<user home>/.ramadda/plugins/somenametemplate.htmlAny plugin file that ends with "template.html" is loaded by RAMADDA as a template.
In the template are a set of properties. You should change the id and name property. There are a number of other macros shown as ${macro} that are used to instantiate a web page. See the above example template for more information.
You can see many examples of templates at the at the Github site.
This file was created from a directory tree:
exampletemplate exampletemplate.html htdocs exampletemplate template.css banner.jpgThe jar file is created with:
mac:jar -Mcvf exampletemplate.jar exampletemplate adding: exampletemplate/(in = 0) (out= 0)(stored 0%) adding: exampletemplate/exampletemplate.html(in = 1406) (out= 595)(deflated 57%) adding: exampletemplate/htdocs/(in = 0) (out= 0)(stored 0%) adding: exampletemplate/htdocs/exampletemplate/(in = 0) (out= 0)(stored 0%) adding: exampletemplate/htdocs/exampletemplate/banner.jpg(in = 55020) (out= 52006)(deflated 5%) adding: exampletemplate/htdocs/exampletemplate/template.css(in = 3680) (out= 1139)(deflated 69%)Note: if you don't have jar installed (it is part of the Java release) then you can just zip the file and call it something.jar.
The template.css and banner.jpg files are in a directory (exampletemplate) under the htdocs directory so they can be referenced in the html as:
<link href="${root}/exampletemplate/template.css" rel="stylesheet" type="text/css" media="screen">You can specify a default template for your site in 2 ways. First, go to the Admin->Users list and edit the anonynmous user. Select the desired template from the list. You can also specify the default template for the site via a property:
ramadda.html.template.default=<your template id>You can set this in a plugin .properties file or you can specify this property (and other properties as well) in the Admin->Settings->Site and Contact Information->Extra Properties field.
ramadda.template.mobile=<template id >You can also specify a mobile=true property in the properties section of your template.


Van Gerwen sends classy message to Price after Grand Slam of Darts defeat
Michael van Gerwen suffered a shock 16-12 defeat to Gerwyn Price in the semi-finals of the Grand Slam of Darts, but has taken the disappointing loss on the chin.
The world number one had never lost to the Iceman in 19 previous meetings, but succumbed to the defending champion in Wolverhampton on Sunday afternoon.
MVG turned in an impressive performance, averaging 101.91, but missed double cost him and the Welshman’s fantastic doubling saw him down the world champ for the first time.
Van Gerwen was magnanimous in defeat, giving his opponent a hug on the stage, and then posting a classy tweet soon after the match.
‘All I can say is Gerwyn deserved to win,’ Van Gerwen tweeted. ‘I made too many mistakes and gave him too many chances. Today he took advantage and credit is to him for that.
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‘Today it hurts not to take the trophy home but tomorrow I start to prepare for the next tournament where I will put it right.’
That next tournament is the Players Championship Finals in Minehead next weekend, the final event before the World Championship gets underway on 13 December in London.
Price now has the chance to retain the trophy he won last year and claim only a second major title in the PDC.
The win over MVG has already seen the Welshman rise to his highest position ever on the PDC Order of Merit as he overtakes Michael Smith at number three in the world.
Van Gerwen’s place at world number one remains extremely safe, though, with a lead of over £500,000 over Rob Cross who is in second spot.
Price takes on Peter Wright in the final of the Grand Slam on Sunday evening at 7pm after Snakebite beat Glen Durrant 16-11 in the first semi-final.
Durrant tweeted his own reaction to his loss, expressing his disappointment, but acknowledging that this would be the last time he appears in a tournament representing the BDO.
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‘Gutted. But thank you @BDOdarts and goodbye – Thanks for the memories,’ tweeted Duzza.


Next: Conses as Lists, Previous: Cons Concepts, Up: Cons Concepts
A tree is a binary recursive data structure made up of conses and atoms: the conses are themselves also trees (sometimes called "subtrees" or "branches"), and the atoms are terminal nodes (sometimes called leaves ). Typically, the leaves represent data while the branches establish some relationship among that data.
caaaar caddar cdar nsubst caaadr cadddr cddaar nsubst-if caaar caddr cddadr nsubst-if-not caadar cadr cddar nthcdr caaddr cdaaar cdddar sublis caadr cdaadr cddddr subst caar cdaar cdddr subst-if cadaar cdadar cddr subst-if-not cadadr cdaddr copy-tree tree-equal cadar cdadr nsublis
Figure 14–2: Some defined names relating to trees.
| • General Restrictions on Parameters that must be Trees: |


J and I had each consumed about 2g of psilocybin that had been disolved into two chocolates (each about the size of bite-size candy 'bars').  Each of us weighed about 140 lbs and had eaten a bit of crackers and other semi-snacks beforehand.
We started by splitting one chocolate (~1/2g for each of us). At T+30minboth of us were feeling a bit of a rise, and were more comfortable taking more. At this point we split the remaining three chocolates (~1.5g for each of us), and the trip slowly built over the next 1-2 hr. At T+3 we were both quite soaked in sensation and played about, sharing the experience. The time was very euphoric and filled with pleasent and intriguing though which we communicated and explored. We laughed and cried and shared a beautiful time.
By T+6 we were both feeling like we'd come down a bit, though our pupils were still rahter dilated and we knew we weren't completely down. We were much more mobile now, and took to a homemade cookie, a sip of water and decided upon a bath. J perferred the bath very hot, and I gave in (against my preference for hot baths) and we soaked together.
At T+7 J began to feel very nauseated and began to quickly feel sick. She stood up to get out of the bath and spoke of dizziness, which I quickly moved on in case she was indeed not well. She became very unstable standing, but couldn't move from the tub for lack of balance. I made it out of the tub while still giving her support in time to help out as she almost fell out of the tub. I wrapped a towel around her and she stumbled toward the bathroom door, which I had to prop her up against to prevent her from falling. At this point her legs gave out from under her and I guided her fall to a sitting position. At this point she 'faded' for a moment and I couldn't seem to feel her breath or heartbeat - both of which returned a moment later and her eyes were much more alert.
I helped her to the bed and waited carefully on her and she moved through a 'bad trip' experience (music, light, etc made her uncomfortable). Her body was very hot during this time as well. She later recounted not remembering the period of time from standing up until she was on the floor of the bathroom. During that time she remembered having to make a conscious decision to 'come back' and not 'go somewhere'. Later in the evening she felt much better and we ordered tofu & vege chinese food and watched some cartoon series - the evening brightened up quite a bit and all felt much better.
I have read naturopathic medical advice against hot baths, though J takes them frequently, and has done so once before when on a mushroom trip. I as well have bathed while tripping (though not on psilocybin) with no detrimental effect. Our belief is that the incident was due to dehydration, as neither one of us consumed much liquid prior to the trip and in the 7hr of the trip. This is purely speculation, and the report is entered here for the general good. Please be extremely careful of bathing when tripping, and at least be well hydrated and take other precautions if you plan on attempting so.
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.


To setup Emby Bookshelf, just add a media library in Emby library setup and set the content type to Books.


JobShop
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--- layout: post title: Exploring Ruby on Rails in a conversation categories: - documentation author: admin published: true date: 2005-04-02 12:02:00.000000000 +01:00 ---
Ara Howard and Doug Fales has a great article on Linux Journal exploring Rails through a conversation. They talk about how thinks work building a small blog engine and touches on many of the Ruby facilities that Rails employ to do its magic. They also talk a bit about why some of the reactions to Rails have been so explosive and what kind of fears that are triggered when new tech hits the street. Great stuff.


XmlFactory Abstract Class
Definition
Line
11
of
System.Xml.Serialization/XmlClassRegistry.cm
Inheritance
Constructors & Destructor
public
nothrow
XmlFactory
(
const
String
<
char
>& className_)
Member Functions
public
nothrow
const
String
<
char
>&
ClassName
()
const
public
abstract
void
*
Create
(
Element
* element)
Member Variables
private
String
<
char
>
className
Constructor& Destructor Details
XmlFactory Constructor
public
nothrow
XmlFactory(
const
String
<
char
>& className_)
Definition
Line
13
of
System.Xml.Serialization/XmlClassRegistry.cm
Member Function Details
ClassName Member Function
public
nothrow
const
String
<
char
>& ClassName()
Definition
Line
17
of
System.Xml.Serialization/XmlClassRegistry.cm
Create Member Function
public
abstract
void
* Create(
Element
* element)
Definition
Line
16
of
System.Xml.Serialization/XmlClassRegistry.cm


Placemark with a coordinate uncertainty
Placemark with any error/questionable info including null coordinate uncertainty
Server side.
Server side, typed.
Server side, typed with error.
Canvas 2 as png on the fly.


Listen to Transformer
Music Transformer is an open source machine learning model from the Magenta research group at Google that can generate musical performances with some long-term structure. We find it interesting to see what these models can and can’t do, so we made this app to make it easier to explore and curate the model’s output.
If you listen to a bunch of samples, you’ll probably discover that most compositions (like a lot of fully AI-generated music) are nowhere near as good and interesting as what people compose. And that’s okay! We just thought it would be fun for more people to be able to hear them, think about them, or remix them in their own music. So here is a radio station of 100,000 random, not cherry-picked, samples. They are all downloadable as MIDI files under a CC0 (“No Rights Reserved”) license, so if you want to take one of the pieces and make it your own, do it -- we’d love to hear all about it!
For those interested in all the ones and zeros of this work, you can read more about the model in the blog post announcing it, the research paper it was published in, or the blog post about this app.
When you favourite a song, it is only stored locally, in your browser's cache, and not on any external server. In order to understand a bit better which pieces people like, skip over, or keep going back to, we are collecting some anonymous click analytics from this app in accordance with Google’s privacy policy.


HDF and OME
Paris 2015
OME team
Outline
- What is HDF5?
- Status update
- Discussion
- A data model.
- A library.
- A file format for storing and managing data.
- HDF5 data format for cell-based assays in HCS
- stored image medata with object measurements
- stored inter-object relations
- CellH5Browser: image browser based on CellH5
- Open source LGPL license
- Bio-Formats support: CellH5Reader
- To come: CellH5Writer (thanks C. Sommer)
- Re-slicing browser for terabyte-sized multi-view image sequences.
- Comes with custom file format based on XML (for metadata) and HDF5 (for raw data).
- Open source GPL license


Servo Starters
Contributing to Mozilla servo is fun! Sometimes it's hard to know where to get started, though. Servo Starters is a list of easy tasks that are good for beginners to rust or servo.
Contributing to Mozilla servo is fun! Sometimes it's hard to know where to get started, though. Servo Starters is a list of easy tasks that are good for beginners to rust or servo.


Sign in to Doszier
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Password
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Purchase Orders
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Add Photo
From Camera
From Photo Library
Upload Photo


League: {{ league.leagueCaption}} Matchday: {{ league.matchday}}
| Team | Played | Points | Goals | Goals Against | Goals Diff | Form | Upcoming | |
|---|---|---|---|---|---|---|---|---|
| {{ st.position }} | {{ st.teamName }} | {{ st.playedGames }} | {{ st.points }} | {{ st.goals }} | -{{ st.goalsAgainst }} | {{ st.goalDifference }} |
|
|
| date | home | home score | away score | away | |
|---|---|---|---|---|---|
| {{ f.matchday }} | {{ f.date | date:'short' }} | {{ f.homeTeamName }} | {{ f.result.goalsHomeTeam }} | {{ f.result.goalsAwayTeam }} | {{ f.awayTeamName }} |


--- layout: components title: Rating current: rating ---
Display a star rating for an item or organisation.
Example showing the stars when wrapped in a larger font, and the option to change colour when ratings are poor.
{% include example.html component="rating" example="options" size="xs" %}


Using HTML Formatting Elements
This text is displayed in bold.
This text is displayed in Italic.
This text is displayed in Underlined.
This text is displayed smaller


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0
00:00
15 puzzle
Play
Scores
GitHub
Congratulations!
Type nickname to save score:
Save
High scores
№
Nickname
Moves
Time
No data.
Menu
3
2
1
GO!


---
layout: post
title: My First Sermon...
date: '2007-08-30T21:31:00.000-05:00'
author: Jabell
tags:
- Affections
- Sermon
- Sovereignty
modified_time: '2007-08-30T21:44:44.429-05:00'
blogger_id: tag:blogger.com,1999:blog-19739956.post-923448610647128515
blogger_orig_url: http://theabellsix.blogspot.com/2007/08/my-first-sermon.html
---
Clicking on the link below will play the very first sermon that I ever preached to a congregation. I had taught in Sunday school situations for over five years, but had never preached. Various circumstances, including our decision to leave Vancouver, WA for seminary, led to this opportunity. On June 6, 2004, I preached this sermon to a total of about 650 people spread across three services. I believe this audio is from the second service. If you listen to John Piper often, you will recognize much from this sermon.
Quest for Joy
Despite my inexperience, it is my prayer and hope that my passion for the Glory of God is apparent.


Normal body temperature is about 37˚C. This is the temperature at which the enzymes enzymes in your cells work best.
The control of body temperature is called thermoregulation. It is coordinated by the nervous system
The skin and temperature control (Edexcel)
The temperature outside your body is detected by nerve endings in the layer of skin called the dermis. The information is sent along neurones to the hypothalamus in the brain. The hypothalamus also monitors the internal body temperature by means of the bloodstream.
If your body temperature falls below about 37˚C, the hypothalamus sends messages to the erector muscles in the skin. These make the hairs stand up so that they trap an insulating layer of air (more useful to animals with lots of hair than to humans!).
Sebaceous glands produce an oily substance that helps to lubricate the skin and make it waterproof.
The hypothalamus also reduces blood flow in blood vessels near the surface of the skin so that less heat is lost from them. The capillaries become narrower (vasoconstriction).
If your body temperature rises above about 37˚C, the hypothalamus causes the sweat glands to produce sweat. The sweat takes heat energy from the skin as it evaporates, so the skin cools down. The hypothalamus also increases blood flow to the skin by making the capillaries wider (vasodilation) so more heat is lost.

Controlling blood glucose (AQA, Edexcel)
Glucose provides the energy needed for the reactions that take place inside cells. It is a product of the digestion of carbohydrates. It is important to control the amount of glucose in the bloodstream.
Blood glucose levels are controlled by hormones released into the bloodstream by the pancreas.
Role of the liver (Edexcel)
When the concentration of glucose in the blood rises too high, the pancreas releases the hormone insulin , which travels to the liver. The liver then changes some of the glucose to glycogen, which is stored in the liver.
When the level of glucose in the blood falls too low, the pancreas produces another hormone, glucagon. Glucagon stimulates the liver to convert some glycogen back to glucose and release it into the bloodstream.


Hux: this chapter is very similar to TAPL - ch13 References But under a “formal verification” concept, it’s more interesting and practical and push you to think about it!
computational effects - “side effects” of computation - impure features
- assign to mutable variables (reference cells, arrays, mutable record fields, etc.)
- perform input and output to files, displays, or network connections;
- make non-local transfers of control via exceptions, jumps, or continuations;
- engage in inter-process synchronization and communication
The main extension will be dealing explicitly with a
- store (or heap) and
- pointers (or reference) that name store locations, or address…
interesting refinement: type preservation
Definition
forms of assignments:
- rare : Gallina - No
- some : ML family - Explicit reference and dereference
- most : C family - Implicit …
For formal study, use ML’s model.
Syntax
Types & Terms
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T ::=
| Nat
| Unit
| T → T
| Ref T
t ::=
| ... Terms
| ref t allocation
| !t dereference
| t := t assignment
| l location
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Inductive ty : Type :=
| Nat : ty
| Unit : ty
| Arrow : ty → ty → ty
| Ref : ty → ty.
Inductive tm : Type :=
(* STLC with numbers: *)
...
(* New terms: *)
| unit : tm
| ref : tm → tm
| deref : tm → tm
| assign : tm → tm → tm
| loc : nat → tm. (** 这里表示 l 的方式是 wrap 一个 nat as loc **)
Typing
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Gamma |- t1 : T1
------------------------ (T_Ref)
Gamma |- ref t1 : Ref T1
Gamma |- t1 : Ref T11
--------------------- (T_Deref)
Gamma |- !t1 : T11
Gamma |- t1 : Ref T11
Gamma |- t2 : T11
------------------------ (T_Assign)
Gamma |- t1 := t2 : Unit
Values and Substitution
1
2
3
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Inductive value : tm → Prop :=
...
| v_unit : value unit
| v_loc : ∀l, value (loc l). (* <-- 注意这里是一个 Π (l:nat) . value (loc l) *)
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Fixpoint subst (x:string) (s:tm) (t:tm) : tm :=
match t with
...
| unit ⇒ t
| ref t1 ⇒ ref (subst x s t1)
| deref t1 ⇒ deref (subst x s t1)
| assign t1 t2 ⇒ assign (subst x s t1) (subst x s t2)
| loc _ ⇒ t
end.
Pragmatics
Side Effects and Sequencing
1
r:=succ(!r); !r
can be desugar to
1
(\x:Unit. !r) (r:=succ(!r)).
then we can write some “imperative programming”
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r:=succ(!r);
r:=succ(!r);
r:=succ(!r);
!r
References and Aliasing
shared reference brings _shared state
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let r = ref 5 in
let s = r in
s := 82;
(!r)+1
Shared State
thunks as methods
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let c = ref 0 in
let incc = \_:Unit. (c := succ (!c); !c) in
let decc = \_:Unit. (c := pred (!c); !c) in (
incc unit;
incc unit; -- in real PL: the concrete syntax is `incc()`
decc unit
)
Objects
constructor and encapsulation!
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newcounter =
\_:Unit. -- add `(self, init_val)` would make it more "real"
let c = ref 0 in -- private and only accessible via closure (特权方法)
let incc = \_:Unit. (c := succ (!c); !c) in
let decc = \_:Unit. (c := pred (!c); !c) in
{ i=incc,
d=decc } -- return a "record", or "struct", or "object"!
References to Compound Types (e.g. Function Type)
Previously, we use closure to represent map, with functional update
这里的”数组” （这个到底算不算数组估计都有争议，虽然的确提供了 index 但是这个显然是 O(n) 都不知道算不算 random access…
并不是 in-place update 里面的数据的，仅仅是一个 ref
包住的 map 而已 （仅仅是多了可以 shared
其实或许 list (ref nat)
也可以表达数组？ 反正都是 O(n) 每次都 linear search 也一样……
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newarray = \_:Unit. ref (\n:Nat.0)
lookup = \a:NatArray. \n:Nat. (!a) n
update = \a:NatArray. \m:Nat. \v:Nat.
let oldf = !a in
a := (\n:Nat. if equal m n then v else oldf n);
Null References
nullptr!
Deref a nullptr:
- exception in Java/C#
- insecure in C/C++ <– violate memory safety!!
1
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type Option T = Unit + T
type Nullable T = Option (Ref T)
Why is Option
outside?
think about C, nullptr
is A special const location, like Unit
(None
in terms of datacon) here.
Garbage Collection
last issue: store de-allocation
w/o GC, extremely difficult to achieve type safety…if a primitive for “explicit deallocation” provided one can easily create dangling reference i.e. references -> deleted
One type-unsafe example: (pseudo code)
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a : Ref Nat = ref 1; -- alloc loc 0
free(a); -- free loc 0
b : Ref Bool = ref True; -- alloc loc 0
a := !a + 1 -- BOOM!
Operational Semantics
Locations
what should be the values of type
Ref T
?
ref
allocate some memory/storage!
run-time store is essentially big array of bytes. different datatype need to allocate different size of space (region)
we think store as array of values, abstracting away different size of different values we use the word location here to prevent from modeling pointer arithmetic, which is un-trackable by most type system
location n
is float
doesn’t tell you anything about location n+4
…
Stores
we defined replace
as Fixpoint
since it’s computational and easier. The consequence is it has to be total.
Reduction
Typing
typing context:
1
Definition context := partial_map ty.
Store typings
why not just make a context a map of pair? we don’t want to complicate the dynamics of language, and this store typing is only for type check.


Go to the source code of this file.
Defines | |
| #define | _WIN32_WINNT 0x0500 |
| precompiled header that includes operating system specific files. | |
| #define | FS_T(x) x |
| #define | FSSIZE_LOW(x) ( ( unsigned int )( ( ( FSsize )( x ) ) & 0xFFFFFFFF ) ) |
| #define | FSSIZE_HIGH(x) ( ( unsigned int )( ( ( FSsize )( x ) >> 32 ) & 0xFFFFFFFF ) ) |
| #define | MAKE_FSIZE(low, high) ( ( ( ( FSsize )( high ) ) << 32 ) | ( ( FSsize )( low ) ) ) |
| #define | _FS_NAME_MANGLE_INTERNAL(x, y) x##y |
| Native word size based defines and macros. | |
| #define | _FS_NAME_MANGLE(x, y) _FS_NAME_MANGLE_INTERNAL( x, y ) |
Typedefs | |
| typedef char | FSchar |
| typedef __int64 | FSsize |
Functions | |
| int | _FS_Swap (volatile int *gate, int value) |
| function prototypes to ease the reading of this file. | |
| int | _FS_CompareAndSwap (volatile int *gate, int value, int compare) |
| void * | _FS_AlignedAlloc (unsigned int size, unsigned int alignmentPow2) |
| void | _FS_AlignedFree (void *ptr) |
Definition at line 38 of file filesystem_afx.h.
| #define _WIN32_WINNT 0x0500 |
precompiled header that includes operating system specific files.
Definition at line 3 of file filesystem_afx.h.
Definition at line 23 of file filesystem_afx.h.
Definition at line 30 of file filesystem_afx.h.
Definition at line 29 of file filesystem_afx.h.
Definition at line 31 of file filesystem_afx.h.
| typedef char FSchar |
Definition at line 22 of file filesystem_afx.h.
Definition at line 28 of file filesystem_afx.h.
| void* _FS_AlignedAlloc | ( | unsigned int | size, | |
| unsigned int | alignmentPow2 | |||
| ) | [inline] |
| void _FS_AlignedFree | ( | void * | ptr | ) | [inline] |
| int _FS_CompareAndSwap | ( | volatile int * | gate, | |
| int | value, | |||
| int | compare | |||
| ) | [inline] |
| int _FS_Swap | ( | volatile int * | gate, | |
| int | value | |||
| ) | [inline] |
function prototypes to ease the reading of this file.


Post-parsing
AddToSet.php
AddToSortedSet.php
Append.php
AppendToList.php
Autoloader.php
Channel.php
Commands.php
CompareSets.php
CompareSortedSets.php
Config.php
Connection.php
Connections.php
ConsistentHashing.php
Crc32.php
Decrement.php
Delete.php
DeleteFromHash.php
DeleteFromList.php
DeleteFromSet.php
DeleteFromSortedSet.php
DeleteFromSortedSetByRank.php
DeleteFromSortedSetByScore.php
DiffSets.php
Exception.php
Exec.php
Exists.php
ExistsInHash.php
ExistsInSet.php
Expire.php
FlushDb.php
Get.php
GetFromHash.php
GetFromList.php
GetFromSortedSetByScore.php
GetHash.php
GetHashFields.php
GetHashLength.php
GetHashValues.php
GetKeysByPattern.php
GetKeysCount.php
GetLastSaveTime.php
GetLifetime.php
GetList.php
GetListLength.php
GetRandomFromSet.php
GetRandomKey.php
GetRankFromSortedSet.php
GetScoreFromSortedSet.php
GetSet.php
GetSetLength.php
GetSortedSet.php
GetSortedSetLength.php
GetType.php
Hash.php
Increment.php
IncrementInHash.php
IncrementScoreInSortedSet.php
Info.php
Interface.php
IntersectSets.php
IntersectSortedSets.php
Json.php
Key.php
List.php
ListNameAndValue.php
Manager.php
Message.php
Monitor.php
MoveToDb.php
MoveToSet.php
Options.php
PhpSerialize.php
Pipeline.php
PopFromList.php
PopFromListBlocking.php
PrependToList.php
Publish.php
Quit.php
Redis.php
Rediska.php
RediskaInstance.php
Rename.php
RewriteAppendOnlyFile.php
Save.php
SelectDb.php
Serializer.php
Set.php
SetAndExpire.php
SetAndGet.php
SetToHash.php
SetToList.php
ShiftFromList.php
ShiftFromListBlocking.php
Shutdown.php
SlaveOf.php
Sort.php
SortedSet.php
Specified.php
Subscribe.php
Substring.php
TimeoutException.php
ToString.php
Transaction.php
TruncateList.php
UnionSets.php
UnionSortedSets.php
Unsubscribe.php
ValueAndScore.php
Post-parsing
Warnings:
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Abstract.php
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AddToSet.php
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AddToSortedSet.php
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Append.php
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AppendToList.php
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Autoloader.php
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Channel.php
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Commands.php
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CompareSets.php
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CompareSortedSets.php
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Config.php
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Connection.php
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Connections.php
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ConsistentHashing.php
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Crc32.php
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Decrement.php
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Delete.php
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DeleteFromHash.php
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DeleteFromList.php
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DeleteFromSet.php
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DeleteFromSortedSet.php
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DeleteFromSortedSetByRank.php
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DeleteFromSortedSetByScore.php
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DiffSets.php
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Exception.php
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Exec.php
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Exists.php
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ExistsInHash.php
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ExistsInSet.php
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Expire.php
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FlushDb.php
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Get.php
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GetFromHash.php
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GetFromList.php
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GetFromSortedSetByScore.php
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GetHash.php
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GetHashFields.php
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GetHashLength.php
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GetHashValues.php
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GetKeysByPattern.php
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GetKeysCount.php
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GetLastSaveTime.php
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GetLifetime.php
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GetList.php
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GetListLength.php
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GetRandomFromSet.php
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GetRandomKey.php
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GetRankFromSortedSet.php
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GetScoreFromSortedSet.php
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GetSet.php
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GetSetLength.php
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GetSortedSet.php
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GetSortedSetLength.php
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GetType.php
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Hash.php
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Increment.php
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IncrementInHash.php
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IncrementScoreInSortedSet.php
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Info.php
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Interface.php
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IntersectSets.php
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IntersectSortedSets.php
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Json.php
Warnings:
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Key.php
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List.php
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ListNameAndValue.php
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Manager.php
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Message.php
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Monitor.php
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MoveToDb.php
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MoveToSet.php
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Options.php
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PhpSerialize.php
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Pipeline.php
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PopFromList.php
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PopFromListBlocking.php
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PrependToList.php
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Publish.php
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Quit.php
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Redis.php
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Rediska.php
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RediskaInstance.php
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Rename.php
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RewriteAppendOnlyFile.php
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Save.php
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SelectDb.php
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Serializer.php
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Set.php
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SetAndExpire.php
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SetAndGet.php
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SetToHash.php
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SetToList.php
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ShiftFromList.php
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ShiftFromListBlocking.php
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Shutdown.php
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SlaveOf.php
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Sort.php
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SortedSet.php
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Specified.php
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Subscribe.php
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Substring.php
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TimeoutException.php
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ToString.php
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Transaction.php
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TruncateList.php
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UnionSets.php
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UnionSortedSets.php
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Unsubscribe.php
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ValueAndScore.php
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Documentation generated on Fri, 27 Aug 2010 13:55:38 +0400 by phpDocumentor 1.4.3


Sorting your drive only requires a quick visit to this website.
Preset configurations and a simplistic user interface makes the G-Drive sorter suitable for all Google Drive users.
Fully customizable conifgurations that sorts all Google Drive files based on type, creation date, name, current owner, and much more.


Lee Warner
-Back end development is my favorite but i am also good at front end
-Responsibilities: Design Database and layout, Design program and layout(prototype and technical), Programmed the calendar, search bar, foodlist(everything you see after logging in) brought together the entire app using both programmers code and placing it in the correct spot
-configured the models which includes both api calls and mysql calls and controllers
-rote every sql query
Anthony Federici
My name is Anthony Federici and I am a quarter 6 software engineering student. I was in charge of coding the front-end, which I feel I am stronger at. I was able to use Bootstrap and CSS to style all of the existing pages. I was responsible for the sidebar, login page, register page, and password reset pages.
- Proposal
- Prototype
- Technical Document
- Database Diagram
-
Screenshots
-
Login and Test Here
Use Email<EMAIL_ADDRESS>Password: erik1


A preliminary design for the JBoss Rules Rule Repository
Ben Truitt (btruitt@rackspace.com), Software Engineer, Rackspace
Managed Hosting
31 July 2006
Abstract
With the growing popularity of JBoss Rules (drools), it is becoming
clear that enterprise users require a well-integrated rule repository
solution to better manage the lifecycle of rules in enterprise
applications. This document outlines a potential design for such
a repository, which is built upon The Content Repository for Java
Technology API (JSR-170). Further input is required to complete
this design, but the ideas outlined here have been successfully
prototyped and tested.
Requirements
The requirements driving this project are:
Required
1. Version rules
2. Allow for different states: draft, review, approved, deploy, outdated
3. Perform a diff of one version against an older version
4. Produce a bundled package of rules (aka ruleset)
5. Backup rules
6. Provide authentication for accounts
7. Audit the access to the rule repository
8. Restore the repository from backup
These are the critical items. The others are nice features, but they
aren't generally critical. For really large and complex cases, many of
the features in the optional category might be required, but it's hard
to say they are required for the general case.
Optional
1. query rules based on a condition. In other words, find all rules that have the condition "account.type == premium".
2. store the data in a normalized format
3. provide translation to other formats
4. understand how rules go from draft to revision and enforce the process if necessary
5. provide an automatic push mechanism to deploy rules
6. automated rule validation at the rule logic level
7. provides basic templates for categories of rule patterns
8. provide plugin architecture for people to extend
For the purposes of the first phase of this project, I suggest that we focus only on the items above that required in order to minimize initial complexity.
A High-Level Design
Not only were requirements already captured for this project in subversion, but so was a high level design:
The JCR Specification (JSR-170)
The Content Repository for Java Technology specification, developed under the Java Community Process as JSR-170,
provides a standard API for accessing any specification-compliant
repository implementation in a way that is vendor neutral.
Implementations are free to use a backend storage mechanism of
their choice (e.g. database, filesystem, WebDAV repository, etc.).
In addition to a standard interface and vendor neutrality, making use of the JCR API offers these advantages to this project:
- Versioning is an optional component of the spec, supported by Apache JackRabbit and other implementations
- We can make a "state" property in the system for rules, to capture "draft", "review", "approved", "deploy", "outdated"
- There are several ways to produce a bundled package of rules
(ruleset) under JCR, from referencing the set of nodes in the rule set,
to using workspaces to capture the concept of a ruleset, to simply
holding this relationship in a text file stored in the repository
- JCR spec includes export of repository to XML
- Authentication will be handled by JAAS
- JCR spec includes an event framework to hook into for auditing purposes
- JCR spec includes import of repository from XML
- JCR spec includes search capability that may be useful not only
for implementing optional requirement 1 above, but also for other
purposes
The Repository Model - Design Strategy
The above image shows an example of the RulesRepository in use. Let's take a look at the repository from the top down.
Notice that all content resides in one workspace within the repository.
There was some discussion about using multiple workspaces as part
of the design of the repository layout to capture, e.g. rule sets or
rule state (draft, review, etc.) information. This seemed like an
interesting idea because of section <IP_ADDRESS> of the JCR Specification.
However, a closer examination of the concept of workspaces in a
JCR repository reveals that a workspace is analogous to local checkouts
from a revision control system (those checkouts are not all the same.
one may only contain a subset of the items that are under revision
control, another may contain revisions of items that are tagged to a
certain milestone. and then you may see items in a checkout that are
not even under version control). So while it might be technically
possible to use workspaces to capture individual rule state
information, etc., doing so would not be a clean or clear design.
Therefore, the design above puts all of the RulesRepository into
a single workspace.
Beneath the root node of the workspace is the 'drools:repository' node.
The subtree below this node captures all of the RulesRepository
content. This extra level of heirarchy will help to make it
easier for other systems to make use of the same JCR content
repository, if that is desirable for some reason. Note that the
drools namespace will be used several times - it is a namespace created
within the JCR repository.
The children of the drools:repository node are:
- drools:rule_area
- drools:dsl_area
- drools:tag_area
- drools:state_area
Each of these nodes is of type 'nt:folder' (see section <IP_ADDRESS> of the JCR specification for more detail).
The 'drools:rule_area' node holds rule nodes. In the example
above, the rule nodes are named 'ruleA' and 'ruleB'. 'ruleA'
provides a view of the properties a node of type
'drools:rule_node_type' has. See below for a more formal
discussion of the node types used by the RulesRepository.
A rule node can have 0 or 1 references to a DSL node (see below).
This reference may be either to the head DSL node, or to a
specific version of the DSL node. If the reference is to the head
DSL node, this reference will continue to follow the head version of
that node in the workspace even as new versions are checked in for the
DSL node.
A rule node can have 0 or many references to a tag node (see below). Tag nodes are not versionable.
A rule node can have 0 or 1 references to a state node (see below). State nodes are not versionable.
A rule node holds the content of a rule in the 'jcr:content' property.
See the more formal definition below, and section <IP_ADDRESS> of the
JCR specification for more detail on this.
The 'drools:dsl_area' node holds DSL nodes. In the above example,
the node named 'dslA' is a DSL node. A DSL node holds the content
of the DSL in the 'jcr:content' property. See the more formal
definition below, and section <IP_ADDRESS> of the JCR specification for
more detail on this.
The 'drools:tag_area' node holds tag nodes. In the above example,
the nodes named 'fun' and 'cheesy' are tags. The reason tags are
their own nodes in this repository, rather than being simple String
properties of the rule nodes, is two-fold:
- making tags their own nodes makes searching on the available tags much easier
- making tags their own nodes allows a user interface to provide a drop-down list of possible tags
The same logic applies to state nodes, which reside in under the
'drools:state_area" node of the repository. In the above example
the nodes named 'draft' and 'review' are state nodes.
Neither state nodes nor tag nodes are versionable under this design.
The primary reason for this decision is to simplify the design as
much as possible.
Formal Description of RulesRepository Node Types
drools:dsl_node_type
NodeTypeName
drools:dsl_node_type
Supertypes
nt:file,
mix:versionable
IsMixin
false
HasOrderableChildNodes
false
PrimaryItemName
null
PropertyDefinition
none
This node type serves to make a distinct node
type for DSL nodes, to help ensure a form of type safety when
manipulating nodes. It makes use of the definition of nt:file,
allowing the content of the DSL file to be stored in the jcr:content
property it inherits from that node type.  It also defines several
properties outlined in the repository layout overview above. It
makes use of the definition of
nt:file, allowing the content of the rule to be stored in the
jcr:content property it inherits from that node type. The node
also
has the mixin type mix:versionable as a supertype, making this a
versionable node type. A node of this type can refer to 0 or 1 DSL
nodes, 0 or more tag nodes, and 0 or 1 state nodes.
drools:ruleset_node_type
NodeTypeName
drools:ruleset_node_type
Supertypes
nt:hierarchyNode
IsMixin
false
HasOrderableChildNodes
false
PrimaryItemName
null
PropertyDefinition
Name drools:dsl_reference
RequiredType REFERENCE
ValueConstraints ['drools:rule_node_type','nt:version']
DefaultValues null
AutoCreated false
Mandatory false
OnParentVersion COPY
Protected false
Multiple true
This
node type serves to
make a distinct node type for ruleset nodes, to help ensure a form of
type
safety when manipulating nodes. It also defines the
property
'dsl_reference' outlined in the repository layout overview above.
It has as a supertype 'nt:hierarchyNode', which allows it to be
stored in a folder node, which the "drools:ruleset_area" node is. A
node of this type can refer to 0 or more rule nodes.
drools:state_node_type
NodeTypeName
drools:state_node_type
Supertypes
nt:hierarchyNode,
mix:referenceable
IsMixin
false
HasOrderableChildNodes
false
PrimaryItemName
null
PropertyDefinition
none
This
node type serves to
make a distinct node type for state nodes, to help ensure a form of
type
safety when manipulating nodes. It
has as a supertype 'nt:hierarchyNode', which allows it to be stored in
a folder node, which the "drools:state_area" node is. This node is referenceable so that a rule node can refer to it.
drools:tag_node_type
NodeTypeName
drools:tag_node_type
Supertypes
nt:hierarchyNode,
mix:referenceable
IsMixin
false
HasOrderableChildNodes
false
PrimaryItemName
null
PropertyDefinition
none
This
node type serves to
make a distinct node type for tag nodes, to help ensure a form of
type
safety when manipulating nodes. It
has as a supertype 'nt:hierarchyNode', which allows it to be stored in
a folder node, which the "drools:tag_area" node is. This node is referenceable so that a rule node can refer to it.
RulesRepository Functionality
The functionality rules repository is still not fully defined. A
prototype implementation has been started, and the javadoc for that
implementation's functionality implemented so far can be viewed here.
Web Service Interface
The rules repository will offer a web service interface that will be
utilized by rule authoring tools. This interface still needs to
be defined. It will likely partially overlap with the
functionality documented in the javadoc
of the prototype implementation, but additional services will likely be
required. This section of the design needs additional work.
Open Questions in this Design / Items left to cover
The following design decisions are still unresolved for this design:
- Should the rule_area have a heirarchy of nodes beneath it corresponding to the package that the rule is in?
- More specifics are needed for the user authenication scheme.
- Support for searching needs to be discussed in this design.
- Support for importing and exporting needs to be more thoroughly discussed in this design.
- Support for observation needs to be added to this design to meet the event auditing requirement.
- Support for exporting rules to DRL / DSL files needs to be included in this design.
- The web service interface needs to be defined.


Category Archives for News
Hjalmar Gislason to deliver a Keynote Speech at KCAP 2013
We are pleased to announce that Hjalmar Gislason is one of our keynote speakers at KCAP 2013. Hjalmar Gislason is the founder and CEO of DataMarket. Hjalmar is a successful entrepreneur, founder of four software companies since 1996. Prior to launching DataMarket, Hjalmar worked on new media and business development for companies in the Skipti Group […]
Crowd-funding KCAP 2013!
We are pleased to announce a crowd-funding initiative to sponsor KCAP 2013. We want to innovate a tiny little bit in how such meetings are organized by adding a new funding source to the organization of a specific scientific conference on Knowledge Capture. Most scientific conferences are funded through a combination of participant registration fees and institutional […]
KCAP2013 Datathon – Registration now open
The KCAP2013 Datathon invites submissions that demonstrate the value of Open Data through innovative applications. Objectives include to identify possible pitfalls along the value chain of the data, and second, to draw a number of conclusions that allow the communities involved in generating and exploiting large-scale data, to deal with such difficulties and flatten the […]
Mark Greaves to deliver a Keynote Speech at KCAP 2013
We are pleased to announce that Mark Greaves is one of our keynote speakers at KCAP 2013. Mark Greaves is currently Technical Director, Analytics, for the USs Pacific Northwest National Laboratory. He works with cutting-edge PNNL scientific teams from analytics, semantic computing, information visualization, and human-centered software systems to develop systems that exploit web-scale symbolic […]
Nigel Shadbolt to deliver a Keynote Speech at KCAP 2013
We are pleased to announce that Nigel Shadbolt is one our keynote speakers at KCAP 2013. Nigel Shadbolt is Professor of Artificial Intelligence (AI) at the University of Southampton and Head of the Web and Internet Science Group (http://users.ecs.soton.ac.uk/nrs/). He is a Director of the Web Science Trust (http://webscience.org/), and of the Web Foundation (http://www.webfoundation.org/) – […]
ACM Confirms Sponsorship of K-CAP 2013
The Association for Computing Machinery (ACM) has confirmed their sponsorship of K-CAP 2013. ACM is the premier organisation for computer science research and their sponsorship of K-CAP 2013, through the Special Interest Group for Artificial Intelligence (SIGART), is a key endorsement of the conference’s contribution to the Artificial Intelligence community.


Unit 2 - Linux/Unix Acquisition¶
Acquisition Preparation and System Information Acquisition¶
Linux/Unix forensics follows the general forensic process of collecting, preserving, analyzing, and reporting evidence.
First is a set of forensic tools, including a bootable live CD.
The reason is simple: You should never trust any tools from the suspect machine since it has potentially compromised. When booting using a forensic bootable CD in forensic mode, the internal suspect hard drive is not touched.
Second is a powerful machine, sometimes we call it forensic machine or evidence server.
This system has forensic tools installed and its drives are wiped clean for storing acquired evidence.
Volatile data acquisition¶
Volatile evidence is evidence that can easily be changed. Every memory dump will be different since memory is constantly changing. That’s why we should first acquire the data that is most volatile.
A possible order of collection from most volatile to least volatile until non-volatile is memory; swap space or page file; network status; connections; processes running; open files; drives, and removable media.
Since you are directly collecting volatile evidence from a suspect machine, you are inevitably changing data. To ensure a minimal impact to the original data, you should always try to use small footprint tools and you should always document everything you have done.
Collect information from a live system¶
On potentially compromised system we cannot trust anything, any tool from this machine. Use trusted tools from somewhere else, eg. a mounted USB.
Note
When we run any commands the output has to be saved to outside from potentially compromised machine, eg. a mounted USB.
On the beging of collecting evidence we store date, how long is the machine booted, logged in users and some basic information about the machine
$ date
St jan 29 23:07:00 CET 2020
$ uptime
23:07:27 up 44 min, 2 users, load average: 0,00, 0,02, 0,30
$ uname -a
Linux l430 5.3.16-300.fc31.x86_64 #1 SMP Fri Dec 13 17:59:04 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux
$ w
18:06:00 up 21 days, 23:14, 1 user, load average: 1,84, 1,27, 1,11
USER TTY LOGIN@ IDLE JCPU PCPU WHAT
ricco tty2 08jan20 21days 0.05s 0.05s /usr/libexec/gnome-session-binary
Check the network interfaces information, and find out if any is switched to PROMISC mode. In promisc mode and it is listening for all the traffic passing through, even the packets is not destinate to this machine it will also collect. A compromised machine, might have promisc mode, so it will try to listening for everything it’s passed into this network.
$ ifconfig
List network connections and the Ports that are open:
$ netstat -tulpen
List processes running on the system:
$ ps -eaf
List of open files (with multiple variants):
$ lsof -i 4 # list of open files all files opened with network connection
$ lsof -p 2918 # list of open files for preocess 2918
$ lsof +L1 # list of open files with link count less than 1, e.g. deleted files, not visible by ls (deleted), but still in memory
If we want to find UID zero (which is root owned, root owned UID is powerful during the execution time you have the root privilege). And then the permission, the perm, for set UID is 4000 and for set GID is 2000. And we don’t want to see error messages because you will see permission denied and lots of permission denied issues so the output will be cleaner. Investigator will look into this list and try to find any malicious set UID program.
$ find / -uid 0 -perm 4000 2> /dev/null
Memory Acquisition¶
For a host-based memory dump approach, the investigator needs to have physical access to the system. MEMDUMP is a part of the coroner’s toolkit, TCT. To overcome memdump limitations, open source tools, Linux Memory Extractor, LiME, and Fmem were developed. Both tools will load a kernel module to the system that allows full memory captures.
A commercial tool called F-Response allows examiners to conduct forensic acquisition remotely. F-Response use a pair of dongles, one for the suspect system and another for the forensic system.
We need to have trusted tools available on a suspected machine. Insert mod and then the module name certainly is the LiME module we are interested. We want to insert this module into the kernel and the path specifies where this image dump will be reside:
$ insmod lime-4.2.0-27-generic.ko "path=/mnt/evidence_folder/memory_dump.bin format=padded"
Once the dump is finished, we need to do a cleanup. First remove the lime module from the memory.
$ lsmod | grep lime
$ rmmod lime
We’ll have memory_dump.bin in out safe directory, eg. on a mounted USB. It’s a binary file. We want to try a very simple tool called a strings, it is able to print out certain lengths of strings, the lengths by default is greater not equal to 4 bytes. Lets do a search in the memory dump for the string greater than 8 bytes and starting with the word forensics:
$ strings -n 8 /mnt/evidence_folder/memory_dump.bin | grep ^forensics
Nonvolatile data acquisition¶
Forensic Imaging of Drives¶
Be aware that certain types of hard drives and solid state drives may self-destroy any data on the drive when you remove the device or power it off completely. Toshiba is one example.
There are many high speed forensic images in the market. High speed forensic images can copy up to 30 gigabytes per minute and usually have built-in write blocker functionalities. Software-based imaging tools like FTK Imager and dd can also be used to create a bit-stream copy of drives. However, you will need a write blocker to separate the original drives from the imaging software to prevent software from modifying data in original drives. Most of these imaging tools will generate the hash value automatically after the imaging is done.
dd reads input blocks one at a time from block level device and it puts them into a memory buffer, applies the selected conversions, then outputs from buffer to the desired location, with a default block size of 512 bytes.
To copy our physical device data, we simply use dd to move chunks of bits from a source device to a destination device, ignoring the end of file marker. dd copies metadata and the data blocks in their entirety. dd can redirect by pipe to netcat or other applications to send the data to a networked machine.
$ dd if=/source/file of=/destination/file
$ dd if=/source/file | nc <IP_ADDRESS> 2222
conv equal to noerror and sync is often used for forensic imaging to skip the unreadable sectors and then continue copying. More specifically, conv equal to noerror will instruct dd to pad the bad sectors with zeros and move on to continue copying the rest of the data. The sync option instructs dd to keep the sectors in the target device aligned with those from the source device. Thus, they data will not be misplaced in the wrong physical location on the destination copy.
$ dd if=/source/file of=/destination/file conv=noerror,sync
Since dd is a simple tool for data duplication, it will not calculate the hash value for the newly generated image. Therefore, after imaging process is complete, it is your responsibility to compute hash values for both the original source and dd image. Only if the hashes match, your forensic imaging process is done.
If /source/file has a bad sector and you use the conv=noerror option, you have a complicated and interesting case, as the hash values will be different, due to the padding of zeros.
Besides creating forensic imaging, dd has other uses.
You can use dd to wiping the drive with all zeros using this command. This process will basically fill your target drive with zeros, overriding any data as it goes. Some sources say that very old hard drives might still contain residual data that an electron microscope might pick up after one pass of cleaning. Therefore, the Department of Defense standard for unclassified hard drive dispersion requires three passes over every byte. Some researchers even suggest the seven passes of wiping. After wiping, you can reformat drive.
$ dd if=/dev/zero of=/dev/hdb
examples of using DD for forensic imaging.
In drive to drive imaging, you physically remove the drive from the suspect computer and connect suspected drive to forensics machine with a write blocker.  We can use both dd copies below to copy the content.
$ dd if=/dev/hda of=/dev/hdb
Since the size of hdb is larger than hda, after dd is done, hdb will contain the data from the source followed by a bunch of zeros. Therefore, the hash value of hdb will not be the same as the hash of hda, due to those extra zeros.
To obtain the same hash value, you can use dd to carve out the number of blocks copied form hda, leaving out zeros. Using the second command, since evidence dot dd is a file containing exactly the data from hda, assuming dd copied successfully, the hash value of hda will be the same as the hash value of the file evidence.dd.
$ dd if=/dev/hda of=/case1/evidence.dd
dd has siblings, sdd, and dcfldd. Both of them improved dd’s functionalities by achieving better performance and also providing copy progresses.


[§329-131] Prescription and pharmacy requirements not applicable. Notwithstanding any other law to the contrary, the prescription requirements of section 329-38 and the board of pharmacy licensure or regulatory requirements under chapter 461 shall not apply to the medical use of cannabis under this part. [L 2015, c 241, pt of §5; am L 2017, c 170, §2]


Node.js to C App via UDP
Help
Current Mode:
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Current Volume:
CPU Info
Linux version
Command Line
BBB Uptime
Current up time [s], and time in idle process [s]:
Select Beat
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ps-guitar-db
A Basic Spring JPA app with an H2 DB
Prerequisites
You will need to following tools in order to work with this project and code
- git (http://git-scm.com/)
- JDK 1.8+ (http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html)
- Maven 3.x+ (http://maven.apache.org/)
- An IDE of your choice. (Eclipse, IntelliJ, Spring STS, Netbeans, etc.)
Getting Started
To run this project locally, perform the following steps.
- Clone project to your machine using git - "git clone https://github.com/dlbunker/ps-guitar-db.git"
- Import the project into your IDE using the maven pom.xml. In spring STS suite this is done by importing an existing maven project
- Run the JUnit tests in the src/test/java folder. If all pass you are good to go.


AM Menu - Full App Style Mega Menu
The "AM Menu" is a responsive, fully customizable and App style mega menu that comes with built-in image lightbox, dropdowns, (auto colorful) cloud tags and variety of CSS3 and SVG animations.
Written in HTML, CSS3 and jQuery
AM Menu UI Features
- Place for Brand Logo
- Search Form
- Navigation Links
- Dropdowns
- Items Grid
- Photo Gallery
- Colorful Cloud Tags
Main Features
- Fully Responsive, Android, iPhone and Windows Phone Friendly (looks on these devices like a native app).
- Unlimited number of Main Items, Sub Items and Dropdowns can be added.
- Automatically Set Colors for Cloud Tags and Makes them Attractive and Colorful.
- Built-in Image Gallery with Light Box, in which Unlimited number of Images can be added.
- Automatically Detect Caption of the Images from alt text and Show them on the Image.
- Animated Search Form and Menu Trigger.
- Clean and Easily Modifiable HTML Structure.
- Chrome, Safari, Firefox, Opera, IE7+, IOS, Android and windows phone supported.
- CSS3, SVG and jQuery Animations Enabled.
- Font Awesome icons and +38 Macaron SVG icons Installed.
- User and SEO Friendly, Easy to Navigate and Implement.
AM Menu Settings
Choose color from the following tray.
Plain Color
Gradient Color
Fixed on Top
Glass Effect
Main Generated Script
$(function(){ $("body").amMenu({theme: 'default-theme',
dimOverLayer: true,
fixed: true,
textShadow: false,
glassEffect: false,
}); });
AM Menu UX Effects
Following are the some basic effects added to this menu for the best User Experience.
- Sliding Effects (Left, Right Up and Down)
- Fading Effects (In and Out)
- Bounce In
- Menu Trigger Bars to Cross (SVG)
- Search Trigger Icon to Cross (CSS3)
- Search Box Border Effect (SVG)


I am best reached by email at either<EMAIL_ADDRESS>or<EMAIL_ADDRESS>I reply to all messages within 24 hours, often less.


The Data & Tech Inventory helps capture all the products and data systems that impact professional learning across multiple departments, including learning management systems, student information systems, evaluation systems, and more.
This is completed collaboratively by a small team of participants. Fill out what you know about your district's data and tech products.


- rankMapForSpearmanCorrelationFromArray(double[]) - Static method in class dsm.parameters.VecSim
-
This function converts the scores stored in @param scoreMap into ranks.
- rankMapForSpearmanCorrelationFromHashMap(HashMap<V, Double>) - Static method in class dsm.util.Evaluation
-
This function converts the scores stored in @param scoreMap into ranks.
- rbo(HashMap<V, Double>, HashMap<X, Double>, HashMap<Y, Double>, HashMap<Z, Double>, HashMap<V, Double>, HashMap<X, Double>, HashMap<Y, Double>, HashMap<Z, Double>) - Static method in class dsm.parameters.VecSim
-
This function computes the Rbo (Rank-Biased Overlap) similarity of the feature vectors of two words, considering all types of features.
- rboP - Static variable in class dsm.parameters.VecSim
-
- readAllCounts(BufferedReader, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in the allXXXCount variables.
- readAllInputWords() - Static method in class dsm.util.OtherInputFilesReader
-
This function is used to read the input words from all the used test data sets.
- readAllKNSNCounts(BufferedReader, String, Long[], int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the the KNS N counts for words and features of type String.
- readEvalDataset() - Static method in class dsm.util.EvalDatasetReader
-
- readExtractedInformationFile() - Static method in class dsm.util.ExtractedInfoReader
-
This function reads in the information from the extracted information file.
- readExtractedInformationJustForInputWords - Static variable in class dsm.parameters.MiscParam
-
- readFile(String) - Static method in class extinfparsed.ExtInfParsedInputCorpusReaderAndProcessor
-
This function reads a file of the parsed English corpus to extract information from it.
- readFileEnParser(String) - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads a file of the parsed English corpus to extract information from it.
- readFileEsTagger(String) - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads a file of the tagged Spanish corpus to extract information from it.
- readFileHuParser(String) - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads a file of the parsed Hungarian corpus to extract information from it.
- readFilesEnNewParser() - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads in the files of an English corpus to extract information from it, when the corpus is
parsed with the C&C CCG parser (Stephen Clark and James R Curran (2007): Wide-Coverage Efficient Statistical
Parsing with CCG and Log-Linear Models.
- readFilesEnOldParser() - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads in the files of an English corpus to extract information from it, when the corpus is
parsed with the C&C CCG parser (Stephen Clark and James R.
- readFilesEsTagger() - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads in the files of a Spanish corpus to extract information from it, when the corpus is tagged with Freelilng.
- readFilesHuParser() - Static method in class extinfbow.ExtInfBowInputCorpusReaderAndProcessor
-
This function reads in the files of a Hungarian corpus to extract information from it, when the corpus is parsed with the Magyar lanc (Hunposchain) parser.
- readFilesNewParser() - Static method in class extinfparsed.ExtInfParsedInputCorpusReaderAndProcessor
-
This function reads in the files of a parsed English corpus to extract information from it, when the corpus is
parsed with the C&C CCG parser (Stephen Clark and James R.
- readFilesOldParser() - Static method in class extinfparsed.ExtInfParsedInputCorpusReaderAndProcessor
-
This function reads in the files of a parsed English corpus to extract information from it, when the corpus is
parsed with the C&C CCG parser (Stephen Clark and James R.
- readInputWords() - Static method in class extinfparsed.ExtInfParsedInputWordsReader
-
This function is used to read in the English input words.
- readInputWordsEnParser() - Static method in class extinfbow.ExtInfBowInputWordsReader
-
This function is used to read in the English input words, when a corpus of parsed English text is used.
- readInputWordsEsTagger() - Static method in class extinfbow.ExtInfBowInputWordsReader
-
This function is used to read in the Spanish input words, when a corpus of tagged Spanish text is used.
- readInputWordsHuParser() - Static method in class extinfbow.ExtInfBowInputWordsReader
-
This function is used to read in the Hungarian input words, when a corpus of parsed Hungarian text is used.
- readKNSNCountsForParaphrases(BufferedReader, String, HashMap<Paraphrase, Long[]>, HashMap<Paraphrase, Double>, Integer, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the the KNS N counts for words and features of type Paraphrase.
- readKNSNCountsForStrings(BufferedReader, String, HashMap<String, Long[]>, HashMap<String, Double>, Integer, HashSet<String>, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the the KNS N counts for words and features of type String.
- readParaphraseDouble(BufferedReader, String, HashMap<Paraphrase, Double>, HashMap<Paraphrase, Double>, Integer, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in a HashMap<Paraphrase, Double>.
- readParaphraseLong(BufferedReader, String, HashMap<Paraphrase, Long>, HashMap<Paraphrase, Double>, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in a HashMap<Paraphrase, Long>.
- readPrepAuxSubjObjFromLine(String[], long) - Static method in class extinfparsed.ExtInfParsedInputCorpusReaderAndProcessor
-
This function processes a grammatical relation.
- readStopWordsList() - Static method in class dsm.util.OtherInputFilesReader
-
This function is used to read in the stop words from a file, when they should be fileterd from the features.
- readStringDouble(BufferedReader, String, HashMap<String, Double>, HashMap<String, Double>, Integer, HashSet<String>, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in a HashMap<String, Double>.
- readStringLong(BufferedReader, String, HashMap<String, Long>, HashMap<String, Double>, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in a HashMap<String, Long>.
- readStringParaphraseDouble(BufferedReader, String, HashMap<String, HashMap<Paraphrase, Double>>, HashMap<String, Double>, HashMap<Paraphrase, Double>, HashMap<String, HashMap<Paraphrase, Double>>, HashSet<String>, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in a HashMap<String, HashMap<Paraphrase, Double>>.
- readStringStringDouble(BufferedReader, String, HashMap<String, HashMap<String, Double>>, HashMap<String, Double>, HashMap<String, Double>, HashMap<String, HashMap<String, Double>>, HashSet<String>, boolean, int) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads in the information to be stored in a HashMap<String, HashMap<String, Double>>.
- readSynonymQuestions(String) - Static method in class dsm.util.EvalDatasetReader
-
This function reads in the file containing the input synonym question dataset.
- readSynonymQuestions(String, POS, HashSet<String>, HashMap<String, String>, HashMap<String, ArrayList<ArrayList<String>>>) - Static method in class dsm.util.EvalDatasetReader
-
This function processes a line of the input synonym question dataset.
- readUntil(BufferedReader, String) - Static method in class dsm.util.ExtractedInfoReader
-
This method reads the input until the line containing the @param readUntilThis string is reached.
- readWordPairSimilarities(String) - Static method in class dsm.util.EvalDatasetReader
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This function reads in the file containing the input word pair similarity dataset.
- readWordPairSimilarities(String, POS, HashSet<String>, HashMap<String, String>, HashMap<String, ArrayList<ArrayList<String>>>, HashMap<ComparablePair<String, String>, Double>) - Static method in class dsm.util.EvalDatasetReader
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This function processes a line of the input word pair similarity dataset.
- readWordVectorsFile() - Static method in class dsm.util.ExtractedInfoReader
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This function reads in the information from the Google News word vectors file.
- relRisk(double, double, double, double) - Static method in class dsm.parameters.Weight
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This method computes the relative risk weight of a (word, feature) pair based on the frequencies given as input parameters.
- removeNonTopFeatures(HashMap<V, Double>, HashMap<String, Double>, String) - Static method in class dsm.parameters.DimRed
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This function removes (sets their weight to 0) those (feature, value) pairs from the @param wordMap, that are not among the top N features
(which are stored in @param wordConcatenatedMapOfFirstNElements.
- rogersTanimoto(double, double, double, double) - Static method in class dsm.parameters.Weight
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This method computes the Rogers-Tanimoto weight of a (word, feature) pair based on the frequencies given as input parameters.


The domestic cat[1][2] (Felis catus[2] or Felis silvestris catus[4]) is a small, usually furry, domesticated, and carnivorous mammal. They are often called a housecat when kept as an indoor pet,[6] or simply a cat when there is no need to distinguish them from other felids and felines. Cats are often valued by humans for companionship, and their ability to hunt vermin and household pests.
Cats are similar in anatomy to the other felids, with strong, flexible bodies, quick reflexes, sharp retractable claws, and teeth adapted to killing small prey. Cat senses fit a crepuscular and predatory ecological niche. Cats can hear sounds too faint or too high in frequency for human ears, such as those made by mice and other small animals. They can see in near darkness. Like most other mammals, cats have poorer color vision and a better sense of smell than humans.
Despite being solitary hunters, cats are a social species, and cat communication includes the use of a variety of vocalizations (mewing, purring, trilling, hissing, growling, and grunting), as well as cat pheromones, and types of cat-specific body language.[7]
Cats have a high breeding rate. Under controlled breeding, they can be bred and shown as registered pedigree pets, a hobby known as cat fancy. Failure to control the breeding of pet cats by neutering, and the abandonment of former household pets, has resulted in large numbers of feral cats worldwide, requiring population control.[8]
Since cats were cult animals in ancient Egypt, they were commonly believed to have been domesticated there,[9] but there may have been instances of domestication as early as the Neolithic from around 9500 years ago (7500 BC).[10] A genetic study in 2007 concluded that domestic cats are descended from African wildcats (Felis silvestris lybica), having diverged around 8000 BC in West Asia.[9][11] Cats are the most popular pet in the world, and are now found in almost every place where humans live.[12]
"Grumpy Cat by Gage Skidmore" by Gage Skidmore. Licensed under CC BY-SA 3.0 via Wikimedia Commons.


This page allows you to set the default folders (otherwise known as directories) which are used when opening or saving a file.
The File Open dialog is used whenever you use the File Open command. You may choose one of these options:
Folder of Active Document - the File Open dialog opens to the folder where the currently active file is from - if no file is open then the Specified folder (below) is used
Folder last used in Open Dialog - the File Open dialog opens to the same folder as when last used
Folder last used in Open/Save Dialog - the File Open dialog opens to the same folder which was used for the last File Open or File Save
Specified - the File Open dialog always uses this folder
The Save As dialog is used whenever you use the File Save As command or you save a file (eg, using File Save command) which has never been saved before. You may choose one of these options:
Folder of Active Document - the Save As dialog opens to the folder where the currently active file is from - if the active file is new (ie, never saved) then Specified folder (below) is used
Folder last used in Open Dialog - the Save As dialog opens to the same folder as when last used
Folder last used in Open/Save Dialog - the Save As dialog opens to the same folder which was used for the last File Open or File Save
Specified - the Save As dialog always defaults to this folder


I made this app
I am a 4th year Digital Arts and Sciences Engineering Major with a minor in Electrical Engineering


Fourth-year senior and three-year letterwinner is on scholarship and enters his fourth year as the starting long snapper in 2015 . . . preseason second-team All-America selection by Phil Steele . . . has played in 40 career games . . . has seven career tackles on special teams.
Played in all 13 games as the starting long snapper . . . recorded solo tackles against Eastern Michigan and Purdue . . . member of a record-breaking special teams unit that set a school record with 72 made extra points.
Saw action in all 14 games as the starting long snapper . . . recorded a solo tackle in the 100th Rose Bowl Game against No. 5 Stanford . . . recovered a fumbled punt that led to a touchdown in the first quarter at Nebraska.
Appeared in all 13 games . . . ranked tied for first on the team with four tackles on punt coverage.
Ranked among the nation's top long snappers by Chris Rubio (No. 6) . . . three-year starter as the long snapper for Coaches Mike Glennie and Joe Palka at Saline (Michigan) High School . . . prior to his senior season, invited to participate in Rubio's "Top 12" Camp in Los Angeles, Calif. . . . attended Chris Sailer Kicking/Long Snapping Camps . . . also participated in National Snapping Events in Las Vegas, Nev. . . . member of the Hornet track team as a sophomore . . . son of Cam and Donna Pepper . . . father Cam started at offensive guard for Illinois in 1989-90 . . . born May 28, 1994 . . . majoring in media and information.