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Download SIM.JS, random.js¶
The current version of SIM.JS is 0.25.
The sim.js file contains the simulator kernel and includes the random.js library. You can also download the random.js library separately from the links below.
Both libraries are available as debug and release versions. The release version has stripped out code to check and validate arguments, and is minified (with Google’s Closure Compiler).
Download links (right-click and save):
- sim.js [
Debug version
] [Release version
] (includes random.js) - random.js [
Debug version
] [Release version
]
Source Code Access¶
The source code is hosted at code.google.com
: http://code.google.com/p/simjs-source/.
Use this command to anonymously check out the latest project source code:
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# Non-members may check out a read-only working copy anonymously over HTTP.
svn checkout http://simjs-source.googlecode.com/svn/trunk/ simjs-source-read-only
License¶
The SIM.JS library is licensed as Lesser GPL (LGPL).


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The RequiresMTAAttribute is used on a test method, class or assembly to specify that the tests should be run in the multi-threaded apartment. It causes creation of a new thread if the parent test is not already running in the MTA.
Note: On test methods, you may also use the MTAThreadAttribute. Although the runtime only recognizes this attribute on the entrypoint of an executable assembly, many users have expected it to work on tests, so we treat it as a synonym.
// An MTA thread will be created and used to run // all the tests in the assembly [assembly:RequiresMTA] ... // TestFixture requiring a separate thread [TestFixture, RequiresMTA] public class FixtureRequiringMTA { // An MTA thread will be created and all // tests in the fixture will run on it // unless the containing assembly is // already running on an MTA Thread } [TestFixture] public class AnotherFixture { [Test, RequiresMTA] public void TestRequiringMTA() { // A separate thread will be created for this test // unless the containing fixture is already running // in the MTA. } }


On 8 August 2019, 6 new articles were published in 6 journals.
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Review of David Lyon (2018). the Culture of Surveillance: Watching As A Way of Life


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At Hex Lighting We believe that our business should reflect and show the light of Christ. Which is why all of our customers recieve a bible upon purchasing a product. As christians it is our duty to encourage others to want to know God. In the Bible God tells us to shine our "light" and to tell others about him. We try to show God in our actions at our company, and We try to show others his love at every oppurtunity we get. Feel free to email us about any questions you have whether they be business or spirtual related.
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Neither do people light a lamp and put it under a bowl. Instead they put it on its stand, and it gives light to everyone in the house. In the same way, let your light shine before others, that they may see your good deeds and glorify your Father in heaven.


Yamaha TG33, SY22, and SY35
Single Patch Editor
This patch editor ought to work properly with all three synthesizers, but it has only been tested on the TG33. Please let me know of any discrepancies you discover.
Communicating with Edisyn
Set your synthesizer to receive and transmit on the same MIDI channel (perhaps Channel 1). Turn on Program Change and System Exclusive data. Turn off memory protect (on the SY22/SY35). The TG-33 also has a "device number": ideally this should be set to the same as the MIDI channel. You set both the device number and MIDI channel in Edisyn when connecting to the synthesizer via the Change MIDI menu.
Selecting the Synthesizer Type
Your choice of Synth Type in the Global panel will determine the waves available in Tones A and C (the SY35 is different), and will also determine the kind of sysex message used to send patches to the synthesizer (the TG33 is different). You need to make sure you have sent the Synth Type appropriately both prior to editing and prior to sending patches to your synth.
About the TG33 Menu
This menu has two additional options for you. Send Patch as Pseudo-MPE will prepare a Multimode patch for the TG33 (not the SY22 or SY35) which references this patch, both in current working memory. The Multimode patch will reference it in every single channel, which makes it easy to use MPE devices to play the patch. Note that you'll need to first put the unit into Multi mode manually (see "Gotchas" below). The name of the multimode patch will be the same as that currently in the single-mode patch editor. Receive Vector Data Only will only update Edisyn in response to vector data, not any other data. Thus if you load a file or if Edisyn receives a patch from the TG33/SY22/SY35, only the vector data portion will be updated. This might be useful for editing the vector on the synth manually, then loading it.
Gotchas
- Edisyn cannot write patches to patch memory locations on these units: you can only send them to the current working memory. From there, you will have to manually save them to an appropriate memory location if you like.
- If the SY22 or SY35 (not TG33) is in Edit mode, you cannot change patches. Thus in order to request a patch or to build an MPE patch, you must first manually exit Edit mode (just press the Voice button). Edisyn has a workaround for this bug on the TG33, but the workaround will likely not help the SY22 or SY35.
- The TG33, SY22, and SY35 are odd machines: they have many more parameters than are available from the front panel. Notably, all of them allow you to program both the carrier and modulator parameters of the FM tones, as well as the FM algorithm in question. So you will find rather more options here than expected.
- Only the TG33 can receive real-time parameter changes; and nearly all Modulator parameters and a few others cannot be sent. Furthermore, the TG33 is very slow in responding to real-time parameter changes.
- A number of parameters range from 0...99 on-screen, but in reality they range from 0...127 or 0...64 and are just mapped to 0...99. Edisyn uses the true mapping values; this means that when you change a number, it may not be the same on Edisyn as it says on the synth.
- The TG33 may occasionally get caught in a strange "Cannot Edit" warning message on-screen when receiving real-time parameter changes. You can get it out of this by selecting the voice and edit buttons again, or some similar combination.
Thanks
Thanks to Rich Hanson who allowed me to use some of his original source code to extract parameter values.
Thanks also to Ben Noble<EMAIL_ADDRESS>for his considerable assistance in debugging.
Thanks to Carlo Bandini<EMAIL_ADDRESS>for finding and helping to fix bugs in the SY22/SY35 patch code.
| By
| Sean Luke
|
| Date
| January 2020
|


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A
- Api - Interface in io.github.ma1uta.matrix.application.api
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Open API definition.
- ApplicationApi - Interface in io.github.ma1uta.matrix.application.api
-
Application service APIs which are used by the homeserver.
E
- events - Variable in class io.github.ma1uta.matrix.application.model.TransactionRequest
-
Required.
G
- getEvents() - Method in class io.github.ma1uta.matrix.application.model.TransactionRequest
- getVisibility() - Method in class io.github.ma1uta.matrix.application.model.RoomVisibility
I
- io.github.ma1uta.matrix.application - package io.github.ma1uta.matrix.application
-
Application API classes.
- io.github.ma1uta.matrix.application.api - package io.github.ma1uta.matrix.application.api
-
Application API interfaces.
- io.github.ma1uta.matrix.application.model - package io.github.ma1uta.matrix.application.model
-
Application API models.
L
- location(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ProtocolApi
-
Retrieve an array of third party network locations from a Matrix room alias.
- locationProtocol(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ProtocolApi
-
Retrieve a list of Matrix portal rooms that lead to the matched third party location.
P
- PRIVATE - Static variable in class io.github.ma1uta.matrix.application.api.RoomServiceApi.Visibility
- protocol(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ProtocolApi
-
This API is called by the homeserver when it wants to present clients with specific information about the various third party networks that an application service supports.
- ProtocolApi - Interface in io.github.ma1uta.matrix.application.api
-
Application services may declare which protocols they support via their registration configuration for the homeserver.
- PUBLIC - Static variable in class io.github.ma1uta.matrix.application.api.RoomServiceApi.Visibility
R
- rooms(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ApplicationApi
-
This endpoint is invoked by the homeserver on an application service to query the existence of a given room alias.
- RoomServiceApi - Interface in io.github.ma1uta.matrix.application.api
-
Application services can maintain their own room directories for their defined third party protocols.
- RoomServiceApi.Visibility - Class in io.github.ma1uta.matrix.application.api
-
Room visibility.
- RoomVisibility - Class in io.github.ma1uta.matrix.application.model
-
JSON body request of the room service api.
- RoomVisibility() - Constructor for class io.github.ma1uta.matrix.application.model.RoomVisibility
S
- setEvents(List<Event>) - Method in class io.github.ma1uta.matrix.application.model.TransactionRequest
- setVisibility(String) - Method in class io.github.ma1uta.matrix.application.model.RoomVisibility
T
- transaction(String, TransactionRequest, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ApplicationApi
-
This API is called by the homeserver when it wants to push an event (or batch of events) to the application service.
- TransactionRequest - Class in io.github.ma1uta.matrix.application.model
-
JSON body request of the transaction api.
- TransactionRequest() - Constructor for class io.github.ma1uta.matrix.application.model.TransactionRequest
U
- updateVisibility(String, String, RoomVisibility, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.RoomServiceApi
-
Updates the visibility of a given room on the application service's room directory.
- user(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ProtocolApi
-
Retrieve an array of third party users from a Matrix User ID.
- userProtocol(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ProtocolApi
-
This API is called by the homeserver in order to retrieve a Matrix User ID linked to a user on the third party network, given a set of user parameters.
- users(String, UriInfo, HttpHeaders, AsyncResponse) - Method in interface io.github.ma1uta.matrix.application.api.ApplicationApi
-
This endpoint is invoked by the homeserver on an application service to query the existence of a given user ID.
V
- visibility - Variable in class io.github.ma1uta.matrix.application.model.RoomVisibility
-
Required.
- Visibility() - Constructor for class io.github.ma1uta.matrix.application.api.RoomServiceApi.Visibility
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Big hug is a music-oriented, multimedia collaboration between the following artists:
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{% extends "base.html" %} {% block content %}
We're looking for the hamsterest hamster who ever hamstered.
Segment Miles is based on the 2.5 mile Gate to Gate segment, so it undercounts your mileage if you did a full lap. However, since this segment is the official measure of "A Hains Point Lap" as far as this contest is concerned, it was thought best to use 2.5 miles.
If you feel the wrong decision has been made here, please be reminded that you are a hamster, and hamsters don't get the admin password to the web server.
| Rank | Hamster | Times Hamstered | Segment Miles | Total Miles | Hamster % |
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| {{loop.index}} | {{a}} | {{b}} | {{b * 2.5}} | {{c|round(1)}} | {{((b*250)/c)|round(1)}} |


Please confirm that your Restriction information is still correct for this evacuation.
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{% extends 'layouts/layout-bsa-design-system.html' %} {% set active = "components" %} {% set activesub = "Cases" %} {% block pageTitle %} Cases - NHSBSA design system {% endblock %} {% block beforeContent %} {% include "includes/breadcrumbs__components.html" %} {% endblock %} {% block content %}
Some content about the cases component
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--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/Understanding.20Alist.html ---
https://github.com/leanprover-community/mathlib/blob/c28497fa056ae52b93aa9aca2fd20155d57fa016/src/data/list/alist.lean#L16 says that alist should have unique keys, but it in not clear to me how this is enforced. The alist.nodupkeys descructor is austensibly a proof that the keys are duplicated, but would this proof make more sense as a constuctor?
For example, #reduce alist.keys (list.to_alist [{2,3}, {4,2}, {2,4}])
gives list.map sigma.fst (list.erase_dupkeys._match_1 {2, 3} (list.erase_dupkeys._match_1 {4, 2} (list.erase_dupkeys._match_1 {2, 4} list.nil)))
, and #reduce (list.to_alist [{2,3}, {4,2}, {2,4}]).nodupkeys
triggers a memory consumption error (emacs).
in order to create an alist you need to provide an element of entries.nodupkeys, which is a proof that there are no duplicate keys
to_alist ensures this by calling erase_dupkeys, which removes all duplicates from the input
The structure
syntax is a helper for defining inductive types with a single constructor (TPiL section). As Marc says, to construct an alist
, you must supply both entries
and nodupkeys
.
By the way, unless you know what you're doing, you probably want to use #eval
instead of #reduce
for this kind of experimenting.
By the way, unless you know what you're doing, you probably want to use
#eval
instead of#reduce
for this kind of experimenting.
Ok, I'll use #eval
So suppose I were to omit using nodupkeys_erase_dupkeys in list.to_alist.
Then why does #check (alist.mk [{2,3}, {4,2}, {2,4}] _).nodupkeys
typecheck?
My understanding is that by using _
I am inferring a proof, which in this case should not exist.
Maybe the distinction is that running eval on this expressions produces don't know how to synthesize placeholder
.
The
structure
syntax is a helper for defining inductive types with a single constructor (TPiL section). As Marc says, to construct analist
, you must supply bothentries
andnodupkeys
.
My bad, nodupkeys
is in fact a constructor here, thanks.
So suppose I were to omit using nodupkeys_erase_dupkeys in list.to_alist.
Then why does#check (alist.mk [{2,3}, {4,2}, {2,4}] _).nodupkeys
typecheck?
If you look at the output of #check
you'll see a metavariable (?M_1
or something). #check
is displaying what the type would be, assuming you were to fill in all the placeholders that couldn't be filled in automatically.
if you do this in regular code, you'll get don't know how to synthesize placeholder
.
e.g.
abbreviation f : ℕ → Type := λ n, ℕ def xs : list (sigma f) := [⟨2,3⟩, ⟨4,2⟩, ⟨2,4⟩] def foo : alist f := alist.mk xs _
So suppose I were to omit using nodupkeys_erase_dupkeys in list.to_alist.
Then why does#check (alist.mk [{2,3}, {4,2}, {2,4}] _).nodupkeys
typecheck?
#check _ : 0 = 1
typechecks.
My bad,
nodupkeys
is in fact a constructor here, thanks.
structures only have a single constructor mk
. a value/proof of entries.nodupkeys
is a parameter to that constructor, not a constructor of alist
itself. one might also call it a projection ;)
This all makes sense. When I actually go to fill in the proof in the first place, I get the following error:
example : list.nodupkeys [sigma.mk 1 3, sigma.mk 2 4] := begin simp, exact eq.mp (ne.def 1 2) (nat.succ_ne_self 1).symm end
tactic failed, result contains meta-variables state: no goals
I think I read somewhere that simp should only be used in a finishing position but it seems that my alternative is a to use a long string of rewrites. Is this preferable?
The problem here is that Lean isn't inferring the type of sigma.mk 1 3
. It's of type sigma f
where f : nat -> Type
where f 1 = nat
and f 2 = nat
, but that's not enough to know f
is the constant function.
example : list.nodupkeys [(sigma.mk 1 3 : sigma (λ _, ℕ)), sigma.mk 2 4] := begin simp, exact eq.mp (ne.def 1 2) (nat.succ_ne_self 1).symm end
Great, I now have a working toy example:
#eval alist.keys (alist.mk [(sigma.mk 1 3 : sigma (λ _, ℕ)), sigma.mk 2 4] (by {simp; exact eq.mp (ne.def 1 2) (nat.succ_ne_self 1).symm}))
produces [1,2]
The following also works
#eval (alist.keys (alist.mk [(sigma.mk 1 [1] : sigma (λ _, list ℕ)), sigma.mk 2 [4,5]] (by {simp; exact eq.mp (ne.def 1 2) (nat.succ_ne_self 1).symm})))
So now my question is the following:
I plan on using assoc lists with natural numbers in the sigma.fst spot.
Is there a tactic that I can use that will take care of disequality proofs between nats when I first define an alist?
You can try dec_trivial
For proving specific disequalities like 1 ≠ 2
you can use norm_num
.
failed to synthesize type class instance for |- decidable (list.nodupkeys [<1,3>,<2,4>])
I think this means that I need to provide information that checking if for key duplicates is a decidable proposition.
dec_trivial points to of_as_true, which implicitly asks for a decidable proposition. Should I somehow provide decidable_eq nat
to @of_as_true
?
For proving specific disequalities like
1 ≠ 2
you can usenorm_num
.
#eval (alist.keys (alist.mk [(sigma.mk 1 [3] : sigma (λ _,list ℕ)), sigma.mk 2 [4]] (by norm_num)))
Woohoo!
But somehow not in this form??:
def a : list (sigma (λ _, list ℕ)) := [sigma.mk 1 [3], sigma.mk 2 [4]] #eval (alist.keys (alist.mk a (by norm_num)))
What kind of witchcraft is this?
But somehow not in this form??:
def a : list (sigma (λ _, list ℕ)) := [sigma.mk 1 [3], sigma.mk 2 [4]]
#eval (alist.keys (alist.mk a (by norm_num)))
What kind of witchcraft is this?
Nevermind, this works:
def a : list (sigma (λ _, list ℕ)) := [sigma.mk 1 [3], sigma.mk 2 [4]] #eval (alist.keys (alist.mk a (by rw a; norm_num)))
failed to synthesize type class instance for |- decidable (list.nodupkeys [<1,3>,<2,4>])
I think this means that I need to provide information that checking if for key duplicates is a decidable proposition.
That should be in mathlib, I guess it was missed. I'm sure list.nodup
already has a decidable instance, and alist.nodupkeys
is just a wrapper around that, so the proof should be easy
alternatively:
abbreviation a : list (sigma (λ _, list ℕ)) := [sigma.mk 1 [3], sigma.mk 2 [4]] #eval (alist.keys (alist.mk a (by norm_num)))
defs are semi-reducible (see https://leanprover.github.io/theorem_proving_in_lean/interacting_with_lean.html?highlight=semi%20reducible#elaboration-hints)
I would suggest norm_num [a]
instead of making it an abbreviation
also
#eval (let a : list (sigma (λ _, list ℕ)) := [sigma.mk 1 [3], sigma.mk 2 [4]] in (alist.keys (alist.mk a (by norm_num)))
works
alternatively:
abbreviation a : list (sigma (λ _, list ℕ)) := [sigma.mk 1 [3], sigma.mk 2 [4]]
#eval (alist.keys (alist.mk a (by norm_num)))
defs are semi-reducible (see https://leanprover.github.io/theorem_proving_in_lean/interacting_with_lean.html?highlight=semi%20reducible#elaboration-hints)
I read this section, but it does not mention the abbreviation keyword. Where is this documented?
I would suggest
norm_num [a]
instead of making it an abbreviation
Can I put a list of lemmas/definitions to rewrite with after any tactic?
I read this section, but it does not mention the abbreviation keyword. Where is this documented?
no idea, sebastian told me about it some day. you can also just tag the def as reducible instead
looks like it used to be in an old version of TPIL: https://leanprover.github.io/tutorial/tutorial.pdf
Consider the following alists:
def a : alist (λ (_:ℕ), ℕ) := alist.mk [sigma.mk 1 2, sigma.mk 2 3, sigma.mk 3 4] (by norm_num) def b : alist (λ (_:ℕ), list ℕ) := alist.mk [sigma.mk 1 [2], sigma.mk 2 [], sigma.mk 3 [1,2]] (by norm_num) #reduce (alist.replace 1 3 a) #reduce (alist.replace 1 [3] b)
Only the last line generates an error, saying that it failed to synthesize type class instance for decidable_eq or has_one. Looking at alist.replace and kreplace, I do not see any mention of decidability. Where is this coming from and how do I fix it?
What do you mean by alist.replace 1 [3] b
? Lean is trying to interpret this, and the errors are what it gets. What do you want it to mean?
You know about the implicit inputs to the function, right? If you hover over alist.replace
in VS Code you will see Π {α : Type u} {β : α → Type v} [_inst_1 : decidable_eq α]
. Lean is trying to figure out what alpha and beta are -- what do you think they are?
When I look for alist.replace I see the following:
def replace (a : α) (b : β a) (s : alist β) : alist β := ⟨kreplace a b s.entries, (kreplace_nodupkeys a b).2 s.nodupkeys⟩
In mathlib/src/data/list/alist.lean
But if you read the mathlib code then you don't see the variables. If you hover over the function then you'll see all the stuff I posted.
Alternatively try #check @alist.replace
The @ means "tell me all the details of all the inputs to this function, including the stuff which Lean is going to figure out by itself"
alist.replace : Π {α : Type u_1} {β : α → Type u_2} [_inst_1 : decidable_eq α] (a : α), β a → alist β → alist β
Lean says "ok I'll guess alpha, I'll guess beta, typeclass inference will guess _inst_1, now it's your turn"
You wrote alist.replace 1 [3] b
. Lean thinks "OK, so a is supposed to be 1, so alpha is some type which has a 1, gosh, there are lots of possibilities". Lean then gets [3] and thinks "Ok so beta 1 is supposed to be [3], I'll bear that in mind". Lean then gets b and thinks "OK so b must have type alist beta, but b definitely has type alist (λ (_:ℕ), list ℕ)
so beta must be (λ (_:ℕ), list ℕ)
. Hey this looks like it should work. I am now intrigued.
I can get a more helpful error message if I put
#check (alist.replace (1:ℕ) ([1]:list ℕ) b)
type mismatch at application alist.replace 1 [1] term [1] has type list var : Type but is expected to have type ?m_1 1 : Type ?
You should comment out those #reduce
s, they really slow things down. So here's how I would start debugging:
#check @alist.replace _ _ _ 1 [3] b
OK so indeed if we tell Lean what beta is, it works fine:
#check @alist.replace _ (λ (_:ℕ), list ℕ) _ 1 [3] b
So the problem is that Lean is failing to guess beta.
This is some issue with the elaborator and it's beyond my pay grade to solve it. I would just fix it with the @ trick and move on.
Great. +1 for showing how you would debug
FYI, same problem and solution for alist.insert
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


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h5. Heading 5
h6. Heading 6
This is a paragraph. For example,

should be wrapped as inline.
This is an item
This is an item
This is an item
This is a paragraph. For example,

should be wrapped as inline.


Click those rectangles and observer console. You should notice that events bubble up the DOM tree and not up the visual layers. In particular, even though green rectangle sticks out of the parent box the event is still bubbled up to the parent.


Export VIA3 Frame Level Video Annotations to COCO Format
This self contained HTML application can be used to export manual video annotations created using VIA3 to COCO format. Please follow the instructions below carefully as it is needed to allow your browser to quickly and easily export video frames and its associated annotations. This application has only been tested to work in Firefox 68.9.0 (or higher).
Ensure that:
Copy this HTML application file (i.e. via3_video_annotation_to_coco.html) to the $TARGER_DIR (e.g. /data/annotation/via3_video_annotation_to_coco.html). Open the newly copied HTML application using a Firefox Web Browser version 68.9.0 (or higher).
Copy all video files referenced in VIA3 project to a folder $TARGET_DIR (e.g. /data/annotation/). This allows the HTML application to access all video files referenced in the VIA3 project.
(for Google Chrome, you have to start chrome browser from command line with as follows:/usr/bin/google-chrome-stable --allow-file-access-from-files). This allows the Firefox web browser to access all the video files present in the folder that contains the HTML application file.
In Firefox browser, enable automatically save downloaded files. Open Preferences → Files and Applications and set "Save files to" a folder of your choice (e.g. Downloads). This avoids the requirement to confirm each downloaded file.
Allow your web browser to access files in local folder. More details are available here:
Mozilla Firefox (68.9.0+) : enter about:config in address bar and set privacy.file_unique_origin = false
Google Chrome (83.0.4103.106+) : close all existing Chrome browser windows and start the Chrome browser from command line with as follows: /usr/bin/google-chrome-stable --allow-file-access-from-files
Enter a VIA3 shared project-id , or select a local VIA3 project file
Only polygon and rectangle regions defined in your project get exported in COCO format.
Region attributes of type RADIO and SELECT are only included in the exported COCO annotations.


Story Synth is designed to be adapted to new types of storytelling games with novel mechanics. The framework is open sourced under an MIT License and you’re free to do almost anything you want with it. Check out the Story Synth codebase on GitHub.
Whether you're doing a small extension of the app by tweaking the sheet template or attempting a more drastic hack, I recommend you get familiar with the Vue.js documentation. Vue.js is incredibly powerful and fairly quick to use, once you’re up to speed.
The code for the homepage and room selector live in /components/RoomPicker.vue – if you’re in a game room, then the RoomPicker just shows the current URL and number of players on the page.
The main code for each game lives in that template’s .vue file in the /component folder.
As Story Synth progresses, I hope to add much more to this section. Until then, feel free to reach out with any questions: randy@storysynth.com


*If you haven’t already used this week’s already, get the app and unlock it.
This is your home’s Takeaway Whoop! It’s your gateway to exclusive prices from your home’s handpicked takeaways
Stop searching for great takeaway deals. We’ve allocated your home with a Whoop! Menu which includes exclusive prices from popular takeaways
Find out about Team Whoop!We work at exclusive prices with all of your home’s preferred takeaways
Find out more about prices hereInstall the free Whoop! Button App and unlock your home’s Whoop Button with your address
Unlock your home’s takeaway Whoop!
View your home’s Whoop! Menu for this week and show your QR code or quote your Whoop! code when ordering


Test designed to run on localhost (minimize impact from network latency)
This should NOT be parsed automatically
If this has a different background and a red border, the page parsed when it shouldn't
Testing ContentPane
Even tough the entire page isn't scanned for widgets,
any sub widgets of a ContentPane will be created when a ContentPane is created This should have a backgroundcolor and a border


Prince Andrew stops royal duties with Queen's approval over Jeffrey Epstein friendship
The Duke of York released a statement addressing criticism over his friendship with sex offender Jeffrey Epstein
by Jenny KirkhamPrince Andrew was given permission from The Queen to step back from public duties over the ongoing Jeffrey Epstein controversy.
The Duke of York issued a statement to say he would be taking a break "for the foreseeable future” amid criticism over his relationship with Epstein.
We'll be bringing you the very latest updates, pictures and video on this breaking news story.
For the latest news and breaking news visit http://www.liverpoolecho.co.uk/news/.
Get all the big headlines, pictures, analysis, opinion and video on the stories that matter to you.
Follow us on Twitter @LivECHONews - the official Liverpool ECHO Twitter account - real news in real time.
We're also on Facebook/theliverpoolecho - your must-see news, features, videos and pictures throughout the day from the Liverpool ECHO.


Using
roll.js
in html canvas.
← Move the mouse around on the canvas to start.
Demo code
· Made with
pt.js


@(Where to send it?)
@(Please choose an app from the below list where to send the screenshot.)
@(SEND)


In this article we will walk through installing and the ins-and-outs of Contacts. Contacts is a lightweight application that allows users to add and organize their friends' contact information.
This tutorial describes:
Installing and running the application
The application's structure and organization
Dividing the application into modular widgets
Tieing the widgets together
Let's get started!
Setup
The application source is hosted by GitHub. You can download the application on github using the following commands:
To run the application, open contacts.html with your browser. We will be using fixtures to simulate the AJAX requests so running it from a server isn’t necessary.
This will run the application in development mode. If you want to build and run the application in production, in the command line run:
$ ./js contacts/scripts/build.js
then change the script tag in contacts.html to be in production mode:
Additionally, the app can be found on Github Pages if you do not want to set it up.
Folder Structure
The application resides in the contacts folder. Steal, CanJS, and CanUI folders sit perpendicular to this for reuse in other projects. The directory structure should mirror below.
less LESS stylesheet such as Boostrap 3.0 and contacts.less
contacts/form child components of contacts
Along with runners and scripts for building and tests.
Division of Modules
The secret to building large applications is NEVER build large applications. Understanding how to divide and isolate modules in the application is the first step towards maintainable architecture.
The goal for dividing your application should be to create modules that are isolated.
Isolated modules are:
Limited to one specific purpose, for example showing a list of data
Rarely reference other modules and never their parents
Have a simple generic API making them easy to swap out
Isolated modules are easily testable because they have a small, well defined scope. Each piece can be worked on in parallel because the code is divided. Reuse is easier because the modules are not coupled to each other.
Dividing Contacts
The contacts app has 3 lists that filter the grid of contacts. You can create additional categories and contacts by clicking the 'new' icon.
This application can be divided up into a few widgets:
List - accepts a generic data source and layout, renders and updates the list.
Grid - accepts a generic data source, renders a grid.
Form - create a new instance from a data source.
Heres a visual representation of how this app is broken up into modules.
Tying it all together
contacts/contacts.js will be where the application starts: loading each module, initializing them, and gluing them together.
In the init method, we initalize all the base objects and inject the base view.
init: function(){
// initalize the lists and objects
this.categoryList = new Models.Category.List;
this.locationList = new Models.Location.List;
this.companyList = new Models.Company.List;
this.contactsList = new Models.Contact.List;
this.edited = new Observe;
this.total = can.compute(0);
this.isLoading = can.compute(function(loading){
loading ? loadingCounter++ : loadingCounter--;
return loading > 0;
});
// Draw the view, setup helpers and partials
this.element.html(initView({ ... });
// Initalize each Form category
can.each(['location', 'category',
'company', 'contact'], function(formType){
new Form(this.element.find('#' + formType), {
edited : this.edited,
model : Models[can.capitalize(formType)],
list : this[formType + 'List']
});
}.bind(this));
this.setupScroll();
this.loadFilters();
this.loadContacts();
}
From this point on, the application uses live-binding to update the lists/views based on the filter/offset.
{{#contacts}}
{{>contact}}
{{/contacts}}
As the contacts list changes, the view automatically updates to reflect the new list.
Wrapup
In this article, we explored:
Installing and running the application
The application's structure and organization
Dividing the application into modular widgets
Tieing the widgets together
If you're interested in other examples, check out the other application examples.
In this article we will walk through installing and the ins-and-outs of Contacts. Contacts is a lightweight application that allows users to add and organize their friends' contact information.
This tutorial describes:
Let's get started!
Setup
The application source is hosted by GitHub. You can download the application on github using the following commands:
To run the application, open contacts.html with your browser. We will be using fixtures to simulate the AJAX requests so running it from a server isn’t necessary.
This will run the application in development mode. If you want to build and run the application in production, in the command line run:
then change the script tag in
contacts.html
to be in production mode:Additionally, the app can be found on Github Pages if you do not want to set it up.
Folder Structure
The application resides in the
contacts
folder. Steal, CanJS, and CanUI folders sit perpendicular to this for reuse in other projects. The directory structure should mirror below.The contacts folder contains:
models
AJAX end-point definitions and helpersviews
EJS/Mustache can.view templatesfixtures
simulated AJAX responseless
LESS stylesheet such as Boostrap 3.0 andcontacts.less
contacts/form
child components of contactsAlong with runners and scripts for building and tests.
Division of Modules
The secret to building large applications is NEVER build large applications. Understanding how to divide and isolate modules in the application is the first step towards maintainable architecture.
The goal for dividing your application should be to create modules that are isolated.
Isolated modules are:
Isolated modules are easily testable because they have a small, well defined scope. Each piece can be worked on in parallel because the code is divided. Reuse is easier because the modules are not coupled to each other.
Dividing Contacts
The contacts app has 3 lists that filter the grid of contacts. You can create additional categories and contacts by clicking the 'new' icon.
This application can be divided up into a few widgets:
Heres a visual representation of how this app is broken up into modules.
Tying it all together
contacts/contacts.js
will be where the application starts: loading each module, initializing them, and gluing them together.In the
init
method, we initalize all the base objects and inject the base view.From this point on, the application uses live-binding to update the lists/views based on the filter/offset.
As the
contacts
list changes, the view automatically updates to reflect the new list.Wrapup
In this article, we explored:
If you're interested in other examples, check out the other application examples.


Talks restart on 'eyesore' Crossways centre at Paignton
Torbay Council is trying to reach a deal to buy the centre so it can get on with proposals to redevelop the site
by Edward OldfieldTorbay Council has restarted talks with the owner of the run-down Crossways shopping centre in Paignton in an effort to speed up regeneration plans.
The council is trying to reach a deal to buy the centre so it can get on with proposals to redevelop the site.
It has now requested an independent valuation of the property to form the basis of negotiations with the owner.
Agreeing a deal on the price would be quicker than opting for compulsory purchase, a legal process which could take up to 18 months.
In September councillors gave senior officers powers to start the compulsory purchase if necessary.
A meeting of Torbay Council heard that it would provide a back-up if negotiations with the owner failed.
Plans have been put forward to redevelop the near-empty concrete complex with an estimated £22.5m scheme.
It would include shops on the ground floor and "extra-care" affordable housing on the upper levels.
The shopping centre has a walkway which links Torquay Road and Hyde Road, but most of the shops are now empty and it has been described as an eyesore.
The site has been zoned for redevelopment in local planning policies in recent years but the owner Gaelic Investments has so far held on to it.
Councillors were told at a meeting it September that the owner said early this year it had its own redevelopment plans.
But because there was no sign of progress, such as a planning application, the council was now intending to get on with the job.
A report said officers would restart talks with the owner to buy the land while preparing the compulsory purchase order as a back-up.
A planning application for the site would also be brought forward, councillors heard.


Blue IT Marketing
Developing Intelligent Business & Marketing Solutions for you
Blue IT Marketing Business Software Products
We are experienced in developing Server Based Point of Sale and Business Management Solutions for the SME, specifically Retail Shops on the following sectors:
- Hardware Shops
- Electrical, Plumbing, Motor Spare Parts Dealers
- Bottle Stores
- Super Markets
- Clothing Shops
This Application helps users manage small to medium sized businesses in the Funeral Industry, there are several modules available in the application some of which helps out clients to:
- Capture and Process Client Information, Create Digital Forms for the client and Policy/Cover Documents.
- Helps with Premium Payments for the Policy/Cover with Reminders that are automatically sent to the client and members of the administration team through SMS, and or Email.
- Helps with the overall financial reporting for the business, by showing daily, weekly and monthly financial reports and also making them easily accessible to the members of the management team.
- Helps with customer/client support by creating reports of all the outstanding problems that needs the attention of either management staff or Client Support Team.
- Client Claim Processing Module enabling members of the staff to process claims on covers
- Payment Reminders and also Payment Verification messages by SMS
- Contact and Messaging Management Allowing for the Marketing to send Marketing and Promotional Messages to their Clients, or for the management team to be able to send reports, and job cards to their staff members.
- Employee Management Module, with integrated application User Access Control, Pay-Slip Processing, Leave Forms and Processing.
- Business Financial Reporting for the Management staff.
This Application is targeted to small and medium sized financial companies that offers micro loans to the public, our Application helps Loan Company, staff to do the following:
- Capture and Process Client Information, Create Digital Documents for the client and also allows for easy access to client files.
- Helps with Loan Repayments by Creating Reports Based on Repayments dates, and also able to send automated reminders to clients, and Process Debit Orders.
- Complete Financial Reporting allowing the manager or owner easy access to the right report at the right time.
- Marketing Module that helps users/employees to easily collect potential client information on site with employees in the office processing those applications(Screening) at the same time and also able to send messages informing those potential clients if they can access their loan facilities.
- Client Repayment Module that helps by sending (SMS) Payment Reminders to clients and also create daily collection reports for members of the staff responsible with payment collections.
- Loan Processing and Approval, with payment notifications being sent in real time to companies financial officers for loan payments.
- Contact and Messaging Management Allowing Staff members easy access to messaging facilities that can be used for anything from, sending Marketing Messages, Mass(General) Payment Reminders, Birthday Messages, and Staff Messages for sending Job Cards and also for assignment reminders.
- Android Loan Applications useful for Clients, which can be used for anything from, Loan Applications, and Repayments, and easy access to company messages and also Promotional Materials from your Financial Institution.
- Employee Management Module, with integrated application User Access Control, Pay-Slip Processing, Leave Forms and Processing.
- Business Financial Reporting for the Management staff.
Our Hotel and Lodge Management Software gives you easy access to modules that makes it easier for you to manage your lodge or hotel, Modules included makes it possible for you to:
- Capture Clients and Company Clients Personal Information and Contact Information
- Create Room Booking Schedules for up to 2 years in advance.
- Easily Create a Booking Quotation and also send it to the client through email from the application, The Quotation itself will remain hosted in the application for secure Quotation Access, and also for future reference.
- Automatic invoice Creation on payment, and also the ability to recall any invoice at any time from the database allows for perfect record keeping and thereby also improves client satisfaction.
- Ability to Send Messages to your client, this makes it easier for management staff to send notifications to the client without having to actually disturb the client if the client is in their rooms, the notification system can also be used for payment reminders, at or near the time the client is expected to vacate their rooms.
- A Central Client Account System that allows for your staff to quickly check if the client owes your business any money before they checkout or vacate the premises.
- A Small Integrated Kiosk allowing your hotel and or lodge to sell refreshments, breakfast, dinner, and lunch straight from the application and also process payments, the kiosk system is integrated with an inventory control for the management staff, and also the Kitchen interface that shows your employees orders as they are placed on the system in real time.
- Venue Management with an ability to add and remove rooms, and also an ability to set general prices for venues and also venue capacity.
- Venue Management also allows you to place a venue under reservations and also with an ability to create a booking schedule for up to a year in advance.
- Client Module allows you to also create packages for a client allowing you to place multiple bookings under one client, at different times and also for different rooms, all under one invoice and quotation, the package system is useful for company conferences and other events like that.
- Contact and Messaging Module, allowing for easy Messaging and Contact management for important business contacts.
- Bulk Messaging System allowing for both Email and SMS Messaging this makes it possible for your institution to send Bulk Marketing Messages to potential clients and existing clients in an easy to use environment.
- Employee Management Module integrated with an Account Control System, Pay-Slip Processing and attendance Register for your employees.
- Easy to use business reporting module with an ability to recall or create any kind of report from your integrated database system.
Contact and Messaging Management Application is an application that allows you to:
- Easily Create update and manage your business contacts, client contacts, Employees contacts.
- An Ability to send messages and track responses to such messages either to a single number or in bulk, the modules can easily be used as a way to conduct a quick survey, or for completing and inline form for purposes such as (Loan Applications, Client Feedback and more), also for sending bulk marketing or promotional messages to potential clients.
- Our Contact Management module also gives you access to an easy to use note system that allows you to keep track of notes related to each of your clients.
- Our Messaging Module for single clients also allows for your employees to make phone calls and record contact responses in a call center like style thereby making it possible to have a record or transcript of Contact Communications even when that contact has been placed as a voice call.
- Ability to create a complete contact report with all the messages ever exchanged between the client and the institution or company using our contact and messaging module.
- Ability to create a complete communication reporting file, with information such as SMS Messages sent and received, Email Messages Sent and Received, Phone Calls made and transcripts of such calls.
Church Admin, a web application intended to simplify management tasks that are often encountered in Churches. Church Admin makes it possible for your congregation to function properly at all times, and for all members to be kept updated on anything that concerns them, their fellow congregants, and thereby enabling the whole congregation to function together as one family. It also simplifies processes and procedure that are performed by any church administrator, with its highly secured and always on database technology thereby allowing for capturing and quick reporting of:
- Event Management Module, Offers you the ability to plan, manage, and promote your church events in a one easy to use module, which also contains attendee registrations, and preferences section.
- Forums, A module allowing your church to host discussion forums based around church activities, and also enabling your church to publish and promote church events, to a larger online community. Our forums support video and audio uploading.
- Church Branch Management, Easy access to all branch management tasks, including, congregants, employees, suppliers, donators, service providers and branch finances and reporting.
- Sermons, Church Sermons allows for the preparations of upcoming church sermons, and also the ability to go through previous church sermons, the module contains an integrated KJV Bible, for easy access and preparations.
- Meetings , The Meetings Module allows for an easy way to create, and manage church meetings, our module also contains and inbuilt meeting reminder system that easily reminds meeting attendees of the meeting subject, venue, date and time of meeting. The module also allows for meeting attendees an easy access to detailed meeting agenda through its inbuilt published meeting page, which is sent together with a meeting reminder.
- Contacts Management Module, General Contact Management and messaging module, allowing your church to manage contact details and also manage communications with important church contacts such as community leaders, committee members of other churches and organizations. Our contact and messaging module mean that you will always be able to keep in touch and never forget what was said in that important communique.
- Newsletters, an easy to use module allowing for the creation of Church Publications and also the distribution of newsletters to various members of the congregation, newsletters can also be promoted amongst members of the general public and those from other congregations. Newsletters are more useful for purposes such as :
- Job Newsletters, geared towards the youth with materials such as job interview openings, and how to properly conduct and interview
- Parenting, a Newsletter geared towards parents offering education, tips and support to parents within the congregations
- Any member of the Church can run a ZNewsletter within Church Admin...
- Birthdays and Calendar Events, This module allows for the creation of well-wishing messages, to the members of the congregation, for important calendar events, such as birthdays, Christmas day, Good Friday, school holidays, and exam periods... The module can run automatically and communicates the right message to the right person without any other user intervention, except setting the messages up of course.
- Bulk SMS Module, this module makes it easy to create general and special list of contacts and send them messages in bulk, for example:
- Emergency Messages, that concern the whole congregation can be easily distributed by making use of our Bulk SMS Module
- Church Committee Messages, Another list can contain members of the church committee and important messages will then be sent to all church committee members at the same time.
- Our Bulk Messaging Utility also contains a scheduling feature allowing you to easily create a message and then schedule that message to be sent later to its intended recipients.
- Employee Management System, allows companies to manage their employee information and also able to:
- Create Employee Labour Files, Ability to process and Print Pay-Slips for your employees, complete with monthly deductions and hours Worked.
- An Attendance Register Module allowing for paperless attendance register marking, that is automatically used in pay calculations in your pay-slip module.
- Leave Module, with labor compliant calculations and applications and approval.
- Employee Messaging Module with an ability to send Pay Notifications Overtime Notifications, Important Announcements, Job Cards, and Assignment reminders and notifications.
Our School Management System is an application that makes it possible for teachers to spend less time doing management tasks and more time actually teaching and helping their learners with their school work.
Our School Management System includes the following modules.
- Learner Personal and Contact Information Module, making it possible for the School to Capture complete personal details of students and also have the ability to report on that information at any time.
- Teacher Personal and Contact Information Module, allowing for the capture of each teacher personal information and reporting.
- Parents Personal and Contact Information Module for capturing parent’s details, and also for reporting details.
- Leaner Registered Subjects Module making it possible for Learners and Parents to access their School Timetables, School Reports, and also Exam Schedules.
- School Educational Forums, for leaners and teachers to exchange school works, Exam Papers, Exam Tips, Homework, and if possible extra educational material available online. Basically a learner or teacher can do a research on a specific topic and then upload that research in your schools educational forum allowing your learners access to such material and also promoting discussions on certain aspects of the research.
- School Event Managements, a module allowing for your school to organize school events, solve problems on logistics, allocate speakers to agendas, organize their event sponsors, and enable easy resource organization and scheduling through an online note system attached to events. An ability to send confirmation messages to event attendees, speakers, sponsors, exhibitors and organizers.
- Meetings Module, to easily organize school meetings involving learners, teachers, school governing bodies, and principals and general staff. The meeting module is able to send automated reminders for meeting venues and dates. And also allows access to meeting agendas, and also minutes and resolutions of such meetings after the meeting.
- Contact Management and Messaging Module, to easily create manage and organize contacts and messaging sent to such contacts, the module allows for easy messaging and response tracking.
- Employee Management, to easily manage school employees, create their pay-slips, and attendance register, send employee notifications and salary notifications.
- Suppliers and Service Providers Module. Enabling your school to capture details of their service provider’s payment methods and also details of the products and services they provide, this makes it simpler to organize school events, and functions, and also to hire contractors that are known to the school. The module also allows for recoding keeping of any contract work that was done on school premises and also payment tracking.
- Assets Tracking and Management. School Assets modules allows your school to keep track of their assets and also track them.
- Optional Library Module. For easy to use library management system fully accessible by school staff, learners and teachers, the module makes it easier for students to hire books, and for the school to keep track of who has which book at all times.
Blog
- Article


|
Sense Android Library
2.7.0
Android library project for the Sense Platform
|
Public Member Functions | |
| FFT (int timeSize, float sampleRate) | |
| void | scaleBand (int i, float s) |
| void | setBand (int i, float a) |
| void | forward (float[] buffer) |
| void | forward (float[] buffReal, float[] buffImag) |
| void | inverse (float[] buffer) |
| Public Member Functions inherited from nl.sense_os.service.ambience.FourierTransform | |
| void | noAverages () |
| void | linAverages (int numAvg) |
| void | logAverages (int minBandwidth, int bandsPerOctave) |
| void | window (int which) |
| int | timeSize () |
| int | specSize () |
| float | getBand (int i) |
| float | getBandWidth () |
| int | freqToIndex (float freq) |
| float | indexToFreq (int i) |
| float | getAverageCenterFrequency (int i) |
| float | getFreq (float freq) |
| void | setFreq (float freq, float a) |
| void | scaleFreq (float freq, float s) |
| int | avgSize () |
| float | getAvg (int i) |
| float | calcAvg (float lowFreq, float hiFreq) |
| void | forward (float[] buffer, int startAt) |
| void | inverse (float[] freqReal, float[] freqImag, float[] buffer) |
| float[] | getSpectrum () |
| float[] | getRealPart () |
| float[] | getImaginaryPart () |
Protected Member Functions | |
| void | allocateArrays () |
| Protected Member Functions inherited from nl.sense_os.service.ambience.FourierTransform | |
| void | setComplex (float[] r, float[] i) |
| void | fillSpectrum () |
| void | doWindow (float[] samples) |
| void | hamming (float[] samples) |
Additional Inherited Members | |
| Static Public Attributes inherited from nl.sense_os.service.ambience.FourierTransform | |
| static final int | NONE = 0 |
| static final int | HAMMING = 1 |
| Protected Attributes inherited from nl.sense_os.service.ambience.FourierTransform | |
| int | timeSize |
| int | sampleRate |
| float | bandWidth |
| int | whichWindow |
| float[] | real |
| float[] | imag |
| float[] | spectrum |
| float[] | averages |
| int | whichAverage |
| int | octaves |
| int | avgPerOctave |
| Static Protected Attributes inherited from nl.sense_os.service.ambience.FourierTransform | |
| static final int | LINAVG = 2 |
| static final int | LOGAVG = 3 |
| static final int | NOAVG = 4 |
| static final float | TWO_PI = (float) (2 * Math.PI) |
FFT stands for Fast Fourier Transform. It is an efficient way to calculate the Complex Discrete Fourier Transform. There is not much to say about this class other than the fact that when you want to analyze the spectrum of an audio buffer you will almost always use this class. One restriction of this class is that the audio buffers you want to analyze must have a length that is a power of two. If you try to construct an FFT with a timeSize
that is not a power of two, an IllegalArgumentException will be thrown.
| nl.sense_os.service.ambience.FFT.FFT | ( | int | timeSize, |
| float | sampleRate | ||
| ) |
Constructs an FFT that will accept sample buffers that are timeSize
long and have been recorded with a sample rate of sampleRate
. timeSize
must be a power of two. This will throw an exception if it is not.
| timeSize | the length of the sample buffers you will be analyzing |
| sampleRate | the sample rate of the audio you will be analyzing |
|
virtual |
Performs a forward transform on buffer
.
| buffer | the buffer to analyze |
Implements nl.sense_os.service.ambience.FourierTransform.
| void nl.sense_os.service.ambience.FFT.forward | ( | float[] | buffReal, |
| float[] | buffImag | ||
| ) |
Performs a forward transform on the passed buffers.
| buffReal | the real part of the time domain signal to transform |
| buffImag | the imaginary part of the time domain signal to transform |
|
virtual |
Performs an inverse transform of the frequency spectrum and places the result in buffer
.
| buffer | the buffer to place the result of the inverse transform in |
Implements nl.sense_os.service.ambience.FourierTransform.
|
virtual |
Scales the amplitude of the ith
frequency band by s
. You can use this to shape the spectrum before using inverse()
.
| i | the frequency band to modify |
| s | the scaling factor |
Implements nl.sense_os.service.ambience.FourierTransform.
|
virtual |
Sets the amplitude of the ith
frequency band to a
. You can use this to shape the spectrum before using inverse()
.
| i | the frequency band to modify |
| a | the new amplitude |
Implements nl.sense_os.service.ambience.FourierTransform.


Watch: Makers of ‘Pagalpanti’ offer another dose of madness with a new teaser
by TIMESOFINDIA.COMSince the release date of the John Abraham starrer ‘Pagalpanti’ is coming close, the makers are doing everything to keep the audience engaged. As a step in the same direction they have got the fans hooked with a new teaser of the film.
Featuring the craziness of the lead cast - John Abraham, Pulkit Samrat and Arshad Warsi, the new teaser is packed with full entertainment. Illeana D’Cruz who will be seen as one of the female leads in the movie, took to her social media handle to share the teaser. Check it out here:
Directed by Anees Bazmee ‘Pagalpanti’ is a Bhushan Kumar and Krishan Kumar production. This laughter packed comedy flick is scheduled to make it to the big screens on November 22nd.


Spotify Web Playback SDK Quick Start Tutorial
Open your console log:
View > Developer > JavaScript Console


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You conjure a phantom watchdog in an unoccupied space that you can see within range, where it remains for the duration, until you dismiss it as an action, or until you move more than 100 feet away from it.
The hound is invisible to all creatures except you and can't be harmed. When a Small or larger creature comes within 30 feet of it without first speaking the password that you specify when you cast this spell, the hound starts barking loudly. The hound sees invisible creatures and can see into the Ethereal Plane. It ignores illusions.
At the start of each of your turns, the hound attempts to bite one creature within 5 feet of it that is hostile to you. The hound's attack bonus is equal to your spellcasting ability modifier + your proficiency bonus.
On a hit, it deals 4d8 piercing damage.


Instrument Type
Entries
Functions
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Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)
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Returns an array containing the constants of this enum type, in the order they're declared.


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We could certainly build peer relationships with anywise DIDs based on a public ledger or a similar source of truth. However, in the same way that a company doesn't want the public to resolve private host names inside its corporate intranet, letting others resolve pairwise and n-wise DIDs is unnecessary, and it represents a privacy and security risk as well as a problem of cost, scale, and performance. We strongly recommend that peer DIDs be used for peer relationships.
In a similar vein, peer DIDs could be used, hypothetically, for anywise scenarios. The main disadvantage would be the lack of a formal publication mechanism. Nothing would prevent a user from publishing a peer DID and its associated DID document on a website. However, information published in this way would be hard to discover, maintain as DID docs evolved, and integrate into interoperable applications. DID methods that use a public ledger or a similar source of truth are a better choice here, because they have authoritative answers to the publication problem.
did:key
and did:nacl
The did:key and did:nacl methods encode a public
key directly as a DID value, and generate a very simple DID Doc in a deterministic way from that key. The only
material that has to be generated or stored when using this method is the public key or DID itself; either
can derive the other and the DID Doc. Using a did:key
or did:nacl
is very similar to
sharing and then using a public SSH key.
The benefit of these methods is their simplicity. Like peer DIDs, they have no dependence on an external source of truth, and they can be implemented in code with little effort. Like peer DIDs, they are cheap to create and use.
However, did:key
and did:nacl
are not direct equivalent of peer DIDs. Here are some
features of peer DIDs that they do not provide:
Peer DIDs use a layering approach so the complexity of key rotation and updates need not be supported if only
static, ephemeral use cases matter. This is the main complexity difference between peer DIDs and these other
two methods, and is optional with peer DIDs. Peer DIDs also use multicodec to encode keys in the same way that
did:key
does. The hope is that these two methods will remain as similar as possible, and that
Peer DIDs will be a logical upgrade choice when use cases go beyond those that did:key
and
did:nacl
are designed to handle.


Authors
{% bootstrap_messages %}Add all the authors of your paper and put them in correct order using drag-and-drop. This list of authors will be used in program preparation, so if you miss some of your co-authors, they will not be listed in the program.
Please note that you MUST be a co-author to add a paper. If you are not an author, please and ask one of the authors to register and upload the paper instead of you.


|
Smartlock
|
DMA transfer configuration structure. More...
#include <fsl_dma.h>
Data Fields | |
| uint32_t | srcAddr |
| uint32_t | destAddr |
| bool | enableSrcIncrement |
| dma_transfer_size_t | srcSize |
| bool | enableDestIncrement |
| dma_transfer_size_t | destSize |
| uint32_t | transferSize |
DMA transfer configuration structure.
| uint32_t destAddr |
DMA destination address.
| dma_transfer_size_t destSize |
Destination transfer unit.
| bool enableDestIncrement |
Destination address increase after each transfer.
| bool enableSrcIncrement |
Source address increase after each transfer.
| uint32_t srcAddr |
DMA transfer source address.
| dma_transfer_size_t srcSize |
Source transfer size unit.
| uint32_t transferSize |
The number of bytes to be transferred.


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| html_fragment {rmarkdown} | R Documentation |
An html fragment is suitable for inclusion into an external html page. See
html_document
for full details - this is a minor variation that
assumes you will include the output into an existing document (e.g. a blog
post).
html_fragment( number_sections = FALSE, section_divs = TRUE, fig_width = 7, fig_height = 5, fig_retina = 2, fig_caption = TRUE, dev = "png", df_print = "default", mathjax = TRUE, includes = NULL, keep_md = FALSE, md_extensions = NULL, pandoc_args = NULL, ... )
number_sections |
|
section_divs |
Wrap sections in <div> tags, and attach identifiers to the enclosing <div> rather than the header itself. |
fig_width |
Default width (in inches) for figures |
fig_height |
Default height (in inches) for figures |
fig_retina |
Scaling to perform for retina displays (defaults to 2, which
currently works for all widely used retina displays). Set to |
fig_caption |
|
dev |
Graphics device to use for figure output (defaults to png) |
df_print |
Method to be used for printing data frames. Valid values
include "default", "kable", "tibble", and "paged". The "default" method
uses a corresponding S3 method of |
mathjax |
|
includes |
Named list of additional content to include within the
document (typically created using the |
keep_md |
Keep the markdown file generated by knitting. |
md_extensions |
Markdown extensions to be added or removed from the
default definition or R Markdown. See the |
pandoc_args |
Additional command line options to pass to pandoc |
... |
Additional arguments passed to |
See the online
documentation for additional details on using the html_fragment
format.
R Markdown output format to pass to render


relative = PSLz4_process_relatives(relatives,current) Process potential successors or predecessor of each point and choose the single one that is most likely to be the actual neighbor. Code is based on the Nevatia & Babu algorithm, but does not deal with triple points. Iasonas Kokkinos<EMAIL_ADDRESS>10/10/2007
0001 function relative = PSLz4_process_relatives(relatives,current); 0002 % relative = PSLz4_process_relatives(relatives,current) 0003 % 0004 % Process potential successors or predecessor of each point and choose the 0005 % single one that is most likely to be the actual neighbor. 0006 % Code is based on the Nevatia & Babu algorithm, but does not deal with 0007 % triple points. 0008 % 0009 % Iasonas Kokkinos<EMAIL_ADDRESS>0010 % 10/10/2007 0011 0012 structure = relatives; expand_structure; 0013 0014 %%------------------------------------------------------------------------- 0015 %% part 1: 0016 %% find which orientations are fine with current linelet's orientation: 0017 %% generates in batch mode the neighboring orientations 0018 %% into which the currnet linelets may branch. It is assumed 0019 %% orientations can change by 45 degrees max at each pixel 0020 %%------------------------------------------------------------------------- 0021 0022 allowed = mod(repmat(current.orient',[3,1]) + repmat([-1:1]',[1,length(current.orient)])-1,4)+1; 0023 0024 %%------------------------------------------------------------------------- 0025 %% and find for each of the possible neigbors 0026 %% check whether his orientation is within the set of allowable 0027 %% orientations 0028 %%------------------------------------------------------------------------- 0029 ok = zeros(size(neigh_orient)); 0030 0031 for k_potential = [1:3], 0032 for k_neigh =[1:3], 0033 ok(k_neigh,:)= max(ok(k_neigh,:),allowed(k_potential,:) == neigh_orient(k_neigh,:)); 0034 ok(k_neigh,:)= 1; 0035 end 0036 end 0037 0038 %%------------------------------------------------------------------------- 0039 %% part 2: 0040 %% for each linelet check how many of its potential neighbors 0041 %% actually lie on the feature skeleton. Treat separately the 0042 %% cases with double and single neighbors (we do not treat 0043 %% triple neighbors). 0044 %%------------------------------------------------------------------------- 0045 relative= -1*ones(1,length(neigh_ind)); 0046 nneighs = sum(neigh_active,1); 0047 single_neigh = find(nneighs==1); 0048 double_neigh = find(nneighs==2); 0049 0050 %%------------------------------------------------------------------------- 0051 %% 2.1 single neighbor 0052 %%------------------------------------------------------------------------- 0053 0054 %%------------------------------------------------------------------------- 0055 %% get `OK' index of the single active neighbor (batch mode code) 0056 [closest_neighbor,dum] = find(neigh_active(:,single_neigh)); 0057 idx = closest_neighbor' + (single_neigh-1)*3; 0058 condition_single = ok(idx); 0059 continued = single_neigh(find(condition_single)); 0060 0061 %%------------------------------------------------------------------------- 0062 %% for those that are indeed ok, store the index of their 0063 %% single closest neighbor 0064 relative(continued) = neigh_ind(idx(find(condition_single))); 0065 0066 %%------------------------------------------------------------------------- 0067 %% 2.2 double neighbors 0068 %% case 1: 4-connected, similar orientation -> no fork 0069 %% case 2: 4-connected, vertical orientations-> fork 0070 %% case 3: 8-connected -> fork 0071 %%------------------------------------------------------------------------- 0072 0073 % for ease, gather all data related to the 2-neighbor pairs 0074 [neigh_active_d,neigh_ener_d,neigh_orient_d,dists_d]= keep_points_double... 0075 (double_neigh,neigh_active,neigh_ener,neigh_orient,neigh_dist); 0076 0077 for k=1:length(double_neigh), 0078 %% examine separately every linelet's neighbors: 0079 index = double_neigh(k); 0080 [neighs] = find(neigh_active_d(:,k)); 0081 0082 %% get the orientations, energies and distances 0083 %% of the two active neighbors of the current linelet 0084 orient(1) = neigh_orient_d(neighs(1),k); 0085 orient(2) = neigh_orient_d(neighs(2),k); 0086 0087 ener_n(1) = neigh_ener_d(neighs(1),k); 0088 ener_n(2) = neigh_ener_d(neighs(2),k); 0089 0090 dist_n(1) = dists_d(neighs(1),k); 0091 dist_n(2) = dists_d(neighs(2),k); 0092 0093 %% are they on contiguous locations? 0094 f_connected = (abs(neighs(2)-neighs(1))==1); 0095 0096 %% do they have similar orientations 0097 siml_orient = ismember2(orient(1),mod(orient(2)+[-1:1]-1,4)+1); 0098 0099 %% case 1: 4-connected, similar orientation -> no fork. e.g.: 0100 %% 0 l 0101 %% l l 0102 %% 0 0 0103 %% keep the neighbor that is closest (line will go through 0104 %% other neighbor afterwards, without changing route). 0105 if (f_connected)&(siml_orient) 0106 [mn,idx_min] = min(dist_n); 0107 rel = neighs(idx_min); 0108 end 0109 0110 %% case 2: 4-connected, vertical orientations-> fork 0111 %% 0 1 0112 %% 1 1 0113 %% 0 1 0114 %% not implemented yet 0115 0116 0117 %% case 3: 8-connected -> fork 0118 %% 0 1 0119 %% 1 0 0120 %% 0 1 0121 %% keep the most active neighbor (naive heuristic) 0122 0123 if (~siml_orient)|(~f_connected) 0124 [mx,idx_max] = max(ener_n); 0125 rel = neighs(idx_max); 0126 end 0127 relative(index) = neigh_ind(rel,index); 0128 end 0129 0130 %%------------------------------------------------------------- 0131 %% internal functions 0132 %%------------------------------------------------------------- 0133 function res = ismember2(input,options), 0134 res = (input == options(1))||(input==options(2)); 0135 0136 function varargout = keep_points_double(pts,varargin); 0137 for k=1:length(varargin) 0138 varargout{k} = varargin{k}(:,pts); 0139 end


Supervised learning has been at the forefront of research in computer vision and deep learning over the past decade.
In a supervised learning setting, humans are required to annotate a large amount of dataset manually. Then, models use this data to learn complex underlying relationships between the data and label and develop the capability to predict the label, given the data. Deep learning models are generally data-hungry and require enormous amounts of datasets to achieve good performance. Ever-improving hardware and the availability of large human-labeled datasets has been the reason for the recent successes of deep learning.
If you think of gaining a new skill only as a means to a very specific end (i.e., getting promoted), your first step should be to adjust your mindset. You need to embrace continuous learning as an integral part of your professional development—today and for the rest of your career.
One major drawback of supervised deep learning is that it relies on the presence of an extensive amount of human-labeled datasets for training. This luxury is not available across all domains as it might be logistically difficult and very expensive to get huge datasets annotated by professionals. While the acquisition of labeled data can be a challenging and costly endeavor, we usually have access to large amounts of unlabeled datasets, especially image and text data. Therefore, we need to find a way to tap into these underused datasets and use them for learning.
Transfer learning means using knowledge from a similar task to solve a problem at hand. In practice, it usually means using as initializations the deep neural network weights learned from a similar task, rather than starting from a random initialization of the weights, and then further training the model on the available labeled data to solve the task at hand.
Transfer learning enables us to train models on datasets as small as a few thousand examples, and it can deliver a very good performance. Transfer learning from pretrained models can be performed in three ways:
Usually, the last layers of the neural network are doing the most abstract and task-specific calculations, which are generally not easily transferable to other tasks. By contrast, the initial layers of the network learn some basic features like edges and common shapes, which are easily transferable across tasks.
The image sets below depict what the convolution kernels at different levels in a convolutional neural network (CNN) are essentially learning. We see a hierarchical representation, with the initial layers learning basic shapes, and progressively, higher layers learning more complex semantic concepts.
Alternatively, we can transfer the layers from a pretrained network and train the entire network on the available labeled data. This setup needs a little more labeled data because you are training the entire network and hence a large number of parameters. This setup is more prone to overfitting when there is a scarcity of data.
This approach is my personal favorite and usually yields the best results, at least in my experience. Here, we train the newly attached layers while freezing the transferred layers for a few epochs before fine-tuning the entire network.
This usually works very well for most image classification tasks because we have huge image datasets like ImageNet that cover a good portion of possible image space—and usually, weights learned from it are transferable to custom image classification tasks. Moreover, the pretrained networks are readily available off the shelf, thus facilitating the process.
However, this approach will not work well if the distribution of images in your task is drastically different from the images that the base network was trained on. For example, if you are dealing with grayscale images generated by a medical imaging device, transfer learning from ImageNet weights will not be that effective and you will need more than a couple of thousand labeled images for training your network to satisfactory performance.
In this section, I will relate an experiment that empirically establishes the potential of unsupervised pre-training for image classification. This was my semester project for a Deep Learning class I took with Yann LeCun at NYU last spring.
What is a chatbot and how does it work?
Chatbot terminology causes confusion. Chatbots are computer programs that respond to human messages. They are designed one of two ways: The first is based on rules that dictate the bot’s replies to specific commands. The second is with AI, where the goal is to comprehend the nuances of human language.
What are chatbots good for?
Some chatbots are designed to carry on casual conversations. Others act as customer service reps, providing deals, booking dates, and product support. There are also “digital assistants” that can do everything listed above while providing hundreds of extra features, like banking, home security, and traffic advice.
What are the types of chatbots?
Chatbot terminology causes confusion. Chatbots are computer programs that respond to human messages. They are designed one of two ways: The first is based on rules that dictate the bot’s replies to specific commands. The second is with AI, where the goal is to comprehend the nuances of human language.
05 Nov 2019 AT 12:00 AM
I recently completed another course from the 365 team "Data Science Boot Camp" where I was able to review my college course work taken many years ago in statistics along with an overview of programming languages (Python) I use regularly.
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06 Nov 2019 AT 11:23 PM
Great course. Excellent introduction. Pretty fast paced. And while I was new to the field I had to do some exploration next to the explanations provided within the course.
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07 Nov 2019 AT 05:23 AM
Great to understand the mechanics, mathematics and also statistics in back of BI. I really liked it, and the exercises are great to confirm the knowledge.
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11 Nov 2019 AT 09:12 AM
It was a decent match, I hate to say this because it was already very long but honestly it probably should have been 1 - 3 hours longer to include more explanations of SQL/MySQL, Python and Tableau.
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11 Dec 2019 AT 07:45 AM
I am on 50% of the course. So far I am very happy about the course. very succinct, practical and straight to the point. I am looking forward to complete this course so I can move onto data science
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This intention replaces an
if-else
statement with an equivalent statement using a conditional expression, if possible.


| Total net profit | -98.38 | Gross profit | 0.04 | Gross loss | -98.42 |
| Profit factor | 0.0 | Expected payoff | -1.56 | ||
| Absolute drawdown | -98.38 | Maximal drawdown (%) | 95.07 (-2872.21%) | ||
| Total trades | 63 | Profit trades (% of total) | 1 (1.59%) | Loss trades (% of total) | 62 (98.41%) |
| Long positions (won %) | 57 (1.75%) | Short positions (won %) | 6 (0.0%) | ||
| Largest | profit trade | 0.04 | loss trade | -3.31 | |
| Average | profit trade | 0.04 | loss trade | -1.59 | |
| Minimum | profit trade | 0.04 | loss trade | -0.45 | |
| Maximum | take profit in pips | 1241.1 | stop loss in pips | -856.5 | |
| Average | take profit in pips | 1.0 | stop loss in pips | -435.8 | |
| Minimum | take profit in pips | -407.2 | stop loss in pips | -332.3 | |
| Maximum | Reward-Risk | 2.5 | Duration in minutes | 24 | |
| Average | Reward-Risk | 0.3 | Duration in minutes | 2.4 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0 | |
| Maximum | consecutive wins (profit in money) | 1.0 (0.04) | consecutive losses (loss in money) | 32.0 (-51.03) | |
| Average | consecutive wins | 1.0 | consecutive losses | 32.0 |
| Total net profit | -87.0 | Gross profit | 0.04 | Gross loss | -87.04 |
| Profit factor | 0.0 | Expected payoff | -1.53 | ||
| Absolute drawdown | -87.0 | Maximal drawdown (%) | 85.0 (-4250.0%) | ||
| Total trades | 57 | Profit trades (% of total) | 1 (1.75%) | Loss trades (% of total) | 56 (98.25%) |
| Largest | profit trade | 0.04 | loss trade | -2.19 | |
| Average | profit trade | 0.04 | loss trade | -1.55 | |
| Minimum | profit trade | 0.04 | loss trade | -0.45 | |
| Maximum | take profit in pips | 991.9 | stop loss in pips | -607.9 | |
| Average | take profit in pips | -52.7 | stop loss in pips | -432.6 | |
| Minimum | take profit in pips | -407.2 | stop loss in pips | -332.3 | |
| Maximum | Reward-Risk | 2.5 | Duration in minutes | 24.0 | |
| Average | Reward-Risk | 0.2 | Duration in minutes | 2.6 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0.0 | |
| Maximum | consecutive wins (profit in money) | 1.0 (0.04) | consecutive losses (loss in money) | 30.0 (-45.9) | |
| Average | consecutive wins | 1.0 | consecutive losses | 30.0 |
| Total net profit | -11.38 | Gross profit | 0.0 | Gross loss | -11.38 |
| Profit factor | 0.0 | Expected payoff | -1.9 | ||
| Absolute drawdown | -11.38 | Maximal drawdown (%) | 8.07 (-243.81%) | ||
| Total trades | 6 | Profit trades (% of total) | 0 (0.0%) | Loss trades (% of total) | 6 (100.0%) |
| Largest | profit trade | 0.0 | loss trade | -3.31 | |
| Average | profit trade | 0.0 | loss trade | -1.9 | |
| Minimum | profit trade | 0.0 | loss trade | -1.43 | |
| Maximum | take profit in pips | 1241.1 | stop loss in pips | -856.5 | |
| Average | take profit in pips | 512.1 | stop loss in pips | -466.5 | |
| Minimum | take profit in pips | 121.2 | stop loss in pips | -366.3 | |
| Maximum | Reward-Risk | 2.0 | Duration in minutes | 1.0 | |
| Average | Reward-Risk | 1.0 | Duration in minutes | 0.2 | |
| Minimum | Reward-Risk | Duration in minutes | 0.0 | ||
| Maximum | consecutive wins (profit in money) | 0.0 (0.0) | consecutive losses (loss in money) | 6.0 (-11.38) | |
| Average | consecutive wins | 0.0 | consecutive losses | 6.0 |


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{% extends 'base.html'%} {% block content %}
Luck or success favour the prepared minds.
Never doubt the capacity of telling the truth.


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{% macro tasks(heading, name, name_plural) -%}
{{ "%.2f" | format(aggregated_stats.stats[attr].count) }}
Points added: {{ metric.points_added }}
Points completed: {{ metric.points_completed }}
Tasks created: {{ metric.num_created }}
Tasks completed: {{ metric.num_closed }}
Max: {{ "%.2f" | format(stats[attr].max) }}
Min: {{ "%.2f" | format(stats[attr].min) }}
Mean: {{ "%.2f" | format(stats[attr].mean) }}
Median: {{ "%.2f" | format(stats[attr].median) }}
{{ task_metric.num_closed }} {{ name_plural }} Closed ({{ task_metric.points_completed }} pts)
{{ task_metric.num_created }} {{ name_plural }} Created ({{ task_metric.points_added }} pts)


More on network switches taking on a security role
Here's another article around the idea of policy enforcement, this time on Switches.
As I said previously I think that this is the right way to go about it. If it is possible to block a machine from getting on the network if it doesn't meet certain criteria, then it would be possible not only to reduce the incidence of virii/worms in corporate networks, it might also provide some defence from non-corporate machines being placed on the network.


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A tiny number formatting library written in JavaScript.
View on GitHub
Please refer to the examples below.


Requirements Gathering for Consumer Startups
Most all development projects start with a hunch at a problem. Seldom do you have the opportunity of enough resources prior beginning building to fully vet all assumptions and define all requirements. Or at the very least if you do, you’re not in startup mode. For this reason the very first thing you build is often not the perfect solution. If you’re lucky its a start at a solution, and even if its not, if you’re close users will tell you what they want.
What this leaves you with is a couple of key items. First is get to the minimum product you can to vet your idea. Most commonly known as Minimally Viable Product. This should be the minimum product you need to vet your idea, and add some form of value for users. Once you’ve created this, don’t refine, don’t keep iterating, launch.
Second is make feedback simple. Often times support can be difficult, if its a form that requires 5 fields on your website forget it. If at all possible, provide multiple ways for users to give feedback. ALL ways should be simple for users. Email is great, because every user already has it. If it can be built on your website, great, but you should make registering as light as possible. Personally, I’m a big fan of Get Satisfaction. They give a great embeddable widget and provide a service that just simply works.
Third, and perhaps most important: Listen to your users! When users start to give you feedback, that’s the best requirements you can receive. There’s a couple of pieces to this step. When users give you feedback, you want to acknowledge them. Give some recognition for giving feedback; respond as positively and supportively as possible. If at all possible to act on requests do it, it will set you apart from the typical services they use of never getting a response and never seeing a change.
In short three key steps make for requirements gathering that trumps all else:
- Get something live
- Make feedback easy
- Respond and react to feedback


Turns assertThat(string).isEqualTo("") or assertThat(string).hasSize(0) into assertThat(string).isEmpty().
Also works with CharSequences.


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- Digital audio is a sequence of numbers
- Quantised in terms of amplitude and time
- Can perfectly recreate any band-limited signal
- Does not loose quality on repeating playback
- Synthesising a custom signal has a lot of pitfalls though
- Most difficult problem is to avoid aliasing
- No frequency above half the sample-rate must be exposed


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Dagre D3 Demo: DOM Example
A sample showing how to use DOM nodes in a graph. Note that IE does not support this technique.