Heather Nevarez
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WITNESS LIST Culture, Recreation, & Tourism Committee August 23, 2006-1:00P Archeological sites and cemeteries On: Hite, Gerron (Texas Historical Commission) Mercado-Allinger, Patricia (Texas Historical Commission) Oaks, Larry (Texas Historical Commission) Fishing Tournaments On: Watson Jr., Mark (Self) Texas State Library and Archives On: Rudd, Peggy (Texas State Library and Archives Commission)


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module MongoSend_lwt: sig
.. end
This module simply define two functions used as underlying low level unix socket output.
val send_no_reply : (Lwt_io.input_channel * Lwt_io.output_channel) Lwt_pool.t ->
string -> unit Lwt.t
this function just send a string out via the supplied file_descr. It does not wait for any reponses. immediately finishes.
val send_with_reply : (Lwt_io.input_channel * Lwt_io.output_channel) Lwt_pool.t ->
string -> MongoReply.t Lwt.t
this function will send the string and wait for a response as a MongoReply


- Accomplishment
- Challenge
- Confidence
- Economic Security
- Growth
- Hope
- Inspiration
- Intellectual Status
- Leadership
- Persistance
- Personal Development
- Self-knowledge
- Wealth
Leadership is the most important value I have. My definition of leadership is the act of guiding others towards a positive outcome as a positive influence. The reason why I find it so important is because it has the most power to change something whether it's a work environment or a large society. I love helping others towards a set goal and making them the best they can be. It is my passion. I find it an opportunity not an obligation and I feel it is the best way I can contribute to society.
| Values: | Accomplishment | Challenge | Confidence | Economic Security | Growth | Hope | Inspiration | Intellectual Status | Leadership | Persistance | Personal Development | Self-knowledge | Wealth |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1-5 | 5 | 5 | 5 | 4 | 5 | 4 | 5 | 4 | 5 | 5 | 5 | 4 | 5 |


| 1 | /* =========================================================== | |
| 2 | * JFreeChart : a free chart library for the Java(tm) platform | |
| 3 | * =========================================================== | |
| 4 | * | |
| 5 | * (C) Copyright 2000-2009, by Object Refinery Limited and Contributors. | |
| 6 | * | |
| 7 | * Project Info: http://www.jfree.org/jfreechart/index.html | |
| 8 | * | |
| 9 | * This library is free software; you can redistribute it and/or modify it | |
| 10 | * under the terms of the GNU Lesser General Public License as published by | |
| 11 | * the Free Software Foundation; either version 2.1 of the License, or | |
| 12 | * (at your option) any later version. | |
| 13 | * | |
| 14 | * This library is distributed in the hope that it will be useful, but | |
| 15 | * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY | |
| 16 | * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public | |
| 17 | * License for more details. | |
| 18 | * | |
| 19 | * You should have received a copy of the GNU Lesser General Public | |
| 20 | * License along with this library; if not, write to the Free Software | |
| 21 | * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, | |
| 22 | * USA. | |
| 23 | * | |
| 24 | * [Java is a trademark or registered trademark of Sun Microsystems, Inc. | |
| 25 | * in the United States and other countries.] | |
| 26 | * | |
| 27 | * ------------------------- | |
| 28 | * StandardXYBarPainter.java | |
| 29 | * ------------------------- | |
| 30 | * (C) Copyright 2008, 2009, by Object Refinery Limited. | |
| 31 | * | |
| 32 | * Original Author: David Gilbert (for Object Refinery Limited); | |
| 33 | * Contributor(s): -; | |
| 34 | * | |
| 35 | * Changes: | |
| 36 | * -------- | |
| 37 | * 19-Jun-2008 : Version 1 (DG); | |
| 38 | * | |
| 39 | */ | |
| 40 | ||
| 41 | package org.jfree.chart.renderer.xy; | |
| 42 | ||
| 43 | import java.awt.Color; | |
| 44 | import java.awt.GradientPaint; | |
| 45 | import java.awt.Graphics2D; | |
| 46 | import java.awt.Paint; | |
| 47 | import java.awt.Stroke; | |
| 48 | import java.awt.geom.Rectangle2D; | |
| 49 | import java.awt.geom.RectangularShape; | |
| 50 | import java.io.Serializable; | |
| 51 | ||
| 52 | import org.jfree.chart.util.GradientPaintTransformer; | |
| 53 | import org.jfree.chart.util.RectangleEdge; | |
| 54 | ||
| 55 | /** | |
| 56 | * An implementation of the {@link XYBarPainter} interface that preserves the | |
| 57 | * behaviour of bar painting that existed prior to the introduction of the | |
| 58 | * {@link XYBarPainter} interface. | |
| 59 | * | |
| 60 | * @see GradientXYBarPainter | |
| 61 | * | |
| 62 | * @since 1.0.11 | |
| 63 | */ | |
| 64 | public class StandardXYBarPainter implements XYBarPainter, Serializable { | |
| 65 | ||
| 66 | /** | |
| 67 | * Creates a new instance. | |
| 68 | */ | |
| 69 | public StandardXYBarPainter() { | |
| 70 | } | |
| 71 | ||
| 72 | /** | |
| 73 | * Paints a single bar instance. | |
| 74 | * | |
| 75 | * @param g2 the graphics target. | |
| 76 | * @param renderer the renderer. | |
| 77 | * @param row the row index. | |
| 78 | * @param column the column index. | |
| 79 | * @param selected is the data item selected? | |
| 80 | * @param bar the bar | |
| 81 | * @param base indicates which side of the rectangle is the base of the | |
| 82 | * bar. | |
| 83 | * | |
| 84 | * @since 1.2.0 | |
| 85 | */ | |
| 86 | public void paintBar(Graphics2D g2, XYBarRenderer renderer, int row, | |
| 87 | int column, boolean selected, RectangularShape bar, | |
| 88 | RectangleEdge base) { | |
| 89 | ||
| 90 | Paint itemPaint = renderer.getItemPaint(row, column, selected); | |
| 91 | GradientPaintTransformer t = renderer.getGradientPaintTransformer(); | |
| 92 |
2
1. paintBar : negated conditional → NO_COVERAGE 2. paintBar : negated conditional → NO_COVERAGE |
if (t != null && itemPaint instanceof GradientPaint) { |
| 93 | itemPaint = t.transform((GradientPaint) itemPaint, bar); | |
| 94 | } | |
| 95 |
1
1. paintBar : removed call to java/awt/Graphics2D::setPaint → NO_COVERAGE |
g2.setPaint(itemPaint); |
| 96 |
1
1. paintBar : removed call to java/awt/Graphics2D::fill → NO_COVERAGE |
g2.fill(bar); |
| 97 | ||
| 98 | // draw the outline... | |
| 99 |
1
1. paintBar : negated conditional → NO_COVERAGE |
if (renderer.isDrawBarOutline()) { |
| 100 | // && state.getBarWidth() > BAR_OUTLINE_WIDTH_THRESHOLD) { | |
| 101 | Stroke stroke = renderer.getItemOutlineStroke(row, column, | |
| 102 | selected); | |
| 103 | Paint paint = renderer.getItemOutlinePaint(row, column, selected); | |
| 104 |
2
1. paintBar : negated conditional → NO_COVERAGE 2. paintBar : negated conditional → NO_COVERAGE |
if (stroke != null && paint != null) { |
| 105 |
1
1. paintBar : removed call to java/awt/Graphics2D::setStroke → NO_COVERAGE |
g2.setStroke(stroke); |
| 106 |
1
1. paintBar : removed call to java/awt/Graphics2D::setPaint → NO_COVERAGE |
g2.setPaint(paint); |
| 107 |
1
1. paintBar : removed call to java/awt/Graphics2D::draw → NO_COVERAGE |
g2.draw(bar); |
| 108 | } | |
| 109 | } | |
| 110 | ||
| 111 | } | |
| 112 | ||
| 113 | /** | |
| 114 | * Paints a single bar instance. | |
| 115 | * | |
| 116 | * @param g2 the graphics target. | |
| 117 | * @param renderer the renderer. | |
| 118 | * @param row the row index. | |
| 119 | * @param column the column index. | |
| 120 | * @param selected is the data item selected? | |
| 121 | * @param bar the bar. | |
| 122 | * @param base indicates which side of the rectangle is the base of the | |
| 123 | * bar. | |
| 124 | * @param pegShadow peg the shadow to the base of the bar? | |
| 125 | * | |
| 126 | * @since 1.2.0 | |
| 127 | */ | |
| 128 | public void paintBarShadow(Graphics2D g2, XYBarRenderer renderer, int row, | |
| 129 | int column, boolean selected, RectangularShape bar, | |
| 130 | RectangleEdge base, boolean pegShadow) { | |
| 131 | ||
| 132 | // handle a special case - if the bar colour has alpha == 0, it is | |
| 133 | // invisible so we shouldn't draw any shadow | |
| 134 | Paint itemPaint = renderer.getItemPaint(row, column, selected); | |
| 135 |
1
1. paintBarShadow : negated conditional → NO_COVERAGE |
if (itemPaint instanceof Color) { |
| 136 | Color c = (Color) itemPaint; | |
| 137 |
1
1. paintBarShadow : negated conditional → NO_COVERAGE |
if (c.getAlpha() == 0) { |
| 138 | return; | |
| 139 | } | |
| 140 | } | |
| 141 | ||
| 142 | RectangularShape shadow = createShadow(bar, renderer.getShadowXOffset(), | |
| 143 | renderer.getShadowYOffset(), base, pegShadow); | |
| 144 |
1
1. paintBarShadow : removed call to java/awt/Graphics2D::setPaint → NO_COVERAGE |
g2.setPaint(Color.gray); |
| 145 |
1
1. paintBarShadow : removed call to java/awt/Graphics2D::fill → NO_COVERAGE |
g2.fill(shadow); |
| 146 | ||
| 147 | } | |
| 148 | ||
| 149 | /** | |
| 150 | * Creates a shadow for the bar. | |
| 151 | * | |
| 152 | * @param bar the bar shape. | |
| 153 | * @param xOffset the x-offset for the shadow. | |
| 154 | * @param yOffset the y-offset for the shadow. | |
| 155 | * @param base the edge that is the base of the bar. | |
| 156 | * @param pegShadow peg the shadow to the base? | |
| 157 | * | |
| 158 | * @return A rectangle for the shadow. | |
| 159 | */ | |
| 160 | private Rectangle2D createShadow(RectangularShape bar, double xOffset, | |
| 161 | double yOffset, RectangleEdge base, boolean pegShadow) { | |
| 162 | double x0 = bar.getMinX(); | |
| 163 | double x1 = bar.getMaxX(); | |
| 164 | double y0 = bar.getMinY(); | |
| 165 | double y1 = bar.getMaxY(); | |
| 166 |
1
1. createShadow : negated conditional → NO_COVERAGE |
if (base == RectangleEdge.TOP) { |
| 167 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x0 += xOffset; |
| 168 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x1 += xOffset; |
| 169 |
1
1. createShadow : negated conditional → NO_COVERAGE |
if (!pegShadow) { |
| 170 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y0 += yOffset; |
| 171 | } | |
| 172 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y1 += yOffset; |
| 173 | } | |
| 174 |
1
1. createShadow : negated conditional → NO_COVERAGE |
else if (base == RectangleEdge.BOTTOM) { |
| 175 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x0 += xOffset; |
| 176 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x1 += xOffset; |
| 177 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y0 += yOffset; |
| 178 |
1
1. createShadow : negated conditional → NO_COVERAGE |
if (!pegShadow) { |
| 179 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y1 += yOffset; |
| 180 | } | |
| 181 | } | |
| 182 |
1
1. createShadow : negated conditional → NO_COVERAGE |
else if (base == RectangleEdge.LEFT) { |
| 183 |
1
1. createShadow : negated conditional → NO_COVERAGE |
if (!pegShadow) { |
| 184 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x0 += xOffset; |
| 185 | } | |
| 186 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x1 += xOffset; |
| 187 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y0 += yOffset; |
| 188 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y1 += yOffset; |
| 189 | } | |
| 190 |
1
1. createShadow : negated conditional → NO_COVERAGE |
else if (base == RectangleEdge.RIGHT) { |
| 191 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x0 += xOffset; |
| 192 |
1
1. createShadow : negated conditional → NO_COVERAGE |
if (!pegShadow) { |
| 193 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
x1 += xOffset; |
| 194 | } | |
| 195 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y0 += yOffset; |
| 196 |
1
1. createShadow : Replaced double addition with subtraction → NO_COVERAGE |
y1 += yOffset; |
| 197 | } | |
| 198 |
3
1. createShadow : Replaced double subtraction with addition → NO_COVERAGE 2. createShadow : Replaced double subtraction with addition → NO_COVERAGE 3. createShadow : mutated return of Object value for org/jfree/chart/renderer/xy/StandardXYBarPainter::createShadow to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return new Rectangle2D.Double(x0, y0, (x1 - x0), (y1 - y0)); |
| 199 | } | |
| 200 | ||
| 201 | /** | |
| 202 | * Tests this instance for equality with an arbitrary object. | |
| 203 | * | |
| 204 | * @param obj the obj (null permitted). | |
| 205 | * | |
| 206 | * @return A boolean. | |
| 207 | */ | |
| 208 | public boolean equals(Object obj) { | |
| 209 |
1
1. equals : negated conditional → KILLED |
if (obj == this) { |
| 210 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → NO_COVERAGE |
return true; |
| 211 | } | |
| 212 |
1
1. equals : negated conditional → KILLED |
if (!(obj instanceof StandardXYBarPainter)) { |
| 213 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → KILLED |
return false; |
| 214 | } | |
| 215 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → KILLED |
return true; |
| 216 | } | |
| 217 | ||
| 218 | /** | |
| 219 | * Returns a hash code for this instance. | |
| 220 | * | |
| 221 | * @return A hash code. | |
| 222 | */ | |
| 223 | public int hashCode() { | |
| 224 | int hash = 37; | |
| 225 | // no fields to compute... | |
| 226 |
1
1. hashCode : replaced return of integer sized value with (x == 0 ? 1 : 0) → SURVIVED |
return hash; |
| 227 | } | |
| 228 | ||
| 229 | } | |
Mutations | ||
| 92 |
1.1 2.2 |
|
| 95 |
1.1 |
|
| 96 |
1.1 |
|
| 99 |
1.1 |
|
| 104 |
1.1 2.2 |
|
| 105 |
1.1 |
|
| 106 |
1.1 |
|
| 107 |
1.1 |
|
| 135 |
1.1 |
|
| 137 |
1.1 |
|
| 144 |
1.1 |
|
| 145 |
1.1 |
|
| 166 |
1.1 |
|
| 167 |
1.1 |
|
| 168 |
1.1 |
|
| 169 |
1.1 |
|
| 170 |
1.1 |
|
| 172 |
1.1 |
|
| 174 |
1.1 |
|
| 175 |
1.1 |
|
| 176 |
1.1 |
|
| 177 |
1.1 |
|
| 178 |
1.1 |
|
| 179 |
1.1 |
|
| 182 |
1.1 |
|
| 183 |
1.1 |
|
| 184 |
1.1 |
|
| 186 |
1.1 |
|
| 187 |
1.1 |
|
| 188 |
1.1 |
|
| 190 |
1.1 |
|
| 191 |
1.1 |
|
| 192 |
1.1 |
|
| 193 |
1.1 |
|
| 195 |
1.1 |
|
| 196 |
1.1 |
|
| 198 |
1.1 2.2 3.3 |
|
| 209 |
1.1 |
|
| 210 |
1.1 |
|
| 212 |
1.1 |
|
| 213 |
1.1 |
|
| 215 |
1.1 |
|
| 226 |
1.1 |


Correlation View¶
The Correlation View displays the relationships found between variables when the ensemble is viewed holistically. Each column of the Correlation View’s bar chart represents a different canonical component. These orthogonal components are ordered from left to right in decreasing importance, as shown by the decreasing R2 and increasing p-values in the first two rows of each component column. Variable names are shown along the left edge with rows for input variables colored in green, and rows for output variables colored in lavender. The number of components returned by CCA is equal to the minimum of the number of inputs versus the number of outputs. So, for the example in Figure 23, where there are four inputs and three outputs, CCA will return three canonical components.
In the bar chart, only one canonical component is expanded at a time (e.g. in Figure 23, CCA1 is expanded, while in Figure 24, CCA1 is collapsed and CCA2 is expanded). Clicking on a CCA column name changes the selected canonical component. This collapses the bar chart from the previously selected component and expands that of the new component.
The horizontal bars in the expanded bar chart visually encode the relationships between variables, both in terms of the magnitude of the structure coefficients, and in terms of the correlation type (positive or negative). Numeric values for the coefficients are displayed in the center of each column. Positive values are drawn as red bars extending towards the right. Negative values are drawn in blue extending to the left. The orientation combined with the color-coding acts to visually reinforce the relationship information. At a glance, you can see correlative relationships between variables and their strength by comparing the color, direction, and length of the bars. Positively correlated variables will display the same color and bar orientation, while negatively correlated variables will be opposed.
The bar chart rows can be sorted by variable strength. To the right of the CCA column name is a small triangular icon. Clicking on this icon sorts the columns by the unsigned magnitudes of the structure coefficients in the expanded column, though all columns will reflect the order returned by this sorting operation (i.e. the rows are sorted using this column as the key). The initial sort is descending and the orientation of the triangle reflects this by rendering the triangle with the wide edge at the top and the point at the bottom (e.g. CCA1 in Figure 23). The sorting order is reversed if you click the triangle again. Ascending sorts are signified by rendering the triangle with the point at the top. Inputs and outputs are sorted independently. For long lists of variables, the input and output variable sets are independently scrollable. Note that in Figure 24, although CCA2 is selected, the decreasing sort order from CCA1 is still maintained. Sorting column is independent of component selection. Hovering over any of the CCA column headers, the sorting icon for that column becomes visible and can be clicked without needing to expand the component.
Clicking on a row in the bar chart selects that variable for color-coding the points in the Simulation View (i.e. each simulation point is color-coded according to its value for that variable). The variable row is highlighted by darkening the background color and changing the font color to white. The color palette, shown in the Legend alongside the value range for the color-coding variable, corresponds to the currently selected theme (see Color Themes). This same color-coding is applied to the cell backgrounds of this column of the Variable Table, as is demonstrated by the Weight column in both Figure 23 and Figure 24.


Hey, you are seeing a demo of Responsive Tabs jQuery plugin (developed by Anup Pandey).
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To know how to use this plugin, see "How to use" tab!
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from your script to the markup you want to make as Responsive Tabs$('#respTabs').responsiveTabs()
in this caseresp-tab = "default"
in my parent div


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{% trans %}
CKAN is the world’s leading open-source data portal platform.
CKAN is a complete out-of-the-box software solution that makes data accessible and usable – by providing tools to streamline publishing, sharing, finding and using data (including storage of data and provision of robust data APIs). CKAN is aimed at data publishers (national and regional governments, companies and organizations) wanting to make their data open and available.
CKAN is used by governments and user groups worldwide and powers a variety of official and community data portals including portals for local, national and international government, such as the UK’s data.gov.uk and the European Union’s publicdata.eu, the Brazilian dados.gov.br, Dutch and Netherland government portals, as well as city and municipal sites in the US, UK, Argentina, Finland and elsewhere.
CKAN: http://ckan.org/
CKAN Tour: http://ckan.org/tour/
Features overview: http://ckan.org/features/


EscaPe is the annual project symposium of the Department of Computer Engineering, University of Peradeniya. It presents you with the research projects of the undergraduates of the Department of Computer Engineering. ESCaPe 2021 is the 6th symposium that is organized by the department and this time the symposium is open for a broader audience and aims to build a platform for the undergraduates to present their research ideas to the industry and academic community.
Mr.Jeevan Gnanam is the founder and Group CEO of VeracityAI. He is a data science & AI enthusiast, an entrepreneurial idea generator, a mentor, and a facilitator for entrepreneurial development for youth in Sri Lanka. He is the Chief Executive Officer and Executive Director at St.Anthony's Industries Group which is one of the oldest and largest conglomerates for manufacturing textiles, building materials, plastic products, industrial fasteners, cement, fiber cement and corrugated roofing sheets.
Mr.Jeevan Gnanam also serves as the CEO of Anton which is one of the largest plastic manufacturers in the country. His commitment has led Anton to many firsts in plastics manufacturing in Sri Lanka. Mr. Jeevan is also a co-founder of Providence which has now grown to include Providence BPO.
He is a founder member of the Lanka Angel Network, which is targeting to support Sri Lankan entrepreneurs and companies to grow by providing venture capital and mentorship.
He is also the immediate past chairman of SLASSCOM, which is the national chamber for the IT/BPM industry in Sri Lanka. Mr. Jeevan is the visionary behind Sri Lanka's first premier operational IT park, Orion City and his leadership encompasses HATCH Sri Lanka, SAKS, OrionStellar.
Mr. Thushera Kawdawatta is the Chief Executive Officer at Axiata Digital Labs which is an innovative software service provider, offering telco-focused digital and IT services and solutions through successful digital transformation.
He is a tech enthusiast leader with accountability and responsibility in software delivery quality and specialized in Software architecture, Engineering management, and process improvement.
Over 24 years of experience in the industry have led him to be a people-oriented leader who thoroughly enjoys his work. Initially, he spent over 19 years at Virtusa as the Chief Software Architect contributing to software product development. During his years, Virtusa won the 2012 WITSA Global ICT Excellence Award for its Àkura School Management System. And also he was awarded for best Productivity software of the year 1999.
With his extensive experience, Mr. Thushera Kawdawatta has been working on over 100 software projects across numerous reputed global enterprises over the past few years while launching many IT initiatives. Mr. Thushera was appointed as a board member of CSSL, and a member of the parliament select committee on AI standards of Sri Lanka.
Malitha Liyanage
PresidentHashan Eranga
SecretaryDevin Gallage
Vice PresidentKshithija Dilhani
Editor


{% extends "base.html" %} {% block content %} {% if validlink %}
Please enter your new password twice so we can verify you typed it correctly.
{% else %}The password reset link was invalid, possibly because it has already been used. Please request a new password reset.
{% endif %} {% endblock %}


1. Introduction
Meshing is a technique that uses a device’s sensors to build a 3 dimensional representation of the world.
The mesh consists of a large collection of geometry of medium complexity that changes slowly over time (aka the world mesh) and a very small collection of complex quickly changing content that represents the geometry close to the user (aka the near mesh).
A user agent can have support for no, one or both types of geometry and the website author can request one or both types of geometry data. Requesting the geometry data is an expensive process so an author should only request it if they will do something with the information.
Typically mesh data is not used to determine things like hand gestures or the recognition of real world objects. (However a UA could choose to infer this through postprocessing.)
The most common use cases for the world mesh are:
-
physics: interaction of virtual objects with the real world
-
occlusion: blocking part or the whole virtual object by a real world one
The most common use cases for the near mesh are:
-
a visual representation of objects near the viewer.
-
occlusion
1.1. Terminology
1.2. Application flow
Most applications using the WebXR Meshing API will follow a similar usage pattern:
-
During the creation of a WebXR session, pass a XRFeatureInit object with parameters for world and near mesh.
-
For each XRFrame, get the requested mesh data and apply it to the scene.
2. Initialization
2.1. XRMeshQuality
enum {
XRMeshQuality ,
"low" ,
"medium" };
"high"
XRMeshQuality
defines the quality of the mesh. A higher quality means that the mesh will be finer but also more resource intensive. It is up to the UA to define the quality level.
2.2. XRWorldMeshFeature
The "worldmesh" feature is used to request world meshing.
dictionary :
XRWorldMeshFeature XRFeatureInit {XRMeshQuality = "medium";
quality double = 10.0;
width double = 10.0;
height double = 10.0; };
breadth
The width
, height
and breadth
attributes define the distance, in meters, of the width, height and breadth of the area around the observer that should be meshed.
The quality
attribute defines the UA dependent quality of the mesh.
immersive-ar
XRSession
with world meshing.
let xrSession; navigator. xr. requestSession( "immersive-ar" , { requiredFeature: { name: "XRWorldMeshFeature" , quality: "medium" }}). then(( session) => { xrSession= session; });
should the world mesh follow the observer or should it stay relative to the original position or should it be configurable?
should the world mesh have an XRSpace?
2.3. XRNearMeshFeature
The "nearmesh" feature is used to request meshing near the observer. It is UA dependent what the scanned area for the near mesh is but it MUST not overlap with the world mesh.
dictionary :
XRNearMeshFeature XRFeatureInit {XRMeshQuality = "medium"; };
quality
The quality
attribute defines the UA dependent quality of the mesh.
immersive-ar
XRSession
with near meshing.
let xrSession; navigator. xr. requestSession( "immersive-vr" , { requiredFeature: { name: "XRNearMeshFeature" , quality: "low" }}). then(( session) => { xrSession= session; });
should the near mesh have an XRSpace?
3. Frame Loop
3.1. XRMesh structures
dictionary {
XRMeshBlock required Float32Array ;
vertices required Uint16Array ;
indices Float32Array ; };
normals
A XRMeshBlock
contains the geometry data of a single mesh instance.
vertices
contains a buffer with points in 3D space. Each point consists of 3 floats.
Each value in indices
points to an offset into a point inside vertices
and defines the corner of a triangle. The set of triangles creates a polygon mesh.
NOTE: the offset of each point is found by taking the index value and multiplying by 3.
XRMeshBlock
can contain an optional normals
which defines a buffer with the normal of each vertex. The size of normals
must be the same as vertices
.
is normals needed? If so, should it be requested during initialisation?
interface {
XRNearMesh readonly setlike <XRMeshBlock >; };interface {
XRWorldMesh readonly maplike <DOMString ,XRMeshBlock >; };dictionary {
XRMetadata XRWorldMesh worldMesh ;XRNearMesh nearMesh ; };
The worldMesh
attribute contains updates to the world mesh. If any key in the dictionary was a previously provided provided XRWorldMesh this new value must replace the previous XRMeshBlock. If the value of a new world XRMeshBlock contains no vertices, the existing XRMeshBlock must be deleted.
The nearMesh
attribute contains a new near mesh which will replace the previous near mesh (if any). If nearMesh contains no new XRMeshBlock object, there is no near mesh.
3.2. XRFrame
partial interface XRFrame {readonly attribute XRMetadata ; };
metaData
Each XRFrame contains a metaData
attribute with new or updated world or near mesh data.
should the mesh data persist per browser session or per xr session?
4. Security and Privacy Considerations
The WebXR Meshing API is a powerful feature with that carries significant privacy risks. A UA MUST ask permission from the user during session creation before meshing data is returned to the page.
An inline session must NOT have access to mesh data.
 It MUST not reveal writing, colors, pictures or other visual content.


49 #ifndef HOMEBOT_INCLUDE_HOMEBOT_REPERTOIRE_HPP_
50 #define HOMEBOT_INCLUDE_HOMEBOT_REPERTOIRE_HPP_
72 std::vector<BotBehavior> behaviors;
A BotBehavior is a set of operations that are executed serially to create a behavior.
bool load(const std::string &pFilename, const OperationParameters &pOpParams)
Load this repertoire with the operations contained in a repertoire file.
Definition: Repertoire.cpp:88
Holds system parameters used to ensure Operations are built to respect the limits of the system...
Definition: OperationParameters.hpp:52
A collection of HomeBot service robot behaviors; used by a BotActor to find behaviors to execute...
Definition: Repertoire.hpp:63
A simple read-only object to pass parameters used to make sure operations are within limits when crea...
BotBehavior getBehavior(const std::string &pName)
Determine whether a particular behavior is in a repertoire of behaviors.
Definition: Repertoire.cpp:68
Repertoire(const std::string &pBotType)
Constructor for Repertoire; creates a Repertoire customized for a specific HomeBot bot type...
Definition: Repertoire.cpp:55
Collection of operations used to perform a behavior.
Definition: BotBehavior.hpp:66


Preparation time
less than 30 mins
Cooking time
1 to 2 hours
Serves
Serves 12
Dietary
Preheat the oven to 160C/320F/Gas 3.
Melt the chocolate and butter together in a heatproof bowl placed over a pan of barely simmering water - make sure that the water does not touch the base of the bowl.
Place a separate heatproof bowl over a second pan of barely simmering water - make sure the water does not touch the base of the bowl. Add the eggs, sugar, soured cream and vanilla seeds to the bowl and whisk constantly for 5-6 minutes, until the mixture is fluffy and has doubled in volume.
Add the melted chocolate and butter mixture to the soured cream mixture and stir to combine.
Sift the flour, cinnamon and baking powder together into a separate bowl, then fold the mixture into the melted chocolate mixture.
Add the chopped chillies and stir gently.
Line a large ovenproof dish or deep baking tray with greased kitchen foil and pour the mixture into the dish.
Bake in the oven for 50-60 minutes, or until cooked through.
For the sauce, place the cream, butter, cocoa powder, caster sugar, brown sugar and cinnamon into a pan over a low heat and stir for 4-5 minutes, until the ingredients are melted and combined as thick sauce.
To serve, cut out slices of the fudge pudding and place onto plates. Drizzle with the sauce and serve with strawberries and whipped cream.


"It's okay. Life doesn't have to be perfect. It just has to be lived."
"Where are your guts?"
I am from the Golden State that is California. We have a bad rap but our rap is pretty good. I mean, look at Tupac. I have lived in a few other states and currently reside in Portland, Oregon. With a family of friends here I have found myself creating a whole new life and am very proud to call Portland my home.
I came from sales. I was ready for a new challenge. I was ready to learn something new. Working in the start-up world really helped me understand was dev was truly about. So, here I am, a student with no programming skills, in a programming boot camp! If I can do it at over 30 years old, you can too!


Do you want steak or chicken?
Steak:
Chicken:
Who is your favorite Super Hero?
Batman
Hulk
Spiderman
Thor
Go!


Anticipating how anthropogenic climate change will affect natural and human systems requires an understanding not only of the changes in the mean climate but also whether and how climate variability will change. For instance, present temperature fluctuations in the tropics are strongly correlated with negative agricultural, economic, and political impacts ( 1– 3). The increasing frequency and persistence of extreme weather events ( 4) like heat waves or droughts can have severe impacts on many biological systems showing nonlinear responses to environmental change ( 5). These effects involve changes in the physiological responses of individual species ( 6), the risk of species extinction ( 7), the functioning of global terrestrial ecosystems ( 8), and human food security ( 9). Furthermore, climate variability can also be an indicator of the sensitivity of climate to perturbations, and variability changes have been proposed to be a forewarning of upcoming tipping points ( 10, 11). It is therefore important to understand the patterns of variability change and the mechanisms behind them.
Previous studies analyzing variability changes predicted by climate models have focused on changes in variance ( 12), mostly in high and mid-latitudes ( 13) and the global mean temperature ( 14, 15). Here, we analyze changes in the standard deviation (SD) of monthly temperature anomalies on a local scale, with the aims of (i) identifying regional hotspots where models agree on the largest magnitude changes and (ii) investigating the physical mechanisms behind the identified changes. Because of the variability of climate on multiple time scales, observational time series are usually too short to detect a clear human influence on climate variability ( 16– 18). Here, instead, we analyze all available state-of-the art climate models from the Coupled Model Intercomparison Project 5 (CMIP5) ( 19), which were used to inform the last report of the Intergovernmental Panel on Climate Change. Our time series consist of the historical simulation starting in 1850, followed by the future scenario with the largest greenhouse gas emissions, RCP8.5 ( 20). The 37 models in total are used to calculate changes until the year 2100, and simulations with nine of the models have been extended until the year 2300. In the following, we examine monthly temperature anomalies, where each anomaly value represents the deviation from the 30-year running mean of the same month at a particular grid cell in a model (see Materials and Methods). We then analyze the changes in SD over time that are associated with global warming.


In the previous challenges you created an Insertion Sort algorithm. It is a simple sorting algorithm that works well with small or mostly sorted data. However, it takes a long time to sort large unsorted data. To see why, we will analyze its running time.
Running Time of Algorithms
The running time of an algorithm for a specific input depends on the number of operations executed. The greater the number of operations, the longer the running time of an algorithm. We usually want to know how many operations an algorithm will execute in proportion to the size of its input, which we will call $N$.
For example, the first two input files for Insertion Sort were small, so it was able to sort them quickly. But the next two files were larger and sorting them took more time. What is the ratio of the running time of Insertion Sort to the size of the input? To answer this question, we need to examine the Insertion Sort algorithm.
Analysis of Insertion Sort
For each element $V$ in an array of $N$ numbers, Insertion Sort shifts everything to the right until it can insert $V$ into the array.
How long does all that shifting take?
In the best case, where the array was already sorted, no element will need to be moved, so the algorithm will just run through the array once and return the sorted array. The running time would be directly proportional to the size of the input, so we can say it will take $N$ time.
However, we usually focus on the worst-case running time (computer scientists are pretty pessimistic). The worst case for Insertion Sort occurs when the array is in reverse order. To insert each number, the algorithm will have to shift over that number to the beginning of the array. Sorting the entire array of $N$ numbers will therefore take $1+2+...+(N-1)$ operations, which is $N(N-1)/2$ (almost $N$$2$$/2$). Computer scientists just round that up (pick the dominant term) to $N$$2$ and say that Insertion Sort is an "$N$$2$ time" algorithm.
What this means
As the size of an input ($N$) increases, Insertion Sort's running time will increase by the square of $N$. So Insertion Sort can work well for small inputs, but becomes unreasonably slow for larger inputs. For large inputs, people use sorting algorithms that have better running times, which we will examine later.
Challenge
Can you modify your previous Insertion Sort implementation to keep track of the number of shifts it makes while sorting? The only thing you should print is the number of shifts made by the algorithm to completely sort the array. A shift occurs when an element's position changes in the array. Do not shift an element if it is not necessary.
Input Format
The first line contains $N$, the number of elements to be sorted. The next line contains $N$ integers $a[1]$, $a[2]$, ..., $a[N]$.
Output Format
Output the number of shifts it takes to sort the array.
Constraints
$1 \le N \le 1001$
$-10000 \le x \le 10000, x ∈ a$
Sample Input
5
2 1 3 1 2
Sample Output
4
Explanation
The first 1 is shifted once. The 3 stays where it is. The next 1 gets shifted twice. The final 2 gets shifted once. Hence, the total number of shifts is $4$.
Task
For this problem, you can copy your code from the InsertionSort problem, and modify it to keep track of the number of shifts instead of printing the array.


{{> head}} {{> test}}
{{> app-banner}} {{> section-banner title='UBC Farm'}}
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Big, loud, jazz
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EDM, Techno, DnB
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Nothing but cool
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this product have many details but we won't tell u . buy this and Know yourself. and also pls let us know also.
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Multilayer networks are used to represent many types of systems, such as those that have multiple types of connections between nodes.
Above we see a multilayer network with five layers (left) and its corresponding supra-adjacency matrix (right) which records the presence of connections between nodes.
- Hover over a node in the network to see it's corresponding location and connections in the supra-adjacency matrix.
- Choose to color nodes by layer or by node identity.
- Rotate the multilayer network 90 degrees.
- Adjust the viewing angle with the sliders.


Speech
Charlie Taylor, Chief Executive of the NCTL, gave a speech about a school-led system to the conference in Nottingham.
Good morning.
The great privilege of this job as Chief Executive of the National College is the opportunity I have to visit schools and hear from remarkable headteachers around the country.
One of these is Lynn Slinger, the inspirational headteacher of Forest Way Special School near Coalville in Leicestershire. It has been rated as ‘outstanding’ by Ofsted in its last 2 inspections and was described as being “conspicuously successful in all that it does”.
But Forest Way is much more than an outstanding school. It is, I believe, a template for education in England in the future. It was one of the first teaching schools designated in 2011 and since then it is quite remarkable what has been achieved.
A few years ago it would have been unthinkable that a school, particularly a special school, would be doing the things Forest Way is now doing. It is leading an alliance in taking on roles that might have traditionally been seen as the sole preserve of the local authority or the government including:
This includes creating maths, English and IT networks for primary teachers and running courses on primary computing, the early years foundation stage, a master’s degree in special needs and training for newly qualified teachers.
The alliance also works with George Spencer Academy, a licensed provider of National College leadership programmes. Together they identify and develop teachers with the potential to become school leaders of the future.
And on top of that they have 30 School Direct places with the universities of Leicester and Derby across both primary and secondary phases.
But I think most impressive of all, is the work Forest Way now does on school improvement.
Every school in the alliance receives an annual ‘health check’ to determine its strengths and needs. Forest Way then commissions national, local and specialist leaders of education to support schools within the alliance. There is real rigour and challenge in this work that has led to changes in the leadership in some alliance schools. At Forest Way there is an absolute determination that outcomes for pupils and Ofsted judgements will improve in all schools.
What are the factors that have allowed Forest Way Teaching School Alliance to develop in the way it has?
Firstly, an exceptional headteacher with the ambition, drive and vision to think way beyond her own school.
Secondly, a group of headteachers within the alliance who know that by working together they can improve the standards of teaching and the performance of their pupils far more than if they work on their own.
But thirdly and perhaps most importantly Forest Way has achieved its success because of the trust placed in it by Leicestershire County Council to improve the schools in its alliance.
But things are not always so healthy.
On the day I visited Forest Way I also met a group of headteachers from teaching schools across the East Midlands. They gave a very varied picture of their relationship with their local authority from excellent to, in one case, downright difficult.
There also seems to be a real nervousness amongst some local authorities about trusting the best schools to take on this work.
This nervousness shouldn’t last long where there are heads like Lynn Slinger.
Successful school-to-school support doesn’t just need to come from such larger alliances. Groups of heads across the country are realising what can be achieved when like-minded people start working together collectively to improve their schools. There is no government formula for this, but there are undoubtedly some essential components of effective school-to-school support.
The first of these is relationships and trust - that doesn’t mean that everyone needs to be best friends, indeed one of the dangers of school partnerships is they become too cosy. But trust is important because heads must be prepared to share information and to expose their schools to their colleagues, warts and all.
I know only too well how powerful this can be - but when I first became a head, I got great mentoring support from Chris Weaving and colleagues from a network of special school headteachers. They were tackling the same sort of problems as me; and often, they’d come up with a solution which I would never have thought of on my own.
This trust is also supported by developing a clear agreement for how the partnership will work - who will do what, how it will be funded and what are the expectations of the members.
Next is a willingness to share information. In my opinion no partnership can function if people are not prepared to put their data on the table for review and discussion. This requirement was one of the fundamental components of the success of the London challenge.
And that word challenge is essential. Heads have got to be prepared to say: “I have got virtually the same pupil profile as you and yet my results for writing are 20% lower. How can you help me to be as good as you are?”
This is not easy, there is professional pride at stake here, but without this openness, things will not change.
And I understand that some heads may not want to work with nearby schools, but there are alternatives. In the last few years there has been a big expansion of networks that are outside local authority areas or regions: groups like Challenge Partners, Leading Edge, By Schools for Schools, the Independent Academies Association and FASNA - the National Association for Freedom and Autonomy for Schools.
These organisations run a wide range of training, CPD and school improvement services, often nationally, along with comprehensive websites where information is shared and heads can stay in touch.
And finally there are the academy chains that have taken over and improved the performance of schools that have been failing for years. Greenwood Dale under the inspirational Barry Day, has sponsored schools in some of the most deprived parts of the country from here in Nottingham to the coast of Lincolnshire. Part of the DNA of chains like Greenwood Dale is that the strongest schools will support the weakest to improve.
School-to-school support - what’s in it for schools?
In a self-improving school-led system, there has to be an expectation that schools will be prepared to help each other - a network of school-to-school support in which the best schools work with schools in difficulties. But the question that heads, governing bodies and parents from the best schools might ask is why?
Why should we in a successful school, expend our time, resource and energy on someone else’s school?
It is a perfectly reasonable question and there is no doubt that any headteacher’s first responsibility is to the pupils in his or her school. But there are, I think, some compelling reasons for getting involved in school-to-school support that go beyond moral purpose and a sense of responsibility to a local community.
The first is the opportunity to develop staff. Teaching is a hard, and at times a draining job. There is no doubt that some of the best teachers become tired and jaded after a few years of teaching. I have often seen good teachers leaving the profession after 3 or 4 years for other careers.
Becoming involved in school-to-school support is a great way for teachers and heads to add some variety to their job - modelling teaching, coaching or delivering training. Teachers gain great satisfaction from helping colleagues in difficulties, and a track record of cross-school support will be enormously valuable for teachers looking to progress their careers.
Moreover, helping other schools means that the supporting school and its leaders must reflect on their own practice: What did we do when we had a similar problem? How did we solve it? What was the impact? And should we be doing things differently?
School-to-school support also means schools begin to build up professional networks between heads and between other teachers across subjects or primary phase.
And finally at some level, I think all schools can learn from each no matter how well they’re already doing. There is great benefit for teachers and heads in visiting a wide range of schools.
Let us look at another example of school-to-school support. Nick Weller, headteacher of Dixons Academy in Bradford decided that schools in the city could, and should, do better.
Bradford is an area of high deprivation (free school meals, child poverty, EAL ). Many people assumed that with such a stack of seemingly insurmountable challenges, things could never get better. But these arguments didn’t wash for Nick. It was time to move away from solutions imposed from local and central government and for schools to take control. He, and a group of equally determined heads, set up the Bradford Partnership with one simple starting objective: to make every secondary school in the city rated at least ‘good’ by Ofsted. Nick describes what has happened in Bradford as: “The academisation of school improvement.”
Because there had been such turbulence, every secondary school chose to join the Bradford Partnership.
The Bradford Partnership was fired up with a moral imperative to make things better and heads knew this couldn’t be done without honesty and challenge.
The next step was to get the data. Schools had to agree to share information with the partnership about their pupils’ attainment and progress. Every autumn term each school now has a one day visit from a serving Ofsted inspector.
As a result, and for the first time, there is solid, clear, unequivocal evidence of how each school is doing in comparison with other schools in the city and nationally. Every school then develops a plan for improvement with the partnership and progress is monitored and reviewed throughout the year.
So what has been the result of the school-led system in Bradford? 5 A* to Cs (including English and maths) increased by 4.9% compared to a 0.4% improvement nationally. Forty-six per cent of students now attend a ‘good’ or ‘outstanding’ school compared to 28% 2 years ago.
The transformation has begun in Bradford and Nick Weller acknowledges that there is a long way to go. But there is an absolute determination to make progress and I am in no doubt that they will succeed.
What do I mean when I talk about a school-led system?
For the last year I have talked about my vision for a self-improving school-led system in which teaching schools and other outstanding schools begin to take more and more responsibility in 4 particular areas:
And it is in initial teacher training that we have seen the biggest shift.
The appetite for schools to become involved in initial teacher training through School Direct has been quite staggering. In the first year we had bids for 1,000 places, last year it was over 9,000 and this year schools asked us for 17,700 places including an increase in primary bids from 3,400 to 6,900.
This posed us a challenge because we needed to honour the guarantee made to teacher training providers rated outstanding by Ofsted that they would continue to receive the same number of training places as they had in 2012. This meant that we could not give out all the places that schools had asked for, particularly in English, history and chemistry.
I know some schools were disappointed not to get their full allocations but overall we were able to give outstanding schools 90% of places they wanted. There is of course a budget for paying bursaries for teacher training and this means we will continue to limit the number of teachers that are trained every year.
We are currently working on our methodology for allocating places for next year and we aim to publish this sooner and to begin the bidding process much earlier - in the second half of the summer term. But I am delighted to say that there are now over 6,000 teachers being trained through School Direct across the country - a remarkable transformation in teacher training in just 2 years.
Michael Gove has repeatedly said that this country has the best teaching workforce it has ever had; and he is right. I am bowled over by the excitement, innovation and enthusiasm that I see in trainees and newly qualified teachers up and down the country.
There are of course some subjects such as maths and physics that continue to be difficult to recruit to. To fill our annual quota we need to attract one third of all graduates in these subjects, every year, into ITT . The government has increased bursaries to £20,000 for trainees with a 2:1 or better. In 2014 to 2015 we have increased the value of ITT scholarships to £25,000 for maths, physics, chemistry, and computing.
School Direct presents a fantastic opportunity to attract the best graduates into teaching. And groups of schools and academy chains are now offering real career development to compete with the best graduate employers.
“Come and work for us,” they are saying “and we will offer you great initial teacher training, support as a newly qualified teacher, continuous professional development including opportunities to undertake a masters or a PhD and if you’re the right person, training to become one of our school leaders in the future.”
I would encourage all School Direct schools to think about what more they can offer to tempt the best trainees to their schools.
After a year of School Direct some schools and academy chains are choosing to go further and become accredited providers of teacher training themselves and open their own school centred initial teacher training or SCITT .
Schools like Dove House Special School in Hampshire, Pimlico Academy in Westminster or the Ark and Harris academy chains are all in the process of opening SCITTs for September 2014.
I would also like to pay tribute to the universities who have supported the development of School Direct. Here at Nottingham Trent, Dr Gill Scott and her team have worked tirelessly with their local schools such as the Greenwood Dale, Redhill Academy, Minster School and Cotgrave Candleby Lane to create bespoke, cutting-edge programmes. Nottingham Trent has always seen strong relationships with schools as essential for successful teacher training and School Direct is making these even stronger.
And other universities are investing in closer school partnerships – the new Deanery at Oxford or the Institute of Education at Sheffield Hallam were conceived with the idea of strengthening and deepening the work they do with local schools. Whilst Birmingham is opening a university training school which will become a beacon of good practice in teacher training.
There is no doubt that the hardest - and most rewarding - part of developing a school-led system is successful, on-going school-to-school support and school-led school improvement.
There are a range of challenges for schools who wish to see school improvement being run and delivered by the best headteachers and their staff. And each area of the country is working differently. Some local authorities such as Torbay and Rotherham have shown great trust in their schools and are commissioning them to deliver school improvement. And in Surrey the local authority works in a 3-way partnership with Babcock Education and the best schools in the county.
In other areas LAs are reluctant to ask schools to take on this sort of work, they may be concerned about the capacity of schools, they may have central teams that they want to protect from competition or they may not yet have made, what is a big cultural shift, to an expectation and a belief that schools, if they are trusted, can take the lead in school improvement.
There is sometimes an ideological argument to be won where local authorities are not in favour of any school autonomy including academy freedoms.
I want now to talk about particular local challenges and what NCTL will do to support school-led solutions in these areas.
In some parts of the country there are simply not enough outstanding schools, teaching schools or national leaders of education to build up strong networks that can support each other. The government has announced the new Talented Leaders Programme to bring in excellent school leaders into underperforming areas of the country.
It is essential that we breathe life and innovation into these areas, particularly those where sometimes, there is a collective acceptance of the status quo even though standards are simply not high enough. Schools can begin to coast or fail because heads and governors have not realised how far behind they have got, both in expectations of their pupils, and in new, innovative, evidence based teaching methods that are developing in higher-performing areas.
The programme will provide a new route for schools in challenging circumstances to benefit from excellent proven leadership. It will also offer a new opportunity for exceptional school leaders to develop their skills and gain experience from the challenge of turning around an underperforming school.
Yesterday David Laws announced that the tender has gone out for this innovative new programme and we will soon be looking to recruit headteachers with strong moral purpose who are prepared to move to these areas of the country - and make a difference where help is needed most of all.
And at last we will begin to answer one of the hardest questions in education - how do we get the best heads into the most challenging schools?
The National College is also reviewing the work of national leaders of education - NLEs - to ensure that they have maximum impact. Many NLEs are making an enormous difference - taking over failing schools, becoming Ofsted inspectors and supporting schools in difficulties before things become too serious and expensive. But we must make sure that NLEs are deployed and used in a way that has the most effect and makes the best use of the time of these busy people. In the future I would like to see teaching schools taking the lead in brokering NLE support with schools and local authorities.
But it is not just in Bradford, Leicester or Torbay where the relationships are changing. Across the country local authorities realise that they simply don’t have the resource to run big central school improvement teams.
And they are having the courage to trust the best heads to take on the role of school improvement, and giving them the support and the money that they need. As a result, we are seeing just what can be achieved by high-quality, well-planned school-to-school support.
In Rotherham in South Yorkshire, Wickersley School, under David Hudson, leads a teaching school alliance that is rooted in the culture of partnership developed in the town over the past decade.
This change has helped to drive GCSE standards, in this former mining and steel town, to above national averages. This improvement has been based on systematic school-to-school support, targeted leadership development and innovative strategies, such as basing school improvement in outstanding subject departments not in LA central teams.
It is also one of the largest, best co-ordinated and most aspirational school-led organisations in the country - another example of what can be achieved when local authorities encourage and fund school-led, school improvement.
So what next?
When I took over as Chief Executive of the National College for Teaching and Leadership and I talked to people about the self-improving school-led system there was almost complete support for the idea. But what worried me was that we were in danger of progressing too slowly.
I don’t want the school-led system to sit just over the horizon, never seeming to get any closer however hard people strive. So I have set September 2016 as our target date for there to be an irrevocable shift from the centre to schools. My expectation is that by 2016 teaching schools and the best schools and academy chains will be leading:
And the delivery of a self-improving, school-led system will not be driven from town halls or from Whitehall, but by outstanding headteachers across the country.
These are exciting times to be working in education.
Challenging? Yes. Difficult? Yes. Daunting? Of course.
But I am confident that for the first time an accountable, effective, strong, school-led system is in our grasp.
I am in no doubt about the size of this challenge and the sheer hard work that will need to be done to get there, but I am also in no doubt about the determination and the ability of our headteachers to succeed.
Published: 17 January 2014


Background education
- Moringa School
- Nyakach Girls
- St Andrew Kaggwa
- Thorn Grove
Background job experience
- not yet worked
Why join programming?
- I believe its enjoyable to practice the knowledge once i know it.
- I have passion in it.
- I want to be able to make some funny websites that are also attractive
Interests
- researching in the websites
Hobbies
- riding bicycle
- watching soap operas
- listening to music
skills
- css
- Git commands
- environment conservation


House in Thermi!
Flat in Kalamaria!
Studio in Thessaloniki Center!
Flat in Euosmos!
House in Oraiokastro!


ErrBufferExceeded means that the buffering limit was exceeded.
var ErrBufferExceeded = errors.New("max buffer exceeded")
func EscapeString(s string) string
EscapeString escapes special characters like "<" to become "<". It escapes only five such characters: <, >, &, ' and ". UnescapeString(EscapeString(s)) == s always holds, but the converse isn't always true.
func Render(w io.Writer, n *Node) error
Render renders the parse tree n to the given writer.
Rendering is done on a 'best effort' basis: calling Parse on the output of Render will always result in something similar to the original tree, but it is not necessarily an exact clone unless the original tree was 'well-formed'. 'Well-formed' is not easily specified; the HTML5 specification is complicated.
Calling Parse on arbitrary input typically results in a 'well-formed' parse tree. However, it is possible for Parse to yield a 'badly-formed' parse tree. For example, in a 'well-formed' parse tree, no  element is a child of another  element: parsing "" results in two sibling elements. Similarly, in a 'well-formed' parse tree, no  element is a child of a
 element: parsing "

" results in a
 with two sibling children; the  is reparented to the
's parent. However, calling Parse on "
" does not return an error, but the result has an  element with an  child, and is therefore not 'well-formed'.
Programmatically constructed trees are typically also 'well-formed', but it is possible to construct a tree that looks innocuous but, when rendered and re-parsed, results in a different tree. A simple example is that a solitary text node would become a tree containing ,  and  elements. Another example is that the programmatic equivalent of "abc" becomes "abc".
func UnescapeString(s string) string
UnescapeString unescapes entities like "<" to become "<". It unescapes a larger range of entities than EscapeString escapes. For example, "á" unescapes to "á", as does "á" and "&xE1;". UnescapeString(EscapeString(s)) == s always holds, but the converse isn't always true.
An Attribute is an attribute namespace-key-value triple. Namespace is non-empty for foreign attributes like xlink, Key is alphabetic (and hence does not contain escapable characters like '&', '<' or '>'), and Val is unescaped (it looks like "a<b" rather than "a<b").
Namespace is only used by the parser, not the tokenizer.
type Attribute struct { Namespace, Key, Val string }
A Node consists of a NodeType and some Data (tag name for element nodes, content for text) and are part of a tree of Nodes. Element nodes may also have a Namespace and contain a slice of Attributes. Data is unescaped, so that it looks like "a<b" rather than "a<b". For element nodes, DataAtom is the atom for Data, or zero if Data is not a known tag name.
An empty Namespace implies a "http://www.w3.org/1999/xhtml" namespace. Similarly, "math" is short for "http://www.w3.org/1998/Math/MathML", and "svg" is short for "http://www.w3.org/2000/svg".
type Node struct { Parent, FirstChild, LastChild, PrevSibling, NextSibling *Node Type NodeType DataAtom atom.Atom Data string Namespace string Attr []Attribute }
func Parse(r io.Reader) (*Node, error)
Parse returns the parse tree for the HTML from the given Reader.
It implements the HTML5 parsing algorithm (https://html.spec.whatwg.org/multipage/syntax.html#tree-construction), which is very complicated. The resultant tree can contain implicitly created nodes that have no explicit <tag> listed in r's data, and nodes' parents can differ from the nesting implied by a naive processing of start and end <tag>s. Conversely, explicit <tag>s in r's data can be silently dropped, with no corresponding node in the resulting tree.
The input is assumed to be UTF-8 encoded.
▹ Example
func ParseFragment(r io.Reader, context *Node) ([]*Node, error)
ParseFragment parses a fragment of HTML and returns the nodes that were found. If the fragment is the InnerHTML for an existing element, pass that element in context.
It has the same intricacies as Parse.
func (n *Node) AppendChild(c *Node)
AppendChild adds a node c as a child of n.
It will panic if c already has a parent or siblings.
func (n *Node) InsertBefore(newChild, oldChild *Node)
InsertBefore inserts newChild as a child of n, immediately before oldChild in the sequence of n's children. oldChild may be nil, in which case newChild is appended to the end of n's children.
It will panic if newChild already has a parent or siblings.
func (n *Node) RemoveChild(c *Node)
RemoveChild removes a node c that is a child of n. Afterwards, c will have no parent and no siblings.
It will panic if c's parent is not n.
A NodeType is the type of a Node.
type NodeType uint32
const ( ErrorNode NodeType = iota TextNode DocumentNode ElementNode CommentNode DoctypeNode )
A Token consists of a TokenType and some Data (tag name for start and end tags, content for text, comments and doctypes). A tag Token may also contain a slice of Attributes. Data is unescaped for all Tokens (it looks like "a<b" rather than "a<b"). For tag Tokens, DataAtom is the atom for Data, or zero if Data is not a known tag name.
type Token struct { Type TokenType DataAtom atom.Atom Data string Attr []Attribute }
func (t Token) String() string
String returns a string representation of the Token.
A TokenType is the type of a Token.
type TokenType uint32
const ( // ErrorToken means that an error occurred during tokenization. ErrorToken TokenType = iota // TextToken means a text node. TextToken // A StartTagToken looks like . StartTagToken // An EndTagToken looks like . EndTagToken // A SelfClosingTagToken tag looks like
. SelfClosingTagToken // A CommentToken looks like . CommentToken // A DoctypeToken looks like <!DOCTYPE x> DoctypeToken )
func (t TokenType) String() string
String returns a string representation of the TokenType.
A Tokenizer returns a stream of HTML Tokens.
type Tokenizer struct {
// contains filtered or unexported fields
}
func NewTokenizer(r io.Reader) *Tokenizer
NewTokenizer returns a new HTML Tokenizer for the given Reader. The input is assumed to be UTF-8 encoded.
func NewTokenizerFragment(r io.Reader, contextTag string) *Tokenizer
NewTokenizerFragment returns a new HTML Tokenizer for the given Reader, for tokenizing an existing element's InnerHTML fragment. contextTag is that element's tag, such as "div" or "iframe".
For example, how the InnerHTML "a<b" is tokenized depends on whether it is for a
 tag or a


Top 5 Picks on Fiona Hill: Things to Know About Trump's Ex-Russia Aide That Penned Book on Putin
Dr Fiona Hill is set to appear before House Democrats looking into allegations of POTUS Trump's requests to Ukraine to dig up dirt on his 2020 rival, Democrat Joe Biden, in exchange for resumed aid.
- Present at Two Meetings?
- 'Operative in Kremlin'
- Reagan-Gorbachev Summit
- Expert on Russia
- Second Testimony: Anything New to Come?
Fiona Hill is the 11th witness to testify publically since the televised phase of the impeachment inquiry kicked off last week.
1. Present at Two Meetings?
Hill is a central figure in the Ukraine call controversy, having allegedly borne witness to two meetings pertaining to Trump’s exchange with Volodymyr Zelensky – one that POTUS dubbed absolutely benign and the transcript of which he vowed to read out loud.
2. ‘Operative in Kremlin'
Hill co-authored an insightful book on Russian President Vladimir Putin called "Mr. Putin, Operative in the Kremlin". The politician is portrayed as a multi-faceted person - “the Statist, the History Man, the Survivalist, the Outsider, the Free Marketeer, and the Case Officer", per a press release stating that “Russia experts Fiona Hill and Clifford Gaddy” base their narration on “a range of sources, including own personal encounters".
3. Reagan-Gorbachev Summit
Hill, who studied for degrees, including a PhD, at the University of St. Andrews in Scotland and Harvard University, had previously travelled to Russia. She happened to be there during the historic summit between President Ronald Reagan and Soviet General Secretary Mikhail Gorbachev in 1988.
4. Expert on Russia
Hill served on the National Intelligence Council (part of the Office of the Director of National Intelligence), which hands over foreign policy data on Russia and Europe to the White House.
5. Second Testimony: Anything New to Come?
In 2017, she joined Trump's National Security Council, serving as the senior director for Europe and Russia. Responding to a subpoena, she already testified behind closed doors in October, claiming she heard EU Ambassador Gordon Sondland outline a quid pro quo offer to the Ukrainians.
"Well, we have an agreement with the Chief of Staff for a meeting if these investigations in the energy sector start", Sondland told Zelensky's delegation, according to Hill, who argued that the “energy sector” was perhaps a euphemism for Burisma, which employed Biden’s son.
The Europe and Russia expert opted to step down in August 2019, and was replaced by Tim Morrison, who resigned on 31 October 2019.
Hill’s appearance in front of Congress comes as the public phase of the Trump impeachment inquiry has entered its second week, upon pressure from Republicans to make the proceedings transparent.
The inquiry surrounds Trump’s alleged abuse of power, with POTUS arguing he hasn’t committed anything impeachable and calling the inquiry a purely political move and a new round of “witch hunt garbage".
He insisted no quid pro quo arrangements with Kiev had been made, while the Democrats have been alleging he conditioned aid to Ukraine on a probe into the Biden family's potentially corrupt operations in the East European country.


Events
const settings = {
"async": true,
"crossDomain": true,
"url": "http://localhost:8080/events",
"method": "POST",
"data": {,
"id":<PHONE_NUMBER>,
"type": "PushEvent",
"actor": {
"id": 2790311,
"login": "daniel33",
"avatar_url": "https://avatars.com/2790311",
},
"repo": {
"id": 2790311,
"name": "johnbolton/exercitationem",
"avatar_url": "https://github.com/johnbolton/exercitationem",
}
}
"headers": {
"accept": "application/json"
}
}
$.ajax(settings).done(function (response) {
console.log(response);
});
To signup, you need to make a POST
call to the
following url :
http://localhost:8080/events
Result example :
{
status: true,
message: "event added successfully"
}


--- layout: page home: '/' --- Thanks for your message! I’ll be in touch soon.
I’ll be in touch soon.


14.21 The posixfile Module
(Obsolete, Unix only) The posixfile module provides a file-like object with
support for file locking, as Example 14-27 shows. New programs should use the
fcntl module instead.
Example 14-27. Using the posixfile Module
File: posixfile-example-1.py
import posixfile
import string
filename = "counter.txt"
try:
# open for update
file = posixfile.open(filename, "r+")
counter = int(file.read(6)) + 1
except IOError:
# create it
file = posixfile.open(filename, "w")
counter = 0
file.lock("w|", 6)
file.seek(0) # rewind
file.write("%06d" % counter)
file.close() # releases lock
|


https://github.com/jaceklaskowski
http://bit.ly/mastering-apache-spark
~
and compile
object ... extends App
args
collection to access argumentsio.Source.fromFile
and getLines
String.split
Seq.foreach
and println
sbt run
(0 to 9).foldLeft...
Map
.
(0 to 9).foldLeft...
Map("evens" -> Seq(0,2,4,6,8), "odds" -> Seq(1,3,5,7,9))
- Visit Jacek Laskowski's blog
- Follow @jaceklaskowski at twitter
- Use Jacek's projects at GitHub
- Read Mastering Apache Spark notes.


2
The Value of Wisdom
1 My son, if you receive my words and treasure up my commandments with you,
2 making your ear attentive to wisdom
and inclining your heart to understanding;
3 yes, if you call out for insight
and raise your voice for understanding,
4 if you seek it like silver
and search for it as for hidden treasures,
5 then you will understand the fear of the LORD
and find the knowledge of God.
6 For the LORD gives wisdom;
from his mouth come knowledge and understanding;
7 he stores up sound wisdom for the upright;
he is a shield to those who walk in integrity,
8 guarding the paths of justice
and watching over the way of his saints.
9 Then you will understand righteousness and justice
and equity, every good path;
10 for wisdom will come into your heart,
and knowledge will be pleasant to your soul;
11 discretion will watch over you,
understanding will guard you,
12 delivering you from the way of evil,
from men of perverted speech,
13 who forsake the paths of uprightness
to walk in the ways of darkness,
14 who rejoice in doing evil
and delight in the perverseness of evil,
15 men whose paths are crooked,
and who are devious in their ways.
16 So you will be delivered from the forbidden woman,
from the adulteress with her smooth words,
17 who forsakes the companion of her youth
and forgets the covenant of her God;
18 for her house sinks down to death,
and her paths to the departed;
19 none who go to her come back,
nor do they regain the paths of life.
20 So you will walk in the way of the good
and keep to the paths of the righteous.
21 For the upright will inhabit the land,
and those with integrity will remain in it,
22 but the wicked will be cut off from the land,
and the treacherous will be rooted out of it.


WITNESS LIST Government Organization Committee May 19, 2003 - 8:00A SB 1952 FOR: Mikels, John K. Geologist (Self), Austin, TX ON: Alexander, Cindy Executive Policy Analyst (Lt. Governor's Office), Austin, TX Frederick, David Atty (Self), Austin, TX Registering, but not testifying: For: Hanna, Mark J. Attorney (Texas Society of Professional Surveyors), Austin, TX Speight, Calvin B. Plumber (Texas Pipe Trades), Houston, TX On: Burnett, Dale Executive Director (Texas Structural Pest Control Board) Ford, Ruthie E-Texas Manager (Comptroller), Austin, TX Garrant, Tony (State Auditor's Office) Hess, Myron Attorney (National Wildlife Federation), Austin, TX Irvine, Timothy Attorney (Texas Departmetn of Housing and Community Affairs, Division of Manufactured Housing), Austin, TX Kuntz, Jr., William H. Executive Director (Texas Department of Licensing and Regulation), Austin, TX Lee, Randy Senior Vice President (Stewart title Guaranty Co.) Mathison, Bob Systems Analyst (Comptroller), Austin, TX Parker, Glenn CFO (Board of Barber Examiners), Austin, TX Quinn, Floyd HR Consultant (SAO) Shotwell, JD Geologist (AIPG- TX), Austin, TX Smith, Sandy Executive Director (Texas Board of Professional Land Surveying), Austin, TX Williams, Cathy Asst. Ex. Dir. (TxDot), Austin, TX Wong, Jr., Raul License Surveyor, Board Member (Texas Board of Professional Land Surveying), Dallas, TX


Spec
SwiftFinderFinder for SWIFT search, must be used together with SwiftPattern.
Finder for SWIFT search, must be used together with SwiftPattern.
| Extends | Finder |
|---|---|
| All Extended | Finder |
| All Subcl's | SwiftLocalFinder, SwiftSemiGlobalFinder |
| Defined in | <seqan/index.h> |
| Signature |
template <typename THaystack, typename TSpec>
class Finder<THaystack, Swift<TSpec> >;
|
Template Parameters
TSpec |
Specifies the type of Swift filter. |
|---|---|
THaystack |
A haystack type. Types: Index, String, StringSet. |
Interface Function Overview
-
THitString getWindowFindHits(finder);
Returns the string of hits from the finder. -
TPair positionRange(finder);
Returns a pair of the begin and end position in the haystack or needle for the last hit found. -
TPair positionRangeNoClip(finder);
Returns a pair of the begin and end position in or beyond the haystack or needle for the last hit found. -
bool windowFindBegin(finder, pattern, errorRate);
Initializes the pattern. Sets the finder on the begin position. Gets the first non-repeat range and sets it in the finder. Used together with windowFindEnd. -
void windowFindEnd(finder, pattern);
Flushes the finder. Used together with windowFindBegin and windowFindNext. -
bool windowFindNext(finder, pattern, finderWindowLength)
Searches over the next window with the finder. The found hits can be retrieved with getWindowFindHits. Used together with windowFindBegin and windowFindEnd.
Interface Functions Inherited From Finder
Member Typedef Overview
-
typedef (...) SwiftFinder::THitString;
The type to use for the hit string returned in getWindowFindHits.
Detailed Description
See SwiftPattern for an overview of the SWIFT algorithm.
See Also
Interface Functions Detail
THitString getWindowFindHits(finder);
Returns the string of hits from the finder.
Parameters
finder
|
A finder with window interface. |
|---|
Returns
THitString |
String of hits, see THitString. |
|---|
Data Races
Thread safety unknown!
See Also
TPair positionRange(finder);
Returns a pair of the begin and end position in the haystack or needle for the last hit found.
Parameters
finder
|
A Finder object. |
|---|
Returns
TPair |
A Pair of the begin and end position in the haystack or needle for the last hit found. The return type is Pair<typename SAValue<THost&g;::Type> if THost is the type of haystack or needle. |
|---|
Data Races
Thread safety unknown!
See Also
TPair positionRangeNoClip(finder);
Returns a pair of the begin and end position in or beyond the haystack or needle for the last hit found.
Parameters
finder
|
A SwiftFinder object to query. |
|---|
Returns
TPair |
A pair of the begin and end position in the haystack or needle for the last hit found. These positions could be negative or beyond the end of finder or pattern when using filter algorithms. The return type is Pair<typename SAValue<THost>::Type> if THost is the type of haystack or needle. |
|---|
Data Races
Thread safety unknown!
See Also
bool windowFindBegin(finder, pattern, errorRate);
Initializes the pattern. Sets the finder on the begin position. Gets the first non-repeat range and sets it
in the finder. Used together with windowFindEnd.
Parameters
finder
|
A finder with window interface. |
|---|---|
pattern
|
A pattern with window interface. Types: SwiftPattern. |
errorRate
|
Error rate that is allowed between reads and reference. Should be the same in as in windowFindNext. Types: double |
Returns
bool |
true if there were bases to be scanned and false otherwise. |
|---|
Data Races
Thread safety unknown!
See Also
void windowFindEnd(finder, pattern);
Flushes the finder. Used together with windowFindBegin and windowFindNext.
Parameters
finder
|
A finder with window interface. |
|---|---|
pattern
|
A pattern with window interface. Types: SwiftPattern |
Data Races
Thread safety unknown!
See Also
bool windowFindNext(finder, pattern, finderWindowLength)
Searches over the next window with the finder. The found hits can be retrieved with getWindowFindHits. Used together with windowFindBegin and
windowFindEnd.
Parameters
finder
|
A SwiftFinder. |
|---|---|
pattern
|
A SwiftPattern. |
finderWindowLength
|
Number of bases that are scanned beginning from the position the finder is at. Including bases that are marked as repeats and that are skipped. Types: nolink:unsigned int |
Returns
bool |
true, if there are bases that can be scanned, false otherwise. |
|---|
Data Races
Thread safety unknown!
See Also
Member Typedef Detail
typedef (...) SwiftFinder::THitString;
The type to use for the hit string returned in getWindowFindHits.


val dateOfDeath: LocalDate?
date when the person died. If the person is currently alive, this should be null.
dateOfDeath - date when the person died. If the person is currently alive, this should be null.
dateOfDeath


Patrick Walther 🇨🇭
- Started programming back in 2005
- PHP/JS and later jQuery for IE 6...
- JavaScript enthusiast!
Zühlke
- Founded in Switzerland in 1968
- Software Engineering Consultancy
- Agile Business Transformation
- Operating in 8 countries
Global Map
Zuhkle Asia
Singapore 🇸🇬
- Started 2 years ago
- Currently 36 employees
- We want to grow to 100 until end of 2020!
Zuhkle Asia
Hong Kong 🇭🇰
- Started 1.5 years ago
- Currently around 20 employees
Come talk to us!
Our Goals
- Basic understanding of Webassembly and its current limits
- Understand how the communication between JS/wasm works
- Trying out fun stuff in wasm!
Schedule
- 60' Intro & Webassembly basics
- 15' Break
- 60' Webassembly In-Depth
- 15' Break
- 60' Experimenting with OpenCV
Course structure
- Theoretical input
- Exercises
- Questions at any time
- Discussions & Feedback
made with reveal.js


|
| file | msgCommon.h [code] |
| | OpenM++: message passing library common classes and interfaces.
|
| |
| file | msgEmpty.h [code] |
| | OpenM++: empty implementation of message passing library.
|
| |
| file | msgExecBase.cpp |
| | OpenM++: message passing library base class.
|
| |
| file | msgExecBase.h [code] |
| | OpenM++: message passing library base class.
|
| |
| file | msgMpi.h [code] |
| | OpenM++: message passing library common classes and interfaces.
|
| |
| file | msgMpiExec.cpp |
| | OpenM++: message passing library main class for MPI-based implementation.
|
| |
| file | msgMpiExec.h [code] |
| | OpenM++: message passing library main class for MPI-based implementation.
|
| |
| file | msgMpiPacked.cpp |
| | OpenM++ message passing library: pack and unpack wrapper class for MPI-based implementation.
|
| |
| file | msgMpiPacked.h [code] |
| | OpenM++ message passing library: pack and unpack wrapper class for MPI-based implementation.
|
| |
| file | msgMpiRecv.cpp |
| | OpenM++ message passing library: receiver classes for MPI-based implementation.
|
| |
| file | msgMpiRecv.h [code] |
| | OpenM++ message passing library: receiver class for MPI-based implementation.
|
| |
| file | msgMpiSend.cpp |
| | OpenM++ message passing library: sender classes for MPI-based implementation.
|
| |
| file | msgMpiSend.h [code] |
| | OpenM++ message passing library: sender class for MPI-based implementation.
|
| |


@*
* Copyright 2019 HM Revenue & Customs
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*@
@(signUpForm: Form[_root_.forms.SignUpForm.Data], notification: Option[(helpers.NotificationType, String)] = None)(
implicit request: Request[_], flash: Flash, user: Option[CachedData], feedbackUrl: String, fasttrackConfig: FasttrackConfig, messages: Messages)
@import helpers.CSRFieldConstructor._
@import views.html.widgets.{ checkbox, select_guard }
@main_template(title = "Create your account", pageForms = Seq(signUpForm), notification = notification) {
@helper.inputPassword(signUpForm("password"),
'class -> "form-control new-password",
'_label -> "Create password",
'_help -> "Requires upper and lowercase letters, a number and at least 9 characters")
@helper.inputPassword(signUpForm("confirmpwd"),
'_label -> "Confirm password",
'class -> "form-control",
'_showConstraints -> false)
Eligibility
Confirm the following statements are true
I'll be 16 or older by 31 August 2018
I have at least 5 GCSEs at grade C and above, or the new grade 4 and above, including English Language and Maths, or equivalent (or I expect to have these by 31 August 2018)
I've been resident in the UK for at least 2 of the 10 years immediately before my application (and this includes at least 1 continuous 12-month period)
If I'm currently a civil servant, or have previously worked for the Civil Service, I'm aware of the conditions that apply
@checkbox(signUpForm("agreeEligibleToApply")) {
I confirm that I am eligible to apply
}
How did you hear about us?
@select_guard(signUpForm("campaignReferrer"), models.CampaignReferrers.list,
"hearAboutUsDetail", "-- Select one --") {
Select how you heard about us (optional)
}
@helper.inputText(signUpForm("campaignOther"),
'_label -> "Provide more information (optional)",
'class -> "form-control",
'_showConstraints -> false)


We investigate the use of a natural phenomenon, i.e., reflection, as the backdoor pattern, and propose the reflection backdoor (Refool) attack to install stealthy and effective backdoor into DNN models.
Our reflection backdoors (rightmost column) are crafted based on the natural reflection phenomenon, thus need not to mislabel the poisoned samples on purpose (A - D, mislabels are in red texts), nor rely on obvious patterns (A - C, E), unpleasant blending (D), or suspicious stripes (F). Therefore, our reflection backdoor attacks are stealthier.
Reflections often influence the performance of computer vision models as illustrated in Fig. 2. Here, we exploit reflections as backdoor patterns and show that a natural phenomenon like reflection can be manipulated by an adversary to perform backdoor attack on DNN models. Table 1 compares the different settings adopted by 4 state-of-the-art backdoor attacks and our proposed reflection backdoor.
Real-world reflections (from ImageNet-a) influence the performance of a DNN classifier. Labels in green and red colors are ground-truth and predicted labels respectively.
Refool main contains the refool pipeline and real reflection image generation:
The training (top) and inference (bottom) procedures of our reflection backdoor attack.
The physical (left) and mathematical (right) models for three types of reflections.
Attack success rates (%) of baselines and our proposed Refool backdoor, and the victim model's test accuracy (%) on the clean test set.
Understandings of Refool with Grad-CAM [43] with two samples from PubFig(left) and GTSRB(right).
@inproceedings{Liu2020Refool, title={Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks}, author={Yunfei Liu, Xingjun Ma, James Bailey, and Feng Lu}, booktitle={ECCV}, year={2020} }
Acknowledgments: This work was supported by the National Natural Science Foundation of China (NSFC) under Grant 61972012.


| PERLTRAP(1) | Perl Programmers Reference Guide | PERLTRAP(1) |
use English;
allows you to refer to special variables (like $/) with names (like $RS), as though they were in awk; see perlvar for details.
Awk Perl ARGC scalar @ARGV (compare with $#ARGV) ARGV[0] $0 FILENAME $ARGV FNR $. - something FS (whatever you like) NF $#Fld, or some such NR $. OFMT $# OFS $, ORS $\ RLENGTH length($&) RS $/ RSTART length($`) SUBSEP $;
for my $variable (keys %hash) { ... }
Furthermore, don't forget the "keys" in there, as "foreach my $kv (%hash) {}" iterates over the keys and values, and is generally not useful ($kv would be a key, then a value, and so on).
condition ? do_something() : variable = 3
and the variable is only assigned if the condition is false. In Perl, you need parentheses:
$condition ? do_something() : ($variable = 3);
Or just use "if".
Note also that the variable is not visible until the following statement. This means that in "my $x = 1 + $x" the second $x refers to one declared previously.
for ($object) { $_->method; }
while (<FH>) { } while (defined($_ = <FH>)) { }.. <FH>; # data discarded!
$x = /foo/; $x =~ /foo/;
As always, if any of these are ever officially declared as bugs, they'll be fixed and removed.
| 2019-10-21 | perl v5.30.3 |


{% extends 'bootstrap/base.html'%} {% block styles%} {{ super() }} {% endblock %} {% block navbar %} {% include 'navbar.html' %} {% endblock %} {% block content %}
In life, you only have 60 seconds to impress someone. 1 minute can make or break you. How do we make sure that you use your 1 minute to actually say something meaningful?
MynerPitches allows users to use that one minute wisely. The users will submit their one minute pitches and other users will vote on them and leave comments to give their feedback on them.
The pitches are organized by category. We have only added a few categories because the application is still in development. Feel free to reach our developers to suggest more categories, perfomance suggestions and reccomendations of how we can develop the application.
.


{% comment %} You can override this template to include extra, custom items in the timepiece navigation bar. We use Bootstrap styling so you can use both plain navigation items and dropdown navigation items. If you add many items, you may want to adjust the width at which the navbar collapses by setting the variable @navbarCollapseWidth in your less file. For example:


Honzi
/
Guides
/
EVE Online
/Keys
Keys
Consumed?
Used For
Angel Diamond Tag
No
Angel Extravaganza (level 4)
Angel Palladium Tag
No
Angel Extravaganza (level 3)
R.S. Officer's Passcard
No
Illegal Activity (3 of 3)


Please wait while we setup your device. Note that if WiFi is being setup, the device will disconnect
momentarily. When that happens, please reconnect by joining this machine to the 'params_new_wifi'
network and wait while we try to reach your device at
http://params_hostname.


Logic groups are a collection of paths which dictate what skills you need in order to access new items. You can view them as a difficulty setting. Glitched is a bit particular because it enables paths which use glitches from the logic group you chose.
Below is a list of all the logic groups. Click on one of the links below to learn what is required from the player in order to play in each logic group.


Testing¶
Contents
You may execute the provided (public) test cases to check your code from the root directory of the repository using the command:
$ python3 -m unittest discover -s tests/public -t .
You may add the option -v to the command above to have more information displayed while testing.
Note, the course instructors will have a very similar set of private test cases that are used to grade submissions. Please ensure that all functionalities are implemented as required by the API and use these test cases only as a sanity-check.


interface Future<T>
A Future defers the resolution of a value to the future. The value can be consumed by calling Future.await method which is expected to block the current thread. Therefore, never call Future.await on the same thread as it will result in a dead lock.
abstract var isCompleted: Boolean
Returns |
abstract fun await(): T
Consume the future value in |
expect fun <T> T.toImmutable(): T
Returns an immutable instance of an object. |
class JobFuture<T, V> : Future<V>
Wraps a job closure in a future. The job is not invoked until await is called. The jobInput is passed as the only argument to job. |
|
expect class NativeFuture<T> : Future<T>
A NativeFuture returns an instance of platform specific Future wrapped in a common API. Calling NativeFuture.await will wait until the result is available. |
|
class ValueFuture<T> : Future<T>
A naive future implementation to wrap a given |


Police report lodged over false post slandering Penang CM
GEORGE TOWN, Nov 21 ― A police report has been lodged against a Facebook account holder over a false posting linked to Penang Chief Minister Chow Kon Yeow containing defamatory elements.
The report was made at the Northeast district police headquarters by Chow’s political secretary Teh Lai Heng, who called for an immediate investigation by the police and the Malaysian Communications and Multimedia Commission (MCMC) against an individual who was spreading false information on social media yesterday.
He said a statement posted on a Facebook account called “EUNOS KHAI” contained a picture of Chow with a slanderous statement against the DAP.
Teh, who is also the Komtar assemblyman, hoped that the police and the MCMC would take immediate action against any party responsible for the spread of this false statement. ― Bernama


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Adarsh Singh
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About Me
Hello, My name is ahmad, I am 24 years old,I am jordinian and I live in Irbid city, I graduated from Yarmouk University wit major in Electronics Engineering and now try to be a web developer, and in my free time play bvideo game like FIFA
Hello, My name is ahmad, I am 24 years old,I am jordinian and I live in Irbid city, I graduated from Yarmouk University wit major in Electronics Engineering and now try to be a web developer, and in my free time play bvideo game like FIFA
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{% extends "templates/base.html" %} {% block content %} {% set chapters = [ { 'city': 'Mumbai, India', 'meetup-link': 'https://www.meetup.com/ERPNext-Community-Meetup/', 'image': '/assets/foundation/img/meetups/mumbai.png', 'members': 720 }, { 'city': 'Bengaluru, India', 'meetup-link': 'https://www.meetup.com/ERPNext-Bangalore-Community/', 'image': '/assets/foundation/img/meetups/bengaluru.png', 'members': 590 }, { 'city': 'Bay Area, United States', 'meetup-link': 'https://www.meetup.com/ERPNext-Community-Bay-Area/', 'image': '/assets/foundation/img/meetups/bay-area.png', 'members': 15 }, { 'city': 'Pune, India', 'meetup-link': 'https://www.meetup.com/Pune-ERPNext-Meetup/', 'image': '/assets/foundation/img/meetups/pune.png', 'members': 540 }, { 'city': 'New England, United States', 'meetup-link': 'https://www.meetup.com/ERPNext-New-England/', 'image': '/assets/foundation/img/meetups/new-england.png', 'members': 10 }, { 'city': 'Dubai, UAE', 'meetup-link': 'https://www.meetup.com/UAE-ERPNext-Meetup/', 'image': '/assets/foundation/img/meetups/dubai.png', 'members': 53 }, { 'city': 'Frankfurt, Germany', 'meetup-link': 'https://www.meetup.com/ERPNext-Europe/', 'image': '/assets/foundation/img/meetups/frankfurt.png', 'members': 24 }, { 'city': 'Jakarta, Indonesia', 'meetup-link': 'https://www.meetup.com/ERPNext-Jakarta-Community-Meetup/', 'image': '/assets/foundation/img/meetups/jakarta.png', 'members': 55 }, { 'city': 'Paris, France', 'meetup-link': 'https://www.meetup.com/ERPNext-France/', 'image': '/assets/foundation/img/meetups/paris.png', 'members': 20 }, ] %} Chapters Become a part of your local ERPNext Community by joining a chapter near you. If you can't find one, start your own! {% for item in chapters %} {{ item.city }} {{ item.members }} members {% if loop.index is divisibleby 3 %} {% endif %} {% endfor %} To start your own chapter, start a group on Meetup.com and get in touch with us. Contact Us To Start a New Chapter {% endblock %}
Become a part of your local ERPNext Community by joining a chapter near you. If you can't find one, start your own!


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Hi! I'm Michael Hansen and I'm a senior software engineer at Google, on the ChromeOS cross-device team. I have 13-ish years of experience as a developer. Prior to Google I worked as a web backend developer, and before that I built iOS apps. I've also earned a masters degree in machine learning. Please see my résumé for more and feel free to reach out if you'd like to connect!