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Two years ago, I wrote about meta-learning to fight imposter feelings. In this blog I made a distinction between impostering because you don’t feel you are up to the job, and because you feel you ought to know something which you don’t. The meta-learning blog focuses on how you define yourself as a data scientist and what, as a consequence, you decide to learn (and more importantly what not). Staying sane while doing data science is something that always has my interest. Imposter feelings are a major foe to the joy this work can bring. I came across/to two more insights on the topic that I found worthwhile sharing. The first is intellectual humility, which I learned about in the book Superforecasters, the art & science of prediction by Philip Tetlock. The second is seeing impostering as a learning alarm, thereby turning it to something positive.
Intellectual Humility
Superforecasters is not about data science, but about forecasting single events, as typically done by intelligence agencies. I thought it was a very interesting read overall, but what I want to highlight here is its treatment of the concept of intellectual humility.
Just like the forecasters, data scientists are faced with complex problems to which there is no perfect solution. Whether doing machine learning, statistical modelling or an exploratory data analysis, we try to paint an overall picture from incomplete information. We have to look carefully at nonlinear relationships, interaction effects and weak correlations. All very difficult for the human mind to conceive. Often the task ahead is daunting and when we are not careful it can quickly inflict feelings of being incapable. Tetlock discusses that the best forecasters are very aware of their limitations and the possibility that their judgement might be off. But at the same time these forecasters do not doubt that they are the person for the job:
The humility required for good judgement is not self-doubt - the sense that you are untalented, unintelligent, or unworthy. It is intellectual humility. It is the recognition that reality is profoundly complex, that seeing things clearly is a constant struggle, when it can be done at all, and that human judgement must therefore be riddled with mistakes. This is true for fools and geniuses alike. So it’s quite possible to think highly of yourself and be intellectual humble. In fact, this combination can be wonderfully fruitful. Intellectual humility compels the careful reflection necessary for good judgement; confidence in one’s abilities inspires determined action. Superforecaster p. 228-229
I usually refrain from a You got this! approach to fight imposter feelings, because I honestly don’t know if you do.  Therefore, I typically focus on the ought to know part. However, what I realized when reading Tetlock, was that the fact that you are puzzled by the problem you are working on, is by no means an indication you are a phoney. Acknowledging that data science is freaking, freaking hard is not a sign of weakness, it is a sign of realism. Don’t look at data science problems as something you are ought to solve on a whim. They are mysteries and only by hard work and perseverance you can chip away some of that mystery and you might even get to insights that are useful.
Learning Alarm
Now turning to my favorite ought to know part of impostering. The feeling of shame, when someone else knows stuff that you don’t. You, the data scientist, does not know this simple thing and therefore you deserve to be fired, to be stripped of all your diplomas and work as a store clerk for the rest of your life. Turn that feeling of shame into a learning alarm. Be excited that you discovered something new, something you can add to your knowledge stack.
Focusing on the shame part of ought-to-know will turn you attention inwards. Chances are that you are so busy giving yourself a hard time that you don’t use the opportunity to learn. It is completely useless to ruminate on if you should have known this already. Fact is that you don’t. Instead turn your attention outwards.  Pick their brain! Otherwise, Google, read blogs, practice, whatever is needed to master the new material.
Thanks for Reading
I realize these two topics are a little less applicable than the earlier blog and are a little more philosophical in nature. Still, I hope you find them as practical. They serve as default responses for situations data scientists can be confronted with; being puzzled by the problem they are trying to solve and not knowing something they think they should.
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Status
Scope
Camera
Settings
Status:
SSID:
Signal:
RA:
DEC:
Version:
Brand:
Model:
Status: Nothing to do


Online", "Offline
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My Home Network
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IP: <IP_ADDRESS>
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IP: <IP_ADDRESS>
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Welcome to ICS Storage Website
Sensor ID
Location
Value
IR Sensor
BL-7F entrance
92
Ultra sound
BL-7F entrance
94


{% block content %}
{% endblock %}
{% cache 36000 sidebar request.user.username %}
{% block sidebar %}
{% endblock %}
{% endcache %}
{% load static %} {% load cache %} {% load compress %}
{% block header %} {% endblock %} {% compress css %} {% endcompress %} {% compress css %} {% comment %} {% endcomment %} {% block compress_css %} {% endblock %} {% endcompress %}Multiple lines of text that form the lede, informing new readers quickly and efficiently about what's most interesting in this post's contents.
This is a wider card with supporting text below as a natural lead-in to additional content.
Continue readingThis is a wider card with supporting text below as a natural lead-in to additional content.
Continue reading


Index
A
activation energy,
164
advisors, betting based on advice of,
6–7
,
74–76
algorithmist, wanting a time guarantee,
167
anti-greedy moves
by flies,
165
probability of taking,
166
As Easy as Pie mind game,
37–39
solution to,
94–96


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--- layout: post status: publish published: true title: Home, I am coming! author: Leask author_login: leask author_email<EMAIL_ADDRESS>author_url: https://leaskh.com wordpress_id: 1504 wordpress_url: https://leaskh.com/?p=1504 date: '2011-03-31 23:11:19 +0800' date_gmt: '2011-03-31 15:11:19 +0800' categories: tags: [] comments: [] ---
// image from vladstudio.com


Effects Menu
QuickBox:
Character Based:
World Based:
Server Software: Running L2J created by L2Chef and the L2J team. www.l2jserver.com for details.


woa_build_profiles
Syntax
[woa] = woa_build_profiles(variable_list,time,xcoords,ycoords)
[woa] = woa_build_profiles(variable_list,time,xcoords,ycoords,zgrid)
Description
[woa] = woa_build_profiles(variable_list,time,xcoords,ycoords)
builds a struct of profiles from World Ocean Atlas 2018 Statistical Mean for All Decades Objectively Analyzed Mean Fields at Standard Depth Levels, pulling profiles nearest to coordinates specified by xcoords
and ycoords
. time
specifies monthly or annual climatology; time ='00'
for annual climatology and '01'
'10'
etc. for monthly climatology. Profiles are loaded into the struct array woa
with all variables specified in variable_list
. The function builds the url, extracting the maximum resolution available (typically 0.25-deg or 1.00-degree grid). Resolution depends on the variable. If the user requests only 0.25-degree variables in variable_list, data will be returned in 0.25-degree resolution. If any requested variable is coarser (1-degree) all variables will be returned in 1-degree resolution.
[woa] = woa_build_profiles(variable_list,time,xcoords,ycoords,zgrid)
depth-interpolates the profiles to a vertical grid of zgrid
, in meters. zgrid=2
would produce profiles interpolated to 2 meter vertical grid.
time
is a string or character array. '00'
is annual climatology, while other codes e.g. '02'
(February) or '11'
(November) indicate monthly climatology.
variable_list
is a cell array where each element is the string name of a variable to be read and included in struct woa
.
xcoords
and ycoords
are vectors of coordinates. Rows or columns are fine, and both -180/180 or 0/360 notation are fine.
Available variables are:
'temperature'
(degrees Celsius)
'salinity'
(psu)
'oxygen'
(umol/kg)
'o2sat'
(%)
'AOU'
(umol/kg)
'silicate'
(umol/kg)
'phosphate'
(umol/kg)
'nitrate'
(umol/kg)
Example 1
% Setup nctoolbox:
setup_nctoolbox
% Plot surface nitrate:
variable = 'nitrate';
time = '03';
region = [-5.0, 45.0 ,-120, -150];
depth = -0;
woa_simple_plot(variable,time,region,depth)
% Click stations on the plot to create a coordinate list:
[xcoords,ycoords] = transect_select('densify',10); % click desired transect on the figure, densify selection by 10x
% Build a uniform struct of profiles:
variable_list = {'temperature','salinity','oxygen'}; % 'temperature' 'salinity' 'oxygen' 'o2sat' 'AOU' 'silicate' 'phosphate' 'nitrate'
time = '00'; % '00' for annual climatology '01' '10' etc. for monthly climatology
zgrid = 1; % vertical grid for linear interpolation in meters
[woa] = woa_build_profiles(variable_list,time,xcoords,ycoords,zgrid); % zgrid optional, no interpolation if unspecified
[woa] = general_remove_duplicates(woa); % thin struct to gridding of source (optional)
% Make a section plot:
general_section(woa,'salinity','lon','depth',1,1)


WATCH: The second trailer for Cats has landed and it's just as bonkers as the first one
by Ciara WalshThe second trailer for Cats has landed.
You might remember the intense reaction to the first trailer for Cats earlier this year - it pretty much left everyone speechless.
With Idris Elba, Judi Dench, James Corden and many more A-list celebs, it has the makings of a great film, however the famous faces attached to cat bodies is a bit too bonkers for some.
Tom Hooper, director of the King's Speech and Les Miserables, is the mastermind behind the highly-anticipated film with one of the main questions related to the use of CGI animation.
You'll recognise some of movie land's most revered names including Sir Ian McKellen but it must be said that seeing them in cat form takes a bit of getting used to.
There's been a strong reaction to the latest trailer featuring Macavity the Mystery Cat (Idris Elba), Grizabella (Jennifer Hudson) and Old Deuteronomy (Judi Dench) to name but a few.
It lands on December 20 and judging by the hype so far, you're going to hear a lot more about this film release over the next few weeks.
Here's what people had to say about the latest sneak peek.
You can check out the full trailer down below.
Cats is scheduled for release on December 20, just in time for Christmas.


Cheeky Results
Date Time
Drink
Rating
Age
Gender
User Agent
Device
IP
Date Time
Drink
Rating
Age
Gender
User Agent
Device
IP


Reports static inner classes annotated with
@Nested
.
The
@Nested
annotation can't be used on static classes.
New in 2018.2


| DOSE: T+ 0:00 |
1.5 Tbsp |
oral |
Nutmeg |
(ground / crushed) |
| T+ 4:00 |
1 Tbsp |
oral |
Nutmeg |
(ground / crushed) |
First my history: I’ve done my fair share of drinking, smoking and a little nitrous. I had my first experience with psychedelics about a week ago with morning glory. It was an experience I definitely enjoyed.
After my morning glory experience, I thirsted for more of this new found world of psychedelics. Two nights ago I was bored and decided to try nutmeg for lack of more interesting things to do. Another friend in a different city, we’ll call him M, decided to do it also and I had a sober friend with me. At 10:00pm I ingested about 1.5 tbsp of ground nutmeg mixed in some orange juice; it wasn’t all that bad tasting. M ate about 3 tablespoons at the same time.
I then decided to settle down, watch a movie and await my trip. I felt nothing the whole rest of the night and neither did M. I was disappointed, but had read somewhere that you may not feel the effects until the next morning. So before I went to bed, at about 2am (T+4:00) I ate another big teaspoon of nutmeg. I then went to sleep feeling completely normal.
I woke up at about 6:00am (T+8:00) to the world spinning around me.  Altogether not even a slightly pleasurable experience. After a bout an hour of struggling to go back to sleep I succeeded.
I woke up at noon (T+14:00) and to my disappointment I still was very dizzy and had the same cotton mouth.  M said he was very disappointed that he felt nothing but some dry mouth. I thought to myself, “I wish I had it that easy.”
Eventually after some random naps during the day, I went to sleep for the night and woke up today completely normal. Today I have felt very happy and content, almost euphoric, and I have found unusual amounts of concentration, focus and patience when doing school work. I don’t know if this is a coincidence, an affect of the nutmeg or just out of comparison with the day before’s stupidity and miserableness.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


RT @rbonales: We have extended the CFP deadline to January 31st because we understand this is a busy time for everyone. Happy holidays!
12/22/2015, 10:56:55 AM
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link--- layout: tweet ---
RT @rbonales: We have extended the CFP deadline to January 31st because we understand this is a busy time for everyone. Happy holidays!
12/22/2015, 10:56:55 AM
Favs: 0
Retweets: 0
link


WITNESS LIST Urban Affairs Committee March 3, 1999-2:00P HB 313 For: Cain, Randy (City of Dallas) Cameron, Andrew (City of San Antonio) Erben, Andrew (Texas Association of Builders) Mintz, David (Texas Apartment Association) Walker, Jerome (City of Fort Worth City Council) HB 485 For: Horton, Susan (Texas Municipal League) Paniagua, Joe (City of Fort Worth City Council) Wetherbee, Diane (City of Plano - City Attorney) HB 485Amendment (#1 (to CSHB 485)) Evans, Charles (Dallas/Fort Worth Airport Board) HB 514 For: Rickleman, Virginia (Self) Strain, Sharon (Galveston Housing Authority Board of Commissioners) HB 516 For: Coody, Lori (City of Galveston City Manager) Horton, Susan (Texas Municipal League) HB 1189 For: Beard, Val (Brewster County Commissioners Court) HB 1260 On: Pederson, Craig (Texas Water Development Board) HB 1413 For: Mintz, David (Texas Apartment Association)


Welcome to Brandon's Portfolio page!
An Applied Physics student from UC Santa Cruz, I hope that I get to apply my knowledge gained from Physics in the future. (Future) Data Scientist and (Future) Physicist. I am currently learning Python and web design. If you want to contact me, I can be reached below.
Web Design Portfolio
These are some of my works that I have done for FreeCodeCamp. This is not an exhaustive list of projects that I have done. I will update this section on a somewhat regular basis. To keep up with all my projects, check out my Github!
Get in Touch!
I can also be reached directly using the email form to the left or email at brandvi1994 [at] gmail [dot] com


Preparation time
less than 30 mins
Cooking time
less than 10 mins
Serves
Serves 6
Use the best quality anchovies you can find for this simple salad recipe.
For the croutons, preheat the oven to 180C/350F/Gas 4.
Cut the crusts off the bread and tear the remainder into small pieces. Toss them in a bowl with the olive oil. Spread onto a baking tray and bake for 5-7 minutes or until crisp and golden-brown. Remove and leave to cool, then season lightly with salt.
Meanwhile, put the eggs into a pan of boiling water and boil for eight minutes. Drain and cover with cold water.
For the dressing, put the garlic, egg yolk, mustard, lemon juice, sugar and some seasoning into a small bowl. Mix together briefly with a hand-held electric whisk, then slowly whisk in the oil to make a smooth dressing.
Discard the outside leaves of the lettuce if necessary and tear the rest into small pieces. Wash and dry well, then spread over the base of six medium serving plates. Peel the hard-boiled eggs and cut them into quarters. Arrange four pieces over each plate of lettuce leaves with the four strips of anchovy fillet and a few croutons. Drizzle one tablespoon of dressing over each plate and serve straight away.


24th January 2015
Ahhh - conflict! Having been brought up in an English/Scottish home conflict is something that was rarely expressed openly. (The WORST thing was being sent to "coventry" - not being spoken to at all for a period of time!). So it took me a while to learn about expressing and dealing with conflict in the open. Something of an ongoing life journey, like many things! So why is dealing with conflict so critical?
“10% of conflict is due to difference in opinion and 90% is due to the wrong tone of voice" —Anonymous, often attributed
Well, once a conflict occurs it is usually accompanied by anger and frustration... which can lead to raised voices and harsh words (or a withdrawl in a more passive expression). Which is why we need to recognise conflict and allow ourselves to acknowledge it before we lash out and compound the situation.
"All conflict we experience in the world, is a conflict within our own selves." —Brenda Shoshanna
And as I look inward, usually when there is conflict, there really is some form of conflict within. Did I have expectations that were unreasonable in this situation? Perhaps I was expecting too much? Or just expecting something from the wrong person. Or am I being stubborn about a point of view because I am afraid of trying things a different way? As the quote above points out - conflict occurs outwardly with other people, but also within ourselves.
"Peace is not the absence of conflict, but the ability to cope with it." —Dorothy Thomas
So, if we can learn to recognise, acknowlege and really stop to look inward can we avoid conflict? No. And in many ways we don't want to - but I believe that we can find healthier and less painful ways to try and cope with the conflict. Perhaps talking about the situation or perhaps removing ourselves from the situation for a time. And if it really is a conflict that cannot be resolved - then walking away and learning from it, so that it hopefully does not occur again in the future.


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The BaseView is a custom extension of Backbone.View with some built in functionality and a defined life cycle. The life cycle methods can be run either synchronously or asynchronously.
To initialize a BaseView, there are several choices of options to pass in.
The life cycle has three main parts: beforeRender
, render
, and afterRender
. beforeRender
and
afterRender
are
noops by default. If they are defined with zero arguments, they are executed synchronously. If they are
defined with
one argument, then a $.Deferred
is passed in as that argument, and the life cycle doesn't continue until
that
$.Deferred
is resolved. The render method uses the same convention.
beforeRender : function() { synchronous },
beforeRender : function($deferred) { must resolve or reject $deferred }
The lifecycle is started with view.start()
. This returns a promise. During the life cycle the promise is
notifed with:
beforeRenderDone
, renderDone
, and afterRenderDone
.
Child views are rendered during a parent views `afterDone`. The views start promise is not resolved until
all the
children's promises are resolved. Children can be nested arbitrariluy deep. Child views can be added
before start using
parent.addChild(child)
.
- Source:
Methods
-
addChild(childView)
-
Add a child view to the array of this views child view references. The child must be started later. This happens in start or manually.
This method can take either a view instance or options for a view.
If options for a view are passed in, then BaseView is the default ViewType. The ViewType can be declared on the
options.ViewType
.Parameters:
Name Type Description childView
- Source:
-
addChildren(childView)
-
Add multiple child views. The method receives either an array of views to be added or is called with all the views to be added.
Parameters:
Name Type Description childView
- Source:
-
appendOrInsertView($startDeferred)
-
Parameters:
Name Type Description $startDeferred
- Source:
-
bindEventListeners(bindingsArray)
-
bindEventListeners Bind all event listeners specified in and 'options.listeners' using 'listenTo'. Either
option.bindings
oroptions.listeners
can be used.Parameters:
Name Type Description bindingsArray
(Array[Array]) - A collection of arrays of arguments that will be used with 'Backbone.Events.listenTo'
- Source:
-
constructor(options, useDefaultOptions)
-
The constructor of BaseView overrides the default BB constructor, so that the options object can be created and applied to
this.el
beforethis.initialize
is called.name
- convenience name string for debugging - will be available on the view instanceappendTo
- if set andel
is not set then the view will be appended to this eleeent.appendTo
can be a sizzle selector, a DOM element, or a jQuery objectbindings
- declarative syntax to setup view listeners array of arrays each sub array contains: what to listen to, the event, and the callback view context is assumed
bindings : [ ['model', 'change:price', 'showNewPrice'], ['model', 'change:discount', 'animateAdvertisement'] ],
defaultOptions
- the options to be used as the default. Passed in options will extend this.ModelType
- if supplied,this.model
will be of typeModelType
- default isMasseuseModel
modelData
- if supplied,this.model
will be initialized with,this.model.set(modelData)
- ViewContext - Convenience helper to acces the view context from within modelData
- this helps in separating view options and view definitions into separate AMDs
modelData : { viewId : ViewContext('cid') }
template
- String to be used as the umderscore templateviewOptions
- list of keys for which each key value pair fromoptions
will be transferred to the view instance
var view = new BaseView({ name : 'MyName', appendView : false, ModelType : MyCustomModel, modelData : { ... }, bindings : [ ['model', 'change:price', 'showNewPrice'], ['model', 'change:discount', 'animateAdvertisement'] ], templateHtml : '
<%= price %> : <%= discount %>
', // Underscore templating that will - if provided - be turned into this.template using _.template(templateHtml) });
Parameters:
Name Type Description options
useDefaultOptions
- Source:
-
dataToJSON() → {Object|string|*}
-
- Source:
Returns:
- Type
- Object | string | *
-
initialize(options)
-
Parameters:
Name Type Description options
- Source:
-
refresh() → {$promise}
-
Remove this view and all its children. Then restart them all.
- Source:
Returns:
- Type
- $promise
-
refreshChildren()
-
Remove all children and restart them.
- Source:
Returns:
$promise - will be resolved once all children are restarted
-
remove()
-
Removes this view and all its children. Additionally, this view removes itself from its parent view.
- Source:
-
removeAllChildren()
-
Remove all children from the parentView.
- Source:
-
removeChild(childView)
-
Remove one child from the parentView.
Parameters:
Name Type Description childView
- Source:
-
render()
-
- Source:
-
start($parentRenderPromise) → {jQuery.promise}
-
Wrapper method for lifecycle methods. Life cycle event are notifed both throw the progress returned by this method's promise, and by events triggered on the view. So - for example - plugins can hook into life cycle events.
In order, this method:
- Calls this.beforeRender()
- Starts any child views
- Notifies that beforeRender is done
- If the view has a parent, waits for its parent to render
- Calls this.render()
- Notifies that render is done
- Calls this.afterRender()
- Notifies that afterRender is done
- Resolves the returned promise
Parameters:
Name Type Description $parentRenderPromise
jQuery.promise If passed in, the start method was called from a parent view start() method.
- Source:
Returns:
A promise that is resolved when when the start method has completed
- Type
- jQuery.promise


{% extends "layout.html" %} {% set ptitle = "Did HMRC allow you to defer paying because of financial hardship?" %} {% block page_title %} {{ ptitle }} - Tax Tribunals Prototype {% endblock %} {% block content %} {% include "includes/phase_banner_beta.html" %} Back Step 6 of 7 {{ ptitle }} If HMRC said no, you can ask the judge to consider your reasons. {{ ptitle }} Yes No I am waiting for a decision Save and come back later {% endblock %}
Back Step 6 of 7
If HMRC said no, you can ask the judge to consider your reasons.
Save and come back later


The final shōdan of the play involves active dance, congruent singing, percussion in strict rhythmic setting, and a striking closing pattern by the nohkan. This brings the Intermedia Index to its second highest point. The mimetic movement matches the text, and the fast music underlines the climactic character of the section.
The kiri can be divided into three parts: introducing the sword as 'Clustering Clouds of Heaven', boasting of its powers as it is offered to the envoy, and the deity’s exit.
To emphasize the name of the sword, an inserted measure of four-beat (toriji) interrupts the steady flow of the honji. It creates a pause that stresses the name “Ama no murakumo…” (). The deity shows the sword by performing the standard sequence of kata: Forward Pointing and Open-retreat, while holding the blade up high at arm's length.
The second part begins with the deity looking at the sword held between stretched arms and . Then, the jiutai repeats the claim and tells about the protection and blessings that the sword will bring. The dance’s momentum picks up until the end of the kiri. The shite reinforces the statements with a series of Six and Seven Stamps, which produces a . The text that follows speaks of ruling the land to the four seas and the abundance of the five staple crops. It is mimicked with a loosely synchronized sequence of formal kata: . As the jiutai sings, “Inari no shintai Kogitsune-maru wo/The manifestation of Inari: the Little Fox,” the shite prepares to formally deliver the blade by performing an that brings him back to Square 1. In an intense moment, the deity, holding the sword with two hands, walks towards the Emperor's envoy, hands the blade to him, moves back, Kneel, and Bow.
The final section of the text starts, "kore made nari to ii-sutete/Now, I am done!", and brings a change of tone created by a of both music and dance. The deity stands up and performs several kata with spectacular agility: Two Large Steps, a Leap Turn, and a sequence of Kneeling that mimic the words "mata mura-kumo ni tobi-nori/he leaps upon the mass of clouds." The closing nohkan’s tome no te pattern confirms the finality of the situation as the deity moves with determination to the Second Pine on the Bridge. Once more he takes Two Large Steps in preparation for a Leap Turn, , as the jiutai sings: "Higashiyama Inari no mine ni zo kaerikeru/and returns to the Eastern Peak of Mt. Inari!." Finally, the deity flips his left sleeve over his head to indicate his disappearance from view, while Munechika keeps his gaze into the distance, as if seeing the deity off.


{% include head.html %}
{% include header.html %} {% include portfolio_grid.html %} {% include skills.html %} {% include exp.html %} {% include personal.html %} {% comment %} Don't forget jekyll uses the liquid templating system. This is how a comment block looks. {% include recommends.html %} {% endcomment %} {% include contact.html %} {% include footer.html %} {% include modals.html %} {% include js.html %}


Welcome to the game! Repeat back the pattern by clicking the buttons. You have up to 3 strikes allowed.


The Deployment Problem, Part2
Throughout this process of learning Rails and thinking about deploying web apps, a constant question has been how to run the web app on a system which is administered by someone else. A large part of my goal for developing web apps has been to use it at work, where I have space on the server but do not have admin privileges. The web pages are on systems likely served by an Apache web server. Since it also serves many other pages and is a production server, I would prefer not to need to edit the servers config file or reboot the server when I change something.
We’ll see how Rails handles this. In worrying about this, I look a quick glance Django. I skimmed the online resource, www.djangobook.com. In the book, Chapter 12 appears to have a workaround that allows Apache to spawn a process for handling a Django web app. The section is titled, “Running Django on a Shared-Hosting Provider with Apache,” which sound like the situation that I will be facing.
One final observation of Rails vs Django (based on the past few hours of skimming) is that Django looks like python. Rails looks like Rails, with some resemblance to Ruby. Being written in Ruby doesn’t mean knowing Ruby helps, like knowing C doesn’t allow someone to understand every program every written in C. I don’t mean to imply any inferiority in the Rails approach. In many ways, this may make it easier to implement because it’s freed of its strong ties to programming in Ruby. These are my first, and admittedly uninformed, initial impressions of Rails and Django.


About me
My name is Yannick Mister. I'm an aspiring (mainly Geo-related) coder. I love Annick.
My bachelors study started in 2012, at the
Wageningen University and Research Centre
. Living far below sea level, and close to water, hydrology always had my interest. Therefore I studiedSoil, Water, Atmosphere
. Soon enough, during this study, I came in contact withGIS
, and this opened a whole new world to me. Being able to create maps myself, choosing what data to show, and how, triggered something in me; I started following more courses on the subject, and even started teached for a while. By the time I finished my bachelors, and now I am proud to say that I am studying for a Master of Science degree in Geo-Information Sciences. And I love it!Coding Skills
In order of level of experience
- R
- Python
- Java
- HTML
- CSS


You may provide full HTML content for you message using the messageTemplate option. The messageTemplate field may contain full HTML including any Angular tags or directives.
messageTemplate
In this example, a hyperlink is included with an ng-click attribute. The scope option is used to pass the current controller scope where the ng-click's handler function is located.
ng-click
scope


Honoring the Fallen: An Interactive Memorial Map
Alexander K. Ward
- Date of Birth: 12/27/1940
- Home of Record: Annapolis
- State: MD
- Branch: USMC
- Place of Death: Quang Tri
- Year of Death: 1968
- Villanova Class Year: 1963
- Major: Biology
About
This is my account of the battle on Valentine’s Ridge, which started on 14 February 1968 and continued to 15 February 1968. In this report there has been input from the Battalion Surgeon, first platoon commander, first & second platoon members, S-3 reports and family of the KIA.
We left Ca Lu on 13 February 1968 for what was soon to be known as Valentine’s Ridge. This is a small 200-meter hill approximately one mile west of Ca Lu combat base and 8 miles east of Khe Sanh combat base. The coordinate is XD990445 to XD978455 running North and South terminating at the Quang Tri River. At 1600 on 14 February 1968 all three platoons and the command group started up the side of this hill with first platoon on the southern flank (nearest the river).
Shortly after part of first platoon left the groomed trail second and third platoon received 50cal. machine gun, automatic weapon and mortar fire. We received rocket, mortar and small arms fire wounding several men. At this time we were isolated from part of our platoon (first) and could not see second or third. Our actions involved calling in fighter jets, destroying a rocket launching position, caring for the wounded, and securing our area.
Contact was lost with the command group early in the battle. They had taken a direct hit killing our CO, XO and Chief Corpsman, Captain Ward, Lieutenant Reese and HM2 Goss. Under the leadership of our platoon commander, Lieutenant John Holladay, we moved off the hill and to a secure location on Route 9 wailing for reinforcements and tending to the wounded.
At 0200 on 15 February 68 first platoon moved down Route 9 towards Ca Lu collecting men separated from second and third platoons and meeting up with India company. What was left of first platoon made it back to Ca Lu at 0300 hours. At daybreak I took 8mm pictures of fighter jets dropping high explosives and napalm on Valentine’s Ridge.
India and Kilo companies moved off the ridge by the end of that day with a loss of 11 Marines and many wounded. This is part of the story about that day and each has his own. I wanted to tie together all that lost their life and to say that I’m sorry for them and their families. The names below are the ones that I have researched.
Captain Alexander Ward Second Lieutenant William Reese HM2 Larry Goss Private First Class Fredrick Bungartz Corporal Lowell Combs Corporal Dennis Fleming Lance Corporal Mark James Private First Class Melvin Jones Private First Class Barry Rigsby Lance Corporal Jeffrey Wentzel Corporal David Schneider
Written by:
Ray(Doc)Felle 1st platoon Kilo 3/9/3 Posted by: Ray (Doc) Felle Email<EMAIL_ADDRESS>Relationship: Captain Ward was my Commanding Officer for Kilo 3/9/3 USMC Friday, December 10, 1999
Works cited
- Alexander K. Ward. Vietnam Veterans Memorial Fund Wall of Faces. https://www.vvmf.org/Wall-of-Faces/54431/ALEXANDER-K-WARD/…
- Alexander K. Ward. Marines Together We Served: Reconnecting Marines Since 2003. https://marines.togetherweserved.com/usmc/servlet/tws.webapp.WebApp?cmd=ShadowBoxProfile&type=Person&ID=123298
- College, V. (1963). Belle Air 1963. Villanova, PA : Villanova College.https://library.villanova.edu/Find/Record/vudl:554479
Cite this article
"Alexander K. Ward." Honoring the Fallen: An Interactive Memorial Map. http://localhost:4000/article/1968-02-15-alexanderkward.html


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{% include meta_tags/base.html %} {% include meta_tags/sharing.html %} {% include externals/styling.html %}
{% include header.html %} {% include headers/cs-search.html %} {% include externals/scripting.html %} {% include externals/google_analytics.html %}


| View in LncBase | View in Ensembl | View in RNAcentral | Target description | Methods |
|---|---|---|---|---|
| Loading data on lncRNA targets... | ||||
| Failed to load data from server | ||||
| {{ target.source_accession.split(":")[1] }}unknown | {{ target.target_accession.split(":")[1] }} | {{ target.target_urs_taxid }} | {{ target.description.split(" [")[0] }} | {{ method }}, |
No lncRNA targets found for this sequence. Learn more →


{# # Copyright 2013 Donald Stufft # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. -#} {% extends "base.html" %} {% block title_base %}{{ config.site.name }}{% endblock %} {% block content %}


Multi dimensional orbits
Note that this funcionality is quite unstable and can provide you some unwanted results
Once again we include jQuery and jOrbital scripts.
/* jquery */  /* jquery.jOrbital plugin */

 Hover

1

2

1

2

3

4

5

4

5

6

Of course you don't have to use DIVs. In fact you can use any TAG that suits you. Only thing to rememeber is structure and .orbit class
Now, lets make the orbits:
$(".orbital-2").jOrbital(); $(".orbital").jOrbital();
It's important to keep the right order of making orbitals. The deepest orbits should be created first. That's why we used two separated classes .orbital and .orbital-2
If everything is okay you should end-up with something like:
Hover
1
2
1
2
3
4
5
4
5
6


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface GameInfo
All of the public game information for the current hand of poker is available through the GameInfo object.
| Method Summary | |
|---|---|
boolean |
canRaise(int seat)
See if the player in the given seat is able to raise |
double |
getAmountToCall(int seat)
Get a player's amount to call |
double |
getAnte()
Get the amount of the ante, if any |
double |
getBankRoll(int seat)
Get a player's bankroll |
double |
getBankRollAtRisk(int seat)
Get the maximum amount the player in the given seat can risk in this hand. |
double |
getBetsToCall(int seat)
Get a player's amount to call in bets |
int |
getBigBlindSeat()
Get the big blind seat |
double |
getBigBlindSize()
Get the amount of the big blind |
Hand |
getBoard()
Get the board cards |
int |
getButtonSeat()
Get the seat the button is on (could be dead button) |
double |
getCurrentBetSize()
Get the amount of the betting increment (for fixed-limit) |
int |
getCurrentPlayerSeat()
Get the seat for the current player to act |
double |
getEligiblePot(int seat)
Get the amount in the pot that a player is eligble to win. |
long |
getGameID()
The unique game identifier for this hand |
java.lang.String |
getLogDirectory()
Get the Log Directory used by all players for keeping logs |
double |
getMainPotSize()
Get the size of the main pot. |
double |
getMinRaise()
Get the smallest legal raise |
int |
getNumActivePlayers()
Get the number of players still active (not folded) in the hand |
int |
getNumActivePlayersNotAllIn()
The number of active players that are not all-in |
int |
getNumberOfAllInPlayers()
Get the number of players in the hand that are all-in |
int |
getNumPlayers()
Get the number of players dealt into the hand |
int |
getNumRaises()
The number of bets and raises made during the current betting round |
int |
getNumSeats()
The number of seats at the table |
int |
getNumSidePots()
Get the number of side pots |
int |
getNumToAct()
The number of players still to act in this betting round if there are no further raises. |
int |
getNumWinners()
The number of players that were awarded a pot in this hand |
PlayerInfo |
getPlayer(int seat)
Get state information for a player in a given seat |
PlayerInfo |
getPlayer(java.lang.String name)
Get state information for a player in a given seat |
java.lang.String |
getPlayerName(int seat)
Get the name of the player in a given seat |
int |
getPlayerSeat(java.lang.String name)
Get the seat number for a player by name |
java.util.List |
getPlayersInPot(double amountIn)
Get a list of all players eligible to win a pot with the given minimum stakes |
double |
getRake()
Get the amount raked from pot so far |
double |
getSidePotSize(int i)
Get the size of the side pot amount. |
int |
getSmallBlindSeat()
Get the small blind seat (could be dead small blind) |
double |
getSmallBlindSize()
Get the amount of the small blind |
int |
getStage()
Get the current game stage (Holdem.PREFLOP, Holdem.FLOP, Holdem.TURN, Holdem.RIVER) |
double |
getStakes()
The stakes are the amount each player must have invested in the pot to stay active in the hand. |
double |
getTotalPotSize()
Get the total size of the pot including the main pot and all side pots. |
int |
getUnacted()
Get the number of players who have not acted yet this round |
boolean |
inGame(int seat)
See if the player in the given seat is dealt into the hand (not sitting out or empty). |
boolean |
isActive(int seat)
See if the player in the given seat is still active in the hand |
boolean |
isCommitted(int seat)
See if a player has invested anything in the current round |
boolean |
isFixedLimit()
Determine if the game is fixed-limit |
boolean |
isFlop()
See if it is currently the flop round |
boolean |
isGameOver()
See if the hand is over |
boolean |
isNoLimit()
Determine if the game is no-limit |
boolean |
isPostFlop()
See if it is currently the post-flop |
boolean |
isPotLimit()
Determine if the game is pot-limit |
boolean |
isPreFlop()
See if it is currently the pre-flop |
boolean |
isReverseBlinds()
In reverse blinds mode, if the game is Heads-up, the small blind is placed on the button. |
boolean |
isRiver()
See if it is currently the river round |
boolean |
isSimulation()
Determine if the game is in simulation mode. |
boolean |
isTurn()
See if it is currently the turn round |
boolean |
isZipMode()
We should play as fast and crudely as possible because the user has requested we zip to the end of the hand. |
int |
nextActivePlayer(int seat)
Get the seat number of the next active player at the table (skips empty seats and folded players) |
int |
nextPlayer(int seat)
Get the seat number of the next player at the table (skips empty seats) |
int |
nextSeat(int seat)
Get the next seat number clockwise from the given seat |
int |
previousPlayer(int seat)
Get the seat number of the previous player at the table (skips empty seats) |
| Method Detail |
|---|
java.lang.String getLogDirectory()
long getGameID()
int getStage()
boolean isPreFlop()
boolean isPostFlop()
boolean isFlop()
boolean isTurn()
boolean isRiver()
double getAnte()
double getSmallBlindSize()
double getBigBlindSize()
double getCurrentBetSize()
int nextSeat(int seat)
seat
- a seat number
int nextPlayer(int seat)
seat
- a seat number
int previousPlayer(int seat)
seat
- a seat number
int nextActivePlayer(int seat)
seat
- a seat number
Hand getBoard()
double getTotalPotSize()
double getMainPotSize()
int getNumSidePots()
double getSidePotSize(int i)
i
- the side pot index [0..n-1]
int getButtonSeat()
int getSmallBlindSeat()
int getBigBlindSeat()
int getCurrentPlayerSeat()
double getEligiblePot(int seat)
seat
- the player in question
int getNumPlayers()
int getNumActivePlayers()
int getNumberOfAllInPlayers()
int getNumActivePlayersNotAllIn()
int getNumToAct()
int getUnacted()
int getNumSeats()
double getStakes()
java.util.List getPlayersInPot(double amountIn)
amountIn
- the amount a player must have in the pot to be eligible to win it
PlayerInfo getPlayer(int seat)
seat
- the seat the check
PlayerInfo getPlayer(java.lang.String name)
name
- the player to check
double getBetsToCall(int seat)
seat
- the seat number to check
double getAmountToCall(int seat)
seat
- the seat number to check
double getBankRoll(int seat)
seat
- the seat number to check
double getBankRollAtRisk(int seat)
seat
- the seat number to check
java.lang.String getPlayerName(int seat)
seat
- the seat to check
int getPlayerSeat(java.lang.String name)
name
- the name of a player
boolean canRaise(int seat)
seat
- a player's seat number
boolean inGame(int seat)
seat
- a player's seat number
boolean isActive(int seat)
seat
- a player's seat number
boolean isCommitted(int seat)
seat
- the seat number to check
int getNumWinners()
boolean isGameOver()
boolean isNoLimit()
boolean isFixedLimit()
boolean isPotLimit()
int getNumRaises()
double getMinRaise()
double getRake()
boolean isSimulation()
boolean isZipMode()
boolean isReverseBlinds()
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


sort
OS/161 Reference Manual
Name
sort - large quicksort-based VM test
Synopsis
/testbin/sort
Description
sort creates an array of 147456 random integers and then sorts it
using quicksort. This will hopefully help show up bugs in the VM
system.
Requirements
sort uses the following system calls:
sort should run correctly to completion once assignment 3 is complete.


Enjoy the tastiest pizza in town. We always ensure that our pizza is fresh and mouth-watering!
Order HereEnjoy the tastiest pizza in town. We always ensure that our pizza is fresh and mouth-watering!
Choose the size of the pizza you want whether small, medium or large.
Choose the type of crust you would like.
Pick from our fresh toppings.
Specify whether the order is for pickup or delivery then place order.
Have any inquiries, complaints or suggestions? Contact us through:


Featured Album
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Check out my newest Music Albums. You can easily purchase our music albums or gifts for your friends via iTunes or Google Play.
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Hints for SRM 610, D2, 250-pointer (DivideByZero)
James S. Plank
Wed Feb 26 13:55:13 EST 2014
Problem Statement.
This one tripped up many of the Topcoder contestants -- in fact, only 68 percent of the
contenstants got it. See if you can do better!
The constraints of this problem state that numbers only holds numbers between 1 and 100.
Since (a div b) is always going to be less than a, John's paper will only
hold numbers between 1 and 100. That puts some constraints on input that we can leverage.
In particular, an n2 solution is going to be plenty fast enough, because the
maximum n is 100.
Here's a solution that comes to mind -- keep two collections of numbers: those that you
have processed (call it P -- it will be a vector),
and those that you have not processed (call it N -- also a vector).
You can also keep a table T
of numbers on John's paper. T should be a vector with 101
elements, and T[i] is set to 1 if i is a number on John's paper. It is set
to zero otherwise.
Do the following:
- Set N to be numbers.
- Set T to be a vector of 101 elements, each of which is zero.
- Now, set T[i] to one for each element i in N
- Set P to be empty.
- Now, for each element n in N, do the following:
- For each element p in P, find k = (n div p), or
k = (p div n), whichever is non-zero.
- Check T to see if k is there, and if it is there, ignore k.
- Otherwise, put k into T, and also add k to N.
- When you're done with each element in P, add n to P.
- Finally, return the size of P.
Let's illustrate this with Example 0, where numbers is { 9, 2 }. Below is the
initial state of the three vectors (we only show the first 12 elements of T,
because all of the higher ones will always be zero):
Now, run through N with an integer i. When i = 0, n = 9.
We want to run through P, but P is empty, so we're done with n -- we
add it to P:
Next, i = 1 and n = 2. We run through P and there is one element: p = 9. Since p is bigger than n, we set k = (p div n) = 4. We check to see
if T[4] = 0, which it does, so we set T[4] = 1 and add 4 to N:
At this point, we're done with P, so we add n to P:
Finally, we continue with i = 2 and n = 4. We run through P: When
p = 9, k = 2, and since T[2] equals 1, we ignore k. Similarly, when
p = 2, k also equals 2, and since T[2] equals 1, we ignore k again.
At this point, we're done with P, so we add n to P:
Now, we're done with N, so we return the size of P, which is three. As you can
see, when we're done, P and N will be identical, so we could simply return
the size of N.
I want you to think about why T is the way it is, and why it isn't, say, a vector
containing the numbers on the paper. The reason is speed -- by having T be a vector
of 101 elements, you can look up a number and see whether it is in T in one operation.
That's much faster, than, say, looping through a vector to see if a number is there.


Make a block diagram in Figure 4.
1. Connect inputs of oscilloscope to the output of the Signal Generator and the other to the output of LPF. Set Cut-off frequency of LPF to 10 kHz and frequency of signal generator to 5 kHz. When signal is a cosine waveform, output waveform of LPF is
2. Increase signal frequency slowly to 8-10-15… kHz. What starts to happen when frequency is around 10 kHz and you still increase it?
3. At cut-off frequency signal level is decreased by 3 dB that is 20*log10 (Vout /Vin ) dB = -3 dB. What is Vout /Vin at cut-off frequency approximately?
4. Change signal generator to rectangular waveform at frequency of 5 kHz. Use oscilloscope to compare signal shape at the input and output of LPF. What do you see?
5. Use Spectrum analyser to compare spectrum of rectangular waveform at the input and output of LPF. What do you see?
6. When high frequency components are attenuated, the signal in time domain:
7. When you increase frequency of the rectangular waveform to 20 kHz
8. This happens because
9. Set signal generator to Cosine waveform and cut-off frequency of LPF to 20 kHz. Compare signal amplitude at output of LPF at frequencies 1 kHz and 20 kHz. At 20 kHz amplitude is compared to 1 kHz amplitude approximately
10. This corresponds to that signal level is reduced by
11. Compare input and output amplitude of LPF at 20 kHz. At output it is reduced approximately by factor of
12. Increase frequency to 40 kHz. Now output compared to input is reduced approximately by factor of
13. This correspond to that signal level is reduced by
14. Increase frequency to 80 kHz. Now output compared to input is reduced approximately by factor of
15. This correspond to that signal level is reduced by
16. When frequency is doubled above cut-off frequency the signal level is reduced by approximately
When you have answered all the questions you can submit your answers.
Test passed. Go to Exercise 3: White Noise in Time and Frequency Domain
Test failed. Consider again answers that are not correct


Two datasets are provided in this website. One for an off-shore location and another one for an onshore location.
The plot below displays the wind speed of each location on 10 meters above ground level.
You can transform this data to a wind speed at any given height and roughness length:
| Height | Roughness length |
|---|---|


BENZEDREX 09-19-2014- propylhexedrine inhalant
BF ASCHER AND CO INC
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
Active ingredient................. Purpose
Propylhexedrine 250 mg......Nasal decongestant
Uses
For the temporarily relief of nasal congestion due to a cold, hay fever, or other upper respiratory allergies (allergic rhinitis).
Uses
Temporarily relieves nasal congestion due to a cold, hay fever, or other upper respiratory allergies (allergic rhinitis).
Warnings
- Do not exceed recommended dosage.
- This product may cause temporary discomfort such as burning, stinging, sneezing, or an increase in nasal discharge.
- The use of this container by more than one person may spread infection.
- Use only as directed.
- Frequent or prolonged use may cause nasal congestion to recur or worsen.
- Ill effects may result if taken internally
Do not use this product for more than three days.
Stop use and consult a doctor if symptoms persist.
If pregnant or breast-feeding, ask a health professional before use.
Keep this and all drugs out of reach of children. In case of overdose or ingestion of contents, get medical help or contact a poison control center immediately.
Directions
- adults and children 6 to 12 years of age (with adult supervision): two inhalations in each nostril not more than every two hours.
- children under 6 years of age: consult a doctor
Directions
- adults and children 6 to 12 years of age (with adult supervision): two inhalations in each nostril not more than every two hours.
- children under 6 years of age: consult a doctor
Other information
- store at 59°-86° F (15°-30° C)
- keep inhaler tightly closed
- mfd. in USA for B.F. Ascher & Co., Inc.
- this inhaler is effective for a minimum of 3 months after first use
Inactive ingredients
lavender oil, menthol
Questions?
Call 1-800-324-1880, 7:30am - 4:00pm Central, Mon. - Fri., or visit us at
www.bfascher.com


Gateway
BOT
06-Jun-19 02:11 PM
[telegram] <Ggokhangark> According to me %15 retrecament is quite enough in current market conditions. I am waiting for big btc correction too. Maybe to 6900 usd. Then, kmd can go to 1750-18 again.
However kmd chart is looking very nice now. Lets see what will happen next week. (re @xarux: correction is inevitable! paired with the dollar - at least! Although the volumes there are not very large! And paired with Bitcoin, it will be interesting to see - maybe when Bitcoin starts a large-scale correction, the komodo team will already solve the issues and we will get out of the bottom zone!)
(edited)
[telegram] <xarux> Paired with the dollar for 6 months growth! And according to the technical analysis, everything is fine - but the negative news influences unpredictably because of the manipulators! (re @Ggokhangark: According to me %15 retrecament is quite enough in current market conditions. I am waiting for big btc correction too. Maybe to 6900 usd. Then, kmd can go to 1750-18 again.
However kmd chart is looking very nice now. Lets see what will happen next week.)
[telegram] <xarux> This means that it is not only a bitcoin transfusion in komodo but also real dollars with bittrex for example - it means that the value is growing for real!
[telegram] <xarux> and you did not think about the mass sale of komodo when they begin to return the money back - people will be afraid of repeating this bad story and will sell if not all that most of their coins! (re @Ggokhangark: According to me %15 retrecament is quite enough in current market conditions. I am waiting for big btc correction too. Maybe to 6900 usd. Then, kmd can go to 1750-18 again.
However kmd chart is looking very nice now. Lets see what will happen next week.)
[telegram] <xarux> although MTGOX people are waiting for a return much more - so we have plenty of time too
[telegram] <ethanwilliamg> KMD was supposed to have breakthrough tech but instead created a vulnerability even for people who were in control of their SEED PHRASE. Doesn’t say much about the tech when people in control of their private keys get hacked. (re @xarux: and you did not think about the mass sale of komodo when they begin to return the money back - people will be afraid of repeating this bad story and will sell if not all that most of their coins!)
[telegram] <Ggokhangark> So you think that people will give up Komodo because of this issue? I do not think so. I am believing in this team. I can not see the future but make some guess about it. According to me Komodo’s future is very bright.
Btw, did you sell of your komodos? Or, you are waiting for back from the team? (re @xarux: and you did not think about the mass sale of komodo when they begin to return the money back - people will be afraid of repeating this bad story and will sell if not all that most of their coins!)
[telegram] <xarux> I wonder if 5% will be rewarded for that period while our coins are kept in the developers' wallet - who is thinking about this?
[telegram] <Seko1900> Attention! Scam Alert!
Please be careful
There will be more fake profiles reported who want to use yesterday's problem sustainably.
Should an admin write to you, turn to real admins about this channel.
[telegram] <xarux> Komodo technology is really cool! But wallets due attention and. Audit before the release is not given! Or the vulnerability of the wallet was too tricky and inconspicuous - this is normal! The infrastructure around Komodo should be getting stronger! (re @ethanwilliamg: KMD was supposed to have breakthrough tech but instead created a vulnerability even for people who were in control of their SEED PHRASE. Doesn’t say much about the tech when people in control of their private keys get hacked.)
Backdoor discovered in Agama cryptocurrency wallet. Unconventional tactic saves users from getting robbed.
Funds worth an estimated $13 million were successfully shielded from attackers after Komodo reacted to a security vulnerability.
https://t.co/n7Z3i2AkkR we are starting to see some positive media coverage regarding the recent incident. #KMD #DEX #BTC #ETH #Komodo
[telegram] <xarux> Sold only what was on the stock exchange for fear of panic sales! And the rest of the means - I am a staunch HODLMAN))) I believe in the team and the project! Just not lucky - before the release of the important such an event! I talked to jl777 - he says that this hacker planned 3 months ago and was preparing for this! Accidents do not happen in the world of cryptocurrencies - all this is part of the manipulation and influence on the crowd! (re @Ggokhangark: So you think that people will give up Komodo because of this issue? I do not think so. I am believing in this team. I can not see the future but make some guess about it. According to me Komodo’s future is very bright.
Btw, did you sell of your komodos? Or, you are waiting for back from the team?)
[telegram] <henkyyyy> Only you are. (re @xarux: I wonder if 5% will be rewarded for that period while our coins are kept in the developers' wallet - who is thinking about this?)
[telegram] <xarux> It is necessary to change the infrastructure and abandon vulnerable libraries and servers by developing a fundamentally new method of storing funds with mandatory independent and deep security audits before release!
[telegram] <kracken> You guys get hacked and kmd price keeps moving up!
[telegram] <Acura360> @WhaleBotAlerts
[telegram] <Acura360> Follow us on Twitter
[telegram] <ionstar> The KMD price isn't reacting to this, which is imho a good thing.
[telegram] <xarux> The market has not yet responded! But what will start when funds will be returned to users? Some hamsters will surely arrange a panic sale - no doubt - we have seen this more than once! (re @Acura360: )
[telegram] <xarux> for day trading is good - and on long charts a mystery ....
[telegram] <ionstar> I mean usually with any news mentioning the word "hack" in combination with a coin/asset, it reacts strongly... downwards. So i think it not going down now conveys trust.
[telegram] <ionstar> As long as Trump doesnt twitter about it, we're all good
[telegram] <Jesse> My wallet stayed the same using a wallet explorer
[telegram] <xarux> maybe we are dealing with a late reaction? After all, on the stock exchanges, coins are intact - that’s where the whales need to move! And when the team starts returning the funds back - then it will be interesting to watch the price! (re @ionstar: I mean usually with any news mentioning the word "hack" in combination with a coin/asset, it reacts strongly... downwards. So i think it not going down now conveys trust.)
[telegram] <ionstar> I don't think so. The team being so proactive in mitigating this attack helps a lot, and will probably provide more trust in the KMD ecosystem. Ofcourse there will be some people exiting, but I doubt it will have any large reaction. (re @xarux: maybe we are dealing with a late reaction? After all, on the stock exchanges, coins are intact - that’s where the whales need to move! And when the team starts returning the funds back - then it will be interesting to watch the price!)
[telegram] <ionstar> That's the guy who caused my regular stock portfolio to tank in just 1 month... (re @xarux: )
[telegram] <Makrura> Was there a hack? If so, did ppl lose KMD?
[telegram] <ionstar> Read the pinned message. (re @Makrura: Was there a hack? If so, did ppl lose KMD?)
Funds worth an estimated $13 million were successfully shielded from attackers after Komodo reacted to a security vulnerability.
[telegram] <Makrura> Ooo ty
[telegram] <ionstar> I do hope the regular (clean) agama will return at some point though. This Verus version is having some problems on my windows system.


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{% extends "joinJob.html" %} {% load static %} {% block head_title %}{{ block.super }} :: Join us :: Postdoctoral Fellow, Scientist, or graduate student in human whole-cell modeling{% endblock %} {% block page_title %}Postdoctoral Fellow, Scientist, or graduate student in human whole-cell modeling{% endblock %} {% block page_pdf %}{% endblock %} {% block job_details %}
The scientist will help develop the first whole-cell model of a human embryonic stem cell and use the model to gain insights into pluripotency maintenance among other fundamental cell behaviors. This will include aggregating and organizing experimental data to build models, designing models, calibrating models, validating models, analyzing simulation results, and using models to generate new hypotheses. The scientist will also have opportunities to contribute to the development of new whole-cell modeling methods and software tools.
Whole-cell modeling is highly interdisciplinary. Consequently, we are looking for teammates with a broad range of relevant experience for cell modeling.


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I do not use drugs very often, but I have always been fascinated by hallucinogens. So when the opportunity to try some shrooms came up, I decided that I wanted to do it. I was excited about it for the whole week before. The night of, my friends and I bought the shrooms and returned to one of my friends houses after buying cigarettes. We ate the shrooms (an eighth each) at eleven thirty at night, chasing them with beer. I also took a thousand milligrams of vitamin c, but my friends did not. Three of us had never tried shrooms before, and one of us had done them numerous times. My friend's girlfriend did not take any.
I began to feel a bit strange after twenty minutes. I began to act a bit randomly and impulsively. I went outside and two of my friends followed. They were talking to each other and I wandered into the front yard to look a the trees. The sun was setting, and they looked a bit more real than trees usually do. I walked closer to the tree and I saw faces in the bark. They didn't move, but wherever I looked it was apparent that the tree was staring back at me. I said hello before I realized that the tree obviously was not happy with my being there, so I scurried back inside. By this time I was shivering rather violently, so I sat down on the couch to try to warm up. I had an intense body high; it felt like electricty was shooting through my legs and up my chest. I was very tense.
The strangest thing that happened all night was when two of my friends needed to get their cigarettes from my other friend and his girlfriend's room. They sent me to get them as they followed behind. I yelled at the door (though I thought that I was whispering) that they needed their cigarettes and they were nagging me to get them. My friend and his girl opened the door, and I must have looked pretty fucked up, because the girl started to usher me into the hall while offering comforting remarks. They asked me where the other two were, and I realized that I had no idea where they were. They had disappeared. I felt a sense of acute shock and fear, and I felt horribly alone. Everything was blue, and when the shock came I heard a loud noise, sort of like a gong, but more ominous and terrifying.
After wandering around the house for a bit in a sort of confused, paranoid stupor, I decided that I had to listen to some music. My friends parents were upstairs, so I couldn't listen to anything loud, and one of my friends was making out with his girlfriend in their room, where the stereo was. I played guitar to make up for it, but I was still shaky, and it was extremely difficult. Eventually it became too much, as the sounds coming from the guitar were very surreal, and every time I knocked the un-trimmed strings on the top of the guitar I could hear the scratchy echo all around me.
Laying on the couch I began to peak. For about a half of an hour I lay there writhing, thinking irrational, nonsensical thoughts. It was unlike anything I had ever experienced before. I felt as if I was going to explode at any moment, and it was very important that I held it in.
After an eternity of anxiously convulsing on the couch I went and interrupted my friend in his room. They were done doing whatever they had been doing, and so I sat down and began to write as I ate strawberries. This is what I wrote while I listened to clair de lune.
There are so many strawberries. So many to choose from, you see, so many. It is not a question of their colour, or of their breadth, but they possess a sort of coastal spirit which is impenetrable by me as of yet. I eat them still, because they are tasty.
 Terrible that I am unable to express myself fully. I am gaining more control of myself. This is not really a full hallucinogenic experience, but instead it is a surreptitious and surreal twisted change in the general ambience of the room. I am making sure that I do not speak in movie cliches. I see nothing, except the occasional shifty shadow creeping behind my back. I feel nothing (ah, but that is a lie). I speak in very flowery and exaggerated terms because they are appropriate to who I am.
The girl named () is beautiful. She's very pink and yellow and orange and not at all any of those rotten dark colors. She glows and she is fairly benevolent. By this I mean she is like a fairy. Sort of.  There. I let it spill.
I pee a lot. Everybody pees a lot, but not as much as me. I am like the old man. Kate is sulking right now, staring ahead at her closed-minded gloom. She is very sure that she is right about her dark surroundings, and it is sad. I will build a wall, because otherwise her gloom will pervade my spirit.  I wish I could play the piano. They don't understand! (Cody and Brandon). I have to include footnotes so that I know what I mean.
I am insane. Clair de Lune is wondrous. I am glad that the most intense phase of the trip has passed. I am a little bit more in control. The anxiety running up my legs has cooled down. Swallowed some of its former drops of beady sweat, you see. Maybe you will remember the visual, Joe. Everything smells like strawberries.  None of this is real. But sober life is just as beautiful, if you know where to look. I get this feeling when I listen to Clair de Lune in real life, too. Dreams are nice. When you read this tomorrow morning, you will say 'Jesus Christ.  What a loony.' I can predict that you will be embarrassed that you wrote any of this.'
After writing that I was fairly calm and in control, but still tripping a fair amount. This was about an hour and a half into the trip. My vision had basically returned to normal. While I was peaking I occasionally saw double and had trouble maintaing focus, because as I focused on things they shifted and changed colors.
As the trip winded down I asked one of my friends if he wanted to go smoke some weed, because I heard that prolonged the trip. Plus, I was still extremely tense. We walked out to the truck in the driveway and both took a few hits each. Everything instantly mellowed out. It was as if a soft filter had been thrown between the harsh unreality of the mushrooms and my now tender psyche. I was pretty stoned, as I rarely smoke pot, and I couldn't stop laughing.  We're in the blueberry room [my friend's house is a bed and breakfast] but we're eating strawberries!' It wasn't really that funny.
For the next few hours I mostly just tried to go to sleep as my two friends watched Go.  Eventually I fell asleep, five hours after ingesting the shrooms. I awoke at eleven thirty the next morning feeling pretty good, although my thoughts were a bit slow.
In retrospect I am very glad that I tried shrooms, as it was a sensation totally unlike any I had ever had before. For five hours I dwelt in a world that made no sense and was subject to the whims of my subconscious and its reactions to the psilocybin. If you are interested in trying hallucinogens, give mushrooms a try. At the very least, it's incredibly interesting.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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This is a simulation of a variant of the Izhikevich neuron. Feel free to use it for educational purposes.
Instructions: Press the yellow square to turn DC current on/off. Press the green or red circle to simulate incoming excitatory and inhibitory spikes using conductance based dynamics. The behaviour of the Izhikevich neuron is determined by four parameters: a, b, c, and d. The buttons in the upper left corner hold seven different sets of these parameters. We have added simple NMDA inspired dynamics to the model. NMDA conductance (blue curve) is increased by the 'NMDA weight' value for every spike of the neuron. Note that this conductance term competes with the adaptation variable and can produce oscillating behaviour from a single input spike.
Created by: Hafsteinn Einarsson


“Machine learning is essentially a form of applied statistics with increased emphasis on the use of computers to statistically estimate complicated functions and a decreased emphasis on proving confidence intervals around these functions”
– Ian Goodfellow, et al60
If we discuss Neural Networks (NN), we should first consider the system we hope to emulate. Let us start with a simple count of neuronal cells in various organisms along the earth’s phylogenetic tree. We might get a better idea of the type of “computing power” these living creatures possess. See table 1.
| Organism | Common Name | Approximate Number of Neurons |
|---|---|---|
| C. elegans | roundworm | 302 |
| Chrysaora fuscescens | jellyfish | 5,600 |
| Apis linnaeus | honey bee | 960,000 |
| Mus musculus | mouse | 71,000,000 |
| Felis silvestris | cat | 760,000,000 |
| Canis lupus familiaris | dog | 2,300,000,000 |
| Homo sapien sapien | humans | 100,000,000,000 |
This table portrays a high-level overview of the computing power of neuronal clusters and brains produced throughout evolution. However, there is one missing number worth noting. The table above does not describe the connectivity between neurons. The connectivity of neurons varies greatly from lower to higher organisms. For example, some simple animals, such as the roundworm, have only “four to eight separate branches,” 61 per nerve cell. While human neurons may have greater than 10,000 inter-connected synaptic junctions per neuron, thus resulting in a total of approximately 600 trillion synapses per human brain.62
Although neurons have differing morphologies, neurons in the human brain are extremely diverse. Indeed, size and shape may not be the definitive way of classifying neurons but instead by what neurotransmitters the cells secrete. “Neurotransmitters can be classified as either excitatory or inhibitory.” 63 Currently the NeuroPep database “holds 5949 non-redundant neuropeptide entries originating from 493 organisms belonging to 65 neuropeptide families.” 64
Given an order of operation via:
Dendrite(s) \(\Longrightarrow\) Cell body \(\Longrightarrow\) Fibrous Axon \(\Longrightarrow\) Synaptic Junction or Synaptic Gap \(\Longrightarrow\) Dendrite(s) … Ad infinitum.
However, nature is more subtle and intricate than to have neurons in a series, only blinking on and off, firing or not. NN are often programmed to classify dangerous road objects, as is the case of Tesla cars. The goal of a Tesla auto-piloted car is to use all available sensors to correctly classify all the conceivable circumstances on the road. On the road, a Tesla automobile uses dozens of senors which the computer needs to evaluate and weigh the values of all these sensors to formulate a ‘decision.’ The altitude of the auto, derived from the GPS, may weigh less heavily than the speed of the vehicle or Lidar estimates on how close objects are. However, our goal of safe driving can be thwarted when an artificial intelligence system decides a truck is a sign and does not apply the brakes.66
If we investigate a one neuron system, our neuron could be diagrammed in four sections.67
If we investigate one neuron for a moment, we find two separate mathematical functions are being carried out by a single nerve cell.
The first segment is a summation function. It receives the real number values from, \(x_1\) to \(x_n\), all the branches of the dendritic trees, and multiplies them by a set of weights. These \(X\) inputs are multiplied by a set of corresponding unique weights from \(w_1\) to \(w_n\). An analogy I prefer is of small or large rivers joining giving a total current. The current moves through the branches giving a total signal or current of sodium ions. Interestingly the summation in each neuron, while dealing with the vectors of inputs and weights, is carrying out the dot product of these vectors.
Initially, the NN researchers used the Heaviside-Threshold Function, as shown in figure 5.4, One Neuron System. The benefits of step functions were their simplicity and high signal to noise ratio. While the detriments were, it is a discontinuous function, therefore not differentiable and a mathematical problem.
Let us take into account the product, \(x_0 \cdot w_0\). If we assign \(x_0 = T\) and \(w_0 = -1\) this simply becomes a bias. This bias allows us the ability to shift our Activation Function and its inflection point in the positive or negative x-direction.
\[\begin{equation} \large \hat Y ~=~ X^T \cdot W - Bias ~~\equiv~~ \sum_{i=0}^n x_i w_i - T \end{equation}\]
The second function is called an Activation Function. Once the Summation Function yields a value, its result is sent to the Activation Function or Threshold Function.
\[\begin{equation} \large {Z}^{(1)} = f \left( \sum_{i=0}^n x_i w_i - T\right) = \{0, 1\} \end{equation}\]
The function displayed in figure #6.4, One Neuron Schema, is a step function. However this step function has a problem mathematically, namely it is a discontinuous and therefore not differentiable. This fact is important.
Therefore several functions may be used in place of the step function. One is the hyperbolic tangent (tanh) function, the sigmoidal function, a Hard Tanh, a reLU, and Softmax Functions. These have certain advantages, namely they simplify the hyperbolic tangent function. Not only does the Hard Tanh and reLU simplify calculations it is useful for increasing the gain near the asymptotic limits of the sigmoidal and tanh functions. The derivatives of the sigmoidal and tanh functions are very small, near 0 and 1, while the reLU and Hard Tanh slopes are one or zero.
\[\begin{equation} \large Z^{(2)} ~=~ tanh(x) = \frac{1 - e^{-{\alpha}}}{1 + e^{-{\alpha}}} ~~~:~~~ \large where ~~~ \large \alpha = \sum_{i=1}^n x_i w_i - T \end{equation}\]
\[\begin{equation} \large Z^{(3)} ~=~ sigmoid(x) ~=~ \frac{1}{1 + e^{-{\alpha}}} \end{equation}\]
\[\begin{equation} \large Z^{(4)} ~=~ Hard ~ Tanh (x) ~=~ \large \left\{ \begin{array}{rcl} 1 & x > 1 \\ x & -1 \leq x \leq 1 \\ -1 & x < -1 \end{array}\right. \end{equation}\]
Several alternative functions are useful for various reasons. The most common of which are Softmax and reLU functions.
Rectified Linear Activation Unit, (ReLU):
\[\begin{equation} \large Z^{(5)} ~=~ \large ReLU ~= \begin{cases} x \geq 0 ~~~~y = x\\ x < 0 ~~~~y = 0 \end{cases} \end{equation}\]
In the case of real neurons, the output is off or on, zero or one. However, in the case of our electronic model, it is advantageous to calculate a probability for greater interpretability.
The Softmax function may appear like the Sigmoid function from above but it differs in major ways.68
- The softmax activation function returns the probability distribution over mutually exclusive output classes.
- The calculated probabilities will be in the range of 0 to 1.
- The sum of all the probabilities is equals to 1.
Typically the Softmax Function is used in binary or multiple classification logistic regression models and in building the final output layer of NN.
\[\begin{equation} \large Z^{(6)} ~=~ Softmax(x) = \frac {e^{\alpha_i}}{\sum_{i=1}^n e^{\alpha_i}} \end{equation}\]
The benefit of these activation functions is that they are now differentiable. This fact becomes important for Back-Propagation, which is discussed later.
Building up in complexity, let us could consider our first Neural Network by using only two neurons. In two neuron systems, let us first generalize a bit more by adding that \(X\) is an array of all the inputs as is \(W_1\) and \(W_2\) is also an array of weights for each neuron. See figure #6.5.
In our two neuron network, we can now write out the mathematics for each step as it progresses in a “forward” (left to right) direction.
Step #1: To move from \(X\) to \(P_1\) \[\begin{equation} f^1( \overrightarrow{x}, \overrightarrow{w}) \equiv~~ P_1 = \left( X^T \cdot W_1 - T \right) \end{equation}\]
Step #2: \(P_1\) feeds forward to \(Y\) \[\begin{equation} f^2(P_1) ~~\equiv~ \hat Y = \left( \frac{1}{1 + e^{- \alpha}} \right) ~~:~~ where ~~~ \alpha = P_1 \end{equation}\]
Step #3: \(Y\) feeds forward to \(P_2\) \[\begin{equation} f^3(\overrightarrow{y}, \overrightarrow{w}) ~~\equiv~ P_2 = \left( Y^T \cdot W_2 - T \right) \end{equation}\]
Step #4: \(P_2\) feeds forward to \(Z\) \[\begin{equation} f^4(P_2) ~~\equiv~ \hat Z = \left( \frac{1}{1 + e^{- \large \alpha}} \right) ~~~:~~~ where ~~ \alpha = P_2 \end{equation}\]
Step #5: Our complicated function is simply a matter of chaining one result so that it may be used in the next step.
\[\begin{equation} \hat Z ~=~ f^4 \left( f^3 \left( f^2 \left( f^1 \left( X, W \right) \right) \right) \right) \end{equation}\]
In our Feed-Forward Propagation, we can now take the values from any numerical system and produce zeros, ones, or probabilities. Remember, in this set of experiments, we are using the concentrations of the 20 amino acids to provide a categorical or binary output, belongs to a) Myoglobin protein family, or b) does not.
Now that we have learned to calculate the output of our neurons using the Feed-Forward process, what if our final answer is incorrect? Can we build a feed back system to determine the weights needed to obtain our desired value of \(\hat z\)? The short answer is yes. The process for determining the weights is known as Error Back-Propagation. Error Back-Propagation, also known as Back-Propagation, is crucial to understanding and tuning a neural network.
Simply stated Back-Propagation is an optimization routine which iteratively calculates the errors that occur at each stage of a neural network. Starting from randomly seeded values for the initial weights, Back-Propagation uses the partial derivatives of the feed forward functions. The chain rule and gradient descent are also used to determine the weights (\(W_1 ~~and~~ W_2\)) which are propagated through the network to find weights used in the summation step of a neuron.69
This thumbnail sketch gives the building blocks to calculate \(W\) which can be run until we reach a value that we desire. However the first time the back-propagation is carried out all the weights are chosen randomly. If the weights were set to the same number there would be no change throughout the system.
In the two neuron system, our first step is to generate an error or performance (Perf) function to minimize. If we call \(d\) our desired value, we can minimize the square error, a common choice.70
Step #1: Performance (Perf) \[\begin{equation} \mathbf{Perf} ~~=~~ c \cdot (d - \hat z)^2 \end{equation}\]
Step #2: \[\begin{equation} \frac{d Z}{d x} ~~=~~ \frac{d \left \{ f^4 \left( f^3 \left( f^2 \left( f^1 \left( X, W \right) \right) \right) \right) \right \}}{dx} \end{equation}\]
Using the chain-rule, and figure 6.6, Two Neuron System as a guide, we can backwards to derive the formulas for error back-propagation. We find:
Step #3: Neuron 2 \(\Rightarrow\) 1 \[\begin{equation} \frac{\delta Perf}{\delta w_1} ~=~ \frac{\delta Perf}{\delta z} \cdot \frac{\delta z}{\delta P_2} \cdot \frac{\delta P_2}{\delta y} \cdot \frac{\delta y}{\delta P_1} \cdot \frac{\delta P_2}{\delta w_1} \end{equation}\]
Step #4: Performance \[\begin{equation} \frac{\delta Perf}{\delta z} ~~=~~ \frac{\delta \left\{ \frac{1}{2} \| \overrightarrow{d} - \overrightarrow{z} \|^2 \right\}} {\delta z} ~~=~~ d - z \end{equation}\]
Step #5: Substitute \(P_2=\alpha\) \[\begin{equation} \frac{\delta z}{\delta P_2} ~~=~~ \frac{\delta~ ((1 + e^{-\alpha})^{-1})}{\delta \alpha} ~~=~~ e^{-\alpha} \cdot (1 + e^{-\alpha})^{-2} \end{equation}\]
Step #6: Rearrange the right expression \[\begin{equation} \frac{ e^{-\alpha} }{ (1 + e^{-\alpha})^{-2} } ~~=~~ \frac{e^{-\alpha}}{1 + e^{-\alpha}} \cdot \frac{1}{1 + e^{-\alpha}} \end{equation}\]
Step #7: Add 1 and subtract 1 \[\begin{equation} = ~~ \frac{ (1+ e^{-\alpha}) -1 }{1 + e^{-\alpha}} \cdot \frac{1}{1 + e^{-\alpha}} \end{equation}\]
Step #8: Rearrange to find \[\begin{equation} = ~~ \left( \frac{ 1+ e^{-\alpha} }{1 + e^{-\alpha}} ~-~ \frac{ 1 }{1 + e^{-\alpha}} \right) \left( \frac{1}{1 + e^{-\alpha}} \right) ~~=~~ \left(1- \frac{1}{1 + e^{-\alpha}} \right) \left( \frac{1}{1 + e^{-\alpha}} \right) \end{equation}\]
Step #9: Therefore we find \[\begin{equation} \frac{\delta z}{\delta \alpha} ~~=~~ \frac{\delta~ ((1 + e^{-\alpha})^{-1})}{\delta \alpha} ~~=~~ \left(1- \frac{1}{1 + e^{-\alpha}} \right) \left( \frac{1}{1 + e^{-\alpha}} \right) \end{equation}\]
Nevertheless, we need one more part to ascertain the weights. As the error back-propagation is computed this process does not reveal how much the weights need to be adjusted/changed to compute the next round of weights given their current errors. For this we require one last equation or concept.
Once we compute the weights from our chain rule set of equations we must change the values in the direction proportional to the change in error. This is performed by using gradient descent.
Step #10: Learning Rate \[\begin{equation} \Delta W ~:~ W_{i+1} ~=~ W_i ~-~ \eta \cdot \frac{\delta Perf}{\delta W} \end{equation}\]
where \(\eta\) is the learning rate for the system. The key to the learning rate is that it must be sought and its range mapped for optimum efficiency. However smaller rates have the advantage of not overshooting the desired minimum/maximum. If the learning rate is too large the values of \(W\) may jump wildly and not settle into a max/min. There is a fine balance that must be considered such that the weights are not trapped in a local minimum and wildly oscillate unable to converge.
The last step of error back-propagation is simply setting up the derivatives mechanically and is not shown for brevity.
# Load Libraries
Libraries <- c("dplyr", "readr", "caret", "MASS", "nnet", "purrr")
for (p in Libraries) {
library(p, character.only = TRUE)
}
# Load Data
c_m_TRANSFORMED <- read_csv("./00-data/02-aac_dpc_values/c_m_TRANSFORMED.csv",
col_types = cols(Class = col_factor(levels = c("0","1")),
PID = col_skip(),
TotalAA = col_skip()))
# Create Training Data
set.seed(1000)
# Stratified sampling
TrainingDataIndex <- createDataPartition(c_m_TRANSFORMED$Class, p = 0.8, list = FALSE)
# Create Training Data
trainingData <- c_m_TRANSFORMED[ TrainingDataIndex, ]
testData <- c_m_TRANSFORMED[-TrainingDataIndex, ]
TrainingParameters <- trainControl(method = "repeatedcv",
number = 10,
repeats = 5,
savePredictions = "final") # Saves predictions
TuneSizeDecay <- expand.grid(size = c(16, 18, 20),
decay = c(1, 0.1, 0.01))
NNPredictions <- predict(NNModel, testData)
# Create confusion matrix
cmNN <-confusionMatrix(NNPredictions, testData$Class)
print(cmNN)
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 239 9
## 1 4 215
##
## Accuracy : 0.9722
## 95% CI : (0.9529, 0.9851)
## No Information Rate : 0.5203
## P-Value [Acc > NIR] : <2e-16
##
## Kappa : 0.9442
##
## Mcnemar's Test P-Value : 0.2673
##
## Sensitivity : 0.9835
## Specificity : 0.9598
## Pos Pred Value : 0.9637
## Neg Pred Value : 0.9817
## Prevalence : 0.5203
## Detection Rate : 0.5118
## Detection Prevalence : 0.5310
## Balanced Accuracy : 0.9717
##
## 'Positive' Class : 0
##
## Neural Network
##
## 1873 samples
## 20 predictor
## 2 classes: '0', '1'
##
## Pre-processing: scaled (20), centered (20)
## Resampling: Cross-Validated (10 fold, repeated 5 times)
## Summary of sample sizes: 1685, 1686, 1686, 1686, 1686, 1685, ...
## Resampling results across tuning parameters:
##
## size decay Accuracy Kappa
## 16 0.01 0.9675458 0.9349866
## 16 0.10 0.9724570 0.9448152
## 16 1.00 0.9609233 0.9216202
## 18 0.01 0.9703226 0.9405495
## 18 0.10 0.9708545 0.9416022
## 18 1.00 0.9618830 0.9235428
## 20 0.01 0.9703157 0.9405366
## 20 0.10 0.9716003 0.9430995
## 20 1.00 0.9612419 0.9222614
##
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were size = 16 and decay = 0.1.
fp_fn_NNModel <- NNModel %>% pluck("pred") %>% dplyr::filter(obs != pred)
# Write/save .csv
write.table(fp_fn_NNModel,
file = "./00-data/03-ml_results/fp_fn_NN.csv",
row.names = FALSE,
na = "",
col.names = TRUE,
sep = ",")
nrow(fp_fn_NNModel) ## NOTE: NOT UNIQUE NOR SORTED
## [1] 258
keep <- "rowIndex"
fp_fn_NN <- read_csv("./00-data/03-ml_results/fp_fn_NN.csv")
NN_fp_fn_nums <- sort(unique(unlist(fp_fn_NN[, keep], use.names = FALSE)))
length(NN_fp_fn_nums)
## [1] 81
## [1] 4 6 15 16 46 57 94 97 100 114 115 116 130 136 149 150 170 179
## [19] 182 183 185 249 445 449 453 503 518 522 526 530 531 532 534 546 547 566
## [37] 570 580 592 655 910<PHONE_NUMBER> 1034 1035 1093 1094 1100 1101 1117 1121 1130 1190
## [55] 1219 1226 1233 1264 1300 1471 1510 1522 1575 1576 1579 1585 1587 1594 1608 1618 1621 1693
## [73] 1697 1734 1771 1773 1780 1789 1831 1833 1873
The Neural Network set included a total of 79 unique observations containing both FP and FN.
Accuracy was the primary criteria used to select the optimal model. There were 20 models tested. The neural network was configured with 20 inputs (one for each amino acid), one hidden layer and one output. The hidden layer was tested with either 10, 12, 14, 16, 18, 20 neurons and a array of different decays (1, 0.1, 0.01, 0.001). The caret software has a tuning parameter named tuneGrid
that allows users to expand
a set of arrays to a matrix of combinations to be tested. Therefore 20 models were tested with the training data set and the best values were size = 20 and decay = 0.1.
At this time, the author is not aware of any heuristic that gives the proper number of hidden layers and the proper number of neurons in each layer therefore one must search the experimental space for an optimized configuration. If a more thorough search of the experiemntal space was carried out using two or three hidden layers would be investigated. The poor showing of the Neural Network suggests that the data may have some additional decision boundary that is not yet represented by only 20 neurons.


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The HTML <select> element represents a control that presents a menu of options. MDL does not provide it's own component for the <select> element.
Select element
Select element with floating label
Disabled Select element
TODO
TODO
TODO
The Select component is based on the following sources


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Gangster killed over land dispute: Police
Mahesh also alleged that a gangster named Leelu Dagar was behind the murder. Police said they are yet to find evidence to verify the allegations.
A day after gangster Ashok Rathi (44) was allegedly shot dead by three aides at his home in Sohna’s Alipur, police said the accused fired 11 bullets at him. The post-mortem showed he received injuries to his abdomen, limbs, ear and chest, they added.
Police suspect the accused, Narendra, Rohit Dagar and Salim, killed Rathi over a land dispute. Rathi’s brother Mahesh claimed, “A week ago, Rohit bought property and wanted money from my brother but Ashok wasn’t interested in investing in it. The three would often meet him about the property.”
Mahesh also alleged that a gangster named Leelu Dagar was behind the murder. Police said they are yet to find evidence to verify the allegations.


@Retention(value=RUNTIME) @Target(value={METHOD,FIELD}) @Documented public @interface ProvidesProperty
PropertyDefinition
based on the
annotated getter method.
@ProvidesProperty
method annotations can be used to automatically generate a
PropertySet
's using a ProvidesPropertyScanner
. The resulting
PropertySet
can then be provided to Grid.withPropertySet()
for example.
This annotation indicates that a read-only Vaadin PropertyDefinition
having the type
equal to the method's return type is accessible by reading that method. Annotated methods must have zero parameters.
For example:
// Container backing object class public class User { public static final String USERNAME_PROPERTY = "username"; public static final String REAL_NAME_PROPERTY = "realName"; private String username; private String realName; public String getUsername() { return this.username; } public void setUsername(String username) { this.username = username; } @ProvidesProperty // property name "realName" is implied public String getRealName() { return this.realName; } public void setRealName(String realName) { this.realName = realName; } @ProvidesProperty(USERNAME_PROPERTY) // display usernames in fixed-width font private Label usernameProperty() { return new Label("<code>" + StringUtil.escapeHtml(this.username) + "</code>", ContentMode.HTML); } } // Build Grid showing users with auto-generated properties Grid<User> grid = Grid.withPropertySet(new ProvidesPropertyScanner(User.class).getPropertySet()); grid.setVisibleColumns(User.USERNAME_PROPERTY, User.REAL_NAME_PROPERTY); ...
Some details regarding @ProvidesProperty
annotations:
@ProvidesProperty
annotations on other methods are ignored@ProvidesProperty
annotations declared in super-types (including interfaces) are supported@ProvidesProperty
, then the overridding method's annotation takes precedence.
@ProvidesProperty
for the same
property name, then the declaration in the class which is a sub-type of the other
wins (if the two classes are equal or not comparable, an exception is thrown). This allows subclasses
to "override" which method supplies a given property.ProvidesPropertyScanner
public abstract String value
If this is left unset (empty string), then the bean property name of the annotated bean property "getter" method is used.
public abstract String caption
If this is left unset (empty string), then the name of the property is used.
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This is how you will appear in search results. {% if profile.profile_completion < 100 %} Completing your profile makes it easier for colleagues to find you. {% endif %}


On Negation (impredicative definition)
Consider the following definitions :
Definition my_False : Prop := forall P:Prop, P. Definition my_not (P:Prop) : Prop := P -> my_False.
Prove the same theorems as in
that exercise
, but using
my_False
and
my_not
instead of
False
and
not
.
Solution
See
this file