Creative video advertising / 2D Animated Explainers for your Business made with Motion Graphics in After Effects. Need to express an idea in an engaging, and fun manner? An explainer cartoon style will be a good fit for you, even big companies like Uber have them! Suitable for: MVPs, Promo Video, Creative Advertising, and Events.
I want a creative ad!(This link will take you to my Fiverr gig)
I will create an elegant, slick and responsive landing page for your Business. The website will be ideal for small businesses and startups looking to get an online presence. Comfort and tranquility are the values I put into my designs, and ensure a enjoyable navigation experience. Languages used: HTML5, CSS, Javascript.
I want a website!


Prototypes
Code I done that has never been used in a game yet!
Procedual Animated Horde
What I Did:
- Translation with Root Motion
- Inverse Kinematic(IK) 2 chain for each leg
- Boids Flocking that adds velocity to Root Motion Translation
- Cubic Bezier Curve Based Leg movement
Each leg has a "Home-Point". When a leg distance is more than X amount, that leg is lerped towards the Home-Point. I also have some overstep programmed in, each leg will overstep the Home-Point so the leg does not lag behind when moving fast.
This is done by a Cubic Bezier Curve with some added Easing. I also raise the leg a little bit so it is not dragged over the floor. That would look weired.
There is some more number tweaking to be done, but the proof of concept is their.
public class ProceduralAnimeController : MonoBehaviour
{
[SerializeField] private Transform _target;
[Header("Head")] [SerializeField] private Transform _headBone;
[SerializeField] private float _headMaxTurnAngle;
[SerializeField] private float _headTrackingSpeed;
[Header("Eyes")] [SerializeField] private Transform _leftEyeBone;
[SerializeField] private Transform _rightEyeBone;
[SerializeField] private float _eyeTrackingSpeed;
[SerializeField] private float _leftEyeMaxYRotation;
[SerializeField] private float _leftEyeMinYRotation;
[SerializeField] private float _rightEyeMaxYRotation;
[SerializeField] private float _rightEyeMinYRotation;
[Header("Legs")]
[SerializeField] private LegIKStepper _frontLeftLegStepper;
[SerializeField] private LegIKStepper _frontRightLegStepper;
[SerializeField] private LegIKStepper _backLeftLegStepper;
[SerializeField] private LegIKStepper _backRightLegStepper;
[Header("Movement")]
[SerializeField] private float _turnSpeed;
[SerializeField] private float _moveSpeed;
[SerializeField] private float _turnAcceleration;
[SerializeField] private float _moveAcceleration;
[SerializeField] private float _minDistToTarget;
[SerializeField] private float _maxDistToTarget;
[SerializeField] private float _maxAngelToTarget;
public Vector3 _currentVelocity;
public Vector3 FlockAdditon;
private float _currentAngularVelocity;
private void Start()
{ //Set our Stepper to world position. Did this so we can save the whole object as a prefab.
_frontLeftLegStepper.gameObject.transform.parent = null;
_frontRightLegStepper.gameObject.transform.parent = null;
_backLeftLegStepper.gameObject.transform.parent = null;
_backRightLegStepper.gameObject.transform.parent = null;
StartCoroutine(LegUpdate());
}
void RootMotionUpdate(float dt)
{
//Rotation
Vector3 towardTarget = _target.position - transform.position;
Vector3 towardTargetProjected = Vector3.ProjectOnPlane(towardTarget, transform.up);
float angelToTarget = Vector3.SignedAngle(transform.forward, towardTargetProjected, transform.up);
float targetAngularVelocity = 0;
if (Mathf.Abs(angelToTarget) > _maxAngelToTarget)
{
if (angelToTarget > 0)
targetAngularVelocity = _turnSpeed;
else
targetAngularVelocity = -_turnSpeed;
}
_currentAngularVelocity = Mathf.Lerp(_currentAngularVelocity, targetAngularVelocity,
1 - Mathf.Exp(-_turnAcceleration * Time.deltaTime));
transform.Rotate(0, _currentAngularVelocity * dt, 0, Space.World); //Y in worldspace
//Position
Vector3 targetVelocity = Vector3.zero;
if (Mathf.Abs(angelToTarget) < 90)
{
float distToTarget = Vector3.Distance(transform.position, _target.position);
if (distToTarget > _maxDistToTarget)
targetVelocity = _moveSpeed * towardTargetProjected.normalized;
else if (distToTarget < _minDistToTarget)
targetVelocity = (_moveSpeed / 2f) * -towardTargetProjected.normalized;
}
_currentVelocity = Vector3.Lerp(_currentVelocity, targetVelocity, 1 - Mathf.Exp(-_moveAcceleration * dt));
transform.position += _currentVelocity * dt;
if((transform.position - _target.position).magnitude > 5f)
transform.position += FlockAdditon * dt;
}
private void LateUpdate()
{
float dt = Time.deltaTime;
RootMotionUpdate(dt);
HeadTrackingUpdate(dt);
EyeTrackingUpdate(dt);
}
IEnumerator LegUpdate()
{
while (true)
{
do
{
_frontLeftLegStepper.TryMove();
_backRightLegStepper.TryMove();
yield return null;
} while (_frontLeftLegStepper.Moving || _backRightLegStepper.Moving);
do
{
_frontRightLegStepper.TryMove();
_backLeftLegStepper.TryMove();
yield return null;
} while (_frontRightLegStepper.Moving || _backLeftLegStepper.Moving);
}
}
}
Influence Maps
What I Did:
- Compute Shader to multiple maps together
- Map System to combine maps in order before evaluation
- Astar Obstacle avoidance using influence map carving
- Hazard System to affect values on influence map
- BoundingBox(AABB) to create NavData
- Basic NavMesh system
- Path slicing to optimize path evaluation


APNewsBreak: New Mexico GOP set to endorse Trump
by RUSSELL CONTRERASALBUQUERQUE, N.M. (AP) - The Republican Party of New Mexico appears set to join Nebraska Republicans and endorse President Donald Trump for re-election.
State GOP chairman Steve Pearce told The Associated Press on Monday that an endorsement “would be a mere formality” since everyone on the party’s central committee is supporting the president.
Pearce says he knew of nobody in New Mexico GOP circles who wasn’t supporting Trump. He also didn’t know if any of Trump’s Republican challengers, like former U.S. Rep. Joe Walsh or former Massachusetts Gov. Bill Weld, would even get on the New Mexico ballot.
The Nebraska GOP announced in August the party had unanimously endorsed Trump for re-election.
Four states have discussed plans to cancel their 2020 GOP presidential primaries.
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Copyright © 2019 The Washington Times, LLC.
Please read our comment policy before commenting.


---
layout: post
title: creative costumes of still practiced pagan rituals
date: '2013-09-23T07:58:54+01:00'
tags: []
tumblr_url: http://backlog.robbevan.com/post/62044772388/creative-costumes-of-still-practiced-pagan-rituals
---
Creative Costumes of Still-Practiced Pagan Rituals of Europe


object Loudness : TuneableTrackAttribute<Float>
The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typically range between -60 and 0 db.


M.K.Poshitha Tharanganie
Project Portfolio
Poshitha is a student of "sri lanka institute of information technology" (SLIIT)
Projects
Interactive AI Assistant For Diabetic Patients (IIDA))
Patient Online booking system
Timetable Management system


public class RecordList
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
protected AbstractRecord |
listHead |
| Constructor and Description |
|---|
RecordList() |
RecordList(RecordList copy) |
| Modifier and Type | Method and Description |
|---|---|
AbstractRecord |
getFront()
Remove and return the element at the front of the list.
|
AbstractRecord |
getNext(AbstractRecord current) |
AbstractRecord |
getRear()
Remove and return the element at the tail of the list.
|
boolean |
insert(AbstractRecord newRecord)
Insert the entry at the head of the list.
|
AbstractRecord |
peekFront() |
AbstractRecord |
peekNext(AbstractRecord curr) |
AbstractRecord |
peekRear() |
void |
print(java.io.PrintWriter strm) |
void |
putFront(AbstractRecord newRecord)
Explicit push onto front of list.
|
void |
putRear(AbstractRecord newRecord)
Explicit push onto rear of list.
|
boolean |
remove(AbstractRecord oldRecord) |
int |
size() |
java.lang.String |
toString() |
protected AbstractRecord listHead
public RecordList()
public RecordList(RecordList copy)
public final AbstractRecord getFront()
public final AbstractRecord getRear()
public AbstractRecord getNext(AbstractRecord current)
public final boolean insert(AbstractRecord newRecord)
public final void print(java.io.PrintWriter strm)
public final void putFront(AbstractRecord newRecord)
public final void putRear(AbstractRecord newRecord)
public final AbstractRecord peekFront()
public final AbstractRecord peekRear()
public final AbstractRecord peekNext(AbstractRecord curr)
public final boolean remove(AbstractRecord oldRecord)
public final int size()
public java.lang.String toString()
toString
in class java.lang.Object
Copyright © 2022 JBoss by Red Hat. All rights reserved.


HAHN (Schiebel), Ursula
Date of death: November 22, 2019
Date of birth: 1926
Age: 93
Location: Elmira, Ontario
Family
- Spouse: Alfred
- Children: Doug and Marlene, Philip and Marlene, Murray and Bonnie, Dennis, Roger and Joan, Kate and Dennis Ertel, Yvonne and Don James, Ursula and Gary Benesch, Karen and Michael Bickers, and Theresa
- Parents: John and Mary (Basler) Schiebel
- Siblings: Alma and Jim Bishop, Mona and Jack Jackson, Marina and Ken Hays, Gregory and Madeline Schiebel, Mello Schiebel, and Cosmos Schiebel
Visitation: Wednesday, December 4, 2019 from 2-4 and 7-9 p.m. at the Dreisinger Funeral Home, 62 Arthur St. S., Elmira.
Service: Thursday, December 5, 2019 at 11 a.m. at St. Teresa of Avila RC Church, 10 Flamingo Dr., Elmira. Cremation will follow.


Raiden Network: Vision, Challenges and Roadmap
Vision
Blockchains are awesome, but they are rather slow.
Imagine you are paying for groceries and it takes 10 seconds after you swiped your card until the cashier receives a confirmation of the payment and lets you leave. That’s roughly nine seconds too long.
Now imagine you are a process running on a computer. You want to sell content, data, bandwidth, processing time, storage or access to infrastructure. Imagine it would take 10 seconds to get confirmation of a payment from another process. That’s orders of magnitude off from your standards. It’s insane. The product you are selling might be obsolete by the time you get confirmation of a payment.
The upcoming machine-to-machine (M2M) economy in which software autonomously engages in trade with other software is set to constitute a significant part of future global commerce. But the machines are demanding. They want quick transfers and plenty thereof at almost zero cost. Therefore fast and low fee (micro-)payments will be a crucial building block of an M2M economy.
Blockchains are a hot candidate to become the payment infrastructure for IoT and the M2M economy. Combined with stable coins, the technology also becomes a viable candidate for everyday payments by machines and humans.
But in order to be viable, blockchain-based payment systems need to be fast, cheap and scalable. Those are properties that current blockchains are not particularly good at.
There are plenty of scalability approaches like sharding, side chains, interactive verification protocols or state channels. While all of these can potentially scale overall transaction capacity, only payment channel networks like Raiden seem to be adding the low cost and low latency properties at the same time.
Our vision is to provide a global infrastructure for fast, scalable and cheap decentralized payments for machines as well as humans. This is basically Satoshi Nakamoto’s initial vision but extended to be scalable and ready to support a world with thousands of different specialized tokens.
But how could it look like in
practice?
Note, the following is a randomly made
up story!
Fast forward five years to Bob buying a coffee. From his perspective he
simply uses his smart phone to pay for a coffee as he’s used to. In the
background though, his wallet carries out multiple tasks to facilitate the
payment. It sends some Moonbucks voucher tokens, plus the user’s preferred
stable coin to pay for the coffee. The merchant sends back some FairCoffeeBuyer
reputation tokens which the wallet automatically atomically swaps off-chain for
the local StreetWorkersFund tokens. The wallet sends some AwesomeWalletCreator
tokens to its developers to pay for it’s usage. To interact with the Raiden
Network without running an always-online full Ethereum and Raiden client, Bob’s
app also automatically pays reliable nodes for their services with RDN tokens as
an entrypoint to the Ethereum ecosystem.
So while the machines in the background carry out exchange in a complex network of commerce and services based on a zoo of tokens, the user still has a flawless experience.
Challenges
Payment channel
networks are a very young idea and technology. They have only first been
proposed roughly two years ago, whereas in comparison blockchains are known for
more than 8 years now. On top, they are a quite complicated technology, with
respect to both conception and implementation. This is emphasized by the fact
that neither the Lightning Network teams nor the Raiden Network team set on a
final specification.
Below we address some of the topics that still need work. While we keep
describing them on a high level in this post, each of them definitely deserves
their own future blog post.
Scalable Routing
One of the biggest problems is how to find a path from sender to receiver, without a global view of all channels and their availability and capacity. An efficient but centralized solution would be to have all participants continuously report their channel capacities to a central service and query it to get a path. A decentralized but inefficient alternative is to brute force a path by trial and error or broadcast channel updates to all participants. Efficient routing models through so called small-world networks exist but require dynamic connectivity between nodes. A viable system needs to find a balance between these approaches.
Maintaining a balanced Network / Fees
Pathfinding algorithms should not come up with just any path, but ideally one that decreases or at least avoids adding imbalances in mediating channels. This can be accomplished by participants announcing fees that incentivize finding the cheapest path that implicitly helps to keep the network balanced. Simulations have shown that increasing fees proportional to added channel imbalances greatly increases channel longevity.
Maintaining privacy while providing low latency messaging
Another big issue is preserving endpoint privacy of all participants. In order to help mediate multihop transfers, participants need to have a hot wallet. In such a setup you preferably don’t want to expose your endpoint publicly. Therefore a passive messaging protocol like Whisper is required, but at the same time needs to be able to scale to millions of users.
Light Clients
We assume, that 99% of all participants will access the system using Raiden light clients instead of full nodes. Similar to how users are using Metamask to access Dapps currently. This requires a protocol that effectively supports weakly connected and rarely available nodes at the leaves of the network.
Delegate Challengers while offline
Payment channels should allow any party to close the channel at any time. However, both parties need to be online during a channel’s settlement period to claim their received tokens. This becomes logistically infeasible for most common use-cases, people go offline more often than not. Therefore we need a system of decentralized third parties who are incentivized to settle on behalf of the offline party.
Upgradability / Governance
An upgrade of the protocol potentially affects millions of payment channels and their funds. It’s impractical to expect millions of end-users to vote on some technical protocol update proposal. Therefore, we need an effective governance mechanism that allows to delegate voting right to groups of experts.
Setting the incentives right to have a lively backbone
We need a decentralized network of pathfinding, monitoring and full node services as the backbone of the system. The providers of these services need to be compensated in order to have the right incentives to provide the service. At the same time, the core of the protocol should not have any fees other than those necessary to guarantee a balanced network.
Testing
Testing a decentralized, scalable peer-to-peer system is difficult. End-to-end testing with thousands of nodes is hard. Addressing all possible attack vectors is even harder. Testing is and remains a large part of the Raiden Network’s development process.
Roadmap
Instead of boring you with details of a roadmap let’s look at the obvious question: when is it ready?
We consider µRaiden to be ready and good to use for many applications already.
For the Raiden Network the answer is more complicated, but according to the initial Raiden concept would be: “It’s ready once it supports transfers between participants that don’t have a direct payment channel with each other and the software had a security audit and is deployed on the main chain”. It took us two years, but we are almost there. Add a security audit, deploy on the mainnet and we are done.
But you know the 80/20 rule. You can get 80% done in 20% of the time and the remaining 20% take another 80% of the time. Successful projects are going the lengths of also delivering as much as possible of the last 20% in order to gain adoption and stay competitive.
There are still many dimensions on which the Raiden Network can and should be improved. For example privacy, efficiency of finding a path, longevity of channels, accessibility through light clients, shorter settlement periods, governance mechanisms, usability etc. And some of them are must haves to satisfy our standards regarding a Minimal Viable Product.
Fortunately, the Raiden Network is built for continuous development with abstractions designed to allow for parallelized progress on many of the components that can be improved. Nonetheless this will take time, require research and hard work. But it’s worth it.
So far we have only addressed the protocols and the software. But in order to see widespread adoption, an even greater endeavor is to bootstrap a healthy ecosystem around the Raiden Network to make it a developer’s first choice when deciding on a payment infrastructure. Being able to set dedicated incentives to third parties via the RDN External Developer Program will be a key to success.
Conclusion
The Raiden team is growing. We have been hiring talented people from all over the world and will keep on doing so. The Raiden Network is an enormous endeavor attempting to become a viable backbone for decentralized global scalable payments.
Development of this exciting new technology will take sweat, time, and effort, but we are dedicated on making our vision of fast, cheap and scalable blockchain based payments a reality.
The Raiden project is led by brainbot labs Est.


John R. Hauser
2018 January 20
1. Introduction 2. Limitations 3. Acknowledgments and License 4. SoftFloat Package Directory Structure 5. Issues for Porting SoftFloat to a New Target 5.1. Standard Headers <stdbool.h>
and<stdint.h>
5.2. Specializing Floating-Point Behavior 5.3. Macros for Build Options 5.4. Adapting a Template Target Directory 5.5. Target-Specific Optimization of Primitive Functions 6. Testing SoftFloat 7. Providing SoftFloat as a Common Library for Applications 8. Contact Information
This document gives information needed for compiling and/or porting Berkeley
SoftFloat, a library of C functions implementing binary floating-point
conforming to the IEEE Standard for Floating-Point Arithmetic.
For basic documentation about SoftFloat refer to
SoftFloat.html
The source code for SoftFloat is intended to be relatively machine-independent
and should be compilable with any ISO-Standard C compiler that also supports
gcc
) for several platforms.
SoftFloat.html
SoftFloat assumes the computer has an addressable byte size of either 8 or
SoftFloat is written in C and is designed to work with other C code.
The C compiler used must conform at a minimum to the 1989 ANSI standard for the
C language (same as the 1990 ISO standard) and must in addition support basic
arithmetic on
<stdbool.h>
and
<stdint.h>
are required for defining standard Boolean and
integer types.
If these headers are not supplied with the C compiler, minimal substitutes must
be provided.
SoftFloat’s dependence on these headers is detailed later in
<stdbool.h>
and <stdint.h>
.
The SoftFloat package was written by me,
Par Lab: Microsoft (Award #024263), Intel (Award #024894), and U.C. Discovery (Award #DIG07-10227), with additional support from Par Lab affiliates Nokia, NVIDIA, Oracle, and Samsung. ASPIRE Lab: DARPA PERFECT program (Award #HR0011-12-2-0016), with additional support from ASPIRE industrial sponsor Intel and ASPIRE affiliates Google, Nokia, NVIDIA, Oracle, and Samsung.
The following applies to the whole of SoftFloat
Copyright 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 The Regents of the University of California. All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions, and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions, and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of the University nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

Because SoftFloat is targeted to multiple platforms, its source code is slightly scattered between target-specific and target-independent directories and files. The supplied directory structure is as follows:
The majority of the SoftFloat sources are provided in thedoc source include 8086 8086-SSE ARM-VFPv2 ARM-VFPv2-defaultNaN build template-FAST_INT64 template-not-FAST_INT64 Linux-386-GCC Linux-386-SSE2-GCC Linux-x86_64-GCC Linux-ARM-VFPv2-GCC Win32-MinGW Win32-SSE2-MinGW Win64-MinGW-w64
source
directory.
The include
subdirectory contains several header files
(unsurprisingly), while the other subdirectories of source
contain
source files that specialize the floating-point behavior to match particular
processor families:
If other specializations are attempted, these would be expected to be other subdirectories of
8086
- Intel’s older, 8087-derived floating-point, extended to all supported floating-point types
8086-SSE
- Intel’s x86 processors with Streaming SIMD Extensions (SSE) and later compatible extensions, having 8087 behavior for
80-bit double-extended-precision (extFloat80_t
) and SSE behavior for other floating-point typesARM-VFPv2
- ARM’s VFPv2 or later floating-point, with NaN payload propagation
ARM-VFPv2-defaultNaN
- ARM’s VFPv2 or later floating-point, with the “default NaN” option
source
alongside the ones listed above.
Specialization is covered later, in
The build
directory is intended to contain a subdirectory for each
target platform for which a build of the SoftFloat library may be created.
For each build target, the target’s subdirectory is where all derived
object files and the completed SoftFloat library (typically
softfloat.a
or libsoftfloat.a
) are created.
The two template
subdirectories are not actual build targets but
contain sample files for creating new target directories.
(The meaning of FAST_INT64
will be explained later.)
Ignoring the template
directories, the supplied target directories
are intended to follow a naming system of
<execution-environment>-<compiler>
<execution-environment>
Linux-386
Linux-386-SSE2
Linux-x86_64
Linux-ARM-VFPv2
Win32
,
Win32-SSE2
Win64
, and
<compiler>
GCC
,
MinGW
, or MinGW-w64
All of the supplied target directories are merely examples that may or may not be correct for compiling on any particular system. Despite requests, there are currently no plans to include and maintain in the SoftFloat package the build files needed for a great many users’ compilation environments, which can span a huge range of operating systems, compilers, and other tools.
As supplied, each target directory contains two files:
The providedMakefile platform.h
Makefile
is written for GNU make
.
A build of SoftFloat for the specific target is begun by executing the
make
command with the target directory as the current directory.
A completely different build tool can be used if an appropriate
Makefile
equivalent is created.
The platform.h
header file exists to provide a location for
additional C declarations specific to the build target.
Every C source file of SoftFloat contains a #include
for
platform.h
.
In many cases, the contents of platform.h
can be as simple as one
or two lines of code.
At the other extreme, to get maximal performance from SoftFloat, it may be
desirable to include in header platform.h
(directly or via
#include
) declarations for numerous target-specific optimizations.
Such possibilities are discussed in the next section, Issues for Porting
SoftFloat to a New Target.
If the target’s compiler or library has bugs or other shortcomings,
workarounds for these issues may also be possible with target-specific
declarations in platform.h
, avoiding the need to modify the main
SoftFloat sources.
<stdbool.h>
and <stdint.h>
The SoftFloat sources make use of standard headers
<stdbool.h>
and <stdint.h>
, which have
been part of the ISO C Standard Library since 1999.
With any recent compiler, these standard headers are likely to be supported,
even if the compiler does not claim complete conformance to the latest ISO C
Standard.
For older or nonstandard compilers, substitutes for
<stdbool.h>
and <stdint.h>
may need to be
created.
SoftFloat depends on these names from <stdbool.h>
:
and on these names frombool true false
<stdint.h>
:
uint16_t uint32_t uint64_t int32_t int64_t UINT64_C INT64_C uint_least8_t uint_fast8_t uint_fast16_t uint_fast32_t uint_fast64_t int_fast8_t int_fast16_t int_fast32_t int_fast64_t
The IEEE Floating-Point Standard allows for some flexibility in a conforming
implementation, particularly concerning NaNs.
The SoftFloat source
directory is supplied with some
specialization subdirectories containing possible definitions for this
implementation-specific behavior.
For example, the 8086
and 8086-SSE
As provided, the build process for a target expects to involve exactly
one specialization directory that defines all of these
implementation-specific details for the target.
A specialization directory such as 8086
is expected to contain a
header file called specialize.h
, together with whatever other
source files are needed to complete the specialization.
A new build target may use an existing specialization, such as the ones
provided by the 8086
and 8086-SSE
specialize.h
header file from any of the provided
specialization subdirectories can be used as a model for what definitions are
needed.
The SoftFloat source files adapt the floating-point implementation according to several C preprocessor macros:
LITTLEENDIAN
- Must be defined for little-endian machines; must not be defined for big-endian machines.
INLINE
- Specifies the sequence of tokens used to indicate that a C function should be inlined. If macro
INLINE_LEVEL
is defined with a value of 1 or higher, this macro must be defined; otherwise, this macro is ignored and need not be defined. For compilers that conform to the C Standard’s rules for inline functions, this macro can be defined as the single keywordinline
. For other compilers that follow a convention pre-dating the standardization ofinline
, this macro may need to be defined toextern
inline
.THREAD_LOCAL
- Can be defined to a sequence of tokens that, when appearing at the start of a variable declaration, indicates to the C compiler that the variable is per-thread, meaning that each execution thread gets its own separate instance of the variable. This macro is used in header
softfloat.h
in the declarations of variablessoftfloat_roundingMode
,softfloat_detectTininess
,extF80_roundingPrecision
, andsoftfloat_exceptionFlags
. If macroTHREAD_LOCAL
is left undefined, these variables will default to being ordinary global variables. Depending on the compiler, possible valid definitions of this macro include_Thread_local
and__thread
.
SOFTFLOAT_ROUND_ODD
- Can be defined to enable support for optional rounding mode
softfloat_round_odd
.
INLINE_LEVEL
- Can be defined to an integer to determine the degree of inlining requested of the compiler. Larger numbers request that more inlining be done. If this macro is not defined or is defined to a value less
than 1 (zero or negative), no inlining is requested. The maximum effective value is no higherthan 5 . Defining this macro to a value greater than 5 is the same as defining itto 5 .SOFTFLOAT_FAST_INT64
- Can be defined to indicate that the build target’s implementation of
64-bit arithmetic is efficient. For newer64-bit processors, this macro should usually be defined. For very small microprocessors whose buses and registers are8-bit or16-bit in size, this macro should usually not be defined. Whether this macro should be defined for a32-bit processor may depend on the target machine and the applications that will use SoftFloat.SOFTFLOAT_FAST_DIV32TO16
- Can be defined to indicate that the target’s division operator
in C (written as/
) is reasonably efficient for dividing a32-bit unsigned integer by a16-bit unsigned integer. Setting this macro may affect the performance of functionf16_div
.SOFTFLOAT_FAST_DIV64TO32
- Can be defined to indicate that the target’s division operator
in C (written as/
) is reasonably efficient for dividing a64-bit unsigned integer by a32-bit unsigned integer. Setting this macro may affect the performance of division, remainder, and square root operations other thanf16_div
.
Following the usual custom INLINE
, THREAD_LOCAL
, and
INLINE_LEVEL
), the content of any definition is irrelevant;
what matters is a macro’s effect on #ifdef
directives.
It is recommended that any definitions of macros LITTLEENDIAN
,
INLINE
, and THREAD_LOCAL
be made in a build
target’s platform.h
header file, because these macros are
expected to be determined inflexibly by the target machine and compiler.
The other five macros select options and control optimization, and thus might
be better located in the target’s Makefile (or its equivalent).
In the build
directory, two template
subdirectories
provide models for new target directories.
Two different templates exist because different functions are needed in the
SoftFloat library depending on whether macro SOFTFLOAT_FAST_INT64
is defined.
If macro SOFTFLOAT_FAST_INT64
will be defined,
template-FAST_INT64
template-not-FAST_INT64
Header file primitives.h
(in directory
source/include
) declares macros and functions for numerous
underlying arithmetic operations upon which many of SoftFloat’s
floating-point functions are ultimately built.
The SoftFloat sources include implementations of all of these functions/macros,
written as standard C code, so a complete and correct SoftFloat library can be
created using only the supplied code for all functions.
However, for many targets, SoftFloat’s performance can be improved by
substituting target-specific implementations of some of the functions/macros
declared in primitives.h
.
For example, primitives.h
declares a function called
softfloat_countLeadingZeros32
that takes an unsigned
A build target can replace the supplied version of any function or macro of
primitives.h
by defining a macro with the same name in the
target’s platform.h
header file.
For this purpose, it may be helpful for platform.h
to
#include
header file primitiveTypes.h
, which defines
types used for arguments and results of functions declared in
primitives.h
.
When a desired replacement implementation is a function, not a macro, it is
sufficient for platform.h
to include the line
where#define <function-name> <function-name>
<function-name>
<function-name>
The supplied header file opts-GCC.h
(in directory
source/include
) provides an example of target-specific
optimization for the GCC compiler.
Each GCC target example in the build
directory has
#include "opts-GCC.h"
in its platform.h
header file.
Before opts-GCC.h
is included, the following macros must be
defined (or not) to control which features are invoked:
On some machines, these improvements are observed to increase the speeds of
SOFTFLOAT_BUILTIN_CLZ
- If defined, SoftFloat’s internal ‘
countLeadingZeros
’ functions use intrinsics__builtin_clz
and__builtin_clzll
.SOFTFLOAT_INTRINSIC_INT128
- If defined, SoftFloat makes use of GCC’s nonstandard
128-bit integer type__int128
.
f64_mul
and f128_mul
by around 20 to 25%, although
other functions receive less dramatic boosts, or none at all.
Results can vary greatly across different platforms.
SoftFloat can be tested using the testsoftfloat
program by the
same author.
This program is part of the Berkeley TestFloat package available at the Web
page
http://www.jhauser.us/arithmetic/TestFloat.html
timesoftfloat
that
measures the speed of SoftFloat’s floating-point functions.
Header file softfloat.h
defines the SoftFloat interface as seen by
clients.
If the SoftFloat library will be made a common library for programs on a
system, the supplied softfloat.h
has a couple of deficiencies for
this purpose:
softfloat.h
depends on another header,
softfloat_types.h
, that is not intended for public use but which
must also be visible to the programmer’s compiler.
softfloat.h
is included in a C source
file, macros SOFTFLOAT_FAST_INT64
and THREAD_LOCAL
must be defined, or not defined, consistent with how these macro were defined
when the SoftFloat library was built.
#include
header
file softfloat.h
, it is recommended that a custom, self-contained
version of this header file be created that eliminates these issues.
At the time of this writing, the most up-to-date information about SoftFloat
and the latest release can be found at the Web page
http://www.jhauser.us/arithmetic/SoftFloat.html


HTML Introduction
In order to make information available on the World Wide Web, we need to develop a website using HTML (HyperText Markup Language). The language describes how the information is to be displayed in a web browser. On top of HTML which creates and present information, CSS (Cascading Style Sheets) is required to format the information into a uniform, consistent and pleasing nature. I learned HTML with videos on youtube ( Learn HTML in 12 Minutes)
A HTML file consist of elements, such as header, paragraph, numbered list etc, and these elements are represented by tags such as h1, h2 and h3 for headers, p for paragraph and nl for numbered list. Elements must be encased in <> and elements comes in pairs, the opening tag, and the closing tag which has a / before the element in the angle brackets.
Some elements do not have a closing tag, such as a break which adds a line, or a photo. Hence, the tagname must end with a slash (/)
To insert a photo, the tag "img" can be used, but the source of the image as well as the size must be specified in the tag.
< img src: "file location" width = "x" />
The file location is found with the folder that the HTML file is in as a starting point. Hence, the file can be specified by including the file name if the picture is in the same folder as the HTML file, using ../ to look in the parent folder or using your computer file directory (C:\Users\Name\Documents...). The size of the picture can also be specified by the number of pixels. In order to not have the picture look distorted due to a difference in given differing aspect ratio and the picture aspect ratio, you can just specify the width or the height.
HTML files are edited with text editors such as Notepad++, Brackets and Atom. In order to display the HTML document, the HTML file must be opened with a web browser such as chrome by dragging the file into the browser. However, in order for a website to be available for the public to view on the web, a server is requried. I used github to host my website by uploading my files into the website which creates a link for the public to view. The default file to open when using the link is index.html, which is why it is the name of the homepage of my website.
Steps
- Created a text document name "index" and change the file type to HTML.
- Opened the file using the text editor (I used brackets)
- Start the document with < html > and end it with < /html > to show that the following code is written in HTML
- Worked on the header and a title "My First Webpage
- Worked on the body with content in it, such as my photo and introduction to myself.
- Saved the file and dragged the file from my file explorer into google chrome to open it.
- Preview the HTML file using Chrome, and make necessary changes.


Performance and Results driven Associate Web Developer with 2 years’ of experience in designing, implementing and supporting interactive User Interface (UI) and Creating Newsletter
Creating Responsive Email Newsletter using HTML5, CSS, Javascript, jQuery and Deployment of Email
Percentage: 59.7%
Percentage: 65%
Percentage: 80%
Responsible for project planning, managing a team of 10 Production specialists and assigning requests, QA the campaign done by Production specialists before sending completion to client.
Independently carried out management and Daily/weekly reporting.
Project management of a program to improve the effectiveness
Accountable for handling day to day email communications ensuring that all deliverables are sent in a timely manner.


These are the richest people in Wales you've probably never heard of
They have all made it to Wales Rich List 2019
by Marcus HughesWales is home to plenty of monumentally wealthy people - many of whom have become household names.
Familiar people top the rich lists every year, including Celtic Manor Resort owner and telecoms magnate Sir Terry Matthew, Admiral insurance founder Henry Engelhardt, and Iceland co-founder Sir Malcolm Walker.
This year's Wales Rich List, published in the latest edition of Wales Business Insider, contains plenty of those recognisable faces, many of whom have had a huge impact on the economy and life in Wales.
But the list also includes a number of people you might not have heard of, in spite of their wealth.
A fortune of £21m was required to make it onto the top 100.
Sir Terry Matthews remains Wales' only billionaire, with his wealth rising to £1.31bn from £1.24bn thanks to success at the Celtic Manor Resort and his other companies.
But many of Wales' richest people are feeling the pinch, with 23 of the individuals and families who featured in this year's list experiencing a fall in the size of their fortunes.
Here are some of Wales Rich List 2019 names you might not have heard of:
Graham Anwyl (76) and family
Worth £77m
Anwyl Group was established in 1930 in Rhyl as a joinery and woodworking contractor and now operates as two divisions: Anwyl Homes and Anwyl Construction.
The company specialises in building large residential projects like care homes and housing developments.
The Ewloe based company enjoyed a record year with turnover growing 49%in 2017-18.
The fourth generation family run business is chaired by Graham Anwyl, and paid out a £2.5m dividend over the past 12 months.
Gerald Leeke (78) and family
Worth £66m
Leekes department store was founded at the end of the nineteenth century by James Henry Leeke.
Since then it has grown to include four department stores, a building centre in Tonypandy and a chain of conservatory concessions.
In 1994 Leekes Retail and Leisure Group bought The Vale Resort in Hensol, in the Vale of Glamorgan.
The family's department store chain dipped into the red in 2017-18, with turnover falling to £85m.
Michael McCarthy (77) and family
Worth £57m
Michael McCarthy set up property developer Rightacres in 1970 and chairs the business to this day, while his son Paul is chief executive.
The company is continuing to work as the exclusive developer of Cardiff's Central Square with more office space and apartments completed in recent years.
BBC Cymru Wales is currently in the process of relocating its headquarters to the site directly outside Cardiff Central train station.
Nicholas Griffith (55) and family
Worth £43m
Nicholas Griffith is the little-known owner of Cardiff's Philharmonic pub and Wyndham Arcade through his property firm G Capital.
His company has reputation for taking disused industrial sites and transforming them into brand new business parks.
William Watkins (53)
Worth £41m
William Watkins made his fortune as the managing director of Radnor Hills, the mineral water and fruit juice company.
The company started in 1989 after a young William returned back to his family farm from university and decided to diversify the business by bottling water on the family land - originally for the airline industry.
Radnor Hills installed their eighth production line last year and saw turnover top £42.1m in 2017/18.
Drew Nelson (64)
Worth £25m
Dr Drew Nelson co-found and CEO of IQE, a supplier of semiconductor components used to make smartphones.
The business was launched in 1988, and more than 30 years on the Cardiff-based technology firm has a stock market value of £443m.
The company have manufacturing plants in the UK, Taiwan, Singapore and America but their headquarters still remain firmly rooted in Cardiff.
Terry Edgell (53), Dilwyn Howells (54), and Nigel Williams (53)
Worth £24m each
Dilwyn Howells, Nigel Williams and Terry Edgell co-founded timber company Premier Forest Products in 1993.
After spending the first month working from Terry's house in Cwmbran, they moved to a number of new sites before settling at Alexandra Dock, Newport, where the headquarters still stand today.
The company supplies wood products for shopfitters, furniture makers, carpenters, caravan makers and a number of other customers.
The business reported profits of £9.3m and a turnover of £126.1m in 2017-18.
Robin Jones (51) and family
Worth £22m
Wrexham-based Village Bakery was established in 1934 and produces a range of bread and pies.
A fire devastated the main production facility earlier this year, but managing director Robin Jones told the media the company would "bounce back".
The fire came after a strong performance in 2017-18, with £4m profit.
Raj Aggarwal (70)
Worth £26m
Raj Aggarwal performs many roles.
Mr Aggarwal studied at Cardiff University before eventually buying his own small pharmacy on City Road and growing a chain.
The public health expert is also India’s Honorary Consul in Wales and last year became the first Indian-born recipient of the position of Honorary Lieutenant Commander in the Royal Navy.
He holds investments in cosmetic retailer Escentual, run by his son Rakesh, and operates Cardiff's Clarins salon.
Mario Kreft (63) and Gill Kreft (62)
Worth £28m
The Kefts own Pendine Park Care, which has eight care homes in Wrexham and Caernarfon with 440 residents.
The company made a steady £4.2m profit on £19.6m sales last year.
Jayne Lewis (54) and family
Worth £59m
Jayne Lewis owns the mining and development company Merthyr (South Wales) which runs the enormous Ffos-y-fran opencast mine just outside Merthyr Tydfil.
The family's company Gwent Holdings made £13.4m profit on £56.1m sales in 2017.
John Burns (70)
Worth £30m
John Burns developed his pet food company while working as a vet in 1993.
His food has been specifically designed to manage common health problem in cats, dogs and rabbits.
According to Inside Business Wales, the Kidwelly-based company's finances took a hit by an £850,000 donation to Burns' foundation in 2019-18 and a £9.2m payment to buy his ex-wife out from the company.
Steve Nicholls (58) and Jacqueline Nicholls (59)
Worth £23m
Steve Nicholls is managing director of Complete Core Business Solutions.
The Abercynon-based business packs and fills tobacco products and e-cigarettes.
Profits fell 20% to £1.9m last year with a turnover of £11.7m.
Alex Loven (32)
Worth £32m
Alex Loven is the youngest person on the 2019 Wales Rich List.
The 32-year-old has built one of the UK's largest online retailers of sports clothing and equipment.
In 2018 they had grown to 100 employees and supplied internationally renowned football clubs including Manchester United and Rangers FC.
Tim Batstone (60) and family
Worth £42m
Tim Batstone's company HB Leisure designs makes and sells theme skill park games - the type that you can win cuddly toys by winning, by, for example throwing balls at a hoop.
The firm's products have become fixtures at Legoland, Alton Towers, Drayton Manor, Blackpool Tower and Madame Tussauds.
Alexander Smart (46) and Gareth Smart (40)
Worth £60m
Brothers Alexander and Gareth Smart run JR Smart (Builders), a Cardiff-based construction company.
The firm was founded by their father John and has developed 2.5 million sq ft of commercial property.
Their recent projects include the development of Cardiff's Capital Quarter.
Company profits rose to £8.2m in 2017.


public static class Apriori.Configuration
extends java.lang.Object
implements java.io.Serializable, java.lang.Cloneable
| Modifier | Constructor and Description |
|---|---|
protected |
Configuration()
Creates a new configuration of the Apriori algorithm with default values.
|
| Modifier and Type | Method and Description |
|---|---|
Apriori.Configuration |
clone() |
boolean |
equals(java.lang.Object obj) |
double |
getConfidenceDelta()
Returns the value, the minimum confidence should be decreased by after each iteration,
when trying to generate a specific number of association rules.
|
int |
getFrequentItemSetCount()
Returns the number of frequent item sets, the Apriori algorithm should try to find.
|
double |
getMaxConfidence()
Returns the minimum confidence, which should initially be used, when trying to generate a
specific number of association rules.
|
double |
getMaxSupport()
Returns the minimum support, which should initially be used, when trying to find a
specific number of frequent item sets.
|
double |
getMinConfidence()
Returns the minimum confidence, which must at least be reached by association rules.
|
double |
getMinSupport()
Returns the minimum support, which must at least be reached by an item set to be
considered frequent.
|
int |
getRuleCount()
Returns the number of association rules, the Apriori algorithm should try to generate.
|
double |
getSupportDelta()
Returns the value, the minimum support should be decreased by after each iteration, when
trying to find a specific number of frequent item sets.
|
int |
hashCode() |
boolean |
isGeneratingRules()
Returns, whether association rules should be generated, or not.
|
protected void |
setConfidenceDelta(double confidenceDelta)
Sets the value, the minimum confidence should be decreased by after each iteration, when
trying to generate a specific number of association rules.
|
protected void |
setFrequentItemSetCount(int frequentItemSetCount)
Sets the number of of frequent item sets, the Apriori algorithm should try to find.
|
protected void |
setGenerateRules(boolean generateRules)
Sets, whether association rules should be generated, or not.
|
protected void |
setMaxConfidence(double maxConfidence)
Sets the minimum confidence, which should initially be used, when trying to generate a
specific number of association rules.
|
protected void |
setMaxSupport(double maxSupport)
Sets the minimum support, which should initially be used, when trying to find a specific
number of frequent item sets.
|
protected void |
setMinConfidence(double minConfidence)
Sets the minimum confidence, which must at least be reached by association rules.
|
protected void |
setMinSupport(double minSupport)
Sets the minimum support, which must at least be reached by an item set to be considered
frequent.
|
protected void |
setRuleCount(int ruleCount)
Sets the number of association rule, the Apriori algorithm should try to generate.
|
protected void |
setSupportDelta(double supportDelta)
Sets the value, the minimum support should be decreased by after each iteration, when
trying to find a specific number of frequent item sets.
|
java.lang.String |
toString() |
protected Configuration()
public double getMinSupport()
Double
valueprotected void setMinSupport(double minSupport)
minSupport
- The support, which should be set, as a Double
value. The
support must at least be 0 and at maximum the maximum supportpublic double getMaxSupport()
Double
valueprotected void setMaxSupport(double maxSupport)
maxSupport
- The support, which should be set, as a Double
value. The
support must be at least the minimum supportpublic double getSupportDelta()
Double
valueprotected void setSupportDelta(double supportDelta)
supportDelta
- The value, which should be set, as a Double
value. The value
must be greater than 0public int getFrequentItemSetCount()
Integer
valueprotected void setFrequentItemSetCount(int frequentItemSetCount)
frequentItemSetCount
- The number of frequent item sets, which should be set, as an
Integer
value or 0, if the Apriori algorithm should
not try to find a specific number of frequent item setspublic boolean isGeneratingRules()
protected void setGenerateRules(boolean generateRules)
generateRules
- True, if association rules should be generated, false otherwisepublic double getMinConfidence()
Double
valueprotected void setMinConfidence(double minConfidence)
minConfidence
- The confidence, which should be set, as a Double
value. The
confidence must be at least 0 and at maximum the maximum confidencepublic double getMaxConfidence()
Double
valueprotected void setMaxConfidence(double maxConfidence)
maxConfidence
- The confidence, which should be set, as a Double
value. The
confidence must be at least 0 and at maximum 1public double getConfidenceDelta()
Double
valueprotected void setConfidenceDelta(double confidenceDelta)
confidenceDelta
- The value, which should be set, as a Double
value. The
value must be greater than 0public int getRuleCount()
Integer
valueprotected void setRuleCount(int ruleCount)
ruleCount
- The number of association rules, which should be set, as an Integer
value or 0, if the Apriori algorithm should not try to generate
a specific number of association rulespublic final Apriori.Configuration clone()
clone
in class java.lang.Object
public final java.lang.String toString()
toString
in class java.lang.Object
public final int hashCode()
hashCode
in class java.lang.Object
public final boolean equals(java.lang.Object obj)
equals
in class java.lang.Object


Create a List lookup filter to send filters based on List data. Whether you let users pick a List item to use in interactive mode, or specify the source item to use directly, the filter value being sent is always the current, live value of a Column you chose.
Specify the URL of the View used to access the List and retrieve its data. The View provides initial pre-filtering and sorting. A View URL includes the file name of the View page (such as AllItems.aspx).
You can specify a full, absolute URL (those starting with http:// or https:// ). Also supported are site-relative URLs (those starting with / ), to which the site collection root web URL will be prepended at run time, and web-relative URLs (those neither starting with http:// nor https:// nor with / ), to which the current web URL will be prepended at run time.
Specify the internal name of the Column in the lookup List providing the filter value to be sent. Typically this is also the Column you will want to use for displaying filter choices, however, you may also optionally specify another internal name for the display Column.


Angular automatically creates a root scope during initialization, and attaches it to the page's
root DOM element (usually
). The root scope object, along with any of its child scope
objects, serves as the infrastructure on which your data model is built. The data model (JavaScript
objects, arrays, or primitives) is attached to angular scope properties. Angular binds the property
values to the DOM where bindings are specified in the template. Angular attaches any controller
functions you have created to their respective scope objects.
Angular scopes can be nested, so a child scope has a parent scope upstream in the DOM. When you display an angular expression in the view, angular walks the DOM tree looking in the closest attached scope object for the specified data. If it doesn't find the data in the closest attached scope, it looks further up the scope hierarchy until it finds the data.
A child scope object inherits properties from its parents. For example, in the following snippet of
code, observe how the value of name
changes, based on the HTML element it is displayed in:

 Name = {{name}}!

Name={{name}}

it('should override the name property', function() { expect(using('.doc-example-live').repeater('li').row(0)). toEqual(['Igor']); expect(using('.doc-example-live').repeater('li').row(1)). toEqual(['Misko']); expect(using('.doc-example-live').repeater('li').row(2)). toEqual(['Gail']); expect(using('.doc-example-live').repeater('li').row(3)). toEqual(['Kai']); expect(using('.doc-example-live').element('pre').text()). toBe('Name=Hank'); });
The angular ngRepeat
directive creates a new scope for each
element that it repeats (in this example the elements are list items). In the

element, we
initialized name
to "Hank", and we created an array called names
to use as the data source for
the list items. In each

element, name
is overridden. Outside of the

repeater, the
original value of name
is displayed.
The following illustration shows the DOM and angular scopes for the example above:


Password Safe provides several mechanisms for using stored names and passwords. Most require copying the user name or password to the clipboard and then pasting the information into the required input field. Password Safe provides a function, AutoType, that automates the entering of a user name and password into a web form.
Note: User names and passwords can also be copied to clipboard through the choices located in the Edit menu, but let's be honest, that's far too much clicking.


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Gecode::Search::EngineBase< T > Class Template Reference
Base-class for search engines. More...
#include <search.hh>
Public Member Functions | |
| virtual T * | next (void) |
| Return next solution (NULL, if none exists or search has been stopped). | |
| virtual Statistics | statistics (void) const |
| Return statistics. | |
| virtual bool | stopped (void) const |
| Check whether engine has been stopped. | |
| virtual NoGoods & | nogoods (void) |
| Return no-goods (the no-goods are empty). | |
| virtual | ~EngineBase (void) |
| Destructor. | |
Protected Member Functions | |
| EngineBase (Engine *e=NULL) | |
| Constructor. | |
Protected Attributes | |
| Engine * | e |
| The actual search engine. | |
Memory management | |
|
| |
| static void * | operator new (size_t s) |
| Allocate memory from heap. | |
| static void | operator delete (void *p) |
| Free memory allocated from heap. |
Detailed Description
template<class T>
class Gecode::Search::EngineBase< T >
Base-class for search engines.
Definition at line 639 of file search.hh.
Constructor & Destructor Documentation
| Gecode::Search::EngineBase< T >::EngineBase | ( | Engine * | e = NULL |
) | [inline, protected] |
Constructor.
Definition at line 46 of file engine-base.hpp.
| Gecode::Search::EngineBase< T >::~EngineBase | ( | void | ) | [inline, virtual] |
Destructor.
Definition at line 70 of file engine-base.hpp.
Member Function Documentation
| T * Gecode::Search::EngineBase< T >::next | ( | void | ) | [inline, virtual] |
Return next solution (NULL, if none exists or search has been stopped).
Definition at line 50 of file engine-base.hpp.
| Statistics Gecode::Search::EngineBase< T >::statistics | ( | void | ) | const [inline, virtual] |
Return statistics.
Definition at line 55 of file engine-base.hpp.
| bool Gecode::Search::EngineBase< T >::stopped | ( | void | ) | const [inline, virtual] |
Check whether engine has been stopped.
Definition at line 60 of file engine-base.hpp.
| NoGoods & Gecode::Search::EngineBase< T >::nogoods | ( | void | ) | [inline, virtual] |
Return no-goods (the no-goods are empty).
Definition at line 65 of file engine-base.hpp.
| void * Gecode::Search::EngineBase< T >::operator new | ( | size_t | s | ) | [inline, static] |
Allocate memory from heap.
Definition at line 75 of file engine-base.hpp.
| void Gecode::Search::EngineBase< T >::operator delete | ( | void * | p | ) | [inline, static] |
Free memory allocated from heap.
Definition at line 80 of file engine-base.hpp.
Member Data Documentation
Engine* Gecode::Search::EngineBase< T >::e [protected] |
The documentation for this class was generated from the following files:
- gecode/search.hh (Revision: 14443)
- gecode/search/engine-base.hpp (Revision: 14437)


This view lets you see the different organisations in the system and their position on the map. Zoom in, pan around and tap the dots to see the individual organisation profiles.


CodeMirror Editor Collaborative Extensions Demo
Source Editor
Type and make selections here.
Target Editor
See changes, remote cursors, and selections here.


Twitter vice president suggests new features for 2020
A senior Twitter executive has suggested a number of new features that could appear on the social network in 2020, including the ability to block being mentioned without permission.
The company’s vice president of design and research tweeted several ideas, although it is not clear whether they will become a reality next year.
Dantley Davis’s account teased that users could have the power to remove themselves from a conversation, as well as the means to disallow retweeting of certain posts if they do not want them being distributed by other people.
He opened a series of tweets, saying: “Features that I’m looking forward to in 2020,” listing removal of a specific mention from a conversation and tweeting only to a specific hashtag, interest or group of friends as potential options.
“Do you agree with the ideas in this list? What else would you add? #designtwitter,” he tweeted.
“I believe giving more control to users will help create a healthier Twitter and reduce abuse. Additionally, these features need to be easy to access and use.”
Mr Davis also suggested that threads should be automatically labelled on the social network, meaning users no longer have to make it obvious themselves.
An edit button allowing users to correct mistakes has been a long-requested feature, which the Twitter executive touched on in response to a comment.
“This can be done with integrity,” he responded.
Twitter recently made headlines by announcing that it was banning political advertising from its service, a decision which has put pressure on Facebook to follow suit.


# coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
import warnings
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.validation import check_is_fitted
from .base import LinearRegression
from ..utils.validation import has_fit_parameter
_EPSILON = np.spacing(1)
def _dynamic_max_trials(n_inliers, n_samples, min_samples, probability):
"""Determine number trials such that at least one outlier-free subset is
sampled for the given inlier/outlier ratio.
Parameters
----------
n_inliers : int
Number of inliers in the data.
n_samples : int
Total number of samples in the data.
min_samples : int
Minimum number of samples chosen randomly from original data.
probability : float
Probability (confidence) that one outlier-free sample is generated.
Returns
-------
trials : int
Number of trials.
"""
inlier_ratio = n_inliers / float(n_samples)
nom = max(_EPSILON, 1 - probability)
denom = max(_EPSILON, 1 - inlier_ratio ** min_samples)
if nom == 1:
return 0
if denom == 1:
return float('inf')
return abs(float(np.ceil(np.log(nom) / np.log(denom))))
class RANSACRegressor(BaseEstimator, MetaEstimatorMixin, RegressorMixin):
"""RANSAC (RANdom SAmple Consensus) algorithm.
RANSAC is an iterative algorithm for the robust estimation of parameters
from a subset of inliers from the complete data set. More information can
be found in the general documentation of linear models.
A detailed description of the algorithm can be found in the documentation
of the ``linear_model`` sub-package.
Read more in the :ref:`User Guide <ransac_regression>`.
Parameters
----------
base_estimator : object, optional
Base estimator object which implements the following methods:
* `fit(X, y)`: Fit model to given training data and target values.
* `score(X, y)`: Returns the mean accuracy on the given test data,
which is used for the stop criterion defined by `stop_score`.
Additionally, the score is used to decide which of two equally
large consensus sets is chosen as the better one.
If `base_estimator` is None, then
``base_estimator=sklearn.linear_model.LinearRegression()`` is used for
target values of dtype float.
Note that the current implementation only supports regression
estimators.
min_samples : int (>= 1) or float ([0, 1]), optional
Minimum number of samples chosen randomly from original data. Treated
as an absolute number of samples for `min_samples >= 1`, treated as a
relative number `ceil(min_samples * X.shape[0]`) for
`min_samples < 1`. This is typically chosen as the minimal number of
samples necessary to estimate the given `base_estimator`. By default a
``sklearn.linear_model.LinearRegression()`` estimator is assumed and
`min_samples` is chosen as ``X.shape[1] + 1``.
residual_threshold : float, optional
Maximum residual for a data sample to be classified as an inlier.
By default the threshold is chosen as the MAD (median absolute
deviation) of the target values `y`.
is_data_valid : callable, optional
This function is called with the randomly selected data before the
model is fitted to it: `is_data_valid(X, y)`. If its return value is
False the current randomly chosen sub-sample is skipped.
is_model_valid : callable, optional
This function is called with the estimated model and the randomly
selected data: `is_model_valid(model, X, y)`. If its return value is
False the current randomly chosen sub-sample is skipped.
Rejecting samples with this function is computationally costlier than
with `is_data_valid`. `is_model_valid` should therefore only be used if
the estimated model is needed for making the rejection decision.
max_trials : int, optional
Maximum number of iterations for random sample selection.
max_skips : int, optional
Maximum number of iterations that can be skipped due to finding zero
inliers or invalid data defined by ``is_data_valid`` or invalid models
defined by ``is_model_valid``.
.. versionadded:: 0.19
stop_n_inliers : int, optional
Stop iteration if at least this number of inliers are found.
stop_score : float, optional
Stop iteration if score is greater equal than this threshold.
stop_probability : float in range [0, 1], optional
RANSAC iteration stops if at least one outlier-free set of the training
data is sampled in RANSAC. This requires to generate at least N
samples (iterations)::
N >= log(1 - probability) / log(1 - e**m)
where the probability (confidence) is typically set to high value such
as 0.99 (the default) and e is the current fraction of inliers w.r.t.
the total number of samples.
residual_metric : callable, optional
Metric to reduce the dimensionality of the residuals to 1 for
multi-dimensional target values ``y.shape[1] > 1``. By default the sum
of absolute differences is used::
lambda dy: np.sum(np.abs(dy), axis=1)
.. deprecated:: 0.18
``residual_metric`` is deprecated from 0.18 and will be removed in
0.20. Use ``loss`` instead.
loss : string, callable, optional, default "absolute_loss"
String inputs, "absolute_loss" and "squared_loss" are supported which
find the absolute loss and squared loss per sample
respectively.
If ``loss`` is a callable, then it should be a function that takes
two arrays as inputs, the true and predicted value and returns a 1-D
array with the i-th value of the array corresponding to the loss
on ``X[i]``.
If the loss on a sample is greater than the ``residual_threshold``,
then this sample is classified as an outlier.
random_state : int, RandomState instance or None, optional, default None
The generator used to initialize the centers. If int, random_state is
the seed used by the random number generator; If RandomState instance,
random_state is the random number generator; If None, the random number
generator is the RandomState instance used by `np.random`.
Attributes
----------
estimator_ : object
Best fitted model (copy of the `base_estimator` object).
n_trials_ : int
Number of random selection trials until one of the stop criteria is
met. It is always ``<= max_trials``.
inlier_mask_ : bool array of shape [n_samples]
Boolean mask of inliers classified as ``True``.
n_skips_no_inliers_ : int
Number of iterations skipped due to finding zero inliers.
.. versionadded:: 0.19
n_skips_invalid_data_ : int
Number of iterations skipped due to invalid data defined by
``is_data_valid``.
.. versionadded:: 0.19
n_skips_invalid_model_ : int
Number of iterations skipped due to an invalid model defined by
``is_model_valid``.
.. versionadded:: 0.19
References
----------
.. [1] https://en.wikipedia.org/wiki/RANSAC
.. [2] http://www.cs.columbia.edu/~belhumeur/courses/compPhoto/ransac.pdf
.. [3] http://www.bmva.org/bmvc/2009/Papers/Paper355/Paper355.pdf
"""
def __init__(self, base_estimator=None, min_samples=None,
residual_threshold=None, is_data_valid=None,
is_model_valid=None, max_trials=100, max_skips=np.inf,
stop_n_inliers=np.inf, stop_score=np.inf,
stop_probability=0.99, residual_metric=None,
loss='absolute_loss', random_state=None):
self.base_estimator = base_estimator
self.min_samples = min_samples
self.residual_threshold = residual_threshold
self.is_data_valid = is_data_valid
self.is_model_valid = is_model_valid
self.max_trials = max_trials
self.max_skips = max_skips
self.stop_n_inliers = stop_n_inliers
self.stop_score = stop_score
self.stop_probability = stop_probability
self.residual_metric = residual_metric
self.random_state = random_state
self.loss = loss
[docs] def fit(self, X, y, sample_weight=None):
"""Fit estimator using RANSAC algorithm.
Parameters
----------
X : array-like or sparse matrix, shape [n_samples, n_features]
Training data.
y : array-like, shape = [n_samples] or [n_samples, n_targets]
Target values.
sample_weight : array-like, shape = [n_samples]
Individual weights for each sample
raises error if sample_weight is passed and base_estimator
fit method does not support it.
Raises
------
ValueError
If no valid consensus set could be found. This occurs if
`is_data_valid` and `is_model_valid` return False for all
`max_trials` randomly chosen sub-samples.
"""
X = check_array(X, accept_sparse='csr')
y = check_array(y, ensure_2d=False)
check_consistent_length(X, y)
if self.base_estimator is not None:
base_estimator = clone(self.base_estimator)
else:
base_estimator = LinearRegression()
if self.min_samples is None:
# assume linear model by default
min_samples = X.shape[1] + 1
elif 0 < self.min_samples < 1:
min_samples = np.ceil(self.min_samples * X.shape[0])
elif self.min_samples >= 1:
if self.min_samples % 1 != 0:
raise ValueError("Absolute number of samples must be an "
"integer value.")
min_samples = self.min_samples
else:
raise ValueError("Value for `min_samples` must be scalar and "
"positive.")
if min_samples > X.shape[0]:
raise ValueError("`min_samples` may not be larger than number "
"of samples ``X.shape[0]``.")
if self.stop_probability < 0 or self.stop_probability > 1:
raise ValueError("`stop_probability` must be in range [0, 1].")
if self.residual_threshold is None:
# MAD (median absolute deviation)
residual_threshold = np.median(np.abs(y - np.median(y)))
else:
residual_threshold = self.residual_threshold
if self.residual_metric is not None:
warnings.warn(
"'residual_metric' was deprecated in version 0.18 and "
"will be removed in version 0.20. Use 'loss' instead.",
DeprecationWarning)
if self.loss == "absolute_loss":
if y.ndim == 1:
loss_function = lambda y_true, y_pred: np.abs(y_true - y_pred)
else:
loss_function = lambda \
y_true, y_pred: np.sum(np.abs(y_true - y_pred), axis=1)
elif self.loss == "squared_loss":
if y.ndim == 1:
loss_function = lambda y_true, y_pred: (y_true - y_pred) ** 2
else:
loss_function = lambda \
y_true, y_pred: np.sum((y_true - y_pred) ** 2, axis=1)
elif callable(self.loss):
loss_function = self.loss
else:
raise ValueError(
"loss should be 'absolute_loss', 'squared_loss' or a callable."
"Got %s. " % self.loss)
random_state = check_random_state(self.random_state)
try: # Not all estimator accept a random_state
base_estimator.set_params(random_state=random_state)
except ValueError:
pass
estimator_fit_has_sample_weight = has_fit_parameter(base_estimator,
"sample_weight")
estimator_name = type(base_estimator).__name__
if (sample_weight is not None and not
estimator_fit_has_sample_weight):
raise ValueError("%s does not support sample_weight. Samples"
" weights are only used for the calibration"
" itself." % estimator_name)
if sample_weight is not None:
sample_weight = np.asarray(sample_weight)
n_inliers_best = 1
score_best = -np.inf
inlier_mask_best = None
X_inlier_best = None
y_inlier_best = None
self.n_skips_no_inliers_ = 0
self.n_skips_invalid_data_ = 0
self.n_skips_invalid_model_ = 0
# number of data samples
n_samples = X.shape[0]
sample_idxs = np.arange(n_samples)
n_samples, _ = X.shape
self.n_trials_ = 0
max_trials = self.max_trials
while self.n_trials_ < max_trials:
self.n_trials_ += 1
if (self.n_skips_no_inliers_ + self.n_skips_invalid_data_ +
self.n_skips_invalid_model_) > self.max_skips:
break
# choose random sample set
subset_idxs = sample_without_replacement(n_samples, min_samples,
random_state=random_state)
X_subset = X[subset_idxs]
y_subset = y[subset_idxs]
# check if random sample set is valid
if (self.is_data_valid is not None
and not self.is_data_valid(X_subset, y_subset)):
self.n_skips_invalid_data_ += 1
continue
# fit model for current random sample set
if sample_weight is None:
base_estimator.fit(X_subset, y_subset)
else:
base_estimator.fit(X_subset, y_subset,
sample_weight=sample_weight[subset_idxs])
# check if estimated model is valid
if (self.is_model_valid is not None and not
self.is_model_valid(base_estimator, X_subset, y_subset)):
self.n_skips_invalid_model_ += 1
continue
# residuals of all data for current random sample model
y_pred = base_estimator.predict(X)
# XXX: Deprecation: Remove this if block in 0.20
if self.residual_metric is not None:
diff = y_pred - y
if diff.ndim == 1:
diff = diff.reshape(-1, 1)
residuals_subset = self.residual_metric(diff)
else:
residuals_subset = loss_function(y, y_pred)
# classify data into inliers and outliers
inlier_mask_subset = residuals_subset < residual_threshold
n_inliers_subset = np.sum(inlier_mask_subset)
# less inliers -> skip current random sample
if n_inliers_subset < n_inliers_best:
self.n_skips_no_inliers_ += 1
continue
# extract inlier data set
inlier_idxs_subset = sample_idxs[inlier_mask_subset]
X_inlier_subset = X[inlier_idxs_subset]
y_inlier_subset = y[inlier_idxs_subset]
# score of inlier data set
score_subset = base_estimator.score(X_inlier_subset,
y_inlier_subset)
# same number of inliers but worse score -> skip current random
# sample
if (n_inliers_subset == n_inliers_best
and score_subset < score_best):
continue
# save current random sample as best sample
n_inliers_best = n_inliers_subset
score_best = score_subset
inlier_mask_best = inlier_mask_subset
X_inlier_best = X_inlier_subset
y_inlier_best = y_inlier_subset
max_trials = min(
max_trials,
_dynamic_max_trials(n_inliers_best, n_samples,
min_samples, self.stop_probability))
# break if sufficient number of inliers or score is reached
if n_inliers_best >= self.stop_n_inliers or \
score_best >= self.stop_score:
break
# if none of the iterations met the required criteria
if inlier_mask_best is None:
if ((self.n_skips_no_inliers_ + self.n_skips_invalid_data_ +
self.n_skips_invalid_model_) > self.max_skips):
raise ValueError(
"RANSAC skipped more iterations than `max_skips` without"
" finding a valid consensus set. Iterations were skipped"
" because each randomly chosen sub-sample failed the"
" passing criteria. See estimator attributes for"
" diagnostics (n_skips*).")
else:
raise ValueError(
"RANSAC could not find a valid consensus set. All"
" `max_trials` iterations were skipped because each"
" randomly chosen sub-sample failed the passing criteria."
" See estimator attributes for diagnostics (n_skips*).")
else:
if (self.n_skips_no_inliers_ + self.n_skips_invalid_data_ +
self.n_skips_invalid_model_) > self.max_skips:
warnings.warn("RANSAC found a valid consensus set but exited"
" early due to skipping more iterations than"
" `max_skips`. See estimator attributes for"
" diagnostics (n_skips*).",
UserWarning)
# estimate final model using all inliers
base_estimator.fit(X_inlier_best, y_inlier_best)
self.estimator_ = base_estimator
self.inlier_mask_ = inlier_mask_best
return self
[docs] def predict(self, X):
"""Predict using the estimated model.
This is a wrapper for `estimator_.predict(X)`.
Parameters
----------
X : numpy array of shape [n_samples, n_features]
Returns
-------
y : array, shape = [n_samples] or [n_samples, n_targets]
Returns predicted values.
"""
check_is_fitted(self, 'estimator_')
return self.estimator_.predict(X)
[docs] def score(self, X, y):
"""Returns the score of the prediction.
This is a wrapper for `estimator_.score(X, y)`.
Parameters
----------
X : numpy array or sparse matrix of shape [n_samples, n_features]
Training data.
y : array, shape = [n_samples] or [n_samples, n_targets]
Target values.
Returns
-------
z : float
Score of the prediction.
"""
check_is_fitted(self, 'estimator_')
return self.estimator_.score(X, y)


✔ The appointment has been cancelled
The provider has been contacted.
Booking reference number
0002 7480 8900
Referred by
Dr Zubeir Smith at Colton Medical Centre
What happens next?
You now need to book a new appointment from your choice of clinics.
If you no longer want an appointment you can cancel this referral.


WinSwitch 1.5 crashes SystemUIServer
-
anonymous
Upon clicking on the WinSwitch 1.5 icon in the Menu Bar the SystemUIServer crashes and relaunches. This happens consistently w/ both of the users I have established on this particular machine (other machines work fine). Here's some possibly relevant info from CrashReporter:
OS Version: 10.3.5 (Build 7M34) Report Version: 2
Command: SystemUIServer Path: /System/Library/CoreServices/SystemUIServer.app/Contents/MacOS/SystemUIServer Version: 1.2.1 (1.2.1) PID: 1095 Thread: 0
Exception: EXC_BREAKPOINT (0x0006) Code[0]: 0x00000001 Code[1]: 0x90a5c740
Thread 0 Crashed: 0 com.apple.Foundation 0x90a5c740 _NSRaiseError + 0xf8 1 com.apple.Foundation 0x90a5c624 +[NSException raise:format:] + 0x2c 2 com.apple.Foundation 0x909fcee8 -[NSObject(NSForwardInvocation) forward::] + 0xb0 3 libobjc.A.dylib 0x90836810 _objc_msgForward + 0xb0 4 com.apple.Foundation 0x90a5c800 _NSRaiseError + 0x1b8 5 com.apple.Foundation 0x90a5c624 +[NSException raise:format:] + 0x2c 6 com.apple.Foundation 0x909fcee8 -[NSObject(NSForwardInvocation) forward::] + 0xb0 7 libobjc.A.dylib 0x90836810 _objc_msgForward + 0xb0 8 com.apple.AppKit 0x92dcce40 -[NSImage _bestRepresentation:device:bestWidth:checkFlag:] + 0x28 c 9 com.apple.AppKit 0x92de98d4 -[NSImage drawInRect:fromRect:operation:fraction:] + 0xec 10 com.apple.AppKit 0x92ec6c24 -[NSImage drawAtPoint:fromRect:operation:fraction:] + 0x98 11 com.apple.AppKit 0x92fa4ad8 -[NSTextAttachmentCell drawWithFrame:inView:] + 0x390
Let me know if you need the rest...
-
Greg Hurrell
Yes, send/show the rest of the crash report. There's not enough detail there to see where the crash is coming from. Probably best if you just email it to me (win@wincent.org).
My suspicion is that Cocoa is somehow choking on one of the custom user icons (or a cached representation of it). If we can find out exactly where the exception is being raised, we can catch it and prevent it from bringing the process down.
The fix would be to change your custom user icon, but then we wouldn't know where the crash is occurring, so probably best not to do that.
-
anonymous
Okay, the full log is headed your way...
-
anonymous
Win Switch 3.0b also crashes SystemUIServer. I'll mail you the log....
-
Greg Hurrell
You should probably read this bug report first. You may find that the issues already been fixed in the build linked to from that report.
Reply
This topic is now closed.


@@include('views/loading.html')
@@include('views/header.html')
@@include('views/hero.html')
@@include('views/magic.html')
@@include('views/immersive.html')
@@include('views/gesture.html')
@@include('views/conception.html')
@@include('views/accessories.html')
@@include('views/applications.html')
@@include('views/stand.html')
@@include('views/footer.html')


[enable JavaScript to render MarkDown]:
# Getting Started on Scrollback ### Simple steps to help you get started on Scrollback Once you are on Scrollback, you can do one of the following two things: 1. Join an existing room 2. Create a new room of your own ### 1. Joining an existing room Click on the 'Get Started' button on the homepage. You will get a modal window which will ask you to enter the name of the room you want to create or join. If you want to join an existing chanel, simply enter its name and click 'Go'. You will be redirected to your chatroom. ![Click on the 'Get Started' button on the homepage](http://i.imgur.com/cwlQLdO.png) ### 2. Creating a new room on Scrollback In the same modal window as above, enter the name of the room you want to create and click on 'Go'. ![Enter name of room and click on 'Go'](http://i.imgur.com/ora5MN8.png) ### **Configuring Scrollback** If a room with that name already exists, you will be redirected to that room. If the room with the given name doesn't exist, you will be notified about it and asked if you want to create the room and claim it. Once you have claimed your room, you will get options to configure your room. ![Option to configure your room on Scrollback](http://i.imgur.com/HXJS4HO.png) ###On the configuration page you will get to make the following configurations: 1. You can do the general settings for your room where you can change the name of your room and also give an appropriate description to your page. 2. You can link your chatroom to some IRC channel. Read more on how to link your Scrollback room to your IRC channel [here](http://scrollback.github.io/irc.html) 3. You can link your chatroom to the appropriate twitter hashtags and twitter handles. 4. You can decide whether you want to apply 'word filter' on your room and keep it from being spammed. This will prevent users from using abusive or unconstitutional words on your room. 5. You can decide whether you want search engines to index your room. 6. You can embed Scrollback into your own website. Read more on how to embed your Scrollback room into your own website [here](http://scrollback.github.io/embedding.html).
![All configuration options for your Scrollback page](http://i.imgur.com/7Ute5z3.png)


This whole security thing is a mess. It’s insane to think this breach could have cost us all a ton of money.
I assume the dev’s sweeped all of our addresses using the same method as the hacker intended to do?
Markus05-Jun-19 11:09 AM
Who said there was any hacker
pretty sure there was not
more the devs finding a bug
1
klein05-Jun-19 11:11 AM
getting closer to 8M coins now
Keppie05-Jun-19 11:12 AM
@Markus they wouldnt have sweeped everything without a real threat
Markus05-Jun-19 11:14 AM
It was a threat but there was no hacker, they did it to secure ppls funds meanwhile they solve the issue
jl777c05-Jun-19 11:14 AM
there was a hacker
there was an exploit in upstream
Markus05-Jun-19 11:15 AM
but no funds were lost?
gcharang05-Jun-19 11:21 AM
not yet
차미숙05-Jun-19 11:23 AM
Oh so there was a bug but that hacker didn't think about kmd yet?
Like the bug was for some other IT shit
Cryptoon05-Jun-19 11:26 AM
I think during the following days we will see some coins with big probs that got maliciously attacked exploiting the vulnerabilities
Good to see kmd devs on top of things
jl777c05-Jun-19 11:27 AM
we dont know what other projects are affected, we have our hands full
dxer66605-Jun-19 11:29 AM
moved btc in agama will back?
jl777c05-Jun-19 11:29 AM
if it went to the 1Gsdq...Lgqk address
1
fill out claim form
dxer66605-Jun-19 11:31 AM
moved to Gkdp4Q
gcharang05-Jun-19 11:32 AM
@dxer666 dm that destination address or check if they were further moved to the address jl said
1
p.05-Jun-19 11:48 AM
All this happens on that specific day on daily chart lmao sure pal.....
grumpygoron05-Jun-19 12:07 PM
So much stress
meatspoon05-Jun-19 12:13 PM
I hope this focuses the team on the wallets for a moment. Last night they were saying, "Quick, transfer to Ocean wallet!" So I downloaded that and it was taking forever to sync, i didnt have enough space on my SSD and the Ocean wallet is plastered with disclaimers about how it is Beta and funds are not Safu in it. So the team was recommending a beta version wallet as a safe haven for funds that were compromised out of their other beta version wallet.
right right
but the idea was, "Take your funds out of our beta wallet that was compromised and create a new wallet that has disclaimers about how your funds are not safu and put your funds in the new non-safu wallet"
jl777c05-Jun-19 12:16 PM
then send it to a ledger, or paper wallet, or even CEX
?
meatspoon05-Jun-19 12:17 PM
I get it (sort of). But the whole mantra over here is that the tech is top notch... that it blows every other project out of the water. But I dont think its controversial to say that if KMD cannot be held and transferred safely, that is a big problem.
and what about all the other coins that barely have wallets within the KMD ecosystem. I got OUR and ZEXO that i am unsure what to do with. Its a giant Cluster F
hyperDEX05-Jun-19 12:18 PM
Can we let the team do what they need to, there is time to kick them later......
meatspoon05-Jun-19 12:18 PM
i get it, but is Agama the official wallet for KMD nor not? Its up there on the Komodo website
hyperDEX05-Jun-19 12:18 PM
Let's focus on making sure everyone's funds are safe
and letting everyone know
meatspoon05-Jun-19 12:18 PM
but thats sort of my point, i dont know where to move them. they were OTC trades
hyperDEX05-Jun-19 12:19 PM
Do you have a ledger?
Tek05-Jun-19 12:19 PM
racist unemployed guy
you mean realist
meatspoon05-Jun-19 12:19 PM
@Deleted User i get it, but it IS a KMD issue because KMD hosts the file download on their site
it looks like an official wallet
Tek05-Jun-19 12:19 PM
i only slept 6 hours lel
or 5
meatspoon05-Jun-19 12:19 PM
there is an agama thread in the official discord
there is official support provided here
AGAMA=KMD
there is an issue of optics here...
grumpygoron05-Jun-19 12:20 PM
Guys it’ll be fine. In two years when the rebrand finally launches we’ll look back at this and laugh at remembering how the vulnerability caused the rebrand to be delayed until 2021
gcharang05-Jun-19 12:20 PM
@meatspoon you can send all the ecosystem coins to any other newly created secure address starting with R
meatspoon05-Jun-19 12:20 PM
if Komodo is telling people, "use Amaga, here it is on our site, its the best thing we can offer" which is the subtext, then that is a problem
Tek05-Jun-19 12:21 PM
yeah very
meatspoon05-Jun-19 12:21 PM
@gcharang what kind of wallet? and dont tell me Ocean
if i understand this correctly, this is the problem. There is no official wallet that isnt beta or isnt a full chain sync sort of thing. I want to be wrong about that, so please tell me if i am
and there are clearly naming convention issues... If two wallets are both called Agama and the idea is Agama is compromised.... sigh
jl777c05-Jun-19 12:25 PM
plz can we discuss this after the funds are secured?
meatspoon05-Jun-19 12:27 PM
Fine. I have tried to discuss this months ago in the wallet channels, giving criticism and suggestions for wallet issues. Most of that was ignored at the time.
bishop05-Jun-19 12:28 PM
@jl777c Are we above the 95% secured threshold yet? I know 90 was floated hours ago
Markus05-Jun-19 12:35 PM
@Tek wow 7k btc buy wtf
Tek05-Jun-19 12:35 PM
im just wondering how mcuh of it went through
volume spiked to 15k butts
so maybe all of it
it honestly looks like some bots are constantly trying to push KCH price down then if it falls below a certain thresshold another bot starts defending the price
BCH*
dokrates05-Jun-19 01:02 PM
wow
komodo hacked coins of people just to protect them
well done
Crabby Paddy05-Jun-19 01:12 PM
If a police found your wallet on the floor and decides to move it into a secure area to give back to you (with proof of ownership) @dokrates would you complain or would you rather they left it on the floor(edited)
Knowing someone can/will take it
McBeastie05-Jun-19 01:13 PM
@dokrates better the money with the Jedi than the Sith Lords.
May the KMD be with you!(edited)
dokrates05-Jun-19 01:13 PM
that's not the same case. A similar would be, police found the mechanism of your door's house vulnerable, and they went inside your home and changed the door, with a letter saying to go police station for the new key, so you can enter your home
dxer66605-Jun-19 01:14 PM
why kmd trading in bittrex disabled?
dokrates05-Jun-19 01:14 PM
btw i think is a very nice help from komodo.
1
jedis power
Crabby Paddy05-Jun-19 01:14 PM
Close enough, it’s the best thing they could do in a blockchain sense the idea remains. Yep thank you komodo for doing this, rather than everyone complaining, they did what they had to do and secured us all
jl777c05-Jun-19 01:15 PM
we are hearing of a few wallets that we were not able to save, so make sure to move them to secure addresses if you used ANY variant of agama this year with ANY coin


Enter SQL to check Syntax:
select count(*), some_column from some_table where pk1 = 123 and other_index is not null and some_string = 'abc' and some_badlyquoted_string = "def" group by some_column order by some_column
jkl


Demonstation of
anki-app-core
https://github.com/jun-g-0/anki-app-core
Request:
GET
POST
PUT
DELETE
http://localhost:3003/api/v1/
questions/
choices/
GO!
body
{ "column": "newValue" }
Database:
Result:


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Generic Class LinkedList. LinkedList like container.
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#include <LinkedList.hpp>
template<typename T>
class LinkedList< T >
Generic Class LinkedList. LinkedList like container.
◆ LinkedList() [1/2]
A constructor.
Constructs a new LinkedList object.
◆ LinkedList() [2/2]
A copy constructor.
Constructs a new LinkedList object.
- Parameters
-
◆ ~LinkedList()
A destructor.
Destructs the Linkedlist object.
◆ add()
◆ find()
◆ get()
Get value by index.
- Parameters
-
- Returns
- <T> value
◆ getHead()
Getter for head.
- Returns
- Node<T> *head;
◆ getLength()
Getter for move_speed.
- Returns
- double move_speed
◆ isEmpty()
Check whether the LinkedList is empty.
- Returns
- bool is empty
◆ print()
◆ remove()
The documentation for this class was generated from the following file:


- First the React app and all other dependencies wanted are installed into the program using the terminal.
- Then you import React and all the dependencies neede for that page.
- Then you create a React component using the es6 class extender method that lets you extend the object and all it's properties


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Ondo promotes 23,720 civil servants
by Peter DadaPeter Dada, Akure
No fewer than 23,720 workers in the Ondo State Civil Service have been promoted.
According to the Ondo State Civil Service Commission, the workers’ promotion came after the workers had passed promotion examinations at various ministries and parastatals.
The Chairman of the Ondo State Civil Service Commission, Dr Afolabi Adewakun, disclosed this while speaking with journalists in Akure, the state capital on Tuesday.
The chairman said the administration in the state had taken the welfare of workers as top priority, saying, “The government has been paying workers salaries as and when due since the inception of Rotimi Akeredolu-led administration.”
Giving the breakdown, Adewakun said a total of 6,941 workers were promoted in 2017; in 2018, 7075 worker got promoted while 9,704 civil servants were elevated in 2019.
He said, “Promotions are not automatic; apart from promotion examinations, there are other factors the government considered before promoting the officers. All the workers concerned have been given letters unless those with issues and these will be looked into.”
He added that between January and October 2019, about 190 officers across the various cadres in the civil service had been given approval “to retire either as mandatory or voluntary retirement after a meritorious service to the state”
On discipline, Adewakun said cases ranging from prolonged absence from duty without official permission to general misconduct have been looked into by the commission while sanctions such as reprimand, written warning and down-grading had been meted on errant officers.
He however failed to give out the number of the sanction officers, saying many of the cases were still under investigation and some were awaiting the approval of the governor.
In her remarks, the Permanent Secretary of the commission, Mrs Folasade Adegoke, said the promotion exercise were carried out on merit and admonished the newly-promoted workers to justify the promotion.
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--- layout: post title: ! 'OSCON ''06 Review Two: Appliances' tags: [] status: publish type: post published: true meta: _edit_last: '1' dsq_thread_id: '17413749' ---
Every MindTouch [Managed Office Server] comes with a subscription to the MindTouch "Zero-Maintenance" Service. You never have to worry about installing, configuring, backing up, upgrading, patching, or anything else, because we take care of it all for you...
MindTouch - Learn More About the Managed Office Server (MOS)
One trend I noticed at OSCON this year is appliances. MindTouch is one vendor on display in the exhibit hall. It wasn't the software that interested me, which is what they demoed over and over. It was that the software was packaged and sold as an appliance.
Not that exciting, eh? I beg to differ. That is what they should have focused on.
Take a look at the list in the quote from MindTouch's website again. With the base price of $2995, an appliance gets the following services:
This is starting to sound like an advertisement. But stop and think about it. Is an appliance is the best analogy we can think of? If I buy a toaster, I expect it to work, but don't necessarily expect upgrades. It won't spontaneously add the ability to cook eggs, for instance.
On the other hand, I like to compare the appliance concept to my parent's swimming pool growing up a dozen or so years ago. Summers in Arizona were hot, so a pool was essential. I have many fond memories swimming with friends.
For a time, I was in charge of maintaining it. It was a beast. Chlorine, acid, among other chemicals are required more periodically than I would have liked. Often calcium build up required more than one person to maintain it. All my brothers would be in the pool with pumice stones, grinding away at the tile. It was a day-long job.
I often imagined what it be like to have a pool service do everything. All the fun, minimal? to no work.
Running IT can be the same way. In order to enjoy the fruits, labor is required. But there are some parts of IT that can be automated, if architected correctly. That is the promise of appliances. Purchasing an appliance should be much more than it "just working" out of the box. Like a swimming pool, an appliance should mean all of the fun with none of the matainence.