I'm a machine learning + data engineering consultant. My professional experiences range across data engineering, natural language processing, and artificial intelligence. My weapon of choice is Python.
Built test cases for testing web vulnerability scanner using C# .NET
Supported internal procurement web application with Java
2003-07
Pennsylvania State University, University Park
BSc, Information Science and Techology, Design and Development
Decisive
Predictive analytics for social marketing content
2014-2015
Data Engineer
I was part of a fantastic startup, working directly with founders David Dundas and Ryan Witt. During my time there, we went through a product pivot, from a self-serve mobile advertising plateform to a social content analytics product. These presented different challenges and allowed me to grow both in breadth and depth.
For the advertising platform, I developed a data pipeline to consume more than 500M events daily. It processed in nearly realtime, with less 1 hour from ingestion to the RESTful API. The endpoints were further designed for efficient reporting and data analysis.
During the pivot to social analytics, I delivered an analytics dashboard MVP within two weeks. The MVP includes an extract-transform-load pipeline for numerous social platforms. The collected social contents were profiled into various parameters for the data science team to model.
Soshio
Social analytics for Chinese language and market
2012-2013
Founder, CTO
Bootstrapped SaaS Startup
For my previous startup, I've built a social analytics product with a bespoke NLP engine to analyze the Chinese social media. It collected the social conversations surround a keyword and determined the prevailing emotions.
I developed the core text mining engine to extract sentiment and emotions from text. Working with a language very different from English presented challenges not covered by the popular tools. I was able to explore new techniques for this problem.
The task was further complicated by the data size which was required to ingest. At nearly 1M weekly, there are a lot of data to acquire and process through the language engine. I achieved this by leveraging crawler queues and analytics workers.
To effectively communicate the results, I used visualization tools, from basic trend plot to more complex heat maps. Users are able to drill into the analytics to compare results across social keywords. With responsive design, users can also access it on devices of all sizes.


{{ partial "header.html" . }} {{ partial "navigation.html" . }}
Hosting web apps and data is tricky and can be quite hard to setup the right infrastructure for your solution. So, we've decided to take care of it for you, and summarise the entire process into just 1 click.


| 13:00–13:30 | Session 1: Regular Papers Q&A (Chair: Yuji Matsumoto) |
Generic Oracles for Structured Prediction
Proof Net Structure for Neural Lambek Categorial Parsing
Findings: Neural Combinatory Constituency Parsing (Pre-Recorded Presentation)
Findings: Rule Augmented Unsupervised Constituency Parsing (Pre-Recorded Presentation)
| 13:30–14:05 | Session 2: Regular Papers Q&A (Chair: Stephan Oepen) |
The Reading Machine: A Versatile Framework for Studying Incremental Parsing Strategies
Semi-Automatic Construction of Text-to-SQL Data for Domain Transfer
Levi Graph AMR Parser using Heterogeneous Attention
Translate, then Parse! A Strong Baseline for Cross-Lingual AMR Parsing
Great Service! Fine-grained Parsing of Implicit Arguments
| 14:05–14:35 | Session 3: Regular Papers Q&A (Chair: Reut Tsarfaty) |
A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
Multilingual Dependency Parsing for Low-Resource African Languages: Case Studies on Bambara, Wolof, and Yoruba
Findings: Climbing the Tower of Treebanks: Improving Low-Resource Dependency Parsing via Hierarchical Source Selection
Findings: Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD (Pre-Recorded Presentation)
| 14:35–15:05 | Session 4: Regular Papers Q&A (Chair: Djamé Seddah) |
Bidirectional Domain Adaptation Using Weighted Multi-Task Learning
Strength in Numbers: Averaging and Clustering Effects in Mixture of Experts for Graph-Based Dependency Parsing
A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
Applying Occam’s Razor to Transformer-Based Dependency Parsing: What Works, What Doesn’t, and What is Really Necessary
| 15:05–15:15 | Break |
| 15:15–16:00 | Session 5: Invited Talk (Chair: Kenji Sagae) |
Incorporating Compositionality and Morphology into End-to-End Models
| 16:00–16:45 | Session 6: Shared Task Q&A (Chairs: Gosse Bouma, Djamé Seddah, Dan Zeman) |
From Raw Text to Enhanced Universal Dependencies: The Parsing Shared Task at IWPT 2021
COMBO: A New Module for EUD Parsing
Splitting EUD Graphs into Trees: A Quick and Clatty Approach
Graph Rewriting for Enhanced Universal Dependencies
Biaffine Dependency and Semantic Graph Parsing for EnhancedUniversal Dependencies
Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings
RobertNLP at the IWPT 2021 Shared Task: Simple Enhanced UD Parsing for 17 Languages
The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task
TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage Generic- to Individual-Language Finetuning
End-to-end mBERT based Seq2seq Enhanced Dependency Parser with Linguistic Typology knowledge
| 16:45–17:00 | Session 7: SIGPARSE Business Meeting (Chairs: Kenji Sagae, Stephan Oepen) |


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{% set pageTitle = "Your details have been submitted" %} {% set mainClasses = "nhsuk-main-wrapper--s" %} {% set version = "v1" %} {% extends "layout.html" %} {% block content %}
We will now check the details you have sent.
If we can confirm you’re on the shielded patients list we will send you a shielding note.
We will send your note by email to the address you used when you registered with your GP surgery. If we do not have an email address for you, we will send you a letter in the post.
Once you have your shielding note you can give it to your employer if they ask to see it.
If you have not received your shielding note by email after 1 day check your junk mail folder.
If there’s no email in your junk mail folder, wait for a letter in the post – this should take 3 days.
If you have not received a letter after 3 days speak to your GP surgery.
You can speak to the GP surgery receptionist to explain the situation – they will decide if you need to speak to a GP.
Check the details your GP surgery has on their system for you are up to date.
If you need medical advice you can also get it by signing up to the NHS App.
Owned and run by the NHS, you can use the NHS App to:
Read more about how to sign up for the NHS App.


Australia
Netherlands
Portugal
French Polynesia
Egypt
Home
Dream Places
Welcome to the Citrus Circus travel site! Let us help you plan your next adventure to one of our featured destinations!
Netherlands
Australia
Portugal
French Polynesia
Egypt


Clear (TqBTorrentsFilter)
Create (TqBTorrentsFilter)
Destroy (TqBTorrentsFilter)
withCategory (TqBTorrentsFilter)
withFilter (TqBTorrentsFilter)
withLimit (TqBTorrentsFilter)
withOffset (TqBTorrentsFilter)
withOutCategory (TqBTorrentsFilter)
withOutFilter (TqBTorrentsFilter)
withOutLimit (TqBTorrentsFilter)
withOutOffset (TqBTorrentsFilter)
withOutReverse (TqBTorrentsFilter)
withOutSort (TqBTorrentsFilter)
withReverse (TqBTorrentsFilter)
withSort (TqBTorrentsFilter)


--- title: Gerbs date: 2003-04-06T10:00:00.000Z age: Almost 18!!! gender: Bloke nickName: Noodles, Gerbs, Gerber city: Sydney and loving it country: "'Straya" religion: Jewish hobbies: cooking, reading, discovering the meaning of life starSign: Scorpio height: dunno...5"6?? eyeColour: Brown hairColour: Black thinkLotrRules: Without a doubt ---
Hey Jaza,nice site!!! This message i assume will make it through the gap in the universe to your inbox so i i just have one thing to say...spam, spam, spam ,spam


The radio stack notifies the entire system that it is about to send a packet. Other modules in the system can call back within this event to modify the packet's metadata. For example, we can setup a module in the system to make every CTP data packet send with low power listening enabled: event void SendNotifier.aboutToSend[AM_COLLECTION_DATA](uint8_t dest, message_t *msg) { call LowPowerListening.setRxSleepInterval(msg, 512); }
dest
- The destination address of the messsage


AutoDo
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Link
Project Name
Repository Address
https://github.com/User/ProjectB.git
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every day
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Hi, I think I'm the only cleveland fan here in San Francisco. But I'm about to switch, just looking for someone that will hand me that bandwagon form.

I have been teaching myself to code prior to this bootcamp so I'm hoping after 3 months I'm web development ready.


This Groestlcoin Node is running 24/7 to support the world wide Groestlcoin Network.
| Groestlcoin Node | ${address}:1331 |
| Number of Connections | ${connections} |
| Block Number | ${blocks} |
| Difficulty | ${difficulty} |
| Node Version | ${version} |
| Node Location | Germany |
| Protocol Version | ${protocolversion} |
| last update of this page | $(date) |


student id
student name
Birth date
First name
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Phone number
Father's name
Joined year


When prompted, please allow access to your location. It may take a few moments to locate you. Make sure you have location services enabled on your phone! Thanks! 😃


VLE vs Informal Learning
Oct 13, 2008
An interesting conversation on Ferl’s splendid VLE discussion list over the last couple of days sparked off by Leon Cych’s observation that institutions generally exhibit a lack of awarenes of the ad hoc and informal networked learning that’s taking place.
Leon certainly has a point. His blog post earlier today about the way mobile technology and ubiquitous networking is making it possible for individual’s to connect, create and collaborate in ways previously impossible, when applied to schools, suggests that things are indeed different now – yes, we’ve always had informal learning alongside the formal, with informal learning not always encouraged institutionally in the secondary phase, but the range of resources and the extent of the network available to the former are now orders of magnitude greater than ever before. As he says:
It’s all personalised, they have complete ownership of their devices and connectivity and they sure know how to use it!
Roger Broadie’s take is a bit different, drawing a comparison between web2 (I think understood principally in social networking terms) in schools and the enterprse, with the institution there to provide the “guided attention” that compliments the personalisation implicit in an informal appraoch, with the VLE having a role in focussing attention and stimulating the sort of use that teachers are looking for.
I think even in Leon’s more radical take, there will for a while yet, remain a role for the VLE and the school/college/university. Wonderful as informal learning, personal learning networks and the resources of the web are, let us not lose sight of the fact that educational institutions and their staff are part of the learner’s learning network, and for many the most important part. Thus the institutionally provided learning space (virtual or real), will continue to be important for the learner.
So what role is there for schools etc in a radically personalised, networked future?
- The Open Content initiatives that we’ve seen from MIT, the Open Univiersity and iTunes U is one possibility, with institutions making their courses, their lessons available digitally to any interested – scary stuff for those of us in the business of running schools if providing courses is all we do.
- Another interesting possibility from the HE model is that of the institution as the awarding or examining body – providing some sort of certification and assurance of a minimum standard, if not in terms of students learning (which I guess the exam boards do for us) then perhaps in terms of teaching.
- Another role, as my own pupils recognise, is as a place where the social networking takes place – I’m not certain, but I think the social networking, collaboration and creativity that’s at the heart of learning 2.0 are skills that are aquired or learnt, even if they’re not always taught, in schools – we bring young people together, we give them (or perhaps forece on them) shared experiences and challenges, intellectually, culturally, physically and they learn to work and learn together, as well as all the content stuff. If one takes out this (enforced) social dimension of education and just leave personal choice and voice, I doubt whether we’d see quite so much learning taking place.
- Finally, but also firstly, there is the sage on the stage and guide on the side stuff that we teachers do, and yes, I think this is a both/and situation. Coaches, mentors, tutors, whatever, the knowledge, wisdom, intuition and care that a teacher brings to their students are things which it will be difficult to replace by informal networks.
In tech terms, whilst I’m all in favour of students using the right tools for the tasks they want to do, from both sides of the wire, and would certainly see some value in a PLE as a way of pulling these together, I think there remain roles for the VLE as the place where the institution and its staff provide the content, the accreditation, the core of the learning network, the shared activities and the 1:1 nurture/challenge.
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for doing that homework assignment that should have been handed in yesterday
In Dee Street Maternity Hospital, Invercargill, New Zealand in 1967
I grew up in Invercargill and went to Waverly Park Primary School (a five-minute walk from home), Lithgow Intermediate (a 15-minute bike ride into a southerly wind) and James Hargest High School (a 10-minute walk). I did a Bachelor of Arts, majoring in English Literature at Otago University in Dunedin and graduated from Victoria University in Wellington (the final year at Otago was a lot of Old English – have you ever tried reading that stuff!).
Just out of Dunedin on a small sheep farm. We also have a few cattle (no dairy cows – I don’t want to get up early in the morning to milk them!)
Send me a plane ticket and I’ll be there, especially if it’s Italy, or Greece or somewhere else exotic and/or hot. In New Zealand I visit lots of schools thanks to New Zealand Book Council.
It’s a pen name, also called a pseudonym (which is trickier to say and impossible to spell so just use the words pen name). Ella was my great aunt who went to Otago University and studied English, just like me. I have some of her books with “Otago University 1909 – 1910) written by her on the first page. It’s very cool. West was because I wrote Thieves, my first book, when I was living at the time on the West Coast of the South Island. Lots of writers use pen names like John Le Carre and Lee Child. It makes us mysterious!
One husband, two children, one cat, two farm dogs and chickens (varying numbers).
I also work as a journalist.
Pizza, a perfectly cooked steak (medium rare), chocolate cake.
PE – I was useless at it. Don’t ever pass me the ball.
Blue
James Bond movie script writer.
When I was really young, I can’t remember what age. The first thing I ever had published (besides stuff in the newspapers I was working for) was in New Zealand School Journals when I was about 30. It was a play about the Santa’s reindeer going on strike on Christmas Eve.
Because it's fun
See above – and really?
I won the Louis Johnson New Writers’ Bursary in 2006. Thieves (2006) was a finalist in the 2007 New Zealand Post Book Awards for Children and Young Adults, and was listed as a 2007 Storylines Notable Young Adult Fiction Book. Anywhere but Here (2008) was a finalist in the SFFANZ (Science Fiction and Fantasy Association of New Zealand) Sir Julius Vogel Awards in 2009 as was Real Life (2009) the following year. Night Vision (2014) won the 2015 Young Adult section of the LIANZA Awards and was the 2015 Young Adult Children’s Choice winner in the New Zealand Book Awards for Children and Young Adults as well as a finalist for the judges awards.
I’m working on that one. If you’re a publisher contact my agent Frances Plumpton at Frances Plumpton Literary Agency and MAKE IT HAPPEN.
We’ll see!
I saw, by chance, a 60 Minutes documentary on kids with XP and started thinking – what could happen to a kid who only goes out at night . . .
No – how many murders can one girl see?
It’s all mostly made up. Except for Jim, the dog in Night Vision, he was our very first farm dog. And in Rain Fall there is a whole lot of stuff that really happened, like the penguin. But none of the people are real so if you live in Westport where the book is set don’t start thinking you are any of the characters!
I get to see them and comment. Most of the time the publisher listens.
No – not really. I can write whenever or wherever. I think it’s the journalist in me.
I don’t get writer’s block. I think it’s a myth, or an excuse.
I know, never say never, but I think it would be unlikely. I’m still figuring out how boys think – even after years of living with three of them!
The entire Children’s Library in Invercargill then I stole my older brother’s library card and started on the Adult Library (there was an age restriction on getting out adult books back then). I remember reading the entire Swallows and Amazons series which is about kids having boating adventures in England, The Lord of the Rings (which I vowed afterwards I would never read another book because I had read the best – I lasted two weeks), lots of sci-fi like DragonSong and Wizard of Earthsea, Watership Downs (which is about rabbits and not dragons) and some classics like Jane Eyre.
Again, no!
It can rain just like in Rain Fall, but not often. Once, when we lived there, it rained for six weeks non-stop. Westport also has beautiful sunny weather. We used to go to the beach lots to swim.


fontlint
A program for checking the validity of fonts
fontlint fontfile1 ...
fontlint checks a font for certain standard problems
It will notice:
-
Any glyphs with intersecting (or self-intersecting) contours.
-
Any contours drawn in the wrong orientation
-
Any glyphs with a flipped reference
-
Missing points at extrema.
For sfd fonts it will also notice:
-
Any open contours (more an issue in sfd files than in released fonts)
-
Adjacent points too far apart in a glyph
-
Unknown glyph referenced in GSUB/GPOS/MATH
For PostScript fonts it will also notice:
-
More points in a glyph than allowed by PostScript.
-
Too many hints in a glyph.
-
Invalid glyph name.
-
Missing BlueValues entry in PostScript Private dictionary
-
Odd number of elements in either the BlueValues or OtherBlues entries in
the PostScript Private dictionary.
-
Disordered elements in either the BlueValues or OtherBlues entries in the
PostScript Private dictionary.
-
Too many elements in either the BlueValues or OtherBlues entries in the
PostScript Private dictionary.
-
Elements too close in either the BlueValues or OtherBlues entries in the
PostScript Private dictionary (must be at least 2*BlueFuzz+1 apart).
-
Non-integral elements in either the BlueValues or OtherBlues entries in the
PostScript Private dictionary.
-
Alignment zone height in either the BlueValues or OtherBlues is too big for
the BlueScale in the PostScript Private dictionary.
-
Odd number of elements in either the FamilyBlues or FamilyOtherBlues entries
in the PostScript Private dictionary.
-
Disordered elements in either the FamilyBlues or FamilyOtherBlues entries
in the PostScript Private dictionary.
-
Too many elements in either the FamilyBlues or FamilyOtherBlues entries in
the PostScript Private dictionary.
-
Elements too close in either the FamilyBlues or FamilyOtherBlues entries
in the PostScript Private dictionary (must be at least 2*BlueFuzz+1 apart).
-
Non-integral elements in either the FamilyBlues or FamilyOtherBlues entries
in the PostScript Private dictionary.
-
Alignment zone height in either the FamilyBlues or FamilyOtherBlues is too
big for the BlueScale in the PostScript Private dictionary.
-
Bad BlueFuzz entry in PostScript Private dictionary.
-
Bad BlueScale entry in PostScript Private dictionary.
-
Bad StdHW entry in PostScript Private dictionary.
-
Bad StdVW entry in PostScript Private dictionary.
-
Bad StemSnapH entry in PostScript Private dictionary.
-
Bad StemSnapV entry in PostScript Private dictionary.
-
StemSnapH does not contain StdHW value in PostScript Private dictionary.
-
StemSnapV does not contain StdVW value in PostScript Private dictionary.
-
Bad BlueShift entry in PostScript Private dictionary.
-
Bad 'CFF ' table.
For TrueType fonts it will also notice:
-
More points in a glyph than specified in 'maxp'
-
More paths in a glyph than specified in 'maxp'
-
More points in a composite glyph than specified in 'maxp'
-
More paths in a composite glyph than specified in 'maxp'
-
Instructions longer than allowed in 'maxp'
-
More references in a glyph than specified in 'maxp'
-
References nested more deeply than specified in 'maxp'
-
Bad 'glyf' or 'loca' table
In any sfnt (True or OpenType font):
-
Bad sfnt table header, bad file/table checksums, overlapping tables, standard
tables with incorrect lengths, etc.
-
Bad PostScript fontname entry in the 'name' table
-
Bad 'hhea', 'hmtx', 'vhea' or 'vmtx' table
-
Bad 'cmap' table
-
Bad 'EBDT', 'bdat', 'EBLC' or 'bloc' (embedded bitmap) table
-
Bad Apple GX advanced typography table
-
Bad OpenType advanced typography table
-
Bad version number in OS/2 table (must be >0, and must be >1 for OT-CFF
fonts)
See Also
FontForge


CERN essentially consists of one main particle accelerator LHC
and 4 detectors around it, called CMS
,Atlas
,Alice
, and LHCb
, situated at different areas around the LHC. I worked on the Compact Muon Solenoid (CMS) experiment.
CERN's overall goal is to detect particles at higher and higher energy levels, such as quarks, muons and neutrinos, which are produced by colliding accelerated particles in the Large Hadron Collider (LHC). Each detector's goal is to study the particle collisions from different aspects and with different technologies.
However, to be able to get to these ever-increasing levels of energies, the technology of both the LHC and the four main detectors must be regularly upgraded.
As it so happened, the CMS detector, with which my lab was affiliated, was not only upgrading its detectors, but actually adding a different type of technology entirely.
These new detectors, Gas Electron Multipliers (GEMs), which are produced in Korea, India, and Florida, are then tested, in 8 quality control checks (QCs 1-8), at the CMS lab, before being put in production.
My role was being involved in the last quality control to verify the detector’s hardware was functioning appropriately, by having python code run through its triggers to see if it correctly detected small electrical test collisions, and then improving the software used for these tests.
This was done by adding new functionalities to the codebase, such as increasing the step size of the displayed graphs, and changing basic configurations of the detectors, which would allow them behave in different ways under different electrical conditions.
Software development:
Implemented requested features on an existing central code repository, relating to GEM detector’s hardware, using Python scripts, and tested them on a Cosmic Stand (Quality Control Stand 8) while maintaining detailed e-logs of results.
--stepSize
flag to one of the CLI scripts so that physicists could input their custom values on the GEM detector's latency scan for testing.DIP
Server documentation. The published data corresponded to the the latest gas levels of a gas mixer using a .txt
file generated from FlowPlot
, FlowView
and FlowDEE2
softwares.Data analysis:
ROOT
C++/Python CLI framework to understand tree and n-tuple data structures, and used them to plot, fit and cut particles physics events such as collisions and trajectories on histograms.latency scans
to verify if implemented features were returning expected values.R&D:
LabVIEW
interface connected to a pico-ammeter and radiation stand to get and plot various data relating to irradiated GEM detector foils of various thicknesses in order to observe and understand relationship between X-Ray energies, electrical current, foil properties and the subsequently varying amount of particles detected.Hardware updates:
There were several challenges during this internship, mostly related to technicalities and a lack of understanding of the global context (which I've summarised above). Specifically:


| Samples: | browser; tcpserver; webview |
| Learn more: | Embed Content; Chrome Apps Office Hours - the WebView Control |
Use the webview
tag to embed 'guest' content
(such as web pages) in your Chrome App.
The guest content is contained within the webview
container;
an embedder page within your Chrome App controls
how the guest content is laid out and rendered.
Different from the iframe
,
the webview
runs in a separate process than your app;
it doesn't have the same permissions as your app and
all interactions between your app and embedded content will be asynchronous.
This keeps your app safe from the embedded content.
To embed a web page in your app,
add the webview
tag to your app's embedder page
(this is the app page that will display the guest content).
In its simplest form,
the webview
tag includes the src
of the web page
and css styles that control the appearance of the webview
container:
<webview id="foo" src="http://www.google.com/" style="width:640px; height:480px"></webview>
If you want to control the guest content in any way,
you can write JavaScript that listens for webview events
and responds to those events using the webview methods.
Here's sample code in app.js
with two event listeners:
one that listens for the web page to start loading,
the other for the web page to stop loading,
and displays a "loading..." message during the load time:
onload = function() { var webview = document.getElementById("foo"); var indicator = document.querySelector(".indicator"); var loadstart = function() { indicator.innerText = "loading..."; } var loadstop = function() { indicator.innerText = ""; } webview.addEventListener("loadstart", loadstart); webview.addEventListener("loadstop", loadstop); }
<webview id="foo" src="http://www.google.com/" style="width:640px; height:480px"></webview>
Returns the visible URL. Mirrors the logic in the browser's omnibox: either returning a pending new navigation if initiated by the embedder page, or the last committed navigation. Writing to this attribute initiates top-level navigation.
Assigning src
its own value will reload the current page.
The src
attribute can also accept data URLs, such as "data:text/plain,Hello, world!"
.
<webview id="foo" src="http://www.google.com/" style="width:640px; height:480px" partition="persist:googlepluswidgets"></webview>
Storage partition ID used by the webview
tag.
If the storage partition ID starts with persist:
(partition="persist:googlepluswidgets"
),
the webview
will use a persistent storage partition
available to all guests in the app
with the same storage partition ID.
If the ID is unset or if there is no 'persist':
prefix,
the webview
will use an in-memory storage partition.
This value can only be modified before the first navigation,
since the storage partition of an active renderer process cannot change.
Subsequent attempts to modify the value will fail with a DOM exception.
By assigning the same partition ID,
multiple webviews can share the same storage partition.
Exception thrown:
The partition attribute must be valid for navigation to proceed.
In the case of an invalid partition, such as partition="persist:"
,
the src attribute cannot be set and an exception is thrown.
<webview id="foo" src="http://www.google.com/" style="width:640px; height:480px" autosize="on" minwidth="576" minheight="432"></webview>
If "on", the webview
will container will automatically resize within the bounds specified
by the attributes minwidth
, minheight
,
maxwidth
, and maxheight
.
These contraints do not impact the webview
UNLESS autosize
is enabled.
When autosize is enabled, the webview
container size cannot be less than the minimum values
or greater than the maximum.


Documents Ganeti version 2.12
Ganeti was developed to run on internal, trusted systems. As such, the security model is all-or-nothing.
Up to version 2.3 all Ganeti code ran as root. Since version 2.4 it is possible to run all daemons except the node daemon and the monitoring daemon as non-root users by specifying user names and groups at build time. The node daemon continues to require root privileges to create logical volumes, DRBD devices, start instances, etc. Cluster commands can be run as root or by users in a group specified at build time. The monitoring daemon requires root privileges in order to be able to access and present information that are only avilable to root (such as the output of the xm command of Xen).
For a host on which the Ganeti software has been installed, but not joined to a cluster, there are no changes to the system.
For a host that has been joined to the cluster, there are very important changes:
As you can see, as soon as a node is joined, it becomes equal to all other nodes in the cluster wrt to SSH and equal to all non-master candidate nodes wrt to RPC, and the security of the cluster is determined by the weakest node.
Note that only the SSH key will allow other machines to run any command on this node; the RPC method will run only:
It is therefore important to make sure that the contents of the /etc/ganeti/hooks and /etc/ganeti/restricted-commands directories are supervised and only trusted sources can populate them.
The restricted commands feature is new in Ganeti 2.7. It enables the administrator to run any commands in the /etc/ganeti/restricted-commands directory, if the feature has been enabled at build time, subject to the following restrictions:
Note that it’s not possible to list the contents of the directory, and there is an intentional delay when trying to execute a non-existing command (to slow-down dictionary attacks).
Since for Ganeti itself this functionality is not needed, and is only provided as a way to help administrate or recover nodes, it is a local site decision whether to enable or not the restricted commands feature.
By default, this feature is disabled.
As mentioned above, there are multiple ways of communication between cluster nodes:
The SSH traffic is protected (after the initial login to a new node) by the cluster-wide shared SSH key.
RPC communication between the master and nodes is protected using SSL/TLS encryption. The server must have must have the cluster-wide shared SSL/TLS certificate. When acting as a client, the nodes use an individual SSL/TLS certificate. On incoming requests, the server checks whether the client’s certificate is that of a master candidate by verifying its finterprint to a list of known master candidate certificates. We decided not to use a CA (yet) to simplify the key handling.
The DRBD traffic is not protected by encryption, as DRBD does not support this. It’s therefore recommended to implement host-level firewalling or to use a separate range of IP addresses for the DRBD traffic (this is supported in Ganeti through the use of a secondary interface) which is not routed outside the cluster. DRBD connections are protected from erroneous connections to other machines (as may happen due to software issues), and from accepting connections from other machines, by using a shared secret, exchanged via RPC requests from the master to the nodes when configuring the device.
The command-line tools to master daemon communication is done via a UNIX socket, whose permissions are reset to 0660 after listening but before serving requests. This permission-based protection is documented and works on Linux, but is not-portable; however, Ganeti doesn’t work on non-Linux system at the moment.
The luxid daemon (automatically enabled if confd is enabled at build time) serves local (UNIX socket) queries about the run-time configuration. Answering these means talking to other cluster nodes, exactly as masterd does. See the notes for masterd regarding permission-based protection.
In Ganeti 2.8, the confd daemon (if enabled at build time), serves network-originated queries about parts of the static cluster configuration.
If Ganeti is not configured (at build time) to use separate users, confd has access to all Ganeti related files (including internal RPC SSL certificates). This makes it a bit more sensitive to bugs (a remote attacker could get direct access to the intra-cluster RPC), so to harden security it’s recommended to:
The monitoring daemon provides information about the status and the performance of the cluster over HTTP. It is currently unencrypted and non-authenticated, therefore it is strongly advised to set proper firewalling rules to prevent unwanted access.
The monitoring daemon runs as root, because it needs to be able to access privileged information (such as the state of the instances as provided by the Xen hypervisor). Nevertheless, the security implications are mitigated by the fact that the agent only provides reporting functionalities, without the ability to actually modify the state of the cluster.
Starting with Ganeti 2.0, Remote API traffic is encrypted using SSL/TLS by default. It supports Basic authentication as per RFC 2617. Users can be granted different capabilities. Details can be found in the RAPI documentation.
Paths for certificate, private key and CA files required for SSL/TLS will be set at source configure time. Symlinks or command line parameters may be used to use different files.
To move instances between clusters, different clusters must be able to communicate with each other over a secure channel. Up to and including Ganeti 2.1, clusters were self-contained entities and had no knowledge of other clusters. With Ganeti 2.2, clusters can exchange data if tokens (an encryption certificate) was exchanged by a trusted third party before.
When running KVM instances under Ganeti three security models ara available: “none”, “user” and “pool”.
Under security model “none” instances run by default as root. This means that, if an instance gets jail broken, it will be able to own the host node, and thus the ganeti cluster. This is the default model, and the only one available before Ganeti 2.1.2.
Under security model “user” an instance is run as the user specified by the hypervisor parameter “security_domain”. This makes it easy to run all instances as non privileged users, and allows one to manually allocate specific users to specific instances or sets of instances. If the specified user doesn’t have permissions a jail broken instance will need some local privilege escalation before being able to take over the node and the cluster. It’s possible though for a jail broken instance to affect other ones running under the same user.
Under security model “pool” a global cluster-level uid pool is used to start each instance on the same node under a different user. The uids in the cluster pool can be set with gnt-cluster init and gnt-cluster modify, and must correspond to existing users on all nodes. Ganeti will then allocate one to each instance, as needed. This way a jail broken instance won’t be able to affect any other. Since the users are handed out by ganeti in a per-node randomized way, in this mode there is no way to make sure a particular instance is always run as a certain user. Use mode “user” for that.
In addition to these precautions, if you want to avoid instances sending traffic on your node network, you can use an iptables rule such as:
iptables -A OUTPUT -m owner --uid-owner <uid>[-<uid>] -j LOG \
--log-prefix "ganeti uid pool user network traffic"
iptables -A OUTPUT -m owner --uid-owner <uid>[-<uid>] -j DROP
This won’t affect regular instance traffic (that comes out of the tapX allocated to the instance, and can be filtered or subject to appropriate policy routes) but will stop any user generated traffic that might come from a jailbroken instance.


|
Uncreative Studios
|
Public Member Functions | |
| constructor | Location (int x, int y) |
| int [] | getLocation () |
Public Attributes | |
| Ship | ship |
| ArrayList< Obstacle > | obstacles |
| Building | building |
Private Attributes | |
| int | x |
| int | y |
Location of an object on the map.
| int [] com.uncreative.game.Location.getLocation | ( | ) |
Returns the x and y co-ordinates of an object.
| Building com.uncreative.game.Location.building |
Initialised to null, set when college or department is created.
| ArrayList<Obstacle> com.uncreative.game.Location.obstacles |
ArrayList (of type Obstacle) of existing obstacles and their locations.
| Ship com.uncreative.game.Location.ship |
Initialised to null, set when ship is created.
|
private |
X co-ordinate of object.
|
private |
Y co-ordinate of object.


eigenvectorcontinuation.continuer package
Submodules
eigenvectorcontinuation.continuer.eigenvector_continuer module
Class that performs Eigenvector Continuation on any type of HSA given some type of target point
An EigenvectorContinuer object is flexible to take any valid implementation of an HSA and use it to calculate values relevant to EC. Requires input of both training points (used in creation of the HSA), and a target point.
- class eigenvectorcontinuation.continuer.eigenvector_continuer.EigenvectorContinuer(hilbert_space, target_point)
Bases:
object
Computes EC on a given HSA and target point.
Houses the functionality to create a Hilbert Space of specified type and perform Eigenvector Continuation for a given set of training points and target points
USE CASE: 1. Create an instance of a HilbertSpaceAbstract concrete class/subclass. Requires training points (and/or other input depending on implementation) 2. Input: a target point to use and calculate the subspace hamiltonian
- OUTPUT:
Eigenvalues and Eigenvectors from the Generalized Eigenvalue Problem constructed from the subspace hamiltonian and overlap matrix calculated by the training and target points
- USEFUL METHODS (documentation given below):
__init__(…) calc_overlap_matrix(…) calc_sub_ham(…) solve_gep(…)
- calc_overlap_matrix(input_training_points=None)
caclulates the overlap matrix based on the Hilbert Space’s current training points
- Parameters
input_training_points – [OPTIONAL] can be used to update the hilbert space’s training points as needed
- Returns
the overlap matrix
- calc_sub_ham(input_target_point=None)
calculates the subspace hamiltonian based on the EC’s current Hilbert Space and target point
- Parameters
input_target_point – [OPTIONAL] can be used to update the current target point of the EC as needed
- Returns
the subspace hamiltonian
- property current_target_point
I’m this EC’s current target point. I’m used to create the sub_ham
- property evals
I’m this EC’s last calculated set of eigenvalues for the diagonalized subspace ham
- property evecs
I’m this EC’s last calculated set of eigenvectors for the diagonalized subspace ham
- property hilbert_space
I’m this EC’s hilbert space
- property overlap_matrix
I’m this EC’s last calculated overlap matrix
- refresh_overlap_matrix()
refreshes the current overlap matrix property based on current properties
- refresh_sub_ham()
refreshes the current subspace hamiltonian based on current properties
- solve_gep(input_training_points=None, input_target_point=None)
solves the generalized eigencvalue problem for this EC
- Parameters
input_training_points – used to calculate the current hilbert space’s overlap matrix. If None is passed, will default to current training_points in the hilbert space
input_target_point – used to calculate the current hilbert space’s subspace hamiltonian. If None is passed, will default to current_target_point in this EC
- Returns
the evals, evecs calculated
- property sub_ham
I’m this EC’s last calculated subspace hamiltonian


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--- layout: post status: publish published: true title: Viasfora v1.2 Released author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 1393 wordpress_url: http://winterdom.com/?p=1393 date: '2013-12-23 02:15:31 +0000' date_gmt: '2013-12-23 02:15:31 +0000' categories: - Visual Studio tags: [] comments: [] ---
Viasfora version 1.2 has been released! Most of the work on this released went into significantly improving the performance of the extension, particularly around Rainbow Parentheses and the Keyword Classifier.
One of the issues that I ran into was that when both features were enabled, they could interact in ways that would easily kill performance, particularly causing the C# editor to blink the highlight on some words, which was not a good thing. Another big challenge was the JavaScript editor, which, because of how it parses JS (in VS2010, in particular), it becomes very sensitive on anything that forces tag updates.
Much of the extra performance work went into improving the lexing code to extract braces when the document changes. I'm still not terribly happy with the current code, but it seems to be holding up for now. Two of the things that improved this the most are keeping a list of all the braces found and then only doing partial invalidation when the document changes, and also providing a quick way to look up ranges of braces based on the document lines. Still lots of room for improvement here!
As for new features? Rainbow parentheses is now supported on VB (often asked about!). Initial support for F# is also provided, but I am sure the default set of F# keywords I chose for this version could use some improvement. If you're an F# fan, let me know of any suggestions!.


dem2stl
provides functions to convert digital elevation map (dem) files to .stl
(and other) 3d-printable model files. It is different from other packages in that:
devtools::install_github("kevinstadler/dem2stl")
dem2stl
relies on R’s rgl
package which requires OpenGL libraries to be installed. On Fedora, these are available through the mesa-libGLU-devel
package
wget https://research.cip.cgiar.org/gis/downloads/dataserver/_msk_alt/NLD_msk_alt.zip
unzip NLD_msk_alt.zip
nl <- raster::raster("NLD_msk_alt.grd")
# aggregate to 2x2 cells because otherwise West-Friesland is clipped
# (the Noordzeekanal, marked with NA values, is so wide that it would split the
# Netherlands into two separated landmasses, with only the biggest rendered)
nl <- raster::aggregate(nl, 2, fun=max)
# render to 10x10cm max, with a thin base
m <- dem2stl::dem2mesh(nl, size=100, thicknessratio=0.001)
dem2stl::mesh2stl("nederland.stl", m)
Full documentation is available at http://kevinstadler.github.io/dem2stl/


Easy Hyper Parameter Optimization with mlr and mlrMBO.
Webservice (Work in progress!)
devtools::install_github("berndbischl/ParamHelpers") # version >= 1.11 needed.
devtools::install_github("jakob-r/mlrHyperopt", dependencies = TRUE)
mlrHyperopt aims at making hyperparameter optimization of machine learning methods super simple. It offers tuning in one line:
Mainly it uses the learner implemented in mlr and uses the tuning methods also available in mlr. Unfortunately mlr lacks of well defined search spaces for each learner to make hyperparameter tuning easy.
mlrHyperopt includes default search spaces for the most common machine learning methods like random forest, svm and boosting.
As the developer can not be an expert on all machine learning methods available for R and mlr, mlrHyperopt also offers a web service to share, upload and download improved search spaces.
ParConfigs are up- and downloaded via JSON and stored on the server in a database. It’s a very basic Ruby on Rails CRUD App generated via scaffolding with tiny modifications https://github.com/jakob-r/mlrHyperoptServer. ToDo: * Voting System * Upload-/Download Count * Improve API * Return existing ID when a duplicate is uploaded (instead of error). * Allow a combined search (instead of one key value pair).
Basic functionality works reliable. Maybe I will improve the optimization heuristics in the future. It still needs more default search spaces for popular learners!
This package is still under construction and the inner workings might change without a version number update. Thus I do not recommend the usage for reproducible research until it is on CRAN. For reproducible research you might want to stick to the more lengthly but more precise mlr tuning workflow. You can still use the Parameter Sets recommended in mlrHyperopt. Just make sure to write them in your source code.


Hello! Welcome to the packet configuration page, where you'll be able to craft the packet of your dreams. First things, first:
- You gotta start selecting which layers you want in this packet. Just click the add layer button, and select which layer you want.
- Next, you gotta configure what's inside each layer.
- And then you just fill out those fields, and click the dandy 'Done' button!
"But wait," I hear you say, "doesn't an Ethernet frame have a checksum / IP packet have a type field / UDP have a length field / etc." YES! However, we here at PPP believe that we are in the future. So we'll fill those out automatically for you.


EROTIQUE A film review by Frank Maloney Copyright 1994 Frank Maloney
EROTIQUE is an anthology film by three directors, Lizzie Borden, Monika Treut, and Clara Law. The casts of their three short films include Kamala Lopez-Dawson, Bryan Cranston, Priscilla Barnes, Camilla Soeberg, Tim Lounibos, and Hayley Man.
EROTIQUE received its world premiere at the Seattle International Film Festival and I understand is booked to return to Seattle later this year (in fact I saw a trailer for it last night when I went to KIKA). Frankly, the fact that EROTIQUE has found a distributor and bookings surprises me because the film is so uneven overall. The first part has the best story; the second has the highest kink contents; the third part looks like outtakes from a much longer film.
"Let's Talk About Sex" is directed by Lizzie Borden and written by Borden and Susie Bright. In it, Kamala Lopez-Dawson is an aspiring actress who is being offered only humiliating roles of hookers and barmaids who have a sex scene and then never heard of again, because she's not blonde and anglo. She supports herself by working in a phone-sex boiler room. She rebels against having the same, blonde-big hooter fantasies imposed on her by customers until she finds one (Bryan Cranston) who want to hear her sexual fantasies. The final upshot of this is a surprising and sexy last scene meeting between the two. The scenes in the boiler room, the women who work the phones and the johns, the man who goads them on to keep the suckers on the line, and calls they handle are hilarious and interesting. The fantasy sequences demonstrate why it is probably imprudent to talk about sexual fantasies to strangers, but the interactions and growing telephonic intimacy between Lopez-Dawson and Cranston is sexy and intriguing. Overall, this the best segment.
"Taboo Parlor," directed by Monika Treut, involves two drop-dead lesbians (Priscilla Barnes and Camilla Soeberg), the younger of whom has yen for seducing men from time to time. They go to a ship-board nightclub in the Hamburg docks (look for Marianne Sagebrecht as the dance mistress) and find a particularly dangerous stud to take home. The three-way develops in a direction that surprises him and us, but him more finally. In the end, the whole smacks a little of the evil lesbian of pulp homophobic literature and left me uncomfortable and not a little puzzled, but the sex was erotic and something of a turn-on, if that was the point because it was pretty hard to find a point to this film.
 The scene where they work their way their the manual is hilarious, but the rest of it is undeveloped and fragmentary at best (interestingly, in the trailer there is scene from this story that is not in the released version I saw). And as the last part of EROTIQUE, it makes one exit with a decidedly negative impression of the entire work.
I cannot really recommend EROTIQUE, even though some of its parts are stimulating in one way or the other.
-- Frank Richard Aloysius Jude Maloney
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Only a few days left before WWDC 2017. I hope that we’ll see a lot of great and useful stuff, besides Swift 4, from Apple which can help us to make the world a better place.
One of the exciting features of upcoming Swift 4 is Multi-Line String Literals. I often need a quick way to create a prototype app with JSON data. Usually, I need to save data to local JSON file and then read from file or use network layer. That takes time. In Swift 4 we can use [Multi-Line String Literals](https://github.com/apple/swift-evolution/blob/master/proposals/0168-multi-line-string-literals.md.
Example: I used http://beta.json-generator.com to generate fake JSON data for this example. The result JSON looks like: sample.json
Previously it wasn’t possible to use such strings like string literals. In Swift 4 you can just copy/past it like this:
""" JSON/XML/OTHERS COMPLEX STRINGS """
Multi-Line String Literals.playground


|
ORACS
0.8
Meta-heuristic for solving VRP problems.
|
#include <solution.h>
Public Member Functions | |
| Solution (Env *env) | |
| Constructor. More... | |
| Solution (Env *env, std::vector< Depot > depots, std::vector< Customer > customer) | |
| void | print () |
| double | totalCost () |
| Calculates the total cost of the solution. More... | |
| bool | feasible () |
| Function to check whether the solution is feasible or not. More... | |
| std::vector< Depot > & | getDepots () |
| std::vector< Customer > & | getCustomers () |
| void | addCustomer (Customer customer) |
| void | addDepot (Depot depot) |
Private Attributes | |
| Env * | d_env |
| std::vector< Depot > | d_depots |
| std::vector< Customer > | d_customers |
| bool | d_feasible |
| double | d_penalty |
The Solution class holds the actual solution. This consist of the data structure as designed, so a vector of depots and a vector customers.
Definition at line 20 of file solution.h.
| Solution::Solution | ( | Env * | env | ) |
|
inline |
Adds customer to the solution.
| customer | Customer to add |
Definition at line 66 of file solution.h.
|
inline |
| bool Solution::feasible | ( | ) |
Function to check whether the solution is feasible or not.
Definition at line 13 of file feasible.cpp.
|
inline |
|
inline |
| double Solution::totalCost | ( | ) |
Calculates the total cost of the solution.
Definition at line 13 of file totalcost.cpp.
|
private |
Vector of customers of the solution
Definition at line 24 of file solution.h.
|
private |
Vector of depots of the solution
Definition at line 23 of file solution.h.
|
private |
Environment pointer
Definition at line 22 of file solution.h.
|
private |
Indicates whether the solution is feasible or not
Definition at line 25 of file solution.h.
|
private |
The total penalty cost of the solution
Definition at line 26 of file solution.h.


"Houston. We have a serious problem."
RATING: 2/10
After making "Mission: Impossible", Brian De Palma has a lot to live up to. By making an epic science fiction and inviting great cast and talented crew, he hopes to reach the modern audience. And the possibilities are certainly there, but the result is a great disaster.
Starting in a near future, with a prologue copied from "Apollo 13", De Palma slowly builds up his "story". The human race has already set foot on Mars. A research expedition has vanished without trace on the red planet and another one has been sent to find out what happened. This is basically the whole plot. So it's hard to imagine that it can be stretched to 2 hours. But De Palma manages to do that. It is not a very good achievement. As we follow this expedition to Mars and watch them slowly float in space, the hardest thing to do is stay awake. The film's major problem is that it tries to seem more clever than it is. David Mamet's dialogue, while trying to seem natural, is distant and simply fake. De Palma and Mamet wanted to combine action with a thought provoking plot. The result is more like an unsuccessful mutation of Kubrick's "2001: A Space Odyssey", "Apollo 13" and "Godzilla". To make time pass , the creators have inserted several "refreshing" scientific details, that would not convince a half-crazed frog. It consists of multiple copies and direct ripp-offs from several great science fiction films and stories. When it finally presents an almost original idea, it falls flat because of its uncovered stupidity. I can't even call this film predictable, since no one with a healthy imagination can come up with something like this. Sometimes it gets so cheesy, that you'll start laughing when you're supposed to cry and cry when you're supposed to laugh. You'll see enormous sandstorms, hear mysterious sounds and, last but not least, on this "constantly surprising" tour you'll see -- an alien. It's really hard to find comparisons to such an experience, and I know that I've never said that before (I thought I never would), but "Lost in Space" is actually better. That's an achievement in itself!
Director Brian De Palma has stroke gold with "Untouchables" that became an instant American classic. It is for this film that he will be remembered, while all his other failures will be forgotten. He'll live to fight another day! I send the actors my condolences, since they truly do try to transform into their undeveloped and dull characters. And both the cinematography, production design and art direction are very decent. It is because of the achievement of 254 people, that I rate this film 2/10. Unfortunately their hard work was in vain. If you have problems with insomnia, I recommend you this film. If you're not asleep within the first half hour, consult your doctor.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


How to use the system:
Download our chat client (GUI), write a name, and you're started
You can type 'msg:<*names*>:message', to type to specific people.
Otherwise you can just type something in, and the GUI will tell the server to write to all
Type logout: to logout
Without our GUI, you can call login:<*username*>, to set your name, note you can only do it once per client
You can write MSG:<*receivers*>:<*message*>, where you're splitting receivers by ','s. You can write to one, many or use '*' to write to all
You'll receive answers from the server in the format MSGRES:<*sender*>:<*message*>.
You'll get a client list everytime a person logs off or on the server.
Type 'logout:' to logout from the server


Start Game
AI
Player
Join Game
Join
View Game
View
Game Status:
Game ID:
Share your game:
Helper Mode


| DOSE: |
|
insufflated |
DPT |
(powder / crystals) |
T+0 - opened 2 x 65mg gelcaps (from previous measurements) and cut up 4 lines on a mirror. Use of the traditional $20 note ... and away we go. It neither burns nor smells too bad, though (+2-3 min) there's kinda an ooky post-nasal drip, but it doesn't smell that bad, and doesn't taste nasty -- just feels like a bogie that won't go (I don't normally snort things, so this is an unusual route for me). I ate a little earlier in the day (couple of light waffles for a late breakfast), that was about 5 hours ago.
T+:05 - post-nasal drip tastes a little more nasty, kinda plastickey. Urgh, yuck.
T+:30 - starting to get trailers, and a spacey feeling. Normal
tryptamine alerts are present, too. Stomach feels a little tight, and I'm glad I didn't eat after breakfast.
T+:45 - at this point, I had to go lie down. Music was playing in the background (swing, I think) and the effect and power of it was such as to transport me to a completely different place. I don't remember clearly, but it was bright -- impressions of a white sand beach, clear blue water, and trees (physically, I'm in San Francisco in late winter).
T+1:00 - full-blown psychedelic spin-o-rama. I'm normally a hardhead
when it comes to visuals, not getting many at all, but this compound has certainly opened a door for me. Everything looks colour-ghosted, as if my eyes had separated red, green, and blue by a few degrees. I feel very cold, though my sitter tells me that my temperature is normal. Climbing into bed eventually makes me feel warm, though I want the human company as well -- I don't feel afraid, just needy. When I close my eyes and listen to the music, I just get completely blown away; normal reality simply isn't there any more, and my mind spins away into whatever reality the DPT has opened up for me, though I can't now remember exactly what. With eyes open, conversation is easy with a measured voice and no trouble cognating, though keeping my thoughts on one subject is tricky. When I get up to walk around a little, I feel kind of shaky, though that may well be because I simply can't see clearly through the trails and colour banding.
T+2:00 - I'm starting to re-emerge into normal reality; sitting on the couch watching a movie is easy, though there's no special insight or extra amusement or depth to the movie (this may be because it's the South Park movie -- which I find funny normally, but no more so at the moment).
T+3:00 - completely baseline. The only after-effects are the normal tryptamine stomach gurgles and a little gas, but it's pretty mild.
Possibly this is because of the route of administration -- oral doses may have a greater digestive impact.
Overall, I like this compound; it bears more research, though probably at lower levels until I can more accurately determine its potential and capabilities.
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.


Florida police say a black Lab named Max drove doughnuts alone in a car, then jumped out, wagging his tail
by Michelle Mark, Associated Press- Florida authorities say a Black Labrador named Max drove doughnuts by himself after his owner stepped away from the running car.
- The Port St. Lucie Police Department posted video of the bizarre incident to Facebook and said the pet knocked the car into reverse somehow.
- A neighbor said the dog was in high spirits after being rescued, adding it “jumped out of the car, wagging his tail.”
- Visit Insider’s homepage for more stories.
Florida authorities say they responded to a rogue vehicle spinning in reverse around a suburban cul-de-sac with a lone occupant inside: a Black Labrador named Max.
News outlets report residents called police Thursday after seeing the dog trapped and clambering around in the car as it spun in circles in a Port St. Lucie neighborhood.
Police say they think the dog’s owner stepped away from the running car and that’s when the pet knocked it into reverse. Neighbor Anne Sabol says she watched the furry speed racer take out a mailbox and a trash can.
“The dog named MAX accidently [sic] hit the shifter into reverse causing the car to circle the cul-de-sac, leaving the owner locked out of the car,” authorities said in a statement.
They added that the owner gave police an extra fob, but its battery was dead so police eventually approached the car and entered a code on the car door’s key pad.
Sabol says the dog was in high spirits after being rescued, adding it “jumped out of the car, wagging his tail.”
Police stopped the joyride by punching a passcode into the driver’s door. No one was hurt and the car received only minor damage.
“MAX was fine, healthy, and happy!” police said.
- Read more:
- No, your pet can’t catch your cold but they have their own version of colds
- Meet ‘Narwhal the Little Magical Furry Unicorn,’ a rescue puppy born with an extra tail on his face
- 10 reasons to consider adopting a senior dog instead of a puppy
- A heartbreaking photo of a dog riding a bus alone went viral, and now people want to adopt her


GAN (Generative Adversarial Network) [1] is a framework proposed by Ian Goodfellow, Yoshua Bengio and others in 2014.
A GAN can be trained to generate images from random noises. For example, we can train a GAN on MNIST (hand-written digits dataset) to generate digit images that look like hand-written digit images from MNIST, which could be used to train other neural networks.
The code in this notebook is based on the GAN MNIST example in TensorFlow by Udacity [2] which uses TensorFlow, but we use Keras on top of TensorFlow for more straightforward construction of networks. Many of the ideas on training are from How to Train a GAN? Tips and tricks to make GANs work [4].
import numpy as np
import keras
import keras.backend as K
from keras.layers import Input, Dense, Activation, LeakyReLU, BatchNormalization
from keras.models import Sequential
from keras.optimizers import Adam
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
%matplotlib inline
The below will download MNIST dataset (if not already).
(X_train, y_train), (X_test, y_test) = keras.datasets.mnist.load_data()
Let's examine sample images. We use 'gray' color map since it has no color information.
plt.figure(figsize=(5, 4))
for i in range(20):
plt.subplot(4, 5, i+1)
plt.imshow(X_train[i], cmap='gray')
plt.xticks([])
plt.yticks([])
plt.tight_layout()
plt.show()
All MNIST digit images come in 28x28 size.
sample = X_train[17]
plt.figure(figsize=(3, 2))
plt.title(sample.shape)
plt.imshow(sample, cmap='gray')
plt.show()
The minimum and maximum sizes of MNIST image data is 0 and 255 respectively.
X_train.min(), X_train.max()
def make_latent_samples(n_samples, sample_size):
#return np.random.uniform(-1, 1, size=(n_samples, sample_size))
return np.random.normal(loc=0, scale=1, size=(n_samples, sample_size))
The sample size is a hyperparameter. Below, we use a vector of 100 randomly generated number as a sample.
make_latent_samples(1, 100) # generates one sample
The generator is a simple fully connected neural network with one hidden layer with the leaky ReLU activation. It takes one latent sample (100 values) and produces 784 (=28x28) data points which represent a digit image.
generator = Sequential([
Dense(128, input_shape=(100,)),
LeakyReLU(alpha=0.01),
Dense(784),
Activation('tanh')
], name='generator')
generator.summary()
The last activation is tanh. According to [4], this works the best. It also means that we need to rescale the MNIST images to be between -1 and 1.
Initially, the generator can only produce garbages.
As such, the generator needs to learn how to generate realistic hand-written images from the latent sample (randomly generated numbers).
How to train this generator? That is the question tackled by GAN.
Before talking about GAN, we shall discuss the discriminator.
The discriminator takes a digit image and classifies whether an image is real (1) or not (0).
If the input image is from the MNIST database, the discriminator should classify it as real.
If the input image is from the generator, the discriminator should classify it as fake.
The discriminator is a simple fully connected neural network with one hidden layer with the leaky ReLU activation.
discriminator = Sequential([
Dense(128, input_shape=(784,)),
LeakyReLU(alpha=0.01),
Dense(1),
Activation('sigmoid')
], name='discriminator')
discriminator.summary()
The last activation is sigmoid to tell us the probability of whether the input image is real or not.
We train the discriminator using both the MNIST images and the images generated by the generator.
We connect the generator and the discriminator to produce a GAN.
It takes the latent sample, and the generator inside GAN produces a digit image which the discriminator inside GAN classifies as real or fake.
If the generated digit image is so realistic, the discriminator in the GAN classifies it as real, which is what we want to achieve.
We set the discriminator inside the GAN not-trainable, so it is merely evaluating the quality of the generated image. The label is always 1 (real) so that if the generator fails to produce a realistic digit image, its cost becomes high, and when the back-propagation occurs in GAN, the weights in the generator network gets updated.
# maintain the same shared weights with the generator and the discriminator.
gan = Sequential([
generator,
discriminator
])
gan.summary()
As you can see, the GAN internally uses the same generator and the discriminator models. The GAN maintains the same shared weights with the generator and the disriminator. Therefore, training the GAN also trains the generator. However, we do not want the discriminator to be affected while training the GAN.
We train the discriminator and the GAN in turn and repeat the training many times until both are trained well.
While training the GAN, the back-propagation should update the weights of the generator but not the discriminator.
As such, we need a way to make the discriminator trainable and non-trainable.
def make_trainable(model, trainable):
for layer in model.layers:
layer.trainable = trainable
make_trainable(discriminator, False)
discriminator.summary()
make_trainable(discriminator, True)
discriminator.summary()
The below function combines everything we have discussed so far to build the generator, discriminator, and GAN models and also compile them for training.
def make_simple_GAN(sample_size,
g_hidden_size,
d_hidden_size,
leaky_alpha,
g_learning_rate,
d_learning_rate):
K.clear_session()
generator = Sequential([
Dense(g_hidden_size, input_shape=(sample_size,)),
LeakyReLU(alpha=leaky_alpha),
Dense(784),
Activation('tanh')
], name='generator')
discriminator = Sequential([
Dense(d_hidden_size, input_shape=(784,)),
LeakyReLU(alpha=leaky_alpha),
Dense(1),
Activation('sigmoid')
], name='discriminator')
gan = Sequential([
generator,
discriminator
])
discriminator.compile(optimizer=Adam(lr=d_learning_rate), loss='binary_crossentropy')
gan.compile(optimizer=Adam(lr=g_learning_rate), loss='binary_crossentropy')
return gan, generator, discriminator
def preprocess(x):
x = x.reshape(-1, 784) # 784=28*28
x = np.float64(x)
x = (x / 255 - 0.5) * 2
x = np.clip(x, -1, 1)
return x
X_train_real = preprocess(X_train)
X_test_real = preprocess(X_test)
We also need a function to reverse the preprocessing so that we can display generated images.
def deprocess(x):
x = (x / 2 + 1) * 255
x = np.clip(x, 0, 255)
x = np.uint8(x)
x = x.reshape(28, 28)
return x
plt.figure(figsize=(5, 4))
for i in range(20):
img = deprocess(X_train_real[i])
plt.subplot(4, 5, i+1)
plt.imshow(img, cmap='gray')
plt.xticks([])
plt.yticks([])
plt.tight_layout()
plt.show()
The labels are 1 (real) or 0 (fake) in 2D shape.
def make_labels(size):
return np.ones([size, 1]), np.zeros([size, 1])
The below is 10 sets of real and fake label values.
y_real_10, y_fake_10 = make_labels(10)
y_real_10, y_fake_10
Later, we prepare the labels for training and evaluation using the train batch size and the test size.
One last point before we start training is the label smoothing which makes the discriminator generalize better [4].
For the real digit images, the labels are all 1s. However, when we train the discriminator, we use a value slightly smaller than 1 with the real digit images. Otherwise, the discriminator might overfit to the training data and rejects anything else that is slightly different from the training images.
We repeat the following to make both the discriminator and the generator better and better:
When training the generator via the GAN, the expect labels are all 1s (real). Initially, the generator produces not very realistic images so the discriminator classifies them as 0s (fake), which causes the back-propagation to adjust the weights inside the generator. The discriminator is not affected as we set it non-trainable in this step.
# hyperparameters
sample_size = 100 # latent sample size (i.e., 100 random numbers)
g_hidden_size = 128
d_hidden_size = 128
leaky_alpha = 0.01
g_learning_rate = 0.0001 # learning rate for the generator
d_learning_rate = 0.001 # learning rate for the discriminator
epochs = 100
batch_size = 64 # train batch size
eval_size = 16 # evaluate size
smooth = 0.1
# labels for the batch size and the test size
y_train_real, y_train_fake = make_labels(batch_size)
y_eval_real, y_eval_fake = make_labels(eval_size)
# create a GAN, a generator and a discriminator
gan, generator, discriminator = make_simple_GAN(
sample_size,
g_hidden_size,
d_hidden_size,
leaky_alpha,
g_learning_rate,
d_learning_rate)
losses = []
for e in range(epochs):
for i in range(len(X_train_real)//batch_size):
# real MNIST digit images
X_batch_real = X_train_real[i*batch_size:(i+1)*batch_size]
# latent samples and the generated digit images
latent_samples = make_latent_samples(batch_size, sample_size)
X_batch_fake = generator.predict_on_batch(latent_samples)
# train the discriminator to detect real and fake images
make_trainable(discriminator, True)
discriminator.train_on_batch(X_batch_real, y_train_real * (1 - smooth))
discriminator.train_on_batch(X_batch_fake, y_train_fake)
# train the generator via GAN
make_trainable(discriminator, False)
gan.train_on_batch(latent_samples, y_train_real)
# evaluate
X_eval_real = X_test_real[np.random.choice(len(X_test_real), eval_size, replace=False)]
latent_samples = make_latent_samples(eval_size, sample_size)
X_eval_fake = generator.predict_on_batch(latent_samples)
d_loss = discriminator.test_on_batch(X_eval_real, y_eval_real)
d_loss += discriminator.test_on_batch(X_eval_fake, y_eval_fake)
g_loss = gan.test_on_batch(latent_samples, y_eval_real) # we want the fake to be realistic!
losses.append((d_loss, g_loss))
print("Epoch: {:>3}/{} Discriminator Loss: {:>6.4f} Generator Loss: {:>6.4f}".format(
e+1, epochs, d_loss, g_loss))
As it turns out, training a GAN is quite hard, and there are many tricks and heuristics required [4]. It is because the discriminator and the generator are not cooperating and individually learning to predict better.
For example, the generator might learn to fool the discriminator with garbage. Ideally, the discriminator should learn earlier than the generator so that it can classify images accurately.
Therefore, I used different learning rates for the generator and the discriminator. I wanted to slow down the generator learning so that the discriminator learns to classify well.
I am not 100% certain if this is a generally good strategy to use but it does seem to work in this project.
As the generator learns more and the loss decreases, the discriminator's loss increases. I see kind of equilibrium around 80-90 epochs.
losses = np.array(losses)
fig, ax = plt.subplots()
plt.plot(losses.T[0], label='Discriminator')
plt.plot(losses.T[1], label='Generator')
plt.title("Training Losses")
plt.legend()
plt.show()
According to [4],
According to [4],
Now we generates some digit images using the trained generator.
latent_samples = make_latent_samples(20, sample_size)
generated_digits = generator.predict(latent_samples)
plt.figure(figsize=(10, 8))
for i in range(20):
img = deprocess(generated_digits[i])
plt.subplot(4, 5, i+1)
plt.imshow(img, cmap='gray')
plt.xticks([])
plt.yticks([])
plt.tight_layout()
plt.show()
The results are not outstanding as we are using simple networks. Deep Convolutional GAN (aka DCGAN) would produce better results than this.
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio
https://arxiv.org/abs/1406.2661
Udacity
https://github.com/udacity/deep-learning/tree/master/gan_mnist
Yann LeCun
http://yann.lecun.com/exdb/mnist/
Facebook AI Research: Soumith Chintala, Emily Denton, Martin Arjovsky, Michael Mathieu


Charles W Bessant
Republican
IT Infrastructure Consultant
MBA: University of Phoenix - 1998 Dual-BS: Marketing & Management Data Systems - Syracuse University - 1981
80831
2020: Donated to Donald Trump, Lauren Boebert. El Paso County and CO State GOP Delegate
Just El Paso County and CO State GOP Delegate, 2020
None
My family situation doesn't provide the time needed to run for or hold public office, I see the opportunity to serve on this committee as my opportunity to participate in state political matters. My career in information technology consulting has been one of analysis on new technologies, risk tolerance with selecting technologies and viewing how to create and drive new solutions differently than other technologists. I look for solutions objectively and openly without alliance to a specific team, product or vendor - I take an agnostic approach to make quality recommendations and challenges. Not all on the "Left" and "Right" are bad, each have qualities that need to be balanced. While I'm a staunch conservative with libertarian leanings, I do my best to see what is fair and right from the "reasonable man" point of view.
I look at situations objectively and in an agnostic manner. I'm open to recommendations and suggestions for all reasonable sides, I'm not willing to take a radical stance from any point of view. America is centrist that extreme. As a consultant, my role was to help guide clients to solutions that reflected their technical and business requirements aligned with their tolerance for risk. Examples: My recommendations and approach with the US Treasury & The IMF were different than with Comcast, and I didn't have a preference for recommending vendors nor did I ever take commissions or cash for recommending a vendor's solution to my clients. My M&A analysis for a $250M Tier 2 buyout by a UK based trans-Atlantic fiber carrier was based on objectivity to provide the UK company the information they needed to make a sound decision. It built trust.
As I discussed in the previous two questions, I do my homework, I do gap analysis, I focus on understanding the data points provided by my clients and interviews, I discuss with my associates to make sure I didn’t miss critical data points, and finally, and most importantly, I listen to all aspects to make informed, agnostic, “reasonable man” decisions. In my experience, engineers and managers have their favorite teams and vendors to work with. I do my best to select solutions objectively based on my and my team’s analysis.
Male by birth


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SCREAM 3 (M). (Miramax/Dimension Films/Village Roadshow) Director: Wes Craven
Stars: David Arquette, Neve Campbell, Courtney Cox Arquette, Patrick Dempsey, Parker Posey, Deon Richmond, Scott Foley, Jenny McCarthy, Lance Henriksen, Matt Keeslar, Liev Schreiber, Emily Mortimer, Patrick Warburton, Kelly Rutherford, Carrie Fisher, Roger Corman, Kevin Smith, Jason Mewes
Running time: 117 minutes. The problem with most long running horror series is that they inevitably have a habit of outstaying their welcome. Friday The 13th, Halloween, and Nightmare On Elm Street, etc, quickly deteriorated once they started producing increasingly ludicrous sequels that moved further and further away from the original in both flavour and intent. On the other hand, true movie trilogies seem to fare better. Star Wars, the Indiana Jones and Jack Ryan series, and, to a lesser extent, The Godfather saga maintained the integrity and standards of the original. Similarly, Scream 3, the third instalment in this popular horror series that revitalised the teen slasher genre, sticks to its established formula. Despite the familiarity of the plotting and a singular lack of originality, though, Scream 3 will not disappoint fans. Scream 3 is set in Hollywood, where a studio, fascinated by the gruesome Woodsboro slayings, is filming Stab 3, a sequel that continues the film-within-a-film that opened Scream 2.  The recent low budget Australian teen slasher film Cut shares a few superficial similarities and may have stolen some of its thunder, but Scream 3 is still a vastly superior film. The brutal murders reunite tenacious reporter Gale Weathers (Courtney Cox Arquette) and Dewie Riley (David Arquette), who is working as a technical advisor on the movie. The key to the killings again seems to be feisty Sidney Prescott (Neve Campbell), who has disappeared into seclusion and now works as a telephone counsellor from the anonymity of her safe house. In probing the new series of murders, the three raise disturbing questions about the past and the real identity of the Woodsboro killer, long thought to have been killed. While the regular stars merely go through the motions, Scream 3 introduces us to some new protagonists, who become victims or suspects. Mark Kincaid (Patrick Dempsey) is a handsome, film literate homicide detective, the perfect man to help investigate a series of murders surrounding a movie set, or so one would assume. And indie queen Parker Posey is an absolute delight as Jennifer Jolie, the actress portraying Gale on screen, who throws herself into the role of playing real life investigative reporter with annoying gusto. Scream 3 has not suffered greatly with the departure of original writer Kevin Williamson, as it manages to retain much of the same flavour. The film supposedly plays around with the conventions of film sequels, and also adds a new dimension to the film-within-a-film concept. Scream 3 also manages to generate some suspense as to which of our three heroes may not survive. However, the writing is not as sharp and there is a greater emphasis on gore here.  Ehren Kruger (who wrote the superb paranoid conspiracy thriller Arlington Road) ups the body count, but still manages to punctuate the grisly slayings with lashings of humour, dubious film lore and heaps of sly in-jokes. Cameo appearances by famed '60's director and producer Roger Corman, Silent Bob and Jay (aka Kevin Smith and Jason Mewes) and Carrie Fisher add to the irreverent flavour of the whole thing. Veteran director Wes Craven knows the rhythms and pacing of the horror genre, and he directs this familiar material with assurance, deftly punctuating the gore with judiciously timed shocks and laughs. Hopefully, though, Craven et al will now quit the Scream series while they are still ahead.
*** greg king http://www.netau.com.au/gregking
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Outpouring of love for boy, 15, found dead in woods
A village has been left grief-stricken following the news that a missing teenage boy was found dead in woodland.
The body of Scott Smith, 15, was found on Saturday at around 1.30pm following a search for the boy who had been missing for three days.
Police said his death is not being treated as suspicious and his heartbroken family are being looked after by specially trained officers.
Following the devastating news, Skirlaugh has united to pay tribute to the young boy who has received an ‘outpouring of love’ from the close-knit community.
Emotional tributes have since been pouring in on social media, with many expressing their shock and pain for Scott’s family.
On Sunday, villagers paid their respects to the teenager at St Augustine’s church and lit a candle in his honour.
Reverend Andy Simpson said: ‘We had a very full church service this morning for Scott, for visitors to pay their respects after a message was sent out for people to join us in a special service.
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‘It is still too soon to say anything, as this community is hurting, but what I will say there was very much an outpouring of love for this young man.’
Scott had not been seen since Thursday, November 21, and police launched a public appeal to help find him.
On Saturday, November 23, police were called to a remote woodland location on the outskirts of the village following an ‘incident’, where they found the boy’s body.
A cordon was put in place for several hours while police and forensic teams investigated the area and residents were advised to stay away from the scene.
He had been reported missing to the police on Thursday evening, after being last seen at about 5.30pm.
Got a story for Metro.co.uk?
Get in touch with our news team by emailing us at<EMAIL_ADDRESS>For more stories like this, check our news page.


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Next: merge, Previous: substitute, Up: Sequences Dictionary
concatenate
result-type &rest sequences ⇒ result-sequence
result-type—a sequence type specifier.
sequences—a sequence.
result-sequence—a proper sequence of type result-type.
concatenate returns a sequence that contains all the individual elements of all the sequences in the order that they are supplied. The sequence is of type result-type, which must be a subtype of type sequence.
All of the sequences are copied from; the result does not share any structure with any of the sequences. Therefore, if only one sequence is provided and it is of type result-type, concatenate is required to copy sequence rather than simply returning it.
It is an error if any element of the sequences cannot be an element of the sequence result.
[Reviewer Note by Barmar: Should signal?]
If the result-type is a subtype of list, the result will be a list.
If the result-type is a subtype of vector, then if the implementation can determine the element type specified for the result-type, the element type of the resulting array is the result of upgrading that element type; or, if the implementation can determine that the element type is unspecified (or *), the element type of the resulting array is t; otherwise, an error is signaled.
(concatenate 'string "all" " " "together" " " "now") ⇒ "all together now" (concatenate 'list "ABC" '(d e f) #(1 2 3) #*1011) ⇒ (#\A #\B #\C D E F 1 2 3 1 0 1 1) (concatenate 'list) ⇒ NIL
(concatenate '(vector * 2) "a" "bc") should signal an error
An error is signaled if the result-type is neither a recognizable subtype of list, nor a recognizable subtype of vector.
An error of type type-error should be signaled if result-type specifies the number of elements and the sum of sequences is different from that number.
Next: merge, Previous: substitute, Up: Sequences Dictionary


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In the time spent away from a computer screen, I enjoy watching sports, drinking a nice IPA, trying out new restaurants around town, or watching my favorite superhero film.


NEWS.md
param
argument of scrape()
is now softly deprecated. New argument query
is introduced. (closing #16)urltools
is removed in favor of native functions in httr
usethis
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for producing own polite scraping infrastructure is includedset_scrape_delay()
and set_rip_delay()
to adjust default scraping rate limithttr_rate_ltd()
out of bow()
(closing #9)html_attrs_dfr()
- function for tidying html_attrs()rip()
GET
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for overriding default data type and encoding


Module: ActiveRecord::ConnectionAdapters::MySQL::Quoting
Do not use. This module is for internal use only.
| Relationships & Source Files | |
| Extension / Inclusion / Inheritance Descendants | |
|
Included In:
| |
| Defined in: | activerecord/lib/active_record/connection_adapters/mysql/quoting.rb |
Constant Summary
-
COLUMN_NAME =
private
# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 93/ \A ( (?: # `table_name`.`column_name` | function(one or no argument) ((?:\w\.|`\w`\.)?(?:\w|`\w`)) | \w+\((?:|\g<2>)\) ) (?:(?:\sAS)?\s(?:\w|`\w`))? ) (?:\s*,\s*\g<1>)* \z /ix
-
COLUMN_NAME_WITH_ORDER =
private
# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 106/ \A ( (?: # `table_name`.`column_name` | function(one or no argument) ((?:\w\.|`\w`\.)?(?:\w|`\w`)) | \w+\((?:|\g<2>)\) ) (?:\sASC|\sDESC)? ) (?:\s*,\s*\g<1>)* \z /ix
-
QUOTED_COLUMN_NAMES =
# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 9Concurrent::Map.new
-
QUOTED_TABLE_NAMES =
# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 10Concurrent::Map.new
Instance Method Summary
Instance Method Details
#column_name_matcher
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 85
def column_name_matcher COLUMN_NAME end
#column_name_with_order_matcher
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 89
def column_name_with_order_matcher COLUMN_NAME_WITH_ORDER end
#quote_bound_value(value)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 12
def quote_bound_value(value) case value when Rational quote(value.to_f.to_s) when Numeric, ActiveSupport::Duration quote(value.to_s) when BigDecimal quote(value.to_s("F")) when true "'1'" when false "'0'" else quote(value) end end
#quote_column_name(name)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 29
def quote_column_name(name) QUOTED_COLUMN_NAMES[name] ||= "`#{super.gsub('`', '``')}`" end
#quote_table_name(name)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 33
def quote_table_name(name) QUOTED_TABLE_NAMES[name] ||= super.gsub(".", "`.`").freeze end
#quoted_binary(value)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 53
def quoted_binary(value) "x'#{value.hex}'" end
#quoted_date(value)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 45
def quoted_date(value) if supports_datetime_with_precision? super else super.sub(/\.\d{6}\z/, "") end end
#type_cast(value)
# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 67
def type_cast(value) # :nodoc: case value when ActiveSupport::TimeWithZone # We need to check explicitly for ActiveSupport::TimeWithZone because # we need to transform it to Time objects but we don't want to # transform Time objects to themselves. if ActiveRecord.default_timezone == :utc value.getutc else value.getlocal end when Date, Time value else super end end
#unquote_identifier(identifier)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 57
def unquote_identifier(identifier) if identifier && identifier.start_with?("`") identifier[1..-2] else identifier end end
#unquoted_false
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 41
def unquoted_false 0 end
#unquoted_true
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/mysql/quoting.rb', line 37
def unquoted_true 1 end


Lightning kills 3 ECD pupils in Goromonzi
Three Early Childhood Development (ECD) pupils at Rusike Primary School in Goromonzi died after they were struck by lightning on their way home from school on Tuesday afternoon.
Goromonzi District Civil Protection Department Chairperson, Prisca Dube confirmed the incident and said the fourth child who was injured was taken to Ruwa Rehabilitation Hospital for treatment.
More to follow…
zbc


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Nearest Storm Direction: {{forecast.nearestStormBearing}} Distance: {{forecast.nearestStormDistance}} mi


You can discover the webos by taking the Symbiose tour.
Customize your desktop to your liking!
Symbiose comes with a large number of apps.
Listen to your favorite music, everywhere.
Choose your favorite interface.
Use Dropbox, Google Drive and FTP right in your webos.


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Cohort exit criteria based on a fixed time period relative to initial event start or end date:
A cohort end date is derived from adding a number of days to be offset from the specified initial event date.
If an offset is added to the initial event start date, all cohort episodes will have the same fixed duration
(subject to further censoring from other cohort exit criteria). If an offset is added to the initial event end date,
persons in the cohort may have varying cohort duration times due to the varying durations of the initial events
(such as eras of persistent drug exposure or visit length of stay). This cohort exit criteria assures that the cohort
end date will be no greater than the selected index event date, plus the days offset.


Coming at these tasks through several channels causes a bit of confusion.
Many languages come into play and multiple formats for new initiates to juggle
may cause information to not sink in, as some balls are heavier than others,
there’s suddenly a beanbag, one ball is pointy somehow.
It is difficult to not turn the juggling of formats into
noise noise noise
noise noise noise
noise noise noise
but there is shelter in layers of attempts and successes and failures through multiple commits along the journey.
Not Journey, but a journey.
This is another type of noise, conceived by the author.
This is a learning experience, and it’s not as hard as drinking from this cup would be, or as making it was.


Quick example to show a scriptprocessor being used to generate white noise. The noise is random data, filled into a 4096 sample output buffer every time the callback function is called. The output of the scriptprocessor is connected to a BiquadFilter with cutoff and resonance controls, and the output of the filter is connected to the destination.


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Events
Take a look at the events we have brought to Native Alaskans in California.
Upcoming Events
Mar 23
11 AM - 5 PM
Culture Camp 2019
View Details ►
Past Events
Oct 12 – Oct 14
10 AM - 5 PM
Paddle Workshop 2018
See What Happened ►
Aug 31 - Sep 2
10AM - 5PM
Bentwood Box Class 2018
See What Happened ►
May 27
11 AM - 6 PM
Anacortes WA Culture Camp 2018
See What Happened ►
Mar 24
10:00 AM - 5:00 PM
Culture Camp 2018
See What Happened ►
Feb 16 - Feb 18
Cedar Hats
Cedar Hat Weaving Class 2018
See What Happened ►
Oct 6 - Oct 8
Canoe Paddles
3 Day Paddle Workshop 2017
See What Happened ►
JUL 28 - JUL 30
Moccasins
Moccasin Class 2017
See What Happened ►
May 19
Dance, Song, Culture, Food, History
Alaska Native Day 2017
See What Happened ►
Mar
Drums, Bags, Paddles, Weaving, Beads
Culture Camp 2017
See What Happened ►
Aug
Drums, Paddles
Culture Camp 2015
See What Happened ►


China: Capital outflows stayed in check in October – Standard Chartered
by Dhwani MehtaEconomists at Standard Chartered are out with their report on China’s capital outflows for the month of October.
Key Quotes:
“Our tracker shows only a marginal increase in non-FDI capital outflows in October as CNY strengthened.
Merchandise trade surplus widened as decline in exports eased; FDI and ODI largely evened out.
Overall cross-border flows stayed balanced; SAFE data indicates increasing incentive to keep FX.
Trade deal optimism likely limited rise in capital outflows.”


About us
A little information about our team and each of our members, so we get to know each other.
Vladimir Manov
Location: Varna
Studying: HTML, CSS, C#, JavaScript
Comment: I'm studying so i can live happily in my country that i love by doing something i love doing. I know that one day I'll achieve everything i ever dreamed of.
The world makes way for the man who knows where he is going
Nasko Daskalov
Location: Sofia
Studying: HTML, CSS, JavaScript
Comment: I am trying to learn new things every day and to involve them in my projects. In my free time I am trying to become better Front-end developer. Personal portfolio www.developine.eu. Also co-founder of CHECK MY LUCK TODAY.
Цвета Стоянова
Местоживеене: София
Изучава: HTML, CSS, WordPress и Търговия
Коментар: Уча Търговия в Университет за национално и световно стопанство. През свободното си време обичам да чета книги. Имам собствен блог - www.OurNerdyStuff.com.
Мария Георгиева
Местоживеене: София
Изучава: HTML, CSS, Marketing
Коментар: I am working in the Marketing field and in my free time I am studying to become a Web Designer.
Our Projects
New Books Release
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Mars Restaurant
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Fugit aliquam aperiam nulla perferendis dolor nobis numquam, rem expedita, aliquid optio, alias illum eaque. Non magni, voluptates quae, necessitatibus unde temporibus.
The world makes way for the man who knows where he is going.
- Ralph Waldo Emerson
Services
Ain't nobody on our level.Pick carefully who are your homies.
HTML Structured
We guarantee that our sites are correctly structured from head to toes, or from head to footer.
Fully Functional
The sites are fully functioning, except maybe the contact forms, but hey you can call us tho.
Responsive Design
Of course we are greedy for all points, so we make it all responsive, so it will look good on your iPhone10.
SEO Friendly
By doing the sites by the rules of structuring a correct html based website, we believe we will be kicking at google.
Web Design
It's all on us.I mean we may take an idea or two from somewhere else, but it's not that important, right?
Brand Design
We created our own brand.The logo is complex connection of many symbols connected to our team.
Testimonials
See what our lovely 'fake' testimonials have to say about us.
I'm really grateful to these guys.They deserve a lamborghini, a little island, or at least A+.
ZlatanIbrahimovic
Zurich Team Production once made my website.Now I'm a billionaire and a president of United States of America.
DonaldTrump
These guys are simply the best i have ever seen.All my colleagues should write them the maximum points, no matter what.
SvetlinNakov
Contact us
If you need to know anything else try to write us from the form down below(don't put too much fate on it).
Mladejka str. 55
Varna, 9000
<EMAIL_ADDRESS>+359 975 321