ZooKeeper Internals
Introduction
This document contains information on the inner workings of ZooKeeper. So far, it discusses these topics:
Atomic Broadcast
At the heart of ZooKeeper is an atomic messaging system that keeps all of the servers in sync.
Guarantees, Properties, and Definitions
The specific guarantees provided by the messaging system used by ZooKeeper are the following:
-
Reliable delivery -
If a message, m, is delivered by one server, it will be eventually delivered by all servers.
-
Total order -
If a message is delivered before message b by one server, a will be delivered before b by all servers. If a and b are delivered messages, either a will be delivered before b or b will be delivered before a.
-
Causal order -
If a message b is sent after a message a has been delivered by the sender of b, a must be ordered before b. If a sender sends c after sending b, c must be ordered after b.
The ZooKeeper messaging system also needs to be efficient, reliable, and easy to implement and maintain. We make heavy use of messaging, so we need the system to be able to handle thousands of requests per second. Although we can require at least k+1 correct servers to send new messages, we must be able to recover from correlated failures such as power outages. When we implemented the system we had little time and few engineering resources, so we needed a protocol that is accessible to engineers and is easy to implement. We found that our protocol satisfied all of these goals.
Our protocol assumes that we can construct point-to-point FIFO channels between the servers. While similar services usually assume message delivery that can lose or reorder messages, our assumption of FIFO channels is very practical given that we use TCP for communication. Specifically we rely on the following property of TCP:
-
Ordered delivery -
Data is delivered in the same order it is sent and a message m is delivered only after all messages sent before m have been delivered. (The corollary to this is that if message m is lost all messages after m will be lost.)
-
No message after close -
Once a FIFO channel is closed, no messages will be received from it.
FLP proved that consensus cannot be achieved in asynchronous distributed systems if failures are possible. To ensure we achieve consensus in the presence of failures we use timeouts. However, we rely on times for liveness not for correctness. So, if timeouts stop working (clocks malfunction for example) the messaging system may hang, but it will not violate its guarantees.
When describing the ZooKeeper messaging protocol we will talk of packets, proposals, and messages:
-
Packet -
a sequence of bytes sent through a FIFO channel
-
Proposal -
a unit of agreement. Proposals are agreed upon by exchanging packets with a quorum of ZooKeeper servers. Most proposals contain messages, however the NEW_LEADER proposal is an example of a proposal that does not correspond to a message.
-
Message -
a sequence of bytes to be atomically broadcast to all ZooKeeper servers. A message put into a proposal and agreed upon before it is delivered.
As stated above, ZooKeeper guarantees a total order of messages, and it also guarantees a total order of proposals. ZooKeeper exposes the total ordering using a ZooKeeper transaction id (zxid). All proposals will be stamped with a zxid when it is proposed and exactly reflects the total ordering. Proposals are sent to all ZooKeeper servers and committed when a quorum of them acknowledge the proposal. If a proposal contains a message, the message will be delivered when the proposal is committed. Acknowledgement means the server has recorded the proposal to persistent storage. Our quorums have the requirement that any pair of quorum must have at least one server in common. We ensure this by requiring that all quorums have size (n/2+1) where n is the number of servers that make up a ZooKeeper service.
The zxid has two parts: the epoch and a counter. In our implementation the zxid is a 64-bit number. We use the high order 32-bits for the epoch and the low order 32-bits for the counter. Because it has two parts represent the zxid both as a number and as a pair of integers, (epoch, count). The epoch number represents a change in leadership. Each time a new leader comes into power it will have its own epoch number. We have a simple algorithm to assign a unique zxid to a proposal: the leader simply increments the zxid to obtain a unique zxid for each proposal. Leadership activation will ensure that only one leader uses a given epoch, so our simple algorithm guarantees that every proposal will have a unique id.
ZooKeeper messaging consists of two phases:
-
Leader activation -
In this phase a leader establishes the correct state of the system and gets ready to start making proposals.
-
Active messaging -
In this phase a leader accepts messages to propose and coordinates message delivery.
ZooKeeper is a holistic protocol. We do not focus on individual proposals, rather look at the stream of proposals as a whole. Our strict ordering allows us to do this efficiently and greatly simplifies our protocol. Leadership activation embodies this holistic concept. A leader becomes active only when a quorum of followers (The leader counts as a follower as well. You can always vote for yourself ) has synced up with the leader, they have the same state. This state consists of all of the proposals that the leader believes have been committed and the proposal to follow the leader, the NEW_LEADER proposal. (Hopefully you are thinking to yourself, Does the set of proposals that the leader believes has been committed included all the proposals that really have been committed? The answer is yes. Below, we make clear why.)
Leader Activation
Leader activation includes leader election. We currently have two leader election algorithms in ZooKeeper: LeaderElection and FastLeaderElection (AuthFastLeaderElection is a variant of FastLeaderElection that uses UDP and allows servers to perform a simple form of authentication to avoid IP spoofing). ZooKeeper messaging doesn't care about the exact method of electing a leader has long as the following holds:
-
The leader has seen the highest zxid of all the followers.
-
A quorum of servers have committed to following the leader.
Of these two requirements only the first, the highest zxid amoung the followers needs to hold for correct operation. The second requirement, a quorum of followers, just needs to hold with high probability. We are going to recheck the second requirement, so if a failure happens during or after the leader election and quorum is lost, we will recover by abandoning leader activation and running another election.
After leader election a single server will be designated as a leader and start waiting for followers to connect. The rest of the servers will try to connect to the leader. The leader will sync up with followers by sending any proposals they are missing, or if a follower is missing too many proposals, it will send a full snapshot of the state to the follower.
There is a corner case in which a follower that has proposals, U, not seen by a leader arrives. Proposals are seen in order, so the proposals of U will have a zxids higher than zxids seen by the leader. The follower must have arrived after the leader election, otherwise the follower would have been elected leader given that it has seen a higher zxid. Since committed proposals must be seen by a quorum of servers, and a quorum of servers that elected the leader did not see U, the proposals of you have not been committed, so they can be discarded. When the follower connects to the leader, the leader will tell the follower to discard U.
A new leader establishes a zxid to start using for new proposals by getting the epoch, e, of the highest zxid it has seen and setting the next zxid to use to be (e+1, 0), fter the leader syncs with a follower, it will propose a NEW_LEADER proposal. Once the NEW_LEADER proposal has been committed, the leader will activate and start receiving and issuing proposals.
It all sounds complicated but here are the basic rules of operation during leader activation:
-
A follower will ACK the NEW_LEADER proposal after it has synced with the leader.
-
A follower will only ACK a NEW_LEADER proposal with a given zxid from a single server.
-
A new leader will COMMIT the NEW_LEADER proposal when a quorum of followers have ACKed it.
-
A follower will commit any state it received from the leader when the NEW_LEADER proposal is COMMIT.
-
A new leader will not accept new proposals until the NEW_LEADER proposal has been COMMITED.
If leader election terminates erroneously, we don't have a problem since the NEW_LEADER proposal will not be committed since the leader will not have quorum. When this happens, the leader and any remaining followers will timeout and go back to leader election.
Active Messaging
Leader Activation does all the heavy lifting. Once the leader is coronated he can start blasting out proposals. As long as he remains the leader no other leader can emerge since no other leader will be able to get a quorum of followers. If a new leader does emerge, it means that the leader has lost quorum, and the new leader will clean up any mess left over during her leadership activation.
ZooKeeper messaging operates similar to a classic two-phase commit.
All communication channels are FIFO, so everything is done in order. Specifically the following operating constraints are observed:
-
The leader sends proposals to all followers using the same order. Moreover, this order follows the order in which requests have been received. Because we use FIFO channels this means that followers also receive proposals in order.
-
Followers process messages in the order they are received. This means that messages will be ACKed in order and the leader will receive ACKs from followers in order, due to the FIFO channels. It also means that if message $m$ has been written to non-volatile storage, all messages that were proposed before $m$ have been written to non-volatile storage.
-
The leader will issue a COMMIT to all followers as soon as a quorum of followers have ACKed a message. Since messages are ACKed in order, COMMITs will be sent by the leader as received by the followers in order.
-
COMMITs are processed in order. Followers deliver a proposals message when that proposal is committed.
Summary
So there you go. Why does it work? Specifically, why does is set of proposals believed by a new leader always contain any proposal that has actually been committed? First, all proposals have a unique zxid, so unlike other protocols, we never have to worry about two different values being proposed for the same zxid; followers (a leader is also a follower) see and record proposals in order; proposals are committed in order; there is only one active leader at a time since followers only follow a single leader at a time; a new leader has seen all committed proposals from the previous epoch since it has seen the highest zxid from a quorum of servers; any uncommited proposals from a previous epoch seen by a new leader will be committed by that leader before it becomes active.
Comparisons
Isn't this just Multi-Paxos? No, Multi-Paxos requires some way of assuring that there is only a single coordinator. We do not count on such assurances. Instead we use the leader activation to recover from leadership change or old leaders believing they are still active.
Isn't this just Paxos? Your active messaging phase looks just like phase 2 of Paxos? Actually, to us active messaging looks just like 2 phase commit without the need to handle aborts. Active messaging is different from both in the sense that it has cross proposal ordering requirements. If we do not maintain strict FIFO ordering of all packets, it all falls apart. Also, our leader activation phase is different from both of them. In particular, our use of epochs allows us to skip blocks of uncommitted proposals and to not worry about duplicate proposals for a given zxid.
Quorums
Atomic broadcast and leader election use the notion of quorum to guarantee a consistent view of the system. By default, ZooKeeper uses majority quorums, which means that every voting that happens in one of these protocols requires a majority to vote on. One example is acknowledging a leader proposal: the leader can only commit once it receives an acknowledgement from a quorum of servers.
If we extract the properties that we really need from our use of majorities, we have that we only need to guarantee that groups of processes used to validate an operation by voting (e.g., acknowledging a leader proposal) pairwise intersect in at least one server. Using majorities guarantees such a property. However, there are other ways of constructing quorums different from majorities. For example, we can assign weights to the votes of servers, and say that the votes of some servers are more important. To obtain a quorum, we get enough votes so that the sum of weights of all votes is larger than half of the total sum of all weights.
A different construction that uses weights and is useful in wide-area deployments (co-locations) is a hierarchical one. With this construction, we split the servers into disjoint groups and assign weights to processes. To form a quorum, we have to get a hold of enough servers from a majority of groups G, such that for each group g in G, the sum of votes from g is larger than half of the sum of weights in g. Interestingly, this construction enables smaller quorums. If we have, for example, 9 servers, we split them into 3 groups, and assign a weight of 1 to each server, then we are able to form quorums of size 4. Note that two subsets of processes composed each of a majority of servers from each of a majority of groups necessarily have a non-empty intersection. It is reasonable to expect that a majority of co-locations will have a majority of servers available with high probability.
With ZooKeeper, we provide a user with the ability of configuring servers to use majority quorums, weights, or a hierarchy of groups.
Logging
Zookeeper uses slf4j as an abstraction layer for logging. log4j in version 1.2 is chosen as the final logging implementation for now. For better embedding support, it is planned in the future to leave the decision of choosing the final logging implementation to the end user. Therefore, always use the slf4j api to write log statements in the code, but configure log4j for how to log at runtime. Note that slf4j has no FATAL level, former messages at FATAL level have been moved to ERROR level. For information on configuring log4j for ZooKeeper, see the Logging section of the ZooKeeper Administrator's Guide.
Developer Guidelines
Please follow the slf4j manual when creating log statements within code. Also read the FAQ on performance , when creating log statements. Patch reviewers will look for the following:
Logging at the Right Level
There are several levels of logging in slf4j. It's important to pick the right one. In order of higher to lower severity:
-
ERROR level designates error events that might still allow the application to continue running.
-
WARN level designates potentially harmful situations.
-
INFO level designates informational messages that highlight the progress of the application at coarse-grained level.
-
DEBUG Level designates fine-grained informational events that are most useful to debug an application.
-
TRACE Level designates finer-grained informational events than the DEBUG.
ZooKeeper is typically run in production such that log messages of INFO level severity and higher (more severe) are output to the log.
Use of Standard slf4j Idioms
Static Message Logging
LOG.debug("process completed successfully!");
However when creating parameterized messages are required, use formatting anchors.
LOG.debug("got {} messages in {} minutes",new Object[]{count,time});
Naming
Loggers should be named after the class in which they are used.
public class Foo { private static final Logger LOG = LoggerFactory.getLogger(Foo.class); .... public Foo() { LOG.info("constructing Foo");
Exception handling
try { // code } catch (XYZException e) { // do this LOG.error("Something bad happened", e); // don't do this (generally) // LOG.error(e); // why? because "don't do" case hides the stack trace // continue process here as you need... recover or (re)throw }


---
layout: default
title: Using O-FISH on Web
nav_order: 30
---
{{ page.title }}
O-FISH is the Officer Fisheries Information Sharing Hub. It was developed to enabled you to gather thorough information and share it quickly and easily.
The web application is designed for administrators back in the office to look at all the boarding information.
Using the web application:
{% assign sortedPosts = site.posts | reverse %}
{% for post in sortedPosts %}
{% if post.site == 'useWeb' %}
- » {{ post.title }}
{% endif %}
{% endfor %}


TeX to Unicode
Input Unicode mathematical symbols by LaTeX
A Chrome extension
Convert by pressing
Alt
+
w
(or
^
+
w
on Mac).
Add to Chrome
Supported symbols
Features
Convert Tex to Unicode by pressing ALT + W (OPT + W on Mac)
Convert underscripts and superscripts (can be enabled by an option)
Works on Stack Exchange, Reddit, Wikipedia, and Gmail
Convert one symbol, or convert all symbols under selection
Free software
Demo
\alpha \to \beta \to \gamma x \in A \subset \mathbb{R} e^x


Arbitrary expression evaluation and GUI, with JIT compilation and optimization.
Written by Edwin Olson (ebolson@umich.edu)


Our Story
We are a group of students with a passion for racing and cars. Hydrogen is a developing form of fuel that has a by-product of water. We hope to gain useful knowledge on how to create hydrogen cars for the future to help alleviate our climate crisis. We currently race in the Horizon Grand Prix. It is a worldwide racing competition challenging students to make the most efficient hydrogen fuel cell R/C car. The race is an endurance race ranging from 3-6 hours depending on the stage of the competition. Our goal is to innovate and find new ways to save energy within the car and win the 2020 World Finals!
Achievements
2017-2018
- 11th - Norcal Regionals
2018-2019
- 4th - Norcal Regionals - 327 laps in 3 hours
- Tied 7th - Nationals - 659 laps in 4.5 hours
- 4th Best School at State Finals
- Current #1 Norcal Team


Names are matched with case-insensitivity.
If the "Match whole name" box is checked, the text entered in the "Variable name" or "Dataset name" field must be the whole variable or dataset name.
For example, "bmi" will match "BMI" but not "BMI_1" or "baseline_bmi".
Searches without the "Match whole name" box checked will match text anywhere in the name, so "bmi" will match "BMI", "BMI_1" and "baseline_bmi".
Description fields
All words entered are required to be in the description, although the order is irrelevant.
The search will match either complete words or the beginning of words, but not the end of words.
For example, "cons" will match both "cons" and "consent" but not "onset", while "ons" will match "onset" but not "consent".
With the exception of apostrophes and underscores, special characters (such as <, >, +, =, ?, and %) are not allowed.
Words that are shorter than 3 letters in the variable description are ignored in the search, so "dir" can be found, but "di" cannot.
The search is case insensitive.


|
udp_stream - UDP stream handle
dest_ip - destination IP address dest_port (optional) - destination port number |
|
Transmits all the data written to the UDP stream to the specified IP address and port. Data is written using the standard stream commands. If no destination port is specified, the port number used to create the UDP Stream is used.
Note that IP addresses must be in integer format, NOT in dotted IP format. |


Space
Whirlpool
1
The Whirlpool Galaxy is a familiar one to stargazers and among the many close galaxy neighbors to our own Milky Way. Because of its shape, it was the first galaxy to be classified as a spiral by astronomers.
Mercury
1
Mercury is the closest planet to the Sun and due to its proximity it is not easily seen except during twilight. For every two orbits of the Sun, Mercury completes three rotations about its axis.
Europa Moon
1
Europa is the smallest of Jupiter’s Galilean moons and the second closest, however it is still the sixth largest moon in the solar system. Europa is known for being one of the first worlds a subsurface water ocean was hypothesised for.
Io Moon
1
Io is the innermost and the second smallest of the four Galilean moons. It was discovered, along with Europa, Ganymede and Callisto by Galileo Galilei in 1610.
Venus
1
Venus is the second planet from the Sun and is the second largest terrestrial planet.
Earth
1
Earth is the third planet from the Sun and is the largest of the terrestrial planets.
Milky Way
1
The Milky Way Galaxy is our home galaxy in the universe. It is a fairly typical barred spiral with four major arms in its disk, at least one spur, and a newly discovered outer arm.


| Fig. 1 |
Brief characterization of Eastern China. Spatial distributio ... |
| Fig. 2 |
Spatial distribution of extreme wet-bulb temperature. Ensemb ... |
| Fig. 3 |
Histogram of daily maximum wet-bulb temperature in 16 cities ... |
| Fig. 4 |
Spatial distribution of 95th percentile of daily maximum wet ... |


Class GaussianAccumulatorKD¶
Defined in File FastGA.hpp
Inheritance Relationships¶
Base Type¶
public FastGA::GaussianAccumulator< uint32_t >
(Template Class GaussianAccumulator)
Class Documentation¶
-
class
GaussianAccumulatorKD
: public FastGA::GaussianAccumulator<uint32_t>¶ This implements the Gaussian Accumulator with K-D Tree search.
Public Functions
-
GaussianAccumulatorKD
(const int level = 1, const double max_phi = 180.0, const size_t max_leaf_size = 10)¶ Construct a new GaussianAccumulatorKD object. This implements the GaussianAccumulator using a k-d tree method. Its actually pretty fast and can be used, though I recommend GaussianAccumulatorS2.
- Parameters
level
: The refinement level. Iterations of recursive subdivision.max_phi
: Latitude degrees from north pole to south pole to include cells in the mesh. Leave at default which includes all of the mesh.max_leaf_size
: The max leaf size when building the k-d tre index. Leave at default, its optimal.
Protected Attributes
-
const nanoflann::KDTreeSingleIndexAdaptorParams
index_params
¶ Used for nanoflann.
-
std::unique_ptr<NFA::nano_kd_tree_t>
kd_tree_ptr
¶ The nanoflann k-d tree.
-


{% extends "time_app/base.html" %} {% block content %} Filter selection Use this form to get the hours worked for any project in a specified date range. Client Open to select client {% for client in clients %} {{client.name}} {% endfor %} Project Select the project after client is selected {% if user.is_staff %} Employee Open to select Employee {% for user in users %} {%if user.username != 'Matthew'%} {{user.username}} {% endif %} {% endfor %} {% endif %} Starting Date Ending Date Submit {% endblock content %}
Use this form to get the hours worked for any project in a specified date range.


--- layout: default title: Home permalink: / ---
We will pay you without fail every month, even when the house isn't fully tenanted
We would be your tenant, so you still earn your tenant finding fee
We will take on all the taxing duties of managing the property and charge you absolutely nothing, while maintaining a high standard for our professional tenants
You still get to earn your full management fee, despite the fact that we take on full management of the property at no extra cost
Management is free and there are absolutely no hidden fees, so the amount we agree to pay you will be the amount you will receive from us
Each month you just have to pass the guaranteed rent on to the landlord, then get on with your more demanding tenants!


I am not teaching in the Summer 2004 session. The courses and office hours that follow are from Spring 2004.
| Math 208 | MTWF 10:30-11:20 | Nebraska Hall W183 | Calculus III |
| Math/CS 447/847 | MWF 12:30-1:20 | Burnett 205 | Numerical Analysis of ODEs |
secant-tangent gives a visual demonstration of how the tangent line is approximated by a sequence of secant lines.
primer1 is an introduction to Maple designed for users who have no Maple experience.
Release 4 or Release 5 or Release 7,8
primer 2 is a demonstration of the use of formulas to represent functions and introduces basic commands for differentiation and integration.
Release 4 or Release 5 or Release 7,8
Click here for the solutions to the exercises in primer 2.
DEtools1 is a demonstration of the use of the DEtools package to plot direction fields and solutions for first order equations.
Release 4 or Release 5 or Release 7,8
DEtools2 is a demonstration of the use of the DEtools package to plot direction fields and solution curves for systems of two first order equations.
Release 4 or Release 5 or Release 7,8
odes is a demonstration of Maple commands for obtaining and graphing analytical and numerical solutions for differential equations and systems.
Release 4 or Release 5 or Release 7,8
Euler is a simple worksheet designed to make it easy to experiment with Euler's method on various differential equations.
Release 4 or 5
HeatIVP is a worksheet that prepares graphs and animations for solutions of the Cauchy problem for the heat equation.WaveIVP is a worksheet that prepares graphs and animations for solutions of the Cauchy problem for the wave equation.
DiffusionDisk is a worksheet that illustrates the use of Maple to solve homogeneous linear PDE's with constant coefficients on a bounded domain by the method of separation of variables. The worksheet solves the problem of radial diffusion in a disk. The worksheet assumes that the user knows the correct Sturm-Liouville equation and can solve the equation for the time-dependent factors by hand. (One can of course add more code to automate some of these simpler features.)
simplex is a worksheet for the simplex algorithm.
Derivative Concept is a handout that briefly summarizes the concept of the derivative for functions of 1 variable, with emphasis on the geometric significance of the derivative.Directional Slope is a handout that lays the groundwork for the development of the directional derivative by considering the slope in a given direction of a linear function. Exercises are included.
Optimization is a handout that summarizes the theory and methods for for finding local and global extrema for functions of two variables.
Portfolio is my teaching portfolio for my Spring 1999 Differential Equations course. This portfolio was prepared in May 2000 for the Peer Review project.
Mail to<EMAIL_ADDRESS>Last
changed: July 1, 2004


How to start learning something? What's for lunch? How did I make that? Find the answers to these questions and more through my articles:


WAEC: Candidates Can Now Request Certificate Online
by Donatus AnichukwuezeThe West African Examinations Council (WAEC) has announced the establishment of an Electronic Certificate Management System that will enable candidates request for their certificates.
The exam body noted that the online portal was for private candidates sitting for the West African Senior Secondary Certificate Examination from September to November.
This was disclosed by the Nigeria National Committee Chairman (WAEC), Mrs Binta Abdulkadri, in Abuja on Thursday at the 57th annual meeting of the council and presentation of awards to best performing candidates and schools.
She said that WAEC has also deployed a “Quick Response Code on its certificates, thereby making it impossible to falsify certificates issued by the council.”
The chairman said: “The Nigeria National Office, in particular, has taken advantage of Information and Communication Technology to improve its service delivery.
“This development has enabled the council in Nigeria to achieve total migration from paper-based to electronic enrolment of candidates for its examinations.
“The adoption of Advanced Printing Technology and deployment of a new technological solution, Item Differential Profile, are some of the innovations adopted by the council to tackle the menace of examination malpractice.
“The Council in Nigeria has also perfected its Electronic Certificate Management System, an online portal being deployed to enable qualified candidates in the WASSCE for private candidates to request for their certificates online via a dedicated platform.”
Olu Adenipekun, WAEC Head of Nigeria National Office, said the annual meeting was to enable members to effect positive changes in the education sector of the country.


GET INTO THE GROOVE
TIME =
0.0000


Pizza is a savory dish of Italian origin, consisting of a usually round,
flattened base of leavened wheat-based dough topped with tomatoes, cheese,
and often various other ingredients baked at a high temperature,
traditionally in a wood-fired oven. A small pizza is sometimes called a pizzetta.


Original tweets vs. retweets:
{{retweets_percent_pie}}
Tweets generated by the 50 most active users:
{{most_tweets_pie}}
Average number of tweets per user:
{{average_tweets}}
Coefficient of traffic manipulation:
The Coefficient of Traffic Manipulation is expressed as follows, where C is the
coefficient of traffic manipulation, R is the percentage of retweets, F is the
percentage of traffic from the top fifty users, and U is the average number of
tweets per user:


API OverviewJDBC APIUse the JDBC API to connect to a database and execute queries. Tools APIThe Tools API can be used to do maintenance operations, such as deleting database files or changing the database file password, that do not require a connection to the database. |


Taking our InOut a step further and distinguishing it from a private hack-competition, we’re coming together with “InOut in your city” in our fourth edition. “InOut in your city” is first of it’s kind in India and will certainly be helpful in driving it’s innovative agenda of making a nationwide developer community with a hackathon post conference. This initiative is for many potential tech groups in prominent colleges of India, who aspire to run a hackathon in their colleges. InOut will help you organise one of your own and direct in keeping IT professionals and new startups across the country connected and educated.
If you are a passionate individual with ambitious dreams and would like to work with talented group of tech loving people, then the opportunity is right for you. It is a platform where you can make a difference by contributing, but at the same time enhance your marketing skills & expertise.
Best assistance in organizing your own student-run hackathon and winners from your own hack-event will be given direct entry to InOut 4.0 in Bangalore.
Regardless of which course you choose you will be paired with a mentor/mentors. Whenever you’re stuck or confused while following your course you can always reach out to our mentors for help. We’re paired up with GDG NIT Surat with this initiative. Check out here
Your innovative ideas on your Institute & InOut binding will be received gladly, helping you set up on-campus activities to spread the word about event.
As soon as you start coordinating with us, a chock-full goodie bag will be sent to you from InOut.
You’ll be granted a free ticket to InOut 4.0 with your winning team.
Raising funds to organise any event is quite challenging and getting a helping hand for the same is an embellishment. We’ll do Sponsor Intros to help you organize your event better.
Days of the old give us many examples where these prominent female coders like Ada Lovelace have paved the way for women in tech. And hence, we encourage and welcome female coders to participate in our initiative. The team with highest women participation will receive a guaranteed shout-out on our social media which will help them reach a greater audience.
Edit this as you need.


[CHAPTER 103B]
EMPLOYMENT OF STATE RESIDENTS ON
CONSTRUCTION PROCUREMENT CONTRACTS
Section
103B-1 Definitions
103B-2 Application of chapter
103B-3 Requirements of contractor
103B-4 Conflict with federal law


To record your fitness progress each week, please click here.
To record your nutrition progress each week, please click here.
To check out ways to get even more points throughout the weeks, please click here.
As the program progresses, your totals for each week will display on this chart.


It is a time consuming process to maintain Blueprints implementations as graph database/framework versions and features change. Many developers focusing on a particular implementation is an ideal way of ensuring that Blueprints has wide reach and is always consistent with the latest developments. If there is a graph database/framework that is currently not supported by Blueprints and you are an expert with that system, please contribute an implementation. To get a feel of what is required, see Property Graph Model and Property Graph Model Test Suite.
Below is a list of desired implementations. This list is not intended to be exhaustive. Please feel free to add to the list.
Sail
constructor is needed)


Temasys Web SDK Demo: Screenshare and Camera
Share screen
Share screen (Replace remote camera)
Share screen (Replace all camera)
© Temasys Communications Pte Ltd 2019. All Rights Reserved.


609 people currently under detention in J&K: Home ministry
The Ministry of Home Affairs (MHA) on Wednesday said that over 609 people are currently under detention in Jammu and Kashmir.
by Asian News InternationalThe Ministry of Home Affairs (MHA) on Wednesday said that over 609 people are currently under detention in Jammu and Kashmir.
The ministry, in reply to a question in Rajya Sabha, said that in order to prevent offences involving a breach of peace, activities prejudicial to the security of the state and maintenance of the public order, as many as 5,161 preventive arrests were made in Kashmir valley since August 4.
Those arrested included stone pelters, miscreants, over ground workers (OGWs), separatists and political workers.
"Out of these, 609 persons are presently under detention, out of which approximately 218 are stone pelters," the ministry in an official statement.
The central government had on August 5 earlier this year announced its decision to bifurcate Jammu and Kashmir into two Union Territories (UTs).
Following this, various mainstream political leaders and others were put under detention.
Earlier today, Union Minister Amit Shah said that the incidents of stone-pelting have witnessed a dip.
"In Jammu and Kashmir, the situation has become fully normal. There are various kinds of rumours in India and all over the world but I want to tell that not a single person has died in police firing after August 5," he clarified.
ALSO READ: No curfew, everything normal in Kashmir: Amit Shah gives status report in Rajya Sabha


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Sound Event Detection¶
The task of sound event detection involves locating and classifying sounds in audio recordings - estimating onset and offset for distinct sound event instances and providing a textual descriptor for each. The usual approach for this problem is supervised learning with sound event classes defined in advance.
Metrics are defined for polyphonic sound event detection, in which the ground truth and system output contain overlapping sound event instances.
Two types of metrics are implemented:
- segment-based metrics - the ground truth and system output are compared in a fixed time grid; sound events are marked as active or inactive in each segment;
- event-based metrics - the ground truth and system output are compared at event instance level;
Intermediate statistics¶
Segment-based¶
- true positive: the ground truth and system output both indicate an event to be active in that segment
- false positive: the ground truth indicates an event to be inactive in that segment, but the system output indicates it as active
- false negative: the ground truth indicates an event to be active in that segment, but the system output indicates it as inactive.
- true negative: the ground truth and system output both indicate an event to be inactive.
Segment-based metrics implementation allow selecting the desired segment length for evaluation (see time_resolution
parameter).
Event-based¶
- true positive: an event in the system output that has a temporal position overlapping with the temporal position of an event with the same label in the ground truth. A collar is usually allowed for the onset and offset, or a tolerance with respect to the ground truth event duration.
- false positive: an event in the system output that has no correspondence to an event with same label in the ground truth within the allowed tolerance;
- false negative: an event in the ground truth that has no correspondence to an event with same label in the system output within the allowed tolerance.
- true negative: event-based metrics have no meaningful true negatives.
Event-based metrics implementation allow selecting the desired collar size (see t_collar
parameter) and use of onset only or onset and offset conditions for evaluation (see evaluate_onset
and evaluate_offset
parameters).
Averaging¶
Micro-averaging - intermediate statistics are aggregated over all test data, then metrics are calculated; each instance has equal influence on the final metric value;
Macro-averaging - intermediate statistics are aggregated class-wise, class-based metrics are calculated, then average of class based metrics; each class has equal influence on the final metric value.
Micro and macro averages can result in very different values when classes are highly unbalanced or performance on individual classes is very different.
Cross-validation¶
Recommended calculation for a cross-validation setup is to run all train/test folds and perform evaluation at the end (no fold-wise evaluation!). The reason is that folds are most often unbalanced due to the multilabel nature of the problem, and this results in biases when averaging. For more details, consult [1].
Implemented metrics¶
Precision, Recall and F-score¶
These can be calculated segment based or event based, micro or macro averaged.
Sensitivity and specificity¶
Balanced accuracy¶
Specificity and accuracy variants are only calculated as segment-based metrics.
Error Rate¶
Segment-based
Substitutions in segment k - S(k) - the number of ground truth events for which a correct event was not output, yet something else was. One substitution is equivalent to having one false positives and one false negatives in the same segment. There is no need to designate which erroneous event substitutes which.
Insertions in segment k - I(k) - events in system output that are not correct (false positives after substitutions are accounted for).
Deletions in segment k - D(k) - events in ground truth that are not correct (false positives after substitutions are accounted for).
N(k) is the number of events in segment k in ground truth.
Event-based
Substitutions - events in system output with correct temporal position but incorrect class label
Insertions - events in system output unaccounted for as correct or substituted
Deletions - events in ground truth unaccounted for as correct or substituted
N is the total number of events in ground truth.
Code¶
Segment-based metrics, main functions:
sed_eval.sound_event.SegmentBasedMetrics.evaluate
: Calculate intermediate values for evaluation and accumulate them.sed_eval.sound_event.SegmentBasedMetrics.results
: Calculate and return all metrics.sed_eval.sound_event.SegmentBasedMetrics.results_overall_metrics
: Calculate and return overall metrics (micro-averaged).sed_eval.sound_event.SegmentBasedMetrics.results_class_wise_metrics
: Calculate and return class-wise metrics.sed_eval.sound_event.SegmentBasedMetrics.results_class_wise_average_metrics
: Calculate and return class-wise average metrics (macro-averaged).
Event-based metrics, main functions:
sed_eval.sound_event.EventBasedMetrics.evaluate
: Calculate intermediate values for evaluation and accumulate them.sed_eval.sound_event.EventBasedMetrics.results
: Calculate and return all metrics.sed_eval.sound_event.EventBasedMetrics.results_overall_metrics
: Calculate and return overall metrics (micro-averaged).sed_eval.sound_event.EventBasedMetrics.results_class_wise_metrics
: Calculate and return class-wise metrics.sed_eval.sound_event.EventBasedMetrics.results_class_wise_average_metrics
: Calculate and return class-wise average metrics (macro-averaged).
Functions sed_eval.sound_event.SegmentBasedMetrics.evaluate
and sed_eval.sound_event.EventBasedMetrics.evaluate
take as a parameter event lists, use sed_eval.io.load_event_list
to read them from a file.
Usage example when reading event lists from disk:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | import sed_eval
file_list = [
{
'reference_file': 'office_snr0_high_v2.txt',
'estimated_file': 'office_snr0_high_out.txt'
},
{
'reference_file': 'office_snr0_low_v2.txt',
'estimated_file': 'office_snr0_low_out.txt'
},
{
'reference_file': 'office_snr0_med_v2.txt',
'estimated_file': 'office_snr0_med_out.txt'
},
{
'reference_file': 'office_snr-6_high_v2.txt',
'estimated_file': 'office_snr-6_high_out.txt'
}
]
data = []
# Get used event labels
all_data = sed_eval.util.event_list.EventList()
for file_pair in file_list:
reference_event_list = sed_eval.io.load_event_list(file_pair['reference_file'])
estimated_event_list = sed_eval.io.load_event_list(file_pair['estimated_file'])
data.append({'reference_event_list': reference_event_list,
'estimated_event_list': estimated_event_list})
all_data += reference_event_list
event_labels = all_data.unique_event_labels
# Start evaluating
# Create metrics classes, define parameters
segment_based_metrics = sed_eval.sound_event.SegmentBasedMetrics(event_label_list=event_labels,
time_resolution=1)
event_based_metrics = sed_eval.sound_event.EventBasedMetrics(event_label_list=event_labels,
t_collar=0.250)
# Go through files
for file_pair in data:
segment_based_metrics.evaluate(file_pair['reference_event_list'],
file_pair['estimated_event_list'])
event_based_metrics.evaluate(file_pair['reference_event_list'],
file_pair['estimated_event_list'])
# Get only certain metrics
overall_segment_based_metrics = segment_based_metrics.results_overall_metrics()
print "Accuracy:", overall_segment_based_metrics['accuracy']['accuracy']
# Or print all metrics as reports
print segment_based_metrics
print event_based_metrics
|
Usage example:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | import sed_eval
reference_event_list = sed_eval.util.EventList(
[
{
'event_label': 'car',
'event_onset': 0.0,
'event_offset': 2.5,
'file': 'audio/street/b099.wav',
'scene_label': 'street'
},
{
'event_label': 'car',
'event_onset': 2.8,
'event_offset': 4.5,
'file': 'audio/street/b099.wav',
'scene_label': 'street'
},
{
'event_label': 'car',
'event_onset': 6.0,
'event_offset': 10.0,
'file': 'audio/street/b099.wav',
'scene_label': 'street'
}
]
)
estimated_event_list = sed_eval.util.EventList(
[
{
'event_label': 'car',
'event_onset': 1.0,
'event_offset': 3.5,
'file': 'audio/street/b099.wav',
'scene_label': 'street'
},
{
'event_label': 'car',
'event_onset': 7.0,
'event_offset': 8.0,
'file': 'audio/street/b099.wav',
'scene_label': 'street'
}
]
)
segment_based_metrics = sed_eval.sound_event.SegmentBasedMetrics(
event_label_list=reference_event_list.unique_event_labels,
time_resolution=1.0
)
# Go through files
for file in reference_event_list.unique_files:
# Get reference event list for file by filtering reference_event_list
reference_event_list_for_current_file = reference_event_list.filter(file=file)
# Get estimated event list for file by filtering estimated_event_list
estimated_event_list_for_current_file = estimated_event_list.filter(file=file)
segment_based_metrics.evaluate(
reference_event_list=reference_event_list_for_current_file,
estimated_event_list=estimated_event_list_for_current_file
)
# Get only certain metrics
overall_segment_based_metrics = segment_based_metrics.results_overall_metrics()
print "Accuracy:", overall_segment_based_metrics['accuracy']['accuracy']
# Or print all metrics as reports
print segment_based_metrics
|
Segment based metrics¶
SegmentBasedMetrics (event_label_list[, ...]) |
Constructor |
SegmentBasedMetrics.evaluate (...) |
Evaluate file pair (reference and estimated) |
SegmentBasedMetrics.results () |
All metrics |
SegmentBasedMetrics.results_overall_metrics () |
Overall metrics |
SegmentBasedMetrics.results_class_wise_metrics () |
Class-wise metrics |
SegmentBasedMetrics.results_class_wise_average_metrics () |
Class-wise averaged metrics |
SegmentBasedMetrics.result_report_parameters () |
Report metric parameters |
SegmentBasedMetrics.result_report_overall () |
Report overall results |
SegmentBasedMetrics.result_report_class_wise () |
Report class-wise results |
SegmentBasedMetrics.result_report_class_wise_average () |
Report class-wise averages |
SegmentBasedMetrics.reset () |
Reset internal state |
-
class
sed_eval.sound_event.
SegmentBasedMetrics
(event_label_list, time_resolution=1.0)[source]¶ Constructor
Parameters: event_label_list : list, numpy.array
List of unique event labels
time_resolution : float (0,]
Segment size used in the evaluation, in seconds (Default value=1.0)
-
evaluate
(reference_event_list, estimated_event_list)[source]¶ Evaluate file pair (reference and estimated)
Parameters: reference_event_list : list of dict or dcase_util.containers.MetaDataContainer
Reference event list
estimated_event_list : list of dict or dcase_util.containers.MetaDataContainer
Estimated event list
Returns: self
-
overall_f_measure
()[source]¶ Overall f-measure metrics (f_measure, precision, and recall)
Returns: dict
results in a dictionary format
-
overall_error_rate
()[source]¶ Overall error rate metrics (error_rate, substitution_rate, deletion_rate, and insertion_rate)
Returns: dict
results in a dictionary format
-
overall_accuracy
(factor=0.5)[source]¶ Overall accuracy metrics (sensitivity, specificity, accuracy, and balanced_accuracy)
Parameters: factor : float [0-1]
balance factor (Default value=0.5)
Returns: dict
results in a dictionary format
-
class_wise_count
(event_label)[source]¶ Class-wise counts (Nref and Nsys)
Returns: dict
results in a dictionary format
-
class_wise_f_measure
(event_label)[source]¶ Class-wise f-measure metrics (f_measure, precision, and recall)
Returns: dict
results in a dictionary format
-
class_wise_error_rate
(event_label)[source]¶ Class-wise error rate metrics (error_rate, deletion_rate, and insertion_rate)
Returns: dict
results in a dictionary format
-
Event based metrics¶
EventBasedMetrics (event_label_list[, ...]) |
Constructor |
EventBasedMetrics.evaluate (...) |
Evaluate file pair (reference and estimated) |
EventBasedMetrics.results () |
All metrics |
EventBasedMetrics.results_overall_metrics () |
Overall metrics |
EventBasedMetrics.results_class_wise_metrics () |
Class-wise metrics |
EventBasedMetrics.results_class_wise_average_metrics () |
Class-wise averaged metrics |
EventBasedMetrics.result_report_parameters () |
Report metric parameters |
EventBasedMetrics.result_report_overall () |
Report overall results |
EventBasedMetrics.result_report_class_wise () |
Report class-wise results |
EventBasedMetrics.result_report_class_wise_average () |
Report class-wise averages |
EventBasedMetrics.reset () |
Reset internal state |
-
class
sed_eval.sound_event.
EventBasedMetrics
(event_label_list, evaluate_onset=True, evaluate_offset=True, t_collar=0.2, percentage_of_length=0.5)[source]¶ Constructor
Parameters: event_label_list : list
List of unique event labels
evaluate_onset : bool
Evaluate onset (Default value=True)
evaluate_offset : bool
Evaluate offset (Default value=True)
t_collar : float (0,]
Time collar used when evaluating validty of the onset and offset, in seconds (Default value=0.2)
percentage_of_length : float in [0, 1]
Second condition, percentage of the length within which the estimated offset has to be in order to be consider valid estimation (Default value = 0.5)
-
evaluate
(reference_event_list, estimated_event_list)[source]¶ Evaluate file pair (reference and estimated)
Parameters: reference_event_list : event list
Reference event list
estimated_event_list : event list
Estimated event list
Returns: self
-
static
validate_onset
(reference_event, estimated_event, t_collar=0.2)[source]¶ Validate estimated event based on event onset
Parameters: reference_event : dict
Reference event
estimated_event: dict
Estimated event
t_collar : float > 0, seconds
Time collar with which the estimated onset has to be in order to be consider valid estimation (Default value = 0.2)
Returns: bool
-
static
validate_offset
(reference_event, estimated_event, t_collar=0.2, percentage_of_length=0.5)[source]¶ Validate estimated event based on event offset
Parameters: reference_event : dict
Reference event
estimated_event : dict
Estimated event
t_collar : float > 0, seconds
First condition, Time collar with which the estimated offset has to be in order to be consider valid estimation (Default value = 0.2)
percentage_of_length : float in [0, 1]
Second condition, percentage of the length within which the estimated offset has to be in order to be consider valid estimation (Default value = 0.5)
Returns: bool
-
overall_f_measure
()[source]¶ Overall f-measure metrics (f_measure, precision, and recall)
Returns: dict
results in a dictionary format
-
overall_error_rate
()[source]¶ Overall error rate metrics (error_rate, substitution_rate, deletion_rate, and insertion_rate)
Returns: dict
results in a dictionary format
-
class_wise_count
(event_label)[source]¶ Class-wise counts (Nref and Nsys)
Returns: dict
results in a dictionary format
-
class_wise_f_measure
(event_label)[source]¶ Class-wise f-measure metrics (f_measure, precision, and recall)
Returns: dict
results in a dictionary format
-
class_wise_accuracy
(event_label)¶
-
class_wise_error_rate
(event_label)[source]¶ Class-wise error rate metrics (error_rate, deletion_rate, and insertion_rate)
Returns: dict
results in a dictionary format
-
overall_accuracy
(factor=0.5)¶
-
result_report_class_wise
()¶ Report class-wise results
Returns: str
result report in string format
-
result_report_class_wise_average
()¶ Report class-wise averages
Returns: str
result report in string format
-
result_report_overall
()¶ Report overall results
Returns: str
result report in string format
-
results
()¶ All metrics
Returns: dict
results in a dictionary format
-
results_class_wise_average_metrics
()¶ Class-wise averaged metrics
Returns: dict
results in a dictionary format
-
results_class_wise_metrics
()¶ Class-wise metrics
Returns: dict
results in a dictionary format
-
results_overall_metrics
()¶ Overall metrics
Returns: dict
results in a dictionary format
-
Rerefences¶
| [1] | Forman, G. and Scholz, M. “Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement”. SIGKDD Explor. Newsl. 12, 1, November 2010, pp. 49-57. http://kdd.org/exploration_files/v12-1-p49-forman-sigkdd.pdf |


Simon Dann
/now
Last updated March 19th, 2021.
This “now page” offers a big picture glimpse into my what I’m focused on at this point in my life. What is a now page?
What am I currently focused on?
- Reinvigorating my blog, there have been many attempts made in the past
- Fedicast, a federated podcast publishing platform
What am I watching?
- The Expanse on Amazon Prime
- Star Trek: The Original Series on Netflix
What am I reading?
You can see my bookshelf at bookwyrm.social or at openlibrary.org here.


Hi, my name is Todd Hayes and I love to write code that is effcient and design web pages that our unquie and creative.
I program code from the eyes of a QA manager. Writing clean, and efficent code is what I do!
I enjoy creating progams and websites with these technologies: HTML, CSS, Javasctipt, Angular, Bootstrap, etc!
I love making unquie but functionl designs come to life!
Javascript, Angular, React no what javascript you use I have your back!
The tried and true way of writing back-end services for my clients-side apps.


a powerful drink
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When you're thirsty at night, take care you don't accidentally reach for the bottled cat, for it will not be pleased. treasure this card and play it when you are certain to have gained the creatures courtesy.
type
mythical
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Esprima (esprima.org, BSD license) is a high performance, standard-compliant ECMAScript parser written in ECMAScript (also popularly known as JavaScript). Esprima is created and maintained by Ariya Hidayat, with the help of many contributors.
Esprima serves as a building block for some JavaScript language tools, from code instrumentation to editor autocompletion.
Esprima runs on many popular web browsers, as well as other ECMAScript platforms such as Rhino and Node.js.
For more information, check the web site esprima.org.


How do you send EUR to your friend using USD on the Stellar network?
Let’s start by explaining what exactly is the Stellar network and how it works.
The Internet is made up of a network servers containing our data,
websites, and applications.
Like the Internet, Stellar is a network of decentralized servers
in many locations that power a distributed ledger.
This ledger records every transaction in the system for people and companies alike.
A complete copy of the global ledger exists on each Stellar server.
Any entity can run a server. The network becomes more robust with more servers.
The servers communicate with each other to verify transactions and sync the ledger every 2-5 seconds. This mechanism is known as consensus.
The ledger records your money as credit, which is issued by anchors. Anchors act as bridges between a given currency and the Stellar network.
Banks and payment processors are good examples of real-world anchors.

Issued credit can be sent and received between people on the network. Stellar has a distributed exchange, so you can send EUR credits to your friend using your USD credit balance. The network will automatically convert it at the lowest rate for you.
Your friend will receive EUR credit,
which she can withdraw using an anchor supporting EUR.


{% extends "includes/lists/object_detail_base.html" %}{% load apps_urls thumbnail common_markdown %} {% block title %}Challenge: {{ object.name }} - {{ block.super }}{% endblock title %} {% block tag_list %} {% include "includes/tag_list.html" with tag_list=object.tags.all tag_type="search" %} {% endblock tag_list %} {% block detail_content %}
{{ object.description }}
Starts on {{ object.start_datetime }}
Ends on {{ object.end_datetime }}
{% if object.event_dates %}{{ object.event_dates|linebreaksbr }}
{% endif %}Entries will be published {% if object.hide_entries %} after the challenge has finished. {% else %} during the challenge. {% endif %}
{{ object.acknowledgments|linebreaksbr }}


SGMLNORM(1) SGMLNORM(1) NAME sgmlnorm - normalize SGML documents An SGML System Conforming to International Standard ISO 8879 -- Standard Generalized Markup Language SYNOPSIS sgmlnorm [ -Cdemnv ] [ -bbctf ] [ -ccatalog ] [ -Ddir ] [ -iname ] [ -wwarning ] sysid... DESCRIPTION sgmlnorm prints on the standard output a normalized document instance for the SGML document contained in the concatenation of the entities with system identifiers sysid... When the normalized instance is prefixed with the original SGML declara‐ tion and prolog, it will have the same ESIS as the original SGML docu‐ ment, with the following exceptions: · The output of sgmlnorm does not protect against the recognition of short reference delimiters, so any USEMAP declarations must be removed from the DTD. · The normalized instance will use the reference delimiters, even if the original instance did not. · If marked sections are included in the output using the -m option, the reference reserved names will be used for the status keywords even if the original instance did not. · Any ESIS information relating to the SGML LINK feature will be lost. The normalized instance will not use any markup minimization features except that: · Any attributes that were not specified in the original instance will not be included in the normalized instance. (Current attributes will be included.) · If the declared value of an attribute was a name token group, and a value was specified that was the same as the name of the attribute, then the attribute name and value indicator will be omitted. For exam‐ ple, with HTML sgmlnorm would output <DL COMPACT> rather than <DL COM‐ PACT="COMPACT">. OPTIONS -bbctf Use the BCTF name bctf for output. See nsgmls(1) for more infor‐ mation about this option. -cfile Use the catalog entry file file. -C The filename... arguments specify catalog files rather than the document entity. The document entity is specified by the first DOCUMENT entry in the catalog files. -d Output a document type declaration with the same external identi‐ fier as the input document, and with no internal declaration sub‐ set. No check is performed that the document instance is valid with respect to this DTD. -Ddirectory Search directory for files specified in system identifiers. Multi‐ ple -D options are allowed. See nsgmls(1) for more information about this option. -e Describe open entities in error messages. -iname Pretend that <!ENTITY % name "INCLUDE"> occurs at the start of the document type declaration subset in the SGML document entity. Since repeated definitions of an entity are ignored, this defini‐ tion will take precedence over any other definitions of this entity in the document type declaration. Multiple -i options are allowed. If the SGML declaration replaces the reserved name INCLUDE then the new reserved name will be the replacement text of the entity. Typically the document type declaration will contain <!ENTITY % name "IGNORE"> and will use %name; in the status key‐ word specification of a marked section declaration. In this case the effect of the option will be to cause the marked section not to be ignored. -m Output any marked sections that were in the input document instance. -n Output any comments that were in the input document instance. -r Raw output. Don't perform any conversion on RSs and REs when printing the entity. The entity would typically have the storage manager attribute records=asis. -v Print the version number. -wtype Control warnings and errors according to type. See nsgmls(1) for the allowed values of type. AUTHOR James Clark<EMAIL_ADDRESS>Conversion to DocBook and man page from original HTML documention by Steve Cheng<EMAIL_ADDRESS>SEE ALSO nsgmls(1) /usr/share/doc/sp/sgmlnorm.htm SP 05 July 1999 SGMLNORM(1)


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{% extends 'layouts/base.html' %} {% block title %} Homepage {% endblock %} {% block content %}
Review and critique your peers' research questions.
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Test Extracted from Guide to Pharmacology
The scraper should extract markup for 49 MolecularEntity and 3 Protein.


--- layout: default nav: attributes > ic-disable-when-doc-hidden ---
ic-disable-when-doc-hidden
- Disable When Document Hidden AttributeThe ic-disable-when-doc-hidden
attribute tells Intercooler to not to issue a given request if the
document is currently hidden, as determined by the document.hidden
property. This allows you to
pause polling, for example, when a document is in an inactive tab, or the screen saver is running.
The value of the attribute should be true
or false
ic-disable-when-doc-hidden
has no dependency implications.


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March
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2015
Practice CTF List / Permanant CTF List
Here’s a list of some CTF practice sites and tools or CTFs that are long-running. Thanks, RSnake for starting the original that this is based on. If you have any corrections or suggestions, feel free to email ctf at the domain psifertex with a dot com tld.
Live Online Games
Recommended
Whether they’re being updated, contain high quality challenges, or just have a lot of depth, these are probably where you want to spend the most time.
- http://hax.tor.hu/
- https://pwn0.com/
- http://www.smashthestack.org/
- http://ringzer0team.com/
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- http://www.overthewire.org/wargames/
- http://counterhack.net/Counter_Hack/Challenges.html
- http://www.hackthissite.org/
- http://exploit-exercises.com/
- http://vulnhub.com/
Others
- http://damo.clanteam.com/
- http://p6drad-teel.net/~windo/wargame/
- http://roothack.org/
- http://bright-shadows.net/
- http://www.mod-x.co.uk/main.php
- http://scanme.nmap.org/
- http://www.hackertest.net/
- http://net-force.nl/
- http://securityoverride.org/ Some good concepts, but “canned” vulnerabilities (string matching on input) will frustrate knowledgable hackers and teach newbies the wrong lessons
Meta
- http://www.wechall.net/sites.php (excellent list of challenge sites)
- http://ctf.forgottensec.com/wiki/ (good CTF wiki, though focused on CCDC)
- http://repo.shell-storm.org/CTF/ (great archive of recent CTFs)
Webapp Specific
- http://demo.testfire.net/
- http://wocares.com/xsstester.php
- http://crackme.cenzic.com/
- http://test.acunetix.com/
- http://zero.webappsecurity.com/
- http://ha.ckers.org/challenge/
- http://ha.ckers.org/challenge2/
Forensics Specific
- http://computer-forensics.sans.org/community/challenges
- http://www.dc3.mil/challenge/
- http://forensicscontest.com/
Recruiting
Paid Training
Downloadable Offline Games
- http://www.badstore.net/
- http://www.owasp.org/index.php/Category:OWASP_WebGoat_Project
- http://www.owasp.org/index.php/Owasp_SiteGenerator
- Damn Vulnerable Web App
- Stanford SecureBench
- Stanford SecureBench Micro
- Damn Vulnerable Linux (not currently live? localmirror)
- http://www.irongeek.com/i.php?page=security/mutillidae-deliberately-vulnerable-php-owasp-top-10
Inactive or Gone
Just around for historical sake, or on the off-chance they come back.
- http://rootcontest.com/
- http://intruded.net/
- https://how2hack.net
- WebMaven (Buggy Bank)
- http://www.foundstone.com/us/resources/proddesc/hacmetravel.htm
- http://www.foundstone.com/us/resources/proddesc/hacmebooks.htm
- http://www.foundstone.com/us/resources/proddesc/hacmecasino.htm
- http://www.foundstone.com/us/resources/proddesc/hacmeshipping.htm
- http://hackme.ntobjectives.com/
- http://testphp.acunetix.com/
- http://testasp.acunetix.com/Default.asp
- http://prequals.nuitduhack.com
- http://www.gat3way.eu/index.php (Russian)
Source: http://captf.com/practice-ctf


The goal of the pipeline is to multiply two long numbers. We pretend that it cannot be done in one operation on a single machine. So we decide to split the task into subtasks of multiplying the first long number by individual digits of the second long number for the sake of an example. At the last step the partial products are shifted and added together to yield the final product.
|
A J-diagram is a directed acyclic graph where nodes represent Jobs, Semaphores or Accumulators with edges representing relationships and dependencies. Most of these objects are created dynamically during the pipeline execution, so here you'll see a lot of action - the J-diagram will be growing. J-diagrams can be generated at any moment during a pipeline's execution by running Hive's visualize_jobs.pl script (new in version/2.5) . |
An A-diagram is a directed graph where most of the nodes represent Analyses and edges represent Rules. As a whole it represents the structure of the pipeline which is normally static. The only changing elements will be job counts and analysis colours. A-diagrams can be generated at any moment during a pipeline's execution by running Hive's generate_graph.pl script. |
The main bulk of this document is a commented series of snapshots of both types of diagrams during the execution of the pipeline.
They can be approximately reproduced by running a sequence of commands, similar to these, in a terminal:
export PIPELINE_URL=sqlite:///lg4_long_mult.sqlite # An SQLite file is enough to handle this pipeline init_pipeline.pl Bio::EnsEMBL::Hive::Examples::LongMult::PipeConfig::LongMult_conf -pipeline_url $PIPELINE_URL # Initialize the pipeline database from a PipeConfig file runWorker.pl -url $PIPELINE_URL -job_id $JOB_ID # Run a specific job - this allows you to force your own order of execution. Run a few of these beekeeper.pl -url $PIPELINE_URL -analyses_pattern $ANALYSIS_NAME -sync # Force the system to recalculate job counts and determine states of analyses visualize_jobs.pl -url $PIPELINE_URL -out long_mult_jobs_${STEP_NUMBER}.png # To make a J-diagram snapshot (it is convenient to have synchronized numbering) generate_graph.pl -url $PIPELINE_URL -out long_mult_analyses_${STEP_NUMBER}.png # To make an A-diagram snapshot (it is convenient to have synchronized numbering) |
|
After executing these two jobs:
|
|


rake spec:controllers
rake spec:helpers
rake spec:lib
rake spec:mailers
rake spec:models
rake spec:requests
rake spec:routing
rake spec:views
# spec/controllers/*.rb
describe MyController do
describe "POST update" do
render_views #optional
it "works" do
post :update, { user: { name: "john" } }
controller
controller.send ...
response
expect(response).to be_success
expect(response).to have_http_status(200)
expect(response).to render_template("index")
expect(response).to redirect_to '/..'
expect(assigns :article).to eq article
response.status
end
end
end
# spec/requests/*.rb
describe "home page" do
it "displays the user's username after successful login" do
get "/login"
post "/login", username: "jdoe", password: "secret"
expect(response.status).to eql 200
expect(response).to redirect_to(...)
expect(response).to render_template(:show)
expect(response.body).to include 'hello'
follow_redirect!
end
end
# spec/routing/*.rb
describe "routing to profiles" do
it "routes /profile/:username to profile#show for username" do
expect(get: "/profiles/jsmith").to route_to(
controller: "profiles",
action: "show",
username: "jsmith"
)
end
it "does not expose a list of profiles" do
expect(get: "/profiles").not_to be_routable
end
end
# spec/helpers/*.rb
describe EventsHelper do
describe "#link_to_event" do
it "displays the title, and formatted date" do
event = Event.new("Ruby Kaigi", Date.new(2010, 8, 27))
# helper is an instance of ActionView::Base configured with the
# EventsHelper and all of Rails' built-in helpers
expect(helper.link_to_event).to match /Ruby Kaigi, 27 Aug, 2010/
end
end
end
# spec/features/*.rb
feature 'Signing in' do
given(:something) { "hi" }
background do
User.make email<EMAIL_ADDRESS>end
scenario 'Signing in with credentials' do
end
end
be_a_new(Widget) # new_record?
render_template("new")
render_template(partial: 'form', locals: {...})
redirect_to(widgets_path)
route_to(..)
be_routable
have_http_status(500)
have_http_status(:created)
travel_to Time.new(2014, 11, 14, 01, 04, 44)
...
travel_back
travel_to Time.new(2014, 11, 14, 01, 04, 44) do
...
end


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Feature List (Current)¶
Authentication and Authorization¶
- Login
- Logout
User Management¶
- Create new user
- View list of existing users
- View individual user details
- Update user details
- Delete user
- Password management still missing
Patient Records¶
- Create new patient
- View list of existing patients
- View individual patient details (personal information)
- Update patient details
- Delete patient
Lab Sections - Create, Read, Update and Delete¶
- Create new lab section
- View list of existing lab sections
- View individual lab section details
- Update lab section details
- Delete lab section
Test Types¶
- Create new test type
- View list of existing test types
- View individual test type details
- Update test type details
- Delete test type
Measures¶
- Create new measure
- View list of existing measures
- View individual measure details
- Update measure details
- Delete measure
Specimen Types - Create, Read, Update and Delete
- Create new specimen type
- View list of existing specimen types
- View individual specimen type details
- Update specimen type details
- Delete specimen type
Inventory¶
The inventory module deals with the laboratory commodities from when they are received from suppliers to issuing to different locations within the hospital as well as stock taking of the laboratory commodities.Commodities are the drugs, reagents and equipment’s required in the laboratory. Metrics or unit of issue is the unit or quantity in which commodities or items are procured, stored, and issued. For example in kilograms, milligrams (100mg) etc.It has the following functionalities
- Add new supplier
- Add item
- Add Item request
- View list of existing items
- View list of existing suppliers
- View list of Item requests


Hi [firstname], Congragulations on your order! here is your order summary.
| Firstname | [firstname] |
|---|---|
| [email] | |
| Order Date | [orderdate] |
| Order Number | [ordernumber] |
| Product Name | [productname] |
| Price | [price] |
| Quantity | [quantity] |
| Session Type | [sessiontype] |
| Length Of Routine | [lengthofroutine] |
| Experience Level | [experiencelevel] |


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A
G
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P
S
A
addData(String, String)
- Method in class http.requests.
PostRequest
addFile(String, File)
- Method in class http.requests.
PostRequest
addFile(String, String)
- Method in class http.requests.
PostRequest
addHeader(String, String)
- Method in class http.requests.
GetRequest
addHeader(String, String)
- Method in class http.requests.
PostRequest
addUser(String, String)
- Method in class http.requests.
GetRequest
addUser(String, String)
- Method in class http.requests.
PostRequest
G
getContent()
- Method in class http.requests.
GetRequest
getContent()
- Method in class http.requests.
PostRequest
getHeader(String)
- Method in class http.requests.
GetRequest
getHeader(String)
- Method in class http.requests.
PostRequest
GetRequest
- Class in
http.requests
GetRequest(String)
- Constructor for class http.requests.
GetRequest
H
http.requests
- package http.requests
P
PostRequest
- Class in
http.requests
PostRequest(String)
- Constructor for class http.requests.
PostRequest
PostRequest(String, String)
- Constructor for class http.requests.
PostRequest
S
send()
- Method in class http.requests.
GetRequest
send()
- Method in class http.requests.
PostRequest
A
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Processing Library httprequests_processing by Rune Madsen. (c) 2014


Members
(static) badges
An object for storing image references (badges)
Properties:
| Type | Description |
|---|---|
(static) is_flipped
Variable for storing selected badge index, enabling second badge selection
Properties:
| Name | Type | Description |
|---|---|---|
int |
number | index |
(static) pairs
An array for storing index of badges pairs
Properties:
| Name | Type | Description |
|---|---|---|
int |
Object | index |
Methods
(static) flipBadge()
A method with flipping badges game logic
(static) generateGrid()
A method for generating game grid markup
(static) initialize()
A method for initializing the game, assigns callback to new_game button
(static) newGame()
A method for initializing the game


utils Class
Exports few utility methods and constants for express-yui
components.
Item Index
Methods
- clone static
- extend static
- joinURLFolder static
- minifyFunction static
Properties
- debugMode static
- DEFAULT_COMBO_CONFIG static
Methods
clone
-
oldObj
Deep clone of an object.
Parameters:
-
oldObj
Objectthe origal object to be cloned
Returns:
The cloned object
extend
-
obj
-
supplier
Extends object with properties from other objects.
var a = { foo: 'bar' }
, b = { bar: 'baz' }
, c = { baz: 'xyz' };
utils.extends(a, b, c);
// a => { foo: 'bar', bar: 'baz', baz: 'xyz' }
Parameters:
-
obj
Objectthe receiver object to be extended
-
supplier
Objectobjects
Returns:
The extended object
joinURLFolder
-
url
Utility method to use the loader base and add the folder name that represents a group to complete the new base and root value for each custom group.
utils.joinURLFolder('http://foo.com/bar', 'baz'); // => http://foo.com/bar/baz/
utils.joinURLFolder('https://foo.com/bar', 'baz'); // => https://foo.com/bar/baz/
utils.joinURLFolder('//foo.com/bar/', 'baz'); // => //foo.com/bar/baz/
utils.joinURLFolder('/bar', 'baz'); // => /bar/baz/
Parameters:
-
url
Stringthe url that should get the new segment added at the end
Returns:
the new url
minifyFunction
-
fn
Minify the body of a function by removing spaces, tabs, comments, breaklines, etc. This is specially useful to optimize the function before serializing it to send it to the client side as a js blob.
Parameters:
-
fn
Functionthe function to minify
Returns:
the minified function
Properties
debugMode
Boolean
static
Whether the app is running in debug mode or not. True if nodejs is running in development mode.
DEFAULT_COMBO_CONFIG
Object
static
The default combo handler configuration for app origin.


I am a hands-on developer with over 3 years’ experience working on a variety of projects from conception to delivery. I have learned a wide range of technologies and programming languages like Java, C++, SQL and PHP. I have over 3 years' experience in Android development.
I follow the latest industry trends with great interest. I always look to code to the highest standards possible. I am seeking a position in a well-established and leading organization where my educational background could be utilized and enhanced.
Mobile Loyalty Program App for customers and merchants. Awards customers with points on their purchases that will eventually be redeemed on future purchases.
Open on play storeAndroid app for Uber users to spend their traffic time browsing through different kinds of digital content. Advertisers can use the app to deliver new & innovative ways of advertising.
Open on play storeAndroid App enables users to view different type of events in Sudi Arabia. Admins can create and modify events.
Open on play storeApp enables users to add their own places to the map and view various places categories. Simply add your own place and choose category (doctor, hospital, market, hotel…etc.) and all users can view it. View other users’ added locations, navigate to it, contact with them by chat or call them.
Open on play storeChat app in which user can add friends and chat with them also he can add posts and join groups . Create local data base to store chat messages so user can preview chat while offline.
Open on play storeApp enables users to view movies list and view by most popular, top rated or favorites. App developed in MVP architecture pattern.
Open on GitHub


Today I've written the first lines of code for the XEOS memory allocator.
For now, I won't implement the malloc()
set of functions in the C library, because I haven't implemented the brk
and mmap
system calls.
Doing this would surely be fun, but right now I need to code some other kernel stuff.
So I decided to write a specific allocator for the Xeos kernel. This way, it will have it's own allocator, managing it's own memory region.
I guess it's the best solution for now, to get things correctly done.
No surprise, this will be kmalloc()
.
This will save me a lot of time, and make the code more maintainable for later.
I'm also going to see if I can build LLVM for Xeos... I'm a bit tired of GCC, since Apple's XCode 4... ; )


{% comment %} ===================== Links List ===================== Used for: - lists of links to content within a particular channel or section. - lists of Related Links when the `isRelated` property is set in the include tag, e.g.: {% include "src/site/components/navigation-links-list.html" with isRelated = true %} NOTE: Can also pass majorlinks or relatedlinks in as a variable on the include tag, e.g.: {% include "src/site/components/navigation-links-list.html" with majorlinks = anothergroupofmajorlinks %} In this example, `anothergroupofmajorlinks` is a group of links that uses the same YAML structure as `majorlinks`, but with a different group name. Pass the different group name as the value for the `majorlinks` variable of the include. See https://help.shopify.com/themes/liquid/tags/theme-tags#include {% endcomment %} {% if isRelated == true %} {% assign linklist = relatedlinks %} {% else %} {% assign linklist = majorlinks %} {% endif %}


Animal Crossing: New Horizons — Stalk Market Calculator
Phase 1: Buying turnips
| What is the turnip price in Bells? | |
| What amount of Bells do you want to spend? | |
|
What is the maximum number of turnip bunches that you can store?
Leave blank if this doesn't apply. |
|
|
What is your safe sell price?
This is a price above the buy price that you believe will definitely occur during the week. |
|
|
What is your risky sell price?
This is a price above your safe sell price that you think has a chance of occurring during the week. |
|
|
What is your projected recoup sell price?
This is the lowest that you think the Saturday PM price would be. You will sell turnips on Saturday PM if the risky sell price isn't reached. |
|
|
Maximum potential loss (if risky sell price not reached):
If you don't see the 'risky' sell price during the week, this is the portion of your initial investment that you could lose. |
|
|
What is your maximum acceptable loss?
What amount of the maximum potential loss are you willing to risk? The more loss you are willing to tolerate, the higher your potential profit will be. |
Based on the values that you have entered, you should buy turnips ( bunches of turnips), which will cost you Bells.
Once the turnip price reaches Bells or more, you should sell turnips ( bunches of turnips).
If the risky sell price does not occur during the week, you will lose at most Bells (assuming the recoup sell price is correct).
If the risky sell price does occur, you will have a profit of at least Bells.
Make sure to come back and fill out phase 2 before selling any turnips.
If the safe sell price is higher than you anticipated, you may be able to save more turnips to sell at an even higher price.
| Number of turnips you can theoretically buy: | |
| Actual amount to buy in hundreds: | |
| Actual amount to buy in bunches: | |
| Actual cost to buy all turnips: | |
| Minimum acceptable total sales: | |
| Sale price from total turnips at recoup price: | |
| Amount to cover through safe sale to offset potential loss: | |
| Profit over recoup per turnip sold at safe price: | |
| Exact amount to sell at safe price: | |
| Actual amount to sell in hundreds: | |
| Actual amount to sell in bunches: | |
| Safe sale gross: | |
| Remaining turnips after safe sale: | |
| Assuming risky profit sell price is not reached: | |
| Sale price of remaining turnips at recoup sell price: | |
| Total gross sales: | |
| Total potential loss: | |
| Assuming risky profit sell price is reached: | |
| Sale price of remaining turnips at risky sell price: | |
| Total gross sales: | |
| Total potential profit: |
Phase 2: Selling first round of turnips
|
What was the actual price when your safe sell price was reached?
Based on the values that you entered for phase 1, this price should be at least Bells. |
Based on the value that you have entered, you should sell turnips ( bunches of turnips).
If the risky sell price does not occur during the week, you will now lose at most Bells (assuming the recoup sell price is correct).
If the risky sell price does occur, you will now have a profit of at least Bells.
| Adjusted risk abatement per turnip sold: | ||
| Adjusted number of turnips to sell: | ||
| Adjusted number to sell in hundreds: | ||
| Adjusted number to sell in bunches: | ||
| Adjusted safe sell price: | ||
| Turnips remaining after safe sale: | ||
| Assuming risky profit sell price is not reached: | ||
| Sale price of remaining turnips at recoup sell price: | ||
| Total gross sales: | ||
| Total potential loss: | ||
| Assuming risky profit sell price is reached: | ||
| Sale price of remaining turnips at risky sell price: | ||
| Total gross sales: | ||
| Total potential profit: |
Phase 3: Selling remaining turnips
| What was the turnip price when you sold your remaining turnips? |
Based on the value you have entered, you have made a total profit of Bells.
| 2nd round sale price: | |
| Total sales: | |
| Total profit: |
Coming soon — Phase 4: Higher sale price occurred after all turnips sold
Phase 4 will calculate lost profit based on having sold some or all turnips at the highest weekly price.
This site uses cookies to store the values that you have entered.
Cookies are stored only on your computer, not on any remote servers.
You may clear this stored data at any time by clicking the button below.


The Ramones
Upcoming Shows
February 3rd at the Ritz
February 7th at the Ritz
February 13th at the Ritz
February 17th at the Ritz
Our cover picture
Our logo
Us in action!


Hello! My name is Ildefonso Orozco, but everybody calls me Ico.
I don't program only websites. Also I care the UI, I improve the UX, I change CSS to make it work as I want, I optimize the page speed and I make a SEO friendly website. So, I'm web developer.
Currently I'm working as Head of Developer Team in a local IT company located in Málaga, Spain. The main activities of this company are: Internet Advertisement, Online Newspapers, Travel Agency and Websites development.
Since 2011 I am the responsible of the Web Programming department reporting directly to the CEO and managing a team of up to 10 people. I am specialised in using methods of agile development (SCRUM) and continue directly involved in the main projects.
I started working at CR Internet in Sep 2006 as a Junior programmer using CMS (Wordpress and Joomla) for creating websites, writing non complex PHP codes for their incorporation to the applications and maintaining the existing webs.
In 2008 I was promoted to Senior programmer taking full responsibility since then for the most important projects, improving the algorithms by optimising the applications performance and using version control tools and Framework MVC (Codelgniter)
Linux Server maintenance. PHP and PERL script development for web reporting generation in HTML and PDF with PostgreSQL. Massive data processing in XML.
Main focused on Linux Servers configuration, Network, Databases and Programming (C, PHP, .NET)
Management and configuration of Networks
The quality and design at the services of middle and small size companies
Learning sessions on IT applications as support of Advertising Campaigns (Photoshop, Freehand, Flash and Go Live)
consola html, extractor contenido, qr.it, cURL, Autopublicar API TW con foto de webcam tomada por HTML, Resultados PageSpeed...
You can download Grayscale for free on the preview page at Start Bootstrap.
Visit Download PageFeel free to email us to provide some feedback on our templates, give us suggestions for new templates and themes, or to just say hello!


Director Madhur Bhandarkar gives an update on Lata Mangeshkar’s health
by FilmfareLata Mangeshkar is a name that needs no introduction to Bollywood fans. Often referred to as the nightingale of India, Lata Mangeshkar has won over the hearts of millions with the help of her melodies and soulful voice. Naturally, when news that she’s been admitted to a hospital broke out, fans were pretty upset. However, recently the family of the veteran singer confirmed that she’s on her road to recovery.
Filmmaker Madhur Bhandarkar also visited veteran singer Lata Mangeshkar at Mumbai's Breach Candy Hospital, and he took to social media to confirm that the melody queen is now “stable". He tweeted, “Visited the Hospital to see @lata_mangeshkar didi glad to inform that she is stable and responding positively to the treatment. Thanks everyone for countless blessings & prayers for her speedy recovery #latamangeshkar”
Well, we weren’t surprised that the comments on the tweet were flooded with fans expressing their joy over the singer’s recovery.


| ActionBuilder |
|
| ActionImpl |
Concrete implementation of Action .
|
| ActionMarshaller |
A thread safe Marshaller for Action objects.
|
| ActionUnmarshaller |
A thread-safe Unmarshaller for Action objects.
|
| AdviceBuilder |
|
| AdviceImpl |
Concrete implementation of Advice .
|
| AdviceMarshaller |
A thread safe Marshaller for Advice objects.
|
| AdviceUnmarshaller |
A thread-safe Unmarshaller for Advice objects.
|
| AssertionArtifactBuilder |
|
| AssertionArtifactImpl |
|
| AssertionArtifactMarshaller |
|
| AssertionArtifactUnmarshaller |
|
| AssertionBuilder |
|
| AssertionIDReferenceBuilder |
|
| AssertionIDReferenceImpl |
|
| AssertionIDReferenceMarshaller |
|
| AssertionIDReferenceUnmarshaller |
|
| AssertionImpl |
This class implements the SAML 1 Assertion statement.
|
| AssertionMarshaller |
A thread safe Marshaller for Assertion objects.
|
| AssertionUnmarshaller |
A thread-safe Unmarshaller for Assertion objects.
|
| AttributeBuilder |
|
| AttributeDesignatorBuilder |
|
| AttributeDesignatorImpl |
|
| AttributeDesignatorMarshaller |
|
| AttributeDesignatorUnmarshaller |
|
| AttributeImpl |
A Concrete implementation of the Attribute Interface.
|
| AttributeMarshaller |
A thread safe Marshaller for Attribute objects.
|
| AttributeQueryBuilder |
|
| AttributeQueryImpl |
|
| AttributeQueryMarshaller |
|
| AttributeQueryUnmarshaller |
|
| AttributeStatementBuilder |
|
| AttributeStatementImpl |
|
| AttributeStatementMarshaller |
|
| AttributeStatementUnmarshaller |
|
| AttributeUnmarshaller |
|
| AudienceBuilder |
|
| AudienceImpl |
Concrete class implementation of Audience .
|
| AudienceMarshaller |
A thread safe Marshaller for Audience objects.
|
| AudienceRestrictionConditionBuilder |
|
| AudienceRestrictionConditionImpl |
Concrete implementation of the org.opensaml.saml.saml1.core.AudienceRestrictionCondition.
|
| AudienceRestrictionConditionMarshaller |
|
| AudienceRestrictionConditionUnmarshaller |
|
| AudienceUnmarshaller |
A thread-safe Unmarshaller for Audience objects.
|
| AuthenticationQueryBuilder |
|
| AuthenticationQueryImpl |
|
| AuthenticationQueryMarshaller |
|
| AuthenticationQueryUnmarshaller |
|
| AuthenticationStatementBuilder |
|
| AuthenticationStatementImpl |
|
| AuthenticationStatementMarshaller |
|
| AuthenticationStatementUnmarshaller |
|
| AuthorityBindingBuilder |
|
| AuthorityBindingImpl |
|
| AuthorityBindingMarshaller |
|
| AuthorityBindingUnmarshaller |
|
| AuthorizationDecisionQueryBuilder |
|
| AuthorizationDecisionQueryImpl |
|
| AuthorizationDecisionQueryMarshaller |
|
| AuthorizationDecisionQueryUnmarshaller |
|
| AuthorizationDecisionStatementBuilder |
|
| AuthorizationDecisionStatementImpl |
|
| AuthorizationDecisionStatementMarshaller |
|
| AuthorizationDecisionStatementUnmarshaller |
|
| ConditionsBuilder |
|
| ConditionsImpl |
This is a concrete implementation of the Conditions interface.
|
| ConditionsMarshaller |
|
| ConditionsUnmarshaller |
A thread-safe Unmarshaller for Conditions objects.
|
| ConfirmationMethodBuilder |
|
| ConfirmationMethodImpl |
|
| ConfirmationMethodMarshaller |
|
| ConfirmationMethodUnmarshaller |
|
| DoNotCacheConditionBuilder |
|
| DoNotCacheConditionImpl |
|
| DoNotCacheConditionMarshaller |
|
| DoNotCacheConditionUnmarshaller |
|
| EvidenceBuilder |
|
| EvidenceImpl |
Concrete implementation of the Evidence interface.
|
| EvidenceMarshaller |
A thread safe Marshaller for Evidence objects.
|
| EvidenceUnmarshaller |
A thread safe Unmarshaller for Evidence objects.
|
| NameIdentifierBuilder |
|
| NameIdentifierImpl |
|
| NameIdentifierMarshaller |
|
| NameIdentifierUnmarshaller |
|
| RequestAbstractTypeImpl |
|
| RequestAbstractTypeMarshaller |
|
| RequestAbstractTypeUnmarshaller |
|
| RequestBuilder |
|
| RequestImpl |
Concrete implementation of Request .
|
| RequestMarshaller |
A thread safe Marshaller for Request objects.
|
| RequestUnmarshaller |
A thread safe Unmarshaller for Request objects.
|
| RespondWithBuilder |
|
| RespondWithImpl |
|
| ResponseAbstractTypeImpl |
|
| ResponseAbstractTypeMarshaller |
|
| ResponseAbstractTypeUnmarshaller |
|
| ResponseBuilder |
|
| ResponseImpl |
|
| ResponseMarshaller |
A thread safe Marshaller for Response objects.
|
| ResponseUnmarshaller |
A thread-safe Unmarshaller for Response
objects.
|
| StatusBuilder |
|
| StatusCodeBuilder |
|
| StatusCodeImpl |
|
| StatusCodeMarshaller |
|
| StatusCodeUnmarshaller |
A thread-safe Unmarshaller for StatusCode objects.
|
| StatusDetailBuilder |
|
| StatusDetailImpl |
|
| StatusDetailMarshaller |
|
| StatusDetailUnmarshaller |
|
| StatusImpl |
Concrete Implementation Status .
|
| StatusMarshaller |
A thread safe Marshaller for Status objects.
|
| StatusMessageBuilder |
|
| StatusMessageImpl |
Concrete implementation of org.opensaml.saml.saml1.core StatusMessage object.
|
| StatusMessageMarshaller |
|
| StatusMessageUnmarshaller |
|
| StatusUnmarshaller |
A thread-safe Unmarshaller for Status objects.
|
| SubjectBuilder |
Builder of (@link org.opensaml.saml.saml1.core.impl.SubjectImpl} objects.
|
| SubjectConfirmationBuilder |
|
| SubjectConfirmationImpl |
Concrete implementation of a SubjectConfirmation object.
|
| SubjectConfirmationMarshaller |
|
| SubjectConfirmationUnmarshaller |
|
| SubjectImpl |
Complete implementation of Subject .
|
| SubjectLocalityBuilder |
|
| SubjectLocalityImpl |
|
| SubjectLocalityMarshaller |
|
| SubjectLocalityUnmarshaller |
|
| SubjectMarshaller |
A thread safe Marshaller for Subject objects.
|
| SubjectQueryImpl |
Concrete (but abstract) implementation of SubjectQuery abstract type.
|
| SubjectQueryMarshaller |
|
| SubjectQueryUnmarshaller |
|
| SubjectStatementImpl |
Abstract type to implement SubjectStatementType.
|
| SubjectStatementMarshaller |
|
| SubjectStatementUnmarshaller |
|
| SubjectUnmarshaller |
A thread-safe Unmarshaller for Subject objects.
|


What makes Boat different?
How does Boat seperate itself from the crowd?
How is Boat different?
An easy way to erase data
Ease of use
Speed, in milliseconds
Boat allows you to easily erase your
user and server data, unlike other
bots where you have to go through
support channels and tickets to reach
the right person.
Boat, unlike other bots is very
easy to use with put out instructions
on our detailed documentation along
with a help desk and a community
server where you can get help fast.
Boat can undergo many actions a
second without losing any real performance, Boat handles lots of data and we can still keep it at below
60ms ping with over 99.9% uptime.
Who uses Boat?
People who trust Boat and use it often to moderate, entertain and maintain there Discord server.
Boat is a great bot that can be used for anything you need, moderation, server setup, etc. The bot has helped me manage all the servers I use.
- Majorpain0600
Boat is an amazing utilitarian & moderation bot. It helps my staff team maintain a safe and secure environment for my community server.
- Techy
Boat allows for easy logging and server administration and moderation; it plays an important role in any discord community and is one of the most responsive bots out there.
- Blender


--- layout: headered title: about extra_css: /css/common.css ---
My name is Ana Neri. I was raised in Southern California to modest Mexican parents. From California I went to MIT to study Computer Science; I belong to the class of 2017.
This site is my personal blog; my thoughts, projects, experiences. Some posts are meant as reminders for things I don't do very often. As a disclaimer, These writings reflect my own opinions and no one else's.