space though
Anthony19-May-19 10:40 PM
its still running, was my internet
Alright19-May-19 10:40 PM
actual minimum is probably like 2 core 4gb with swap(edited)
but that's asking for problems
Anthony19-May-19 10:40 PM
We never ran rpc
Alright19-May-19 10:40 PM
what?
Anthony19-May-19 10:40 PM
to use komodo-cli to import that address
or validate it, to see if it is in the wallet
Alright19-May-19 10:41 PM
"we"?
confused man, just use ./komodo-cli -ac_name=CFEKORC validateaddress <address> to verify it owns the key for it
Anthony19-May-19 10:41 PM
thats the trick.
-ac_name
without ac_name it defaults to komodo and not the asset chain
My balance is 10000
Success! Please wait for 9ca9ed39434efc37339c0749b0391f66d0071edb78c64e83fcb95686ed1e0f66 to be confirmed.
registered
"confirmations": 0,
The cost was 0.0001
Blocktime is quite long? or is it until a certain parameter is met
PHBA206119-May-19 10:46 PM
it's long yes, 1800s
Alright19-May-19 10:50 PM
it's not actually, it's 1 minute
when i made it I wasn't aware that ac_blocktime wouldn't work with ac_algo=verushash11(edited)
going to start a new chain after launch that is 30 minute blocks
sorry, really dropped the ball on that
PHBA206119-May-19 10:52 PM
lol
that explain why I actually felt the block time is much shorter than 1800s when I was mining on it(edited)
Anthony19-May-19 10:55 PM
"confirmations": 1,
Ok lets go
TUI logged out, waiting for another register
Alright19-May-19 10:57 PM
don't register again
Anthony19-May-19 10:57 PM
"blocks": 21424,
Alright19-May-19 10:58 PM
just do Join Lottery option if the register tx confirmed
Anthony19-May-19 10:58 PM
I did and it says I must register
so perhaps this sync isnt complete
Alright19-May-19 10:58 PM
registering again won't hurt
Anthony19-May-19 10:58 PM
"rawconfirmations": 3,
"confirmations": 1,
Error: Please use the "Register for lottery". You must also wait for at least 1 confirmation
The gettransaction of the txid shows a confirmation but it saying otherwise
Alright19-May-19 10:59 PM
yea not sure, I can push some debug prints right now if you have a minute to debug it


Weighted dependence measures. More...
Classes | |
| class | Indep_test |
Functions | |
| double | wdm (const Eigen::VectorXd &x, const Eigen::VectorXd &y, std::string method, Eigen::VectorXd weights=Eigen::VectorXd(), bool remove_missing=true) |
| Eigen::MatrixXd | wdm (const Eigen::MatrixXd &x, std::string method, Eigen::VectorXd weights=Eigen::VectorXd(), bool remove_missing=true) |
| double | wdm (std::vector< double > x, std::vector< double > y, std::string method, std::vector< double > weights=std::vector< double >(), bool remove_missing=true) |
Detailed Description
Weighted dependence measures.
Function Documentation
|
inline |
calculates (weighted) dependence measures.
- Parameters
-
x,y input data. method the dependence measure; see details for possible values. weights an optional vector of weights for the data. remove_missing if true
, all observations containing anan
are removed; otherwise throws an error ifnan
s are present.
Available methods:
"pearson"
,"prho"
,"cor"
: Pearson correlation"spearman"
,"srho"
,"rho"
: Spearman's \( \rho \)"kendall"
,"ktau"
,"tau"
: Kendall's \( \tau \)"blomqvist"
,"bbeta"
,"beta"
: Blomqvist's \( \beta \)"hoeffding"
,"hoeffd"
,"d"
: Hoeffding's \( D \)
- Returns
- the dependence measure
|
inline |
calculates (weighted) dependence measures.
- Parameters
-
x,y input data. method the dependence measure; see details for possible values. weights an optional vector of weights for the data. remove_missing if true
, all observations containing anan
are removed; otherwise throws an error ifnan
s are present.
Available methods:
"pearson"
,"prho"
,"cor"
: Pearson correlation"spearman"
,"srho"
,"rho"
: Spearman's \( \rho \)"kendall"
,"ktau"
,"tau"
: Kendall's \( \tau \)"blomqvist"
,"bbeta"
,"beta"
: Blomqvist's \( \beta \)"hoeffding"
,"hoeffd"
,"d"
: Hoeffding's \( D \)
- Returns
- the dependence measure
|
inline |
calculates a matrix of (weighted) dependence measures.
- Parameters
-
x input data. method the dependence measure; see details for possible values. weights an optional vector of weights for the data. remove_missing if true
, all observations containing anan
are removed; otherwise throws an error ifnan
s are present.
Available methods:
"pearson"
,"prho"
,"cor"
: Pearson correlation"spearman"
,"srho"
,"rho"
: Spearman's \( \rho \)"kendall"
,"ktau"
,"tau"
: Kendall's \( \tau \)"blomqvist"
,"bbeta"
,"beta"
: Blomqvist's \( \beta \)"hoeffding"
,"hoeffd"
,"d"
: Hoeffding's \( D \)
- Returns
- a matrix of pairwise dependence measures.


Security through deposits
Cryptoeconomic protocols are ensuring security through deposits. This includes for example stablecoins like Dai, NOCUST, Plasma, payment channels (Raiden, PERUN), verifiable computation (TrueBit) or cross-chain protocols like XCLAIM. If an agent Alice wants to participate in these protocols, Alice needs to provide a cryptocurrency deposit as an insurance against misbehaviour. A cryptoeconomic protocol has, in an abstract sense, a list of desired and undesired actions.
In the first step, Alice commits to a contract A by depositing some cryptocurrency. Next, Alice can decide if she wants to execute a "desired action" or an "undesired action". In case Alice performs an undesired action, her deposit is usually "slashed", i.e. the collateral is destroyed or the "victim" of the undesired action is refunded with that collateral. Contrary, if Alice performs a desired action, she is usually rewarded with a fee that the consumer of the service is paying (e.g. a solver in TrueBit).
But how much deposit do I need?
The problem is: no one really knows how much deposit you actually need in a wide range of protocols. For example, as the USD to Ether value is volatile, it is unclear how much deposit is actually needed for the CDP in Dai. Hence, we see the deposit level fluctuating from 300% to 600%. Also, how much a computation is worth is very subjective to the service provider and the receiver of the result. We can say there are two sources of uncertainty:
- Private information: These are unknown values that different parties assign to a certain outcome. For example, a solver of a computation might just value the result by the payment he gets. The receiver of the result might require it for a critical application and hence assign a much higher value to it.
- Event-dependency: These are values that change over time in an unpredictable manner. For example, the USD to Ether exchange rate in exactly 26 days is practically impossible to forecast.
Because of these sources of uncertainty, protocol designers might require more deposit than the currently perceived risk. They need to anticipate different private information and future events to ensure their protocol remains secure over time.
Balance: Reducing deposits with the same level of security
Enter Balance: a protocol that allows you to reduce these deposits securely. We now know that we need to over-collateralize if we have private information and event-dependency. However, we can reduce deposits over time while keeping the same level of protection. We achieve this by assigning agents to layers that represent a certain level of deposit. An agent can be any users or organization in a protocol and is identified by its public key. Simply speaking, it works like this:
An agent starts at Layer 1 when the agent first commits to the protocol. So for example, I would start with a deposit factor of 2.0 at first, requiring 200% collateral. When I perform desired action, I can move to Layer 2 and reduce my deposit factor to 1.75. Hence, I just reduced my collateral factor by 25 percentage points! I keep doing desired actions until I make it to the highest layer with the lowest deposit factor.
Feedback mechanism
Assume you are receiving points as an agent if you perform actions that are part of the desired actions. The smart contract implementing the protocol is aware of all these actions. Thereby, the agents actions are directly translated into a score for performing this action. The more contributions the higher the ranking. The higher the ranking, the less collateral the agent has to provide. We end up with a construct like this:
The higher I move up the layers, the more difficult it becomes to maintain my position. At the same time, my utility gets higher since I need to lock less deposit to participate in the protocol.
Less deposit and the same security?
Balance allows agents to reduce their capital deposits over a sequence of periodic rounds, while preventing the addition of incentives to act maliciously. In fact, malicious agents that aim to misbehave in a protocol obtain more utility if they do early on, before any reductions in their deposit occurs. Conversely, honest and rational agents receive a higher utility by consistently acting in the interest of the protocol. Balance achieves this property for protocols which feature over-collateralization by reducing deposits to a lower bound. Above the lower bound, the additional utility gained from reducing the deposit is less than the opportunity cost for locking-up the deposit in the first place. Hence, a malicious agent gains no additional utility from cheating in a later round with a reduced deposit. However, honest and rational agents gain additional utility by reducing the opportunity cost of the locked deposit.
Reducing deposits is restricted to a boundary
Unfortunately, we cannot reduce deposits indefinitely. Generally speaking, the reduction depends on parameters like the total number of layers and the expected opportunity cost for locking deposits. We can illustrate this with the figure below:
The higher the initial deposit factor, the more we can reduce the deposit factor up to a certain bound. Each of the five curves above represent the boundary with a starting deposit level ranging from 1.0 to 2.0. As long as the deposit level is set above the boundary, we enjoy the same level of security. If we set the deposit factor below the boundary, the protocol will be less secure.
Balance in detail
Balance is implemented as a smart contract and can be integrated with existing cryptoeconomic protocols. Agents collect points that add up to their score within a single period. After the end of the period, the agents are curated to layers depending on their current score and their current layer. They can either:
- Stay in the same layer.
- Get promoted to the next layer.
- Get demoted to the previous layer.
- Get removed from the registry.
The idea is to set a fixed amount of time or events in which agents can collect these points.
At t_0
, each agent starts with 0 points. Each layer defines a lower and upper bound.
If an agent manages to collect enough points to make the cut of the current layer (its upper bound), then the agent
gets promoted to that layer at t_1
.
If the agent falls below the lower bound of the current layer, it gets demoted to the previous layer.
At the end of the period, scores are reset and the agent starts from 0 again.
Applying Balance to XCLAIM
We integrate Balance with XCLAIM. XCLAIM is a protocol that allows secure, trustless, and efficient cross-chain interoperability between any pair of blockchains. In XCLAIM, over-collateralization is required due to the volatility of the cryptocurrencies of the connected chains. With Balance, we can reduce this by 10% and maintain the same level of security.


AGORA
Transaction History
Add a Transaction
| Name | Date | Category | Price |
|---|---|---|---|
| McDonald's | 04/02/2017 | Food | $15.00 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Cinema | 01/01/2017 | Entertainment | $69.69 |
| Textbook | 05/12/2016 | Education | $129.00 |


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