I was able to join some fantastic educators today last Friday for a Flipped Learning workshop hosted by the Michigan Association of Secondary School Principals. I was part of a group from TechSmith, while Dan Spencer, Laura Bell, Jonathan Palmer, Missy McCarthy, Delia Bush, David Fouch, and Greg Green were panelists for the workshop.
I’ve been acquainted with Greg since I heard about his plans to flip his entire high school. I met him in person this past fall, and I’ve been challenged by his thoughtfulness and questions ever since.
Last fall, Greg and I had a conversation about why he flipped Clintondale…he wanted more control.
Confession: I didn’t understand what he meant at all. I was actually a little put off by the discussion…why should we want to control the learning more? Don’t we (as teachers) want students to be in control of their own learning? Needless to say, I left feeling confused, but invigorated by the discussion.
Fast forward to this morning. Greg was sharing again about the control he wanted to regain, and it hit me like a ton of bricks. He didn’t flip to control student’s learning. He flipped to give teachers more control over the support for learning they give every day in the classroom. It made so much sense.
We are at a point where information and support are constantly in a power struggle. As teachers, we are faced with the decision to choose one or the other. Do we support students? Or do we give information? Up until recently, there has not been any other option besides choice because the teacher was the only source of information in the classroom.
Enter personal computing. Students today have access to any information they could want. As the teacher, we can now focus even more energy into supporting the student. The control Greg talked about was being able to control the support given during the school day. We know students (typically) ignore homework. Well, now we can eliminate it totally, and support practice in the classroom. We know students have a hard time engaging with science and math. Now, we can give access to information, and the support our students as they build new schema for understanding as they work through material.
The key to this is that we successfully blend the access to information and the support only a teacher can give. Flipped Learning does not eliminate the need for teachers. Flipped Learning accentuates the importance of a supportive, professional educator when working with students.
I’m still working through what this means for school reform, but I’m excited about it. This is a message that teachers can latch on to. It’s empowering, rather than discrediting. You’re more important than ever. Let’s make the choice to let information become on-demand and put the support of students back on top of the list of things to do to change schools.
Written on May 13th, 2013 by Brian Bennett Categorized in: All Flipclass Technology
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Steven J. Zwick
Unafffiliated
I am currently retired from the practice of law in Colorado. My Colorado attorney registration is now inactive. I served as the County Attorney for San Miguel County, Colorado, from 1994 until my retirement in February 2018. Prior to that position I served as the La Plata County Attorney from 1985to 1990, and as an Assistant Garfield County Attorney from 1981to 1985, and in 1993. I served as an attorney in the Colorado Rural Legal Services program in Trinidad and Grand Junction, Colorado from 1978 to 1981. A copy of my professional resume, which was prepared while I was residing in Telluride, CO, prior to my moving to Ridgway in 2002, is attached.
I received my Bachelor of Arts degree, with Honors, majoring in History, from Harpur College, State University of New York at Binghamton, in 1974. I received my Juris Doctor degree from the University of Colorado School of Law in Boulder in 1977, following which I received my Master in Public Administration, Mid-Career Program, degree from the Harvard University Kennedy School of Government, in 1991. I recently received the Law School Alumni Council's 2020 Distinguished Alumni Achievement - Public Sector Award.
81432
In addition to voting in the 2016, 2018, and 2019 general elections by past political activity has been primarily limited to donating money to various political candidates' campaigns and political organizations. My political contributions since November 10, 2015 were made to the following political candidates campaigns and political organizations: Joe Biden, Michael Bennet, Diane Mitsch Bush, Gail Schwartz, Mark Kelly, Jacky Rosen, Jon Tester, John Hickenlooper, James Iacino, Heidi Heitkamp, Barbara McLachlan, Let America Vote PAC, Giffords PAC - IE, Mark Udall, Democratic National Committee, Yes on National Popular Vote, End Citizens United, Kamala Harris, Bill Nelson, PAC to the Future, Jared Golden, and Nancy Pelosi. I worked as a volunteer for Colorado state representative Barbara McLachlan's 2020 reelection campaign.
During my years of service as a county and assistant county attorney I belonged to the Colorado County Attorneys Association, including two terms on its board of directors, as well as a member of the Colorado Bar Association. I ceased participating in those organizations upon my retirement in 2018.
In my capacity as a county attorney, and assistant attorney, in San Miguel, La Plata, and Garfield counties I obtained considerable experience representing and advocating for the interests of those county governments and their elected officials, before Colorado legislative bodies and regulatory agencies pertaining to various public policy matters.
After more than thirty years of public service in county governments in Colorado, involving a wide variety of public policy matters, I believe that I have significant relevant professional knowledge and experience that would be beneficial to the commission's redistricting responsibilities. Service on the commission would provide me with the opportunity to contribute to the political health and well being of Colorado's citizens.
During my more than thirty years of public service in county government in Colorado a considerable amount of my time and effort was devoted to promoting consensus and creating agreement between various county elected officials, including county commissioners and other county elected and appointed officials on a wide variety of public policy and non-policy matters. As legal counsel to boards of county commissioners a paramount consideration was providing the members of those boards with fair and impartial advice and guidance on legally and politically sensitive matters. As an attorney whose clients included both elected and appointed public officials I was always cognizant that my role was not that of a policy maker, as that responsibility resided with the various public officials to whom I provided legal counsel.
Over the course of a forty year legal career I have had the opportunity to use my legal training and analytical skills, including the application of logic and reason to a wide variety of legal matters, including litigating matters in both Colorado state and federal courts. I have litigated a wide variety of legal matters involving county government in both trial and appellate courts, including the Colorado Court of Appeals and the Supreme Court. Providing legal counsel and advice to various county officials frequently involved the use of various legal analytical skills in both the development of policy as well as its implementation. I applied my legal analytical skills to advising the board of county commissioners regarding the decennial redistricting of the county commissioner districts in San Miguel County following the 2000 and 2010 census.
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User contribution—Brian
Brian has created a double-high, 8-board version of the plyrack, with two backboards rather than the single one found in the original.
For greater stability, he attached the backboards using metal brackets, rather than hinges. He also used four front cross members (also attached with brackets), in place of a single, slotted front cross member.
Brian has added pipe insulation around the arms to protect the bottoms of the boards from dings. I haven't found this necessary, myself, but it might keep your boards looking nice in the long run.
With a rack this tall, you'll probably want to secure it to the wall or ceiling at the top, especially in earthquake country. Bungees to hold the boards in place in the event of a tremor might be a good idea, too.


The YRFPD Board meets on the second Monday and fourth Thursday of the month at 10:30 AM.
Meetings are held at 215 West 2nd Street, Yachats.
All meetings are open to the public and the public is encouraged to attend.
If you need special assistance in order to attend or participate, please call<PHONE_NUMBER>.


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--- title: Work --- @@include('../templates/_head.tpl')
@@include('../templates/_homenav.tpl')California Health Advocates
The EDM Network
Yiddish Books
Bond Music Group
StubHub
California Pacific Medical Center Research Institute
OCEANA
Cabrillo Economic Development Corporation
Kick Push


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This page is a very simple basic webpage tutorial to show 'how a web page works' i.e. 'how to create a 'first' basic simple HTML page'.
For an alternate start, some prefer A Basic HTML Generator (HTML editor) - or more advanced users may prefer the newer CSS Template Generator or the complete PHP (includes) Template Tutorial - followed by a complete php / css / html combination Template Code Maker.
This page shows how to practice / make changes on your local computer. After the index.html file has been created, it can be uploaded to the host server with FTP software (Such as: WS-FTP LE Tutorial.)
To create a simple web page, the first step is to learn a few HTML tags. And copy n paste, the HTML tags into a file using a text editor (such as WordPad or notepad). Then save the file as an ASCII (DOS text) file with the name index.html. BTW: index.html is the default name for the homepage on most web host.
Here are some basic HTML tags that show how a web page is created. For a fast start, just copy n paste this code into a text editor - save as index.html. Then read the 'practice' tips on this page.

<title> favorites / bookmark title goes here </title>

 My first page

This is my first web page and I can say anything I want in here - I do that by putting text or images in the body section - where I'm typing right now :)

Notes:
Summary:

<title> ... favorites title ... </title>

.... all the web page is here ...

That's really all you need for a web page e.g :
Practice:
Now Practice Practice Practice before you upload / publish your web page. In other words, it is better to practice and finalize your web page on your local computer. To do this with MSIE browser:
Summary: By saving the index.html file - then opening it in MSIE browser - then switching back to the text editor - making changes to the info between the body tags - saving the changes - restore the MSIE view - use refresh. Using this 'back n forth' procedure you can design - finalize the web page - all on the local computer. Then when it's finished just upload it to your web host.
After playing with the tags in the first example, here a few more to 'practice' with:

<title> favorites / bookmark title goes here </title>

 second page - smaller heading e.g. h2

This is my second web page with a few more HTML tags.
Let's start with a tag for a horizontal line =

Now let's put in an image (that is in the same folder as this file so we don't have to put the full path / URL

This example only added two new tags but it shows how to improve you page as you learn new HTML tags. Also keep in mind that a lot of HTML tags have more attributes. For example, the
 tag in this example could be changed to

Now that you know the basic 'structure' of a web page all you need to do is start learning HTML tags (and their attributes) to use in the  .........  sections.


Week 47: Unsupervised learning (PCA and Clustering) and Summary of Course
Contents
Overview of week 47
Basic ideas of the Principal Component Analysis (PCA)
Introducing the Covariance and Correlation functions
More on the covariance
Reminding ourselves about Linear Regression
Simple Example
The Correlation Matrix
Numpy Functionality
Correlation Matrix again
Using Pandas
And then the Franke Function
Links with the Design Matrix
Computing the Expectation Values
Towards the PCA theorem
More on the PCA Theorem
A kind of Bird's view on PCA
Writing our own PCA code
Implementing it
First Step
Scaling
Centered Data
Exploring
Diagonalize the sample covariance matrix to obtain the principal components
Collecting all Steps
Classical PCA Theorem
The PCA Theorem
Geometric Interpretation and link with Singular Value Decomposition
PCA and scikit-learn
Back to the Cancer Data
Incremental PCA
Randomized PCA
Kernel PCA
Other techniques
Clustering and Unsupervised Learning
Basic Idea of the \( k \)-means Clustering Algorithm
The \( k \)-means Algorithm
Basic Math of the \( k \)-means Algorithm
Within Cluster Point Scatter
More Details
Total Cluster Variance
The \( k \)-means Clustering Algorithm
Summarizing
Writing our own Code, the Data Set
Implementing the \( k \)-means Algorithm
Plotting
Continuing
Wrapping it up
Summary of course
What? Me worry? No final exam in this course!
What is the link between Artificial Intelligence and Machine Learning and some general Remarks
Going back to the beginning of the semester
Not so sharp distinctions
Topics we have covered this year
Statistical analysis and optimization of data
Machine learning
Learning outcomes and overarching aims of this course
Perspective on Machine Learning
Machine Learning Research
Starting your Machine Learning Project
Choose a Model and Algorithm
Preparing Your Data
Which Activation and Weights to Choose in Neural Networks
Optimization Methods and Hyperparameters
Resampling
Other courses on Data science and Machine Learning at UiO
Additional courses of interest
What's the future like?
Types of Machine Learning, a repetition
Why Boltzmann machines?
Boltzmann Machines
Some similarities and differences from DNNs
Boltzmann machines (BM)
A standard BM setup
The structure of the RBM network
The network
Goals
Joint distribution
Network Elements, the energy function
Defining different types of RBMs
More about RBMs
Autoencoders: Overarching view
Bayesian Machine Learning
Reinforcement Learning
Transfer learning
Adversarial learning
Dual learning
Distributed machine learning
Meta learning
The Challenges Facing Machine Learning
Explainable machine learning
Scientific Machine Learning
Quantum machine learning
Quantum machine learning algorithms based on linear algebra
Quantum reinforcement learning
Quantum deep learning
Social machine learning
The last words?
AI/ML and some statements you may have heard (and what do they mean?)
Best wishes to you all and thanks so much for your heroic efforts this semester
Choose a Model and Algorithm
Supervised?
Start with the simplest model that fits your problem
Start with minimal processing of data
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Lists Phidgets that are available to your system. Be sure to clean up after this call using Release All.vi
Specifically, List Phidgets.vi will give you a list of Phidget IDs that you can use to
get information about the attached Phidgets.
Do not use these IDs to open Phidgets directly, though you can use
Common requests such as getDeviceInfo to get all the information
needed to open that Phidget separately.
Once you are done, remember to clean up the list of temperary
references using Release All.vi
|
Timeout The amount of time to scan for available Phidgets in milliseconds |
|
error out error out passes error or warning information out of a VI to be used by other VIs. |
|
status status is TRUE (X) if an error occurred or FALSE (checkmark) to indicate a warning or that no error occurred. Right-click the error out indicator on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
code code is the error or warning code. Right-click the error out indicator on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
source source string describes the origin of the error or warning. Right-click the error out indicator on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
Available Handles A list of handles for available Phidgets |
|
Device In Device # Identification |


|
This demo shows how to collect, transform, and compare Planet imagery over a certain area. The demo consists of three workspaces. One workspace checks and downloads new Planet images as soon as they become available. It produces four outputs - RGB thumbnails, full resolution RGB, NIr (Near Infrared ), and NDVI (Normalized Difference Vegetation Index). The second workspace displays this page - it shows the latest image and allows selecting the date range for visualization. The third workspace shows the previews of all available images within the given range and allows comparing two selected images in any of three representations - RGB, NIr, and NDVI. Select time frame for visualization and press "Submit" button. |


---
layout: post
title: Storyboard scene 93
date: '2016-09-04T03:37:47+02:00'
categories:
- Storyboards
picture_url: https://film-Storyboards.tumblr.com/post/149922855961/Storyboards-scene-93-for-a-film-currently-under
---
Storyboard — scene #93 for a film currently under pre production.


Use the button below to connect/disconnect the virtual gamepad, then click on the buttons and axes to simulate working with the gamepad. Info messages will be displayed on screen and in the console.
Connect Clear log


odsFacets
ods-widgets
This widget displays filters (facets) for a dataset or a domain's catalog of datasets, allowing the users to dynamically "refine" on one or more categories for the context, typically to restrict the data displayed by another widget such as odsTable.
Used alone without any configuration, the widget will display by default filters from all the "facet" fields of a dataset if it is used with a Dataset Context, or based on typical metadata from a dataset catalog if used with a Catalog Context.
<ods-facets context="mycontext"></ods-facets>
To configure which facets are displayed, you can use the odsFacet directive within the odsFacets widget. You can also use regular HTML within the odsFacets widget:
<ods-facets context="mycontext">
First field
 <ods-facet name="myfield"></ods-facet>
Second field
 <ods-facet name="mysecondfield"></ods-facet> </ods-facets>
The odsFacet directive supports the following parameters:
name
string the name of the field to display the filter on
title
string (optional) a title to display above the filters
sort
string (optional, default is count) How to sort the categories: either count
, -count
(sort by number of items in each category),
num
, -num
(sort by the name of category if it is a number), alphanum
, -alphanum
(sort by the name of the category).
It is also possible to configure a specific order by setting a list of values: ['value1', 'value2']
.
visible-items
number (optional, default 6) the number of categories to show; if there are more,
they are collapsed and can be expanded by clicking on a "more" link.
hide-if-single-category
boolean (optional) if 'true', don't show the filter for that facet if there is
only one available category to refine on.
hide-category-if
string (optional) an AngularJS expression to evaluate; if it evaluates to true, then
the category is displayed. You can use category.name
(the value of the category), category.path
(the complete path
to the category, including hierarchical levels) and category.state
(refined, excluded, or displayed) in the expression.
disjunctive
boolean (optional) if 'true', then the facet is in "disjunctive" mode, which means that after a first value selected,
you can select other possibles values that are all combined as "or". For example, if you click "red", then you can also click "green" and "blue",
and the resulting values can be green, red, or blue.
timerangeFilter
boolean (optional) if 'true', then an option to filter with on a time range is displayed above the facets categories.
Only works for date and datetime fields. Must be used with a context (see below).
context
string (optional) name of the context to refine on. Mandatory with timerange filter.
valueSearch
string (optional) if 'true', then a search box is displayed above the categories, so that you can search within them easily.
If 'suggest', then the matching categories are not displayed until there is at least one character typed into the search box, effectively making it
into a suggest-like search box.
refineAlso
DatasetContext|CatalogContext|DatasetContext[]|CatalogContext[] (optional) An
other context (or a list of contexts) that you want to filter based on your primary context's facets. This
is especially usefull for contexts who share common data.
mysecondarycontextFacetName
string (optional) The name of the facet in one of your secondary
contexts (defined through the refineAlso
parameter) that you want to map your original's facet on. You can
see an example below of such a behaviour.
<ods-facets context="mycontext"> <ods-facet name="myfield" sort="-num" visible-items="10"></ods-facet> <ods-facet name="mysecondfield" hide-if-single-category="true" hide-category-if="category.name == 'hiddencategory'"></ods-facet> </ods-facets>
You can write HTML within the odsFacet tag to change the display template of each category. The available variables
within the template are facetName
(the name of the field that the filter is based on), category.name
(the value of the category), category.path
(the complete path to the category, including hierarchical levels)
and category.state
(refined, excluded, or displayed).
For this to work properly, you must use an ng-non-bindable
wrapper element around your display template.
<ods-facets context="mycontext"> <ods-facet name="myfield"> {{category.name}} @ {{category.state}} </ods-facet> </ods-facets>
You can filter multiple contexts through this widget. To illustrate how this works, we'll consider 3 datasets
containing information relative to zipcodes: one containing the geo-shape of each zipcode (the zipcode being
stored in the column zipcode
), one containing the population (again, the zipcode is stored in the zipcode
column) and a last one containing the name of the area (the zipcode being this time stored in the
code_postal
column because this is a french dataset). In order to have a single zipcode facet that will
refine all 3 contexts simultaneously, we need to write the following.
<ods-facets context="shapes"> <ods-facet name="zipcode" refine-also="[population,areanames]" areanames-facet-name="code_postal"></ods-facet> </ods-facets>
<ods-facets context="{DatasetContext}"> </ods-facets>
| Param | Type | Details |
|---|---|---|
| context | DatasetContext | Catalog Context or Dataset Context to use |


My Referral Videos
These are the Official, Unbiased Referral Videos for Li Zhuohuan
Si Shen is my good friend and schoolmate. She used to work for Google and now is the co-founder of PapayaMobile.com .
Nathan is my bachata classmate, also a dear friend. He is from the States, and is working in Beijing now.
Champion paraglider Meiyuan is my instructor, the coolest paraglider in China, and he is the founder of SuperWing Paragliding Club.
Dr. Zhao, Haiyan is my professor in Tsinghua University.
Click here to view referral(English) from Haiyan.
Click here to view referral(Chinese) from Haiyan.
Shanshan is the hottest bachata teacher I've ever met. She is the founder of 7Class Dancing Club.
Nari Shin is one of the best salsa dancer in China from Korea, and he is the co-founder of D-Zone Dancing Club. He is from Korea.


Oh no it's 404 ERROR
Well, who is to blame for this? Come on, you will check the address of the page, and we will not do anything. And in general - use only the buttons. Come on to some lobby.
{% load static %}
Well, who is to blame for this? Come on, you will check the address of the page, and we will not do anything. And in general - use only the buttons. Come on to some lobby.


A potential tail position call that is immediately followed by return GetValue of the call result is also a possible tail position call. Function calls cannot return reference values, so such a GetValue operation will always return the same value as the actual function call result.


nevermined-sdk-py API Reference Docs¶
These docs are API Reference docs. They are not tutorials or examples of how to use sdk-py. For those, see the Ocean Protocol docs site.
These docs are API Reference docs. They are not tutorials or examples of how to use sdk-py. For those, see the Ocean Protocol docs site.


Bill
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Jeremiah 10:6
Forasmuch as there is none like unto thee, O LORD; thou art great, and thy name is great in might.


| Opcode/Instruction | Op / En | 64/32 bit Mode Support | CPUID Feature Flag | Description |
|---|---|---|---|---|
|
F3 0F 10 /r MOVSS xmm1, xmm2 |
RM | V/V | SSE | Merge scalar single-precision floating-point value from xmm2 to xmm1 register. |
|
F3 0F 10 /r MOVSS xmm1, m32 |
RM | V/V | SSE | Load scalar single-precision floating-point value from m32 to xmm1 register. |
|
VEX.NDS.LIG.F3.0F.WIG 10 /r VMOVSS xmm1, xmm2, xmm3 |
RVM | V/V | AVX | Merge scalar single-precision floating-point value from xmm2 and xmm3 to xmm1 register |
|
VEX.LIG.F3.0F.WIG 10 /r VMOVSS xmm1, m32 |
XM | V/V | AVX | Load scalar single-precision floating-point value from m32 to xmm1 register. |
|
F3 0F 11 /r MOVSS xmm2/m32, xmm1 |
MR | V/V | SSE | Move scalar single-precision floating-point value from xmm1 register to xmm2/m32. |
|
VEX.NDS.LIG.F3.0F.WIG 11 /r VMOVSS xmm1, xmm2, xmm3 |
MVR | V/V | AVX | Move scalar single-precision floating-point value from xmm2 and xmm3 to xmm1 register. |
|
VEX.LIG.F3.0F.WIG 11 /r VMOVSS m32, xmm1 |
MR | V/V | AVX | Move scalar single-precision floating-point value from xmm1 register to m32. |
|
EVEX.NDS.LIG.F3.0F.W0 10 /r VMOVSS xmm1 {k1}{z}, xmm2, xmm3 |
RVM | V/V | AVX512F | Move scalar single-precision floating-point value from xmm2 and xmm3 to xmm1 register under writemask k1. |
|
EVEX.LIG.F3.0F.W0 10 /r VMOVSS xmm1 {k1}{z}, m32 |
T1S-RM | V/V | AVX512F | Move scalar single-precision floating-point values from m32 to xmm1 under writemask k1. |
|
EVEX.NDS.LIG.F3.0F.W0 11 /r VMOVSS xmm1 {k1}{z}, xmm2, xmm3 |
MVR | V/V | AVX512F | Move scalar single-precision floating-point value from xmm2 and xmm3 to xmm1 register under writemask k1. |
|
EVEX.LIG.F3.0F.W0 11 /r VMOVSS m32 {k1}, xmm1 |
T1S-MR | V/V | AVX512F | Move scalar single-precision floating-point values from xmm1 to m32 under writemask k1. |
| Op/En | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| RM | ModRM:reg (r, w) | ModRM:r/m (r) | NA | NA |
| RVM | ModRM:reg (w) | VEX.vvvv (r) | ModRM:r/m (r) | NA |
| MR | ModRM:r/m (w) | ModRM:reg (r) | NA | NA |
| XM | ModRM:reg (w) | ModRM:r/m (r) | NA | NA |
| MVR | ModRM:r/m (w) | vvvv (r) | ModRM:reg (r) | NA |
| T1S-RM | ModRM:reg (r, w) | ModRM:r/m (r) | NA | NA |
| T1S-MR | ModRM:r/m (w) | ModRM:reg (r) | NA | NA |
Description
Moves a scalar single-precision floating-point value from the source operand (second operand) to the destination operand (first operand). The source and destination operands can be XMM registers or 32-bit memory locations. This instruction can be used to move a single-precision floating-point value to and from the low doubleword of an XMM register and a 32-bit memory location, or to move a single-precision floating-point value between the low doublewords of two XMM registers. The instruction cannot be used to transfer data between memory locations.
Legacy version: When the source and destination operands are XMM registers, bits (MAX_VL-1:32) of the corre-sponding destination register are unmodified. When the source operand is a memory location and destination operand is an XMM registers, Bits (127:32) of the destination operand is cleared to all 0s, bits MAX_VL:128 of the destination operand remains unchanged.
VEX and EVEX encoded register-register syntax: Moves a scalar single-precision floating-point value from the second source operand (the third operand) to the low doubleword element of the destination operand (the first operand). Bits 127:32 of the destination operand are copied from the first source operand (the second operand). Bits (MAX_VL-1:128) of the corresponding destination register are zeroed.
VEX and EVEX encoded memory load syntax: When the source operand is a memory location and destination operand is an XMM registers, bits MAX_VL:32 of the destination operand is cleared to all 0s.
EVEX encoded versions: The low doubleword of the destination is updated according to the writemask.
Note: For memory store form instruction “VMOVSS m32, xmm1”, VEX.vvvv is reserved and must be 1111b other-wise instruction will #UD. For memory store form instruction “VMOVSS mv {k1}, xmm1”, EVEX.vvvv is reserved and must be 1111b otherwise instruction will #UD.
Software should ensure VMOVSS is encoded with VEX.L=0. Encoding VMOVSS with VEX.L=1 may encounter unpredictable behavior across different processor generations.
Operation
VMOVSS (EVEX.NDS.LIG.F3.0F.W0 11 /r when the source operand is memory and the destination is an XMM register)
IF k1[0] or *no writemask*
THEN
DEST[31:0] (cid:197) SRC[31:0]
ELSE
IF *merging-masking*
; merging-masking
THEN *DEST[31:0] remains unchanged*
ELSE
; zeroing-masking
THEN DEST[31:0] (cid:197) 0
FI;
FI;
DEST[511:32] (cid:197) 0
VMOVSS (EVEX.NDS.LIG.F3.0F.W0 10 /r when the source operand is an XMM register and the destination is memory)
IF k1[0] or *no writemask*
THEN
DEST[31:0] (cid:197) SRC[31:0]
ELSE
*DEST[31:0] remains unchanged*
; merging-masking
FI;
VMOVSS (EVEX.NDS.LIG.F3.0F.W0 10/11 /r where the source and destination are XMM registers)
IF k1[0] or *no writemask*
THEN
DEST[31:0] (cid:197) SRC2[31:0]
ELSE
IF *merging-masking*
; merging-masking
THEN *DEST[31:0] remains unchanged*
ELSE
; zeroing-masking
THEN DEST[31:0] (cid:197) 0
FI;
FI;
DEST[127:32] (cid:197) SRC1[127:32]
DEST[MAX_VL-1:128] (cid:197) 0
MOVSS (Legacy SSE version when the source and destination operands are both XMM registers)
DEST[31:0] (cid:197)SRC[31:0]
DEST[MAX_VL-1:32] (Unmodified)
VMOVSS (VEX.NDS.128.F3.0F 11 /r where the destination is an XMM register)
DEST[31:0] (cid:197)SRC2[31:0]
DEST[127:32] (cid:197)SRC1[127:32]
DEST[MAX_VL-1:128] (cid:197)0
VMOVSS (VEX.NDS.128.F3.0F 10 /r where the source and destination are XMM registers)
DEST[31:0] (cid:197)SRC2[31:0]
DEST[127:32] (cid:197)SRC1[127:32]
DEST[MAX_VL-1:128] (cid:197)0
VMOVSS (VEX.NDS.128.F3.0F 10 /r when the source operand is memory and the destination is an XMM register)
DEST[31:0] (cid:197)SRC[31:0]
DEST[MAX_VL-1:32] (cid:197)0
MOVSS/VMOVSS (when the source operand is an XMM register and the destination is memory)
DEST[31:0] (cid:197)SRC[31:0]
MOVSS (Legacy SSE version when the source operand is memory and the destination is an XMM register)
DEST[31:0] (cid:197)SRC[31:0]
DEST[127:32] (cid:197)0
DEST[MAX_VL-1:128] (Unmodified)
Intel C/C++ Compiler Intrinsic Equivalent
VMOVSS __m128 _mm_mask_load_ss(__m128 s, __mmask8 k, float * p);
VMOVSS __m128 _mm_maskz_load_ss( __mmask8 k, float * p);
VMOVSS __m128 _mm_mask_move_ss(__m128 sh, __mmask8 k, __m128 sl, __m128 a);
VMOVSS __m128 _mm_maskz_move_ss( __mmask8 k, __m128 s, __m128 a);
VMOVSS void _mm_mask_store_ss(float * p, __mmask8 k, __m128 a);
MOVSS __m128 _mm_load_ss(float * p)
MOVSS void_mm_store_ss(float * p, __m128 a)
MOVSS __m128 _mm_move_ss(__m128 a, __m128 b)
SIMD Floating-Point Exceptions
None
Other Exceptions
Non-EVEX-encoded instruction, see Exceptions Type 5; additionally
| #UD |
If VEX.vvvv != 1111B. EVEX-encoded instruction, see Exceptions Type E10. |


Hi, I am Hemansu Kumar Tanty, Software Engineer at Grab.
I am a Java & Go Ninja and Full Stack Enthusiast.
I love Travel and Photography.
I am a huge Batman fan.


--- layout: a_base nav_light: PARTNERS cssUrls: style.css jsUrs: script.js cssContentClassName: mt-5 mb-5 ---


Intro
open-toggle is a jQuery plugin that makes sure that only one element has (user-defined)open class at a time amongst the selected elements.
Demo
Usage
Download the plugin and add it to the page.
<script src="/path/to/jquery.open-toggle.min.js"></script>
Add some HTML elements to the page.
Add the following script at the end of the <body> tag.
<script>
$(document).ready(function(){
$(".open-toggle").openToggle();
});
</script>
Thats it! This plugin will make sure that only one element has open class.
Options
$( selector ).openToggle( <className> );
selector
Defines which element are to be considered by this plugin.
className - Optional. Default: open
Defines the class name that is to be added to element when it is clicked(opened).


Hypergraph partitioning is a useful partitioning and load balancing method when connectivity data is available. It can be viewed as a more sophisticated alternative to the traditional graph partitioning.
A hypergraph consists of vertices and hyperedges. A hyperedge connects one or more vertices. A graph is a special case of a hypergraph where each edge has size two (two vertices). The hypergraph model is well suited to parallel computing, where vertices correspond to data objects and hyperedges represent the communication requirements. The basic partitioning problem is to partition the vertices into k approximately equal sets such that the number of cut hyperedges is minimized. Most partitioners (including Zoltan-PHG) allows a more general model where both vertices and hyperedges can be assigned weights. It has been shown that the hypergraph model gives a more accurate representation of communication cost (volume) than the graph model. In particular, for sparse matrix-vector multiplication, the hypergraph model exactly represents communication volume. Sparse matrices can be partitioned either along rows or columns; in the row-net model the columns are vertices and each row corresponds to an hyperedge, while in the column-net model the roles of vertices and hyperedges are reversed.
Zoltan contains a native parallel hypergraph partitioner, called PHG
(Parallel HyperGraph partitioner). In addition, Zoltan provides
access to PaToH,
a serial hypergraph partitioner.
Note that PaToH is not part of Zoltan and should be obtained
separately from the
PaToH web site.
Zoltan-PHG is a fully parallel multilevel hypergraph partitioner. For
further technical description, see [Devine et al, 2006].
| Method String: | HYPERGRAPH |
| Parameters: | |
| HYPERGRAPH_PACKAGE |
PHG (parallel) or PaToH (serial) |
| CHECK_HYPERGRAPH |
Check if input data is valid.
(Slows performance;intended for debugging.) |
|
PHG_OUTPUT_LEVEL |
Level of verbosity; 0 is silent. |
| PHG_FINAL_OUTPUT |
Print stats about final
partition? (0/1) |
| PHG_NPROC_VERTEX |
Desired number of processes in the vertex direction (for 2D internal layout) |
| PHG_NPROC_HEDGE |
Desired number of processes in the hyperedge direction (for 2D internal layout) |
| PHG_COARSENING_METHOD | The method to use in matching/coarsening; currently these are
available. agg - agglomerative inner product matching (a.k.a. heavy connectivity matching) ipm - inner product matching (a.k.a. heavy connectivity matching) c-ipm - column ipm; faster method based on ipm within processor columns a-ipm - alternate between fast method (l-ipm ) and ipm l-ipm - local ipm on each processor. Fastest option but often gives poor quality. h-ipm - hybrid ipm that uses partial c-ipm followed by ipm on each level |
| PHG_COARSENING_LIMIT |
Number of vertices at which to stop coarsening. |
| PHG_VERTEX_VISIT_ORDER |
Ordering of vertices in greedy
matching scheme: 0 - random 1 - natural order (as given by the query functions) 2 - increasing vertex weights 3 - increasing vertex degree 4 - increasing vertex degree, weighted by pins |
| PHG_EDGE_SCALING |
Scale edge weights by some
function of size of the hyperedges: 0 - no scaling 1 - scale by 1/(size-1) [absorption scaling] 2 - scale by 2/((size*size-1)) [clique scaling] |
| PHG_VERTEX_SCALING |
Variations in "inner product"
similarity metric (for matching): 0 - Euclidean inner product: <x,y> 1 - cosine similarity: <x,y>/(|x|*|y|) 2 - <x,y>/(|x|^2 * |y|^2) 3 - scale by sqrt of vertex weights 4 - scale by vertex weights |
| PHG_COARSEPARTITION_METHOD | Method to partition the coarsest (smallest) hypergraph;
typically done in serial: random - random linear - linear (natural) order greedy - greedy method based on minimizing cuts auto - automatically select from the above methods (in parallel, the processes will do different methods) |
| PHG_REFINEMENT_METHOD |
Refinement algorithm: fm - two-way approximate FM none - no refinement |
| PHG_REFINEMENT_LOOP_LIMIT | Loop limit in FM refinement. Higher number means more
refinement. |
| PHG_REFINEMENT_MAX_NEG_MOVE |
Maximum number of negative moves allowed in FM. |
| PHG_BAL_TOL_ADJUSTMENT |
Controls how the balance tolerance is adjusted at
each level of bisection. |
| PHG_RANDOMIZE_INPUT |
Randomize layout of vertices and
hyperedges in internal parallel 2D layout? (0/1) |
| PHG_EDGE_WEIGHT_OPERATION | Operation to be applied to edge
weights supplied by different processes for the same hyperedge: add - the hyperedge weight will be the sum of the supplied weights max - the hyperedge weight will be the maximum of the supplied weights error - if the hyperedge weights are not equal, Zoltan will flag an error, otherwise the hyperedge weight will be the value returned by the processes |
| EDGE_SIZE_THRESHOLD |
Ignore hyperedges greater than this fraction times
number of vertices. |
| PATOH_ALLOC_POOL0 |
Memory allocation for PaToH; see
the PaToH manual for details. |
| PATOH_ALLOC_POOL1 |
Memory allocation for PaToH; see the PaToH manual for details. |
| Default values: | |
| HYPERGRAPH_PACKAGE = PHG |
|
| CHECK_HYPERGRAPH
= 0 |
|
| PHG_OUTPUT_LEVEL=0 | |
| PHG_FINAL_OUTPUT=0 | |
| PHG_REDUCTION_METHOD=ipm | |
| PHG_REDUCTION_LIMIT=100 | |
| PHG_VERTEX_VISIT_ORDER=0 | |
| PHG_EDGE_SCALING=0 | |
| PHG_VERTEX_SCALING=0 | |
| PHG_COARSEPARTITION_METHOD=greedy | |
| PHG_REFINEMENT_METHOD=fm | |
| PHG_REFINEMENT_LOOP_LIMIT=10 | |
| PHG_REFINEMENT_MAX_NEG_MOVE=100 | |
| PHG_BAL_TOL_ADJUSTMENT=0.7 | |
| PHG_RANDOMIZE_INPUT=0 | |
| PHG_EDGE_WEIGHT_OPERATION=max | |
| EDGE_SIZE_THRESHOLD=0.25 | |
| PATOH_ALLOC_POOL0=0 | |
| PATOH_ALLOC_POOL1=0 | |
| Required Query Functions: | |
| ZOLTAN_NUM_OBJ_FN | |
| ZOLTAN_OBJ_LIST_FN or ZOLTAN_FIRST_OBJ_FN/ZOLTAN_NEXT_OBJ_FN pair | |
| ZOLTAN_HG_SIZE_CS_FN
ZOLTAN_HG_CS_FN |
|
| Optional Query Functions: | |
| ZOLTAN_HG_SIZE_EDGE_WTS_FN | |
| ZOLTAN_HG_EDGE_WTS_FN |
It is possible to provide the graph query functions instead of the hypergraph queries, though this is not recommended. If only graph query functions are registered, Zoltan will automatically create a hypergraph from the graph, but some information (specifically, edge weights) will be lost.


{% extends 'base.html'%} {% block content %} {{block.super}}
Police information
Police station name{{info.name}} Neighbrhood{{info.location}} Contact{{info.contact}}
Health information


An open source thermostat which is customizable, cost effective and smart. This tutorial will teach you how to build a thermostat for the home or the office heating system, remotely controlled via a mobile app running on iOS or Android.
You will learn how to:
Moreover, because in the IoT reality software interacts with the physical world, you will also learn how to:
errors
This is also a good opportunity to explore all of the possibilities offered by Rotilio Maker, our IoT development platform based on Particle.io’s Photon/Electron..


How to Create a Simple PowerPoint Video Lecture
Welcome to our tutorial "How to Create a Simple PowerPoint Video".

This tutorial will show and guide you, step by step, how to create a simple PowerPoint Video for an online course.
Here are the topics you will learn:


@* Copyright 2018, Oath Inc. Licensed under the terms of the Apache License 2.0. Please see LICENSE file in project root for terms. *@ @(workerLists: List[Map[String, Any]],workerConfig: String )
| Middle Manager | Action |
|---|---|
| @worker("host") | @if(worker("status").asInstanceOf[Boolean]) { } else { } |
To be done!
*@ @*To be done
*@ @*@workerConfig


LCARSLibrary Class
Constructor
LCARSLibrary
(
-
configuration
Parameters:
-
configuration
Object
Methods
checkAccess
(
private
-
session
-
request
-
action
Parameters:
-
session
Session -
request
String -
action
String
Throws:
Object:
On no access
emit
(
-
session
-
request
-
key
-
data
-
origin
Parameters:
-
session
Session -
request
String -
key
String -
data
Object -
origin
String
Throws:
Object:
On no access
propagating
(
-
id
-
event
Parameters:
-
id
StringThe Element causing the event emission from this set.
-
event
EventThe Event that is propagating.
Properties
description
String
name
String
Default: "Library"
updated
Number
updater
String
Username of who last updated this library.
Default: "System"


Hugo (https://www.github.com/spf13/hugo) is a static site generator written in Go. It’s super fast and fairly flexible. I’ve really enjoyed using it to build this site.
However, it requires a very strict folder layout and filenaming convention which is daunting when first starting out. This project aims to provide a small helper tool that will help you through creating the initial project structure as well as project types. It’s modelled after django-admin.
hugoadmin is written in Go using Cobra (https://www.github.com/spf13/cobra).
hugoadmin createproject new-project-name
creates an initial project.hugoadmin createtype new-type-name
creates a new content type.


Welcome
Welcome to the course. Internet is the most relevant information technology of our age. World Wide Web is its most important application. In this course we will learn the architecture of WWW, its main protocols and representation formats. The practical component of the course will focus on design and implementation of Web applications. Additional topics such as Semantic Web, Social Web and Adaptive Web will help us better undestand current trends of Web development.
Course News
Formal Data
| Lectures |
Wednesday (13:15 - 15:00) Friday (11:00 - 12:45) |
|
|---|---|---|
| Practice |
Wednesday (15:15 - 17:00) Friday (13:15 - 15:00) |
|
| Instructor | Sergey Sosnovsky | |
| Teaching assistants |
Christopher Ferguson Sander Vanheste |
|
| Student assistants |
Michiel van Heusden Rick de Boer Silvan Eelman |


Privacy Policy
Repost (hereafter, “my,” “me,” “myself”, “I” or the “App”), is committed to protecting your privacy. This Website Privacy Policy (“Privacy Policy”) is provided in order to ensure the confidence of users and of visitors (hereafter, “you” or “your”) to this App (defined below)
This Privacy Policy governs the use and collection of information from you by the App through your use of this app. This Privacy Policy does not apply to any other information you may provide me through other means (e.g., via mail, via telephone or at a live event).
I reserve the right to add, change, update, or modify this Privacy Policy at any time and without notice by posting such addition, change, update, or modification in the App. Any such addition, change, update or modification will be effective immediately upon posting on the App. Please check this page periodically for changes. Information collected prior to the time any change is posted will be used according to the rules and policies that are applied at the time the information was collected.
Copyright Information
All images in the App are readily available in various places on the Internet and are believed to be in public domain. Images posted are believed to be posted within my rights according to the U.S. Copyright Fair Use Act (title 17, U.S. Code.)
Information Collected
Analytics automatically collects some or all of the following information when you visit the app, including: (i) your device type, (ii) your operating system version, (iii) the URL being requested, (iv) the app settings being used, (v) total images viewed, (vi) the date and time of the request, and (vii) source of any link (collectively, “Traffic Data”). Traffic Data is anonymous information that does not personally identify you but is helpful for improving your experience on the App. I use Traffic Data to help diagnose potential problems with the App and to report and collect aggregate non-personal information.
Advertisers
You will note the presence of third party advertisers on the App. In addition, from time to time these advertisers may post their own giveaways, contests and surveys or requests for registration. If you respond, in any way, to an advertiser tile, banner, contest, giveaway, survey or link in this App, this Privacy Policy may not apply and you will then be subject to the privacy policy, terms, conditions and copyright policies of the advertiser’s website and governing policies, divisions or bodies. For example, I do not control how third party advertisers use cookies that originate from their own websites even if linked from this App.
I use third-party advertising companies to serve ads when you visit this App. These companies may use information (not including your name, address, email address or telephone number) about your visits to this App and other websites in order to provide advertisements about goods and services of interest to you. If you would like more information about this practice and to know your choices about not having this information used by these companies, click “HERE”.
Some vendors such as Google use cookies to serve ads in the App. Google’s DART cookie enables it to serve ads to users based on their visit to the App and other websites on the Internet. Users may opt out of the use of the DART cookie by visiting the Google ad and content network privacy policy.
Links to Other Websites
This App provides links and pointers to various websites maintained by other organizations. The App provides these links as a convenience to the users, but does not operate, control or endorse these outside linked sites unless otherwise expressly and duly noted. I, ON MY OWN BEHALF, EXPRESSLY DISCLAIM ANY OBLIGATION, RESPONSIBILITY OR LIABILITY FOR THE COLLECTION, USE OR DISTRIBUTION OF INFORMATION COLLECTED THOUGH ANY THIRD PARTY SITES. I encourage you to read the privacy policies contained on each of the websites you visit.
Contact
If you have any questions about this Privacy Policy or the practices of this app, please contact me at info[at]dodgingpixels[dot]com.


Save the Puppies!
Please use a unique name for each new animal
Name your animal!
Create your animal!
Start!