Fans trouble young Tamil actress, asking phone number! - Tamil News - IndiaGlitz.com
Though she had acted in many advertisements, Model and actress Raiza Wilson had become a popular name among Tamil audience after she participated as a contestant in the first season of the reality game show Bigg Boss hosted by Kamal Haasan.
She had acted in a small role in Dhanush's Velaiyilla Pattadhari 2, and as the show got her a lot of fans, she was cast as the female lead in the romantic movie Pyaar Prema Kadhal, where she was paired with her fellow contestant Harish Kalyan and the movie turned a success.
Recently, the actress shared her photo on Twitter, captioning it "Call me on my landline", and this has lead to numerous netizens asking Raiza her number and the photo has turned viral. Raiza is next acting in Alice produced by Yuvan Shankar Raja and Kadhalika Yarumillai starring GV Prakash.
Trending News
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Dhanush gets two huge releases on same day!
Tamannaah's opens on Rajni- Kamal political entry!
Siva Karthikeyan's next reaches crucial phase!
28 year old actress found dead
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Headlines
Picture: Woman gives birth to baby with two faces and three hands
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Unhappy over not having male child, woman kills daughters; commits suicide
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Breaking: Devendra Fadnavis becomes Maharashtra CM again!


JavaScript
In an effort to have Elements be as lightweight as possible, it does not ship with jQuery. Instead, we have chosen to use a jQuery alternative called Cash. If Cash is not robust enough for a site built on Elements, it can be replaced with jQuery with no loss of functionality in the core. The majority of JavaScript used in Elements is "vanilla" in nature. We have found this to perform well and work cross-browser.
While you can create and call JavaScript function using the familiar $('#some_ID')
or $('.some_CLASS')
way, the preferred way in Elements is to
use a data attribute called hook, $.hook('some_data_hook')
.
Using data-hook
allows for having multiple possible elements,
like when using a class
.
Use it in your JavaScript
Although the core of Elements may not be updated often, it is recommended that all theme based
functionality be added to the THEME_NAME/ui/js/theme.js
file
within the proper page function call.


plants stress helicase expression miRNAs rice salinity gene OsDBH OsDSHCT Plant response targets osa-MIR RNA NaCl Tuteja using OsABP miRNA osa-MIRe predicted .-fold salt plant {border-style DEAD-box helicases target DNA OsABP, compared genes levels performed px;} #ffffff;} conditions plants, treatment PDH analysis miR osa-MIR, protein PCR control proline Biol mRNA observed plants. shown used ectopically tolerance content decrease expressing free present showed transcript transgenic validated LOC_Osg accumulation chlorophyll different domain order up-regulated wild Bartel cDNA induced involved profiles qRT-PCR study type vector ATP-dependent changes demonstrated level microRNAs proteins results sequences step (Figure ./s--- Arabidopsis Cell Forward Mol activity data early file including increase px; samples solution {font-family BMC Figure WT, abiotic amplification cleavage control. down-regulated font-size important similarity targeted tested validation Behav DEAD Kit Res Rice Table according acid carried case change conditions. conserved differences double; genes, greenhouse high identified mg/g miR, n.d primer primers recent reduction regulation required revealed role small specific stress, stress. treatments used, work (.-fold .-fold, ./psb... Analysis Expression Helicase) However, Reverse Salinity Yes adaptation border-color border-width complementarity control) decreased drought encoding experimentally expressed family function gene, genes. grown helicases, higher information initial leaf means microRNA pea previously reported resulted roles sativa significantly silico solid; study, test total treated treatments. water {font-style {font-weight (.- (.-fold) (Additional (EV) (Invitrogen) (LOC_Osg) (TR), ./--- AGO Acid Helicase Macovei Medicago Nested Nucl Oryza RACE RNAs Sci Zhang available bold cell characterization courier; deficit described domain, early-induced em; environmental evident experimental helicases: highest instructions. measured miRNAs, min, modified molecular non-treated play presented promotes proteins. proven provided pt;} rRNA relation relative respectively. responsive reverse search similar synthesis thaliana transcription transcripts treatment, used. validated. weeks yield


Good-day to you and compliment of the day, This letter may come to you as a surprise due to the fact that we have not yet met before. I managed to get your contact details through the senegalese chambers of commerce myself and humbly solicit for your co-operation seeing that time is of importance and I am desperately looking for an honest and reliable person to assist me in this confidential transaction. My movement and that of other my sister has been highly restricted; but luckily I was able to move out from Luanda Angola capital territory and am now in Dakar Senegal. I am Eloy Sakiata Savimbi, son of the late General Jonas Savimbi; leader of Unita Rebel of Angola who died on the 22nd February 2002. Before the death of my father, he deposited the sum of US$15,000,000.00(fifteen million United States Dollars) in a private security trust company for safe keeping only. All the related documents are intact with me and I have currently contacted the company. My younger sister and I are in Dakar Senegal as asylum seekers pending when I get a Foreign partner; because of the monetary laws here which do not allow asylum seekers to operate any bank account. MUTUAL TRUST AND CONFIDENTIALITY Based on the above, I am contacting you so that you Will help me in retrieval and transfer of this fund to your account or any other designated by you for the mutual benefit of both of us and hoping that you will remain trust worthy. The fund was realised from gold and diamond sales when my late father was leading some region in our Country. If you are ready I will give you all the information needed. PLEASE YOUR CONFIDENTIALITY IN THIS TRANSACTION IS HIGHLY REQUIRED. Yours sincerely, Eloy Savimbi Nb= You can contact me on alternate<EMAIL_ADDRESS><mailto:eloy_savimdev@juno.com>)


Welcome to the College of Health Sciences and Nursing. The Division of Nursing is dedicated to providing educational opportunities that embody the value of caring, excellence in practice, and leadership. We prepare graduates to serve as nursing leaders in clinical and teaching venues.
Our graduates know how to collaborate with colleagues, demonstrate professional values, and use reflection to improve teaching and clinical practice. This site has been designed as a resource for students as well as campus personnel seeking information about the various undergraduate and graduate nursing degrees offered by the college. Check the site often for material updates and new links with additional information.


1. Integrated deployment
1.1 Scale up registry-integration
Assume that three registry-integration servers have been deployed currently, which are namely node1, node2, and node 3. The new node to be added to the cluster is node 4.
Operation steps:
Step 1. Deploy the new registry-integration node
First, deploy registry-integration.tgz
on node4 by referencing the Deployment topic. Note that you need to set the nodes.metaNode configuration item on node4 to a 4-server endpoint list:
nodes.metaNode=DefaultDataCenter:<node1>,<node2>,<node3>,<node4>
In this step, after node4 is started, visit curl http://<node4>:9615/health/check
. The status will be unhealthy, because node4 has not been added to the cluster yet. To add it to the cluster, perform the next step.
Step 2. Call the changePeer operation to add a new node to a cluster
Run the changePeer command on one of the existing servers (node1, node2, and node3), to modify the current cluster from a three-node cluster (node1, node2, and node3) to a four-node cluster (node1, node2, node3, and node4):
curl -X POST "http://<node1>:9615/manage/changePeer" -d "ipAddressList=<node1>,<node2>,<node3>,<node4>"
After completing this step, visit curl http://<node4>:9615/health/check
. The status will be healthy.
1.2 Scale down registry-integration
Assume that you have three servers in one cluster, which are respectively node1, node2, and node3, and you want to scale down node3.
1.2.1 Smooth scale-down
Operation steps:
Step 1. Call the changePeer operation to remove a node
Run the changePeer command on either node1 or node2 to change the cluster list from “node1, node2, node3” to “node1,node2”. This removes node3 from the endpoint list of the cluster:
curl -X POST "http://<node1>:9615/manage/changePeer" -d "ipAddressList=<node1>,<node2>"
After completing this step, visit curl http://<node3>:9615/health/check
. The status will be unhealthy, because node3 has already been removed from the cluster.
Step 2. Close node3
This step is optional, because node3 has already been removed from the cluster, and it does not affect the cluster even if it is still running.
1.2.2 Handling of node failure
If node3 is no longer functional, you need to remove it from the cluster.
Operation steps:
Step 1. Call the changePeer operation to remove a node
Run the changePeer command on either node1 or node2 to change the cluster list from “node1, node2, node3” to “node1,node2”. This removes node3 from the endpoint list of the cluster:
curl -X POST "http://<node1>:9615/manage/changePeer" -d "ipAddressList=<node1>,<node2>"
2. Independent deployment
2.1 Scale up registry-meta
Assume that you have already deployed three registry-meta servers, which are respectively metaNode1, metaNode2, and metaNode3. The new node to be added to the cluster is node 4.
Operation steps:
Step 1. Deploy the new registry-meta node
First, deploy registry-meta.tgz
on metaNode4 by referencing the Deployment topic. Note that you need to set the nodes.metaNode configuration item on metaNode4 to a 4-server endpoint list:
nodes.metaNode=DefaultDataCenter:<metaNode1>,<metaNode2>,<metaNode3>,<metaNode4>
In this step, after metaNode4 is started, visit curl http://localhost:9615/health/check
. The status will be unhealthy, because metaNode4 has not been added to the cluster yet. To add it to the cluster, perform the next step.
Step 2. Call the changePeer operation to add a new node to a cluster
Run the changePeer command on metaNode1, metaNode2, or metaNode3, to change a legacy cluster (metaNode1,metaNode2,metaNode3) to a new cluster (metaNode1,metaNode2,metaNode3,metaNode4):
curl -X POST "http://<metaNode1>:9615/manage/changePeer" -d "ipAddressList=<metaNode1>,<metaNode2>,<metaNode3>,<metaNode4>"
After completing this step, visit curl http://localhost:9615/health/check
. The status will be healthy.
2.2 Scale down registry-meta
Assume that you have three servers in one cluster, which are respectively metaNode1, metaNode2, and metaNode3. Now you need to scale down metaNode3.
2.2.1 Smooth scale-down
Operation steps:
Step 1. Call the changePeer operation to remove a node
Run the changePeer command on either metaNode1 or metaNode2, to change the cluster list from “metaNode1, metaNode2, metaNode3” to “metaNode1,metaNode2”. This removes metaNode3 from the endpoint list of the cluster:
curl -X POST "http://<metaNode1>:9615/manage/changePeer" -d "ipAddressList=<metaNode1>,<metaNode2>"
After completing this step, visit curl http://<metaNode3>:9615/health/check
. The status will be unhealthy, because metaNode3 has already been removed from the cluster.
Step 2. Close metaNode3
This step is optional, because metaNode3 has already been removed from the cluster, and it does not affect the cluster even if it is still running.
2.2.2 Handling of node failure
If metaNode3 is no longer functional, you need to remove it from the cluster.
Operation steps:
Step 1. Call the changePeer operation to remove a node.
Run the changePeer command on either metaNode1 or metaNode2, to change the cluster list from “metaNode1, metaNode2, metaNode3” to “metaNode1,metaNode2”. This removes metaNode3 from the endpoint list of the cluster:
curl -X POST "http://<metaNode1>:9615/manage/changePeer" -d "ipAddressList=<metaNode1>,<metaNode2>"
2.3 Scale up registry-data
Scaling up registry-data is simple. You can simply add a node to the cluster by configuring the metaNode list, without having to call the changePeer operation.
Operation steps:
Step 1. Deploy the new registry-data node
First, deploy registry-data.tgz
on the newDataNode by referencing the Deployment topic. You can simply set the nodes.metaNode configuration item on the newDataNode to the same metaNode server list as that of other registry-data nodes.
nodes.metaNode=DefaultDataCenter:<metaNode1>,<metaNode2>,<metaNode3>
2.4 Scale down registry-meta
Scaling down registry-data is simple. You can simply close the data node, which will then be automatically removed from the cluster (due to a heartbeat timeout). You do not have to call the changePeer operation.
2.5 Scale up registry-session
Scaling up registry-session is simple. You can simply add a node to the cluster by configuring the metaNode list, without having to call the changePeer operation.
Operation steps:
Step 1. Deploy the new registry-session node
First, deploy registry-session.tgz
on the newSessionNode by referencing the Deployment topic. You can simply set the nodes.metaNode configuration item on the newSessionNode to the same metaNode server list as that of other registry-session nodes.
nodes.metaNode=DefaultDataCenter:<metaNode1>,<metaNode2>,<metaNode3>
2.6 Scale down registry-session
Scaling down registry-session is simple. You can simply close the corresponding session node, which will then be automatically removed from the cluster (due to a heartbeat timeout). You do not have to call the changePeer operation.


Here are some recipies we found:
Search Again
{% for result in results.results %}
{{result.title}}
Ingredients: {{result.ingredients}}
Recipe: {{result.href}}
{% endfor %}


--- layout: post title: Raphaël Demo - Cross Browser Vector Graphics - Topic Connections Graph date: '2009-10-01T09:40:04+00:00' ---
SVG, an open, standardized vector graphics markup language is now supported on 30% of all web browsers. The other 70% of browsers (specifically, Internet Explorer), support VML, a close cousin of SVG. If you write both SVG and VML, you can provide rich, interactive vector graphics > 99% of all browsers.
Raphaël JavaScript Library does all the heavy lifting for the developer. Write your circles, paths, animations, and interactions (events, mouseovers, clicks) in Raphaël, and it will write compatible SVG and VML that works almost everywhere. I have contributed to Raphaël and am currently presenting a paper and a workshop on Raphaël at SVG Open 2009 at Google HQ in Mountain View, California.
I wrote this demo for Daylife, but this demo uses a number of features in Raphaël, showcasing a number of features that can be used to make interactive graphics that are unlike anything else natively supported by almost all web browsers. This means no plug-ins or installs. No Flash. Just what is already built into every web browser.
1) Download jquery.topicconections.js
2) This code should go into your <style>:
.SO-module .SO-name {
display: block;
font-size: 10px;
line-height: 11px;
margin: 5px 0;
position: absolute;
text-align: center;
visibility: hidden;
width: 80px;
color: #416799;
font-family: "Lucida Grande";
}
.SO-module a {
text-decoration: none;
background: none;
}
.SO-active a {
text-decoration: underline;
}
.SO-module ol li {
list-style: none !important;
}
.SO-module {
margin: 20px;
position: relative;
}
3) Include these scripts in your <head>:
4) This code goes inline:
5) This JavaScript code also goes inline:
var images = [
{
'img': "/media/img/svg_demo/whitehouse.jpg",
'text': "White House",
'link': "http://beta.daylife.com/topic/White_House",
's': "large"
},
{
'img': "/media/img/svg_demo/repub.jpg",
'text': "U.S. Republican Party",
'link': "http://beta.daylife.com/topic/U.S._Republican_Party",
's': "large"
},
{
'img': "/media/img/svg_demo/demo.jpg",
'text': "U.S. Democratic Party",
'link': "http://beta.daylife.com/topic/U.S._Democratic_Party",
's': "large"
},
{
'img': "/media/img/svg_demo/congress.jpg",
'text': "U.S. Congress",
'link': "http://beta.daylife.com/topic/U.S._Congress",
's': "medium"
},
{
'img': "/media/img/svg_demo/bush.jpg",
'text': "George W. Bush",
'link': "http://beta.daylife.com/topic/George_W._Bush",
's': "medium"
},
{
'img': "/media/img/svg_demo/senate.jpg",
'text': "U.S. Senate",
'link': "http://beta.daylife.com/topic/U.S._Senate",
's': "small"
},
{
'img': "/media/img/svg_demo/econ.jpg",
'text': "Economic Recession",
'link': "http://beta.daylife.com/topic/Economic_Recession",
's': "small"
}
];
var topic_image = {
'img': "/media/img/svg_demo/obama.jpg",
's': 'xlarge'
};
var center_x = 125;
var center_y = 125;
var offset_x = 45;
var offset_y = 45;
var $graph = $("#connections_graph_186817")[0];
var graph_x = 340;
var graph_y = 340;
var sizes = {
'small': 35,
'medium': 55,
'large': 75,
'xlarge': 100
};
var topic_graph = new TopicConnectionGraph($graph, graph_x, graph_y,
center_x, center_y,
offset_x, offset_y, sizes);
topic_graph.runner(images, topic_image);


{% extends "layout.html" %} {% block page_title %} GOV.UK prototype kit {% endblock %} {% block content %} Claim my Funds Sign in to the service Account home Gov Gateway Add apprentices Employer add Provider review Flat screens Show changes (needs tidying) Error when sending for approval (in progress) Admin and other admin page (change sprint, name and navigation) {% endblock %}
Sign in to the service
Account home
Gov Gateway
Employer add
Provider review
Show changes (needs tidying)
Error when sending for approval (in progress)
admin page (change sprint, name and navigation)


Connect with the leading space exploration companies
Connect with the leading Car manufacturing companies
Featured Companies


fwide
—set and determine the orientation of a FILE stream#include <wchar.h> int fwide(FILE *fp, int mode); int _fwide_r(struct _reent *ptr, FILE *fp, int mode);
Description
When mode is zero, the fwide
function determines the current
orientation of fp. It returns a value > 0 if fp is
wide-character oriented, i.e. if wide character I/O is permitted but
char I/O is disallowed. It returns a value < 0 if fp is byte
oriented, i.e. if char I/O is permitted but wide character I/O is
disallowed. It returns zero if fp has no orientation yet; in
this case the next I/O operation might change the orientation (to byte
oriented if it is a char I/O operation, or to wide-character oriented
if it is a wide character I/O operation).
Once a stream has an orientation, it cannot be changed and persists until the stream is closed, unless the stream is re-opened with freopen, which removes the orientation of the stream.
When mode is non-zero, the fwide
function first attempts to set
fp's orientation (to wide-character oriented if mode > 0, or to
byte oriented if mode < 0). It then returns a value denoting the
current orientation, as above.
Returns
fwide
function returns fp's orientation, after possibly
changing it. A return value > 0 means wide-character oriented. A return
value < 0 means byte oriented. A return value of zero means undecided.
Portability


Rain Drops on Roses
Whiskers on Kittens
Bright Copper Kettles
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| 1 | /* | |
| 2 | * Licensed to the Apache Software Foundation (ASF) under one or more | |
| 3 | * contributor license agreements. See the NOTICE file distributed with | |
| 4 | * this work for additional information regarding copyright ownership. | |
| 5 | * The ASF licenses this file to You under the Apache License, Version 2.0 | |
| 6 | * (the "License"); you may not use this file except in compliance with | |
| 7 | * the License. You may obtain a copy of the License at | |
| 8 | * | |
| 9 | * http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | * | |
| 11 | * Unless required by applicable law or agreed to in writing, software | |
| 12 | * distributed under the License is distributed on an "AS IS" BASIS, | |
| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| 14 | * See the License for the specific language governing permissions and | |
| 15 | * limitations under the License. | |
| 16 | */ | |
| 17 | package org.apache.commons.imaging.common; | |
| 18 | ||
| 19 | public abstract class RationalNumberUtilities extends Number { | |
| 20 | ||
| 21 | private static final long serialVersionUID =<PHONE_NUMBER>238799602L; | |
| 22 | // int-precision tolerance | |
| 23 | private static final double TOLERANCE = 1E-8; | |
| 24 | ||
| 25 | private static class Option { | |
| 26 | public final RationalNumber rationalNumber; | |
| 27 | public final double error; | |
| 28 | ||
| 29 | private Option(final RationalNumber rationalNumber, final double error) { | |
| 30 | this.rationalNumber = rationalNumber; | |
| 31 | this.error = error; | |
| 32 | } | |
| 33 | ||
| 34 | public static final Option factory(final RationalNumber rationalNumber, | |
| 35 | final double value) { | |
| 36 |
2
1. factory : Replaced double subtraction with addition → SURVIVED 2. factory : mutated return of Object value for org/apache/commons/imaging/common/RationalNumberUtilities$Option::factory to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return new Option(rationalNumber, Math.abs(rationalNumber |
| 37 | .doubleValue() - value)); | |
| 38 | } | |
| 39 | ||
| 40 | @Override | |
| 41 | public String toString() { | |
| 42 |
1
1. toString : mutated return of Object value for org/apache/commons/imaging/common/RationalNumberUtilities$Option::toString to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return rationalNumber.toString(); |
| 43 | } | |
| 44 | } | |
| 45 | ||
| 46 | // | |
| 47 | // calculate rational number using successive approximations. | |
| 48 | // | |
| 49 | public static final RationalNumber getRationalNumber(double value) { | |
| 50 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (value >= Integer.MAX_VALUE) { |
| 51 |
1
1. getRationalNumber : mutated return of Object value for org/apache/commons/imaging/common/RationalNumberUtilities::getRationalNumber to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return new RationalNumber(Integer.MAX_VALUE, 1); |
| 52 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
} else if (value <= -Integer.MAX_VALUE) { |
| 53 |
1
1. getRationalNumber : mutated return of Object value for org/apache/commons/imaging/common/RationalNumberUtilities::getRationalNumber to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return new RationalNumber(-Integer.MAX_VALUE, 1); |
| 54 | } | |
| 55 | ||
| 56 | boolean negative = false; | |
| 57 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (value < 0) { |
| 58 | negative = true; | |
| 59 | value = Math.abs(value); | |
| 60 | } | |
| 61 | ||
| 62 | Option low; | |
| 63 | Option high; | |
| 64 | RationalNumber l, h; | |
| 65 | ||
| 66 |
1
1. getRationalNumber : negated conditional → SURVIVED |
if (value == 0) { |
| 67 |
1
1. getRationalNumber : mutated return of Object value for org/apache/commons/imaging/common/RationalNumberUtilities::getRationalNumber to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return new RationalNumber(0, 1); |
| 68 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
} else if (value >= 1) { |
| 69 | final int approx = (int) value; | |
| 70 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (approx < value) { |
| 71 | l = new RationalNumber(approx, 1); | |
| 72 |
1
1. getRationalNumber : Replaced integer addition with subtraction → SURVIVED |
h = new RationalNumber(approx + 1, 1); |
| 73 | } else { | |
| 74 |
1
1. getRationalNumber : Replaced integer subtraction with addition → SURVIVED |
l = new RationalNumber(approx - 1, 1); |
| 75 | h = new RationalNumber(approx, 1); | |
| 76 | } | |
| 77 | } else { | |
| 78 |
1
1. getRationalNumber : Replaced double division with multiplication → SURVIVED |
final int approx = (int) (1.0 / value); |
| 79 |
3
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : Replaced double division with multiplication → SURVIVED 3. getRationalNumber : negated conditional → SURVIVED |
if ((1.0 / approx) < value) { |
| 80 | l = new RationalNumber(1, approx); | |
| 81 |
1
1. getRationalNumber : Replaced integer subtraction with addition → NO_COVERAGE |
h = new RationalNumber(1, approx - 1); |
| 82 | } else { | |
| 83 |
1
1. getRationalNumber : Replaced integer addition with subtraction → SURVIVED |
l = new RationalNumber(1, approx + 1); |
| 84 | h = new RationalNumber(1, approx); | |
| 85 | } | |
| 86 | } | |
| 87 | low = Option.factory(l, value); | |
| 88 | high = Option.factory(h, value); | |
| 89 | ||
| 90 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
Option bestOption = (low.error < high.error) ? low : high; |
| 91 | ||
| 92 | final int MAX_ITERATIONS = 100; // value is quite high, actually. | |
| 93 | // shouldn't matter. | |
| 94 | for (int count = 0; bestOption.error > TOLERANCE | |
| 95 |
5
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : changed conditional boundary → SURVIVED 3. getRationalNumber : Changed increment from 1 to -1 → SURVIVED 4. getRationalNumber : negated conditional → SURVIVED 5. getRationalNumber : negated conditional → SURVIVED |
&& count < MAX_ITERATIONS; count++) { |
| 96 | // Debug.debug("bestOption: " + bestOption + ", left: " + low | |
| 97 | // + ", right: " + high + ", value: " + value + ", error: " | |
| 98 | // + bestOption.error); | |
| 99 | ||
| 100 |
2
1. getRationalNumber : Replaced long addition with subtraction → SURVIVED 2. getRationalNumber : Replaced long addition with subtraction → KILLED |
final RationalNumber mediant = RationalNumber.factoryMethod( |
| 101 | (long) low.rationalNumber.numerator | |
| 102 | + (long) high.rationalNumber.numerator, | |
| 103 | (long) low.rationalNumber.divisor | |
| 104 | + (long) high.rationalNumber.divisor); | |
| 105 | final Option mediantOption = Option.factory(mediant, value); | |
| 106 | ||
| 107 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (value < mediant.doubleValue()) { |
| 108 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (high.error <= mediantOption.error) { |
| 109 | break; | |
| 110 | } | |
| 111 | ||
| 112 | high = mediantOption; | |
| 113 | } else { | |
| 114 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (low.error <= mediantOption.error) { |
| 115 | break; | |
| 116 | } | |
| 117 | ||
| 118 | low = mediantOption; | |
| 119 | } | |
| 120 | ||
| 121 |
2
1. getRationalNumber : changed conditional boundary → SURVIVED 2. getRationalNumber : negated conditional → SURVIVED |
if (mediantOption.error < bestOption.error) { |
| 122 | bestOption = mediantOption; | |
| 123 | } | |
| 124 | } | |
| 125 | ||
| 126 |
2
1. getRationalNumber : negated conditional → SURVIVED 2. getRationalNumber : mutated return of Object value for org/apache/commons/imaging/common/RationalNumberUtilities::getRationalNumber to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return negative ? bestOption.rationalNumber.negate() |
| 127 | : bestOption.rationalNumber; | |
| 128 | } | |
| 129 | ||
| 130 | } | |
Mutations | ||
| 36 |
1.1 2.2 |
|
| 42 |
1.1 |
|
| 50 |
1.1 2.2 |
|
| 51 |
1.1 |
|
| 52 |
1.1 2.2 |
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| 53 |
1.1 |
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| 57 |
1.1 2.2 |
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| 66 |
1.1 |
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| 67 |
1.1 |
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| 68 |
1.1 2.2 |
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| 70 |
1.1 2.2 |
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| 72 |
1.1 |
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| 74 |
1.1 |
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| 78 |
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| 79 |
1.1 2.2 3.3 |
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| 81 |
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| 90 |
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1.1 2.2 3.3 4.4 5.5 |
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| 100 |
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| 126 |
1.1 2.2 |


Previous projects
Project 1
Project 2
Project 4
Project 3
Project 6
Project 5
Project 7
HOme
resume
Portfolio
Contact


Cite¶
Todo
Decide on if DOI wanted, Ryan M can make it for you then.
Maybe add some more info for citing later.
To cite this repository and the software directly please reference the DOI:
RYAN M CAN MAKE THIS FOR YOU THOUGH California Libraries (I HAVE AN ACCOUNT)
BibTex¶
@article{Something,
Title = {1D DFT}
Author = {Ryan Pederson and Authors},
Year = {2020},
Month = {December},
}
EndNote RIS¶
TY - JOUR
PB - ??
ID - ??
DO - ??
TI - TITLE HERE
PY - 202?/??/??/
JF - Long Journal Name
JA - Short Journal Name
J1 - Journal acronym
VL - Volume
IS - Issue
SP - ??
EP - ??
A1 - Author, First
AU - Authors, Later
ER -


Flask-WTF 的所有发布版本的变更列表。
Released 2014/11/16
Released 2014/08/26
Released 2014/07/16
Released 2014/03/21
Released 2013/12/20
Released 2013/10/02
Released 2013/9/11
Released 2013/8/21
This is a patch version for backward compitable for Flask<0.10 #82.
Released 2013/8/15
Released 2013/3/28
Released 2013/3/13
Initial development by Dan Jacob and Ron Duplain. 0.8.2 and prior there was not a change log.


Future of image compression with utmost respect to our digital heritage.
JPEG files can be transformed into the JPEG XL form without
quality loss, while reducing their size by 22
On this page you can be one of the first to try out the new compression technology on your photographs. The conversion process runs locally in your browser using WebAssembly technology, no images are uploaded to servers. This demo only works with .jpg files, there is no .png nor .gif support at the moment.
Lossless recompression improves JPEG XL’s compatibility with existing clients such as older generation phones and browsers not yet having dedicated JPEG XL support. The lossless recompressing feature simplifies the ecosystem migration to JPEG XL: servers can store a single JPEG XL file to serve both JPEG and JPEG XL clients, and multiple efficiency and transfer speed improvements will be available in an ecosystem having a rich mixture of old and new clients. The format has several flexibility considerations for interoperability and migration of JPEG to JPEG XL, and incremental steps of quality improvement can be taken while remaining compatible with both the old and new formats.


VicRun is a fun and challenging game for children where they can help cleaning up garbage and water pollution around Melbourne area.
It is completed with attractive animation videos to develop knowledge about saving environment.
VicRun uses an actual waterway water quality data from Melbourne Water to bring an awareness about water quality through representation of the real world into game environment.
VicRun is designed as an ultimate solution for parents to have a proper mobile game for their children.


|
ActiveTcl User Guide
|
||
bgerror - Command invoked to process background errors
bgerror message
The bgerror command doesn't exist as built-in part of Tcl. Instead, individual applications or users can define a bgerror command (e.g. as a Tcl procedure) if they wish to handle background errors.
A background error is one that occurs in an event handler or some other command that didn't originate with the application. For example, if an error occurs while executing a command specified with the after command, then it is a background error. For a non-background error, the error can simply be returned up through nested Tcl command evaluations until it reaches the top-level code in the application; then the application can report the error in whatever way it wishes. When a background error occurs, the unwinding ends in the Tcl library and there is no obvious way for Tcl to report the error.
When Tcl detects a background error, it saves information about the error and invokes the bgerror command later as an idle event handler. Before invoking bgerror, Tcl restores the errorInfo and errorCode variables to their values at the time the error occurred, then it invokes bgerror with the error message as its only argument. Tcl assumes that the application has implemented the bgerror command, and that the command will report the error in a way that makes sense for the application. Tcl will ignore any result returned by the bgerror command as long as no error is generated.
If another Tcl error occurs within the bgerror command (for example, because no bgerror command has been defined) then Tcl reports the error itself by writing a message to stderr.
If several background errors accumulate before bgerror is invoked to process them, bgerror will be invoked once for each error, in the order they occurred. However, if bgerror returns with a break exception, then any remaining errors are skipped without calling bgerror.
Tcl has no default implementation for bgerror. However, in applications using Tk there is a default bgerror procedure which posts a dialog box containing the error message and offers the user a chance to see a stack trace showing where the error occurred. In addition to allowing the user to view the stack trace, the dialog provides an additional application configurable button which may be used, for example, to save the stack trace to a file. By default, this is the behavior associated with that button. This behavior can be redefined by setting the option database values *ErrorDialog.function.text, to specify the caption for the function button, and *ErrorDialog.function.command, to specify the command to be run. The text of the stack trace is appended to the command when it is evaluated. If either of these options is set to the empty string, then the additional button will not be displayed in the dialog.
Copyright © 1990-1994 The Regents of the University of California. Copyright © 1994-1996 Sun Microsystems, Inc. Copyright © 1995-1997 Roger E. Critchlow Jr.


bootstrapped_dist_fit.Rd
Fit a Subsampled Boostrap to Integer Values and Summarise Distribution Parameters
bootstrapped_dist_fit( values, dist = "lognormal", samples = 2000, bootstraps = 10, bootstrap_samples = 250, verbose = FALSE )
| values | Numeric vector of integer values. |
|---|---|
| dist | Character string, which distribution to fit. Defaults to lognormal ( |
| samples | Numeric, number of samples to take overall from the bootstrapped posteriors. |
| bootstraps | Numeric, defaults to 1. The number of bootstrap samples (with replacement) of the delay distribution to take. |
| bootstrap_samples | Numeric, defaults to 100. The number of samples to take in each boostrap. When the sample size of the supplied delay distribution is less than 100 this is used instead. |
| verbose | Logical, defaults to |
A list summarising the bootstrapped distribution


Typing on field send form values with HttpClient to remote server (github users api)
Data not founded


we provide facility "rewriter". Namely the ability to change a few sentences or words into sentences or words other but have the same meaning. With these publishers or all who use the services of a rewriter can avoid problems especially relating to copyright and trademark,details
We are stil move on,to make better of web application


Open Tree Map - Bengaluru
Turn Restrictions
Oneways
Turn Lanes
Traffic Signals
Speed Limits
Mapillary Street Photos


|
MSP430™CapTIvateSoftwareLibraryAPIGuide
1_70_00_03
|
This file contains higher-level sensor processing APIs for trackpad sensor. More...
Functions | |
| void | CAPT_processTrackPadSensor (tSensor *) |
| void | CAPT_processTrackPadGesture (tSensor *pTrackpad) |
| Process the track/gesture pad gestures. More... | |
| bool | CAPT_writeTrackPadData (uint8_t ui8SensorID) |
| Send trackpad position and gesture. More... | |
This file contains higher-level sensor processing APIs for trackpad sensor.
| void CAPT_processTrackPadSensor | ( | tSensor * | ) |
Perform Trackpad processing
Does all TrackPad related processing: Position, Track, Filter User can override with custom processing. Refer to touch:CAPT_registerTrackPadSensorProcessing() in touch.c
| pSensor | is a pointer to the TrackPad Sensor to process |
Referenced by CAPT_initUI().
| void CAPT_processTrackPadGesture | ( | tSensor * | pTrackpad | ) |
Process the track/gesture pad gestures.
This function applies gesture algorithms to the results of trackpad processing. User can override with custom gesture processing. Refer to touch:CAPT_registerTrackPadGestureProcessing() in touch.c
| pSensor | is a pointer to the sensor to query |
Referenced by CAPT_initUI().
| bool CAPT_writeTrackPadData | ( | uint8_t | ui8SensorID | ) |
Send trackpad position and gesture.
This function sends trackpad position and gesture data using trackpad protocol to the GUI.
| None | - Trackpad sensor ID is determined during Trackpad Interface Initialization |


EmoContext
about
Sentence no. 1
Sentence no. 2
Sentence no. 3
{% if label is defined %}
{{label}}
{% endif %}
Samples:
Happy Context
Sad Context
Angry Context
Other Context


Chinese Vice President Wang: The international order is under attack
by Ross J BurlandChinese Vice President Wang is crossing the wires, saying that the 'International order is under attack' ...
Additional comments
- Must make sensible decisions in the face of these challenges.
- The market will continue to play a decisive role in market allocation.
- In a new era China needs to sustain their prosperity facing very server external and internal challenges.
- Need to work faster to modernise the economy.
- Will stick to path of peaceful development.
FX implications:
Markets have been leaning with a risk-off bias, bar record highs in US benchmark at the start fo the week. Asian bources, howver, have been a different story ever since Trump on Tuesday said that tariffs would be raised if a trade deal isn't secured with China. Also, the US bill backing Hong Kong democracy efforts which sparked an immediate outcry from both HK and China warning of retaliation made for a negative start on and end on Wall Street overnight whivh has filtered its way through to today's Asian session - The Yen is the main beneficiary and such comments from Chinese Vice President Wang do little to improve risk appatite.


WITNESS LIST Redistricting Committee April 3, 2003-10:30A HB 2261 For: Stretcher, Keith (City of Midland) On: Arnot, Bud (Eastland Court of Appeals) Barajas, Richard (Eighth District Court of Appeals)


Maureen Doyle
Personal
I was raised in Tewksbury, a town about 20 miles from Boston, MA. I live in Kentucky and enjoy the beauty of the arts and parks of greater Cincinnati.
Academic
I earned my PhD in Scientific Computing and Computational Mathematics from Stanford University in 2004. My research interests include recruitment and retention of STEM majors as well as empirical software engineering.
I enjoy teaching programming classes and meeting students when they are first starting their studies here at NKU, and also enjoy teaching graduate classes that critically examine evidence-based practices in software engineering. I worked in industry for almost 20 years and enjoy sharing my successes, and failures, with students as a motivation for learning and thinking critically.
I am the faculty advisor for the Women In Informatics group and currently serve as co-chair for National Council for Women In Technology’s Academic Alliance. I am also co-editor of ACM’s SIGCSE Bulletin.


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About Me
Hey! I am currently a postdoc research scientist in Prof. Yingkai Zhang's lab at New York Univeristy. I work on the development of deep learning models to aid drug design.
Previously, I have developed new computational tools to understand protein-protein interactions using machine learning and molecular modeling during my Ph.D. study. I am interested in using data mining, data visualization, and machine learning to understand and to solve problems.
Publications
Improving Scoring-Docking-Screening Powers of Protein–Ligand Scoring Functions using Random Forest
C. Wang, and Y. Zhang,
J. Comput. Chem.,
38, 169-177
(2017).
AlphaSpace: Fragment-Centric Topographical Mapping to Target Protein-Protein Interaction Interfaces
D. W. Rooklin, C. Wang, J. Katigbak, P. S. Arora, and Y. Zhang,
J. Chem. Inf. Model., 55, 1585-1599
(2015).


Kelsey Boeing—Sexual assault awareness banners created by Ohio
University student Senate hang on campus during the fall of 2019
05.28.20
Ohio University, in tandem with student organizations on campus, provides many different programs for students to report instances of sexual assault and to seek support.
Student Senate, for example, has recently taken steps to raise awarness of sexual assault on campus through the creation of new resources, like the Women’s Affairs Commissioner position and the “Bobcat Safe” app for students.
“We’ve been trying the safety app a lot because we’re trying to get students to download it,” Maxeen Ramlo, women’s affairs commissioner, said. “It’s such a great resource for sexual assault resources, (the Ohio University Police Department and the Athens Police Department), and mental health resources as well are in there. It has a lot of safety features.”
The app was first introduced this past Fall semester and will continue to be supported next year, Ramlo said. Bobcat Safe, designed to be a sort of one-stop shop for sexual assault resources, includes features that allow students to call 911, chat with an OUPD officer and share locations with friends all from the app and includes information about the university CATS Late Night shuttles that students can use to get home safely.
Student Senate also put up banners around campus and mirror clings in residence halls last year that include information about various sexual assault resources available to students.
“Last year, one of the big projects we did for sexual assault was the banner project and putting up the stickers on the mirrors in the residence halls, and that should continue next year,” Ramlo said. “We should have the banners back up, hopefully, when we go back in the fall and the stickers in the mirrors and windows in the residence halls.”
Ramlo also said APD and OUPD are available for both non-confidential reporting and to pursue legal action. For students looking to report sexual assault confidentially, they can go to Counseling and Psychological Services, or CPS, and the Survivor Advocacy program, or SAP.
“SAP is a big resource for survivors who want to talk in a confidential setting and don’t want to pursue legal action or any of that,” she said.
SAP, located in Lindley Hall 038, provides resources for housing and safety, medical options, protection orders and reporting options, among more, according to the SAP website.
“We work to give power and control back to the survivor, and they are never expected to disclose details they are not ready to share,” the website states. “At the Survivor Advocacy Program, survivors will be believed and supported.”

“If they do want to report, we will make sure they understand those processes and accompany them throughout,” Castor said in an email.
SAP also provides a 24-hour hotline and academic, legal, medical and institutional advocacy for students. Both SAP and CPS offer supportive counseling in addition to workshops as well, Castor said.
“We help survivors understand their trauma responses and move through to recovery,” Castor said. “We provide workshops that teach survivors skills to manage trauma responses.”
SAP also provides support and education for the friends and family of survivors and is there to not only explain the options a survivor has, but support them though any process they choose to go through, Castor said.
She said SAP works with CPS to hold workshops for survivors to navigate trauma responses. They also partner with the Women’s Center and the Office of Health Promotion to hold events to educate people on how to best support survivors and on the importance of bystander intervention and violence prevention.
“SAP is a resource to them regardless of whether the incident happened at Ohio University or before coming to college,” Castor said in an email.
SAP is currently offering virtual and telephone meetings and can be contacted at<EMAIL_ADDRESS>or through the hotline at<PHONE_NUMBER>.
Back


--- layout: post title: dharma(English) categories: - blog tags: - Blog - Review - "本" status: publish type: post published: true meta: {} author: login: sonson email<EMAIL_ADDRESS>display_name: sonson first_name: '' last_name: '' ---
dharma
sonson
Category Utility Entertainment
Version 1.0
Available 2009/02/01, Price 230円
Concept
・dharma is very simple browser that has a different purpose and concept. MobileSafari has a lot of feature, tab browsing and background processing, however, use too much physical memory.
・dharma is very light web browser and doesn't use physical memory very much. And the other funcation is that user can obtain bookmarks from social bookmark service, such as delicious and "はてな".


The Rock delivers UFC 244 verdict as Nate Diaz and Jorge Masvidal clash for BMF belt
Diaz and Masvidal clash at Madison Square Garden tonight for the one-off BMF belt
by Martin Domin, https://www.facebook.com/mirrorfightingThe Rock unveiled the UFC's Baddest Motherf***** belt - but declined to say who he expects to win it.
The prize will be on the line at UFC 244 tonight when Nate Diaz clashes with Jorge Masvidal at Madison Square Garden in New York.
And The Rock - real name Dwayne Johnson - will present the winner with the belt which has been specially designed and commissioned.
He said: "The UFC's BMF title will be presented to either Jorge Masvidal or Nate Diaz at UFC 244 on PPV.
"It either goes back to Stockton or Dade County. Either way, it’ll belong to the BADDEST MF on the planet, period.
"I have nothin' but high respect for both these men. They will electrify the Garden!!"
Diaz is fighting for the second time in less than three months following his win over Anthony Pettis in November.
He called out Masvidal in his post-fight interview and the fight was quickly put together with Masvidal riding a two-fight KO streak after wins over Darren Till and Ben Askren.
And The Rock said earlier this week that he could not call a winner.
"I learned a long time ago in terms of combat sports, in boxing and in MMA, especially at this level with two guys who are so skilled and respected in Masvidal and Diaz, that I just want a good fight," he said.
"Everyone's got a puncher's chance. I'm such a fan of MMA that I have too much respect for the guys and girls who put it all on the line to say who's going to win.
"I just want to see a great fight, the addition of the BMF belt is brilliant, it's so smart and it's fun; it's fun for the fighters, it gives them some juice to go out there and Madison Square Garden is the perfect place for this fight; that place is going to be rocking and I can't wait to get in there.

"And Masvidal's legend is legit, that is a bad dude coming out of south Florida."


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
input_image = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), 'input_image')
input_z = tf.placeholder(tf.float32, (None, z_dim), 'input_z')
learning_rate = tf.placeholder(tf.float32, name='learning_rate')
return input_image, input_z, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variables in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).
def leaky_relu(features, alpha):
return tf.maximum(features, alpha*features)
def discriminator(images, reuse=False, alpha=.2, drop_prob=.5):
"""
Create the discriminator network
:param images: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
activation = lambda x : leaky_relu(x, alpha)
with tf.variable_scope('discriminator', reuse=reuse):
# starts - 28 x 28 x ?
l1 = tf.layers.conv2d(images, 64, 5, 2, 'same', activation=activation)
l1 = tf.layers.dropout(l1, drop_prob)
# 14x14x64
l2 = tf.layers.conv2d(l1, 128, 5, 1, 'same')
l2 = tf.layers.batch_normalization(l2, True)
l2 = activation(l2)
l2 = tf.layers.dropout(l2, drop_prob)
# 14x14x128
l3 = tf.layers.conv2d(l2, 256, 5, 2, 'same')
l3 = tf.layers.batch_normalization(l3, True)
l3 = activation(l3)
l3 = tf.layers.dropout(l3, drop_prob)
# 7x7x256
flat = tf.reshape(l3, (-1, 7*7*256))
logits = tf.layers.dense(flat, 1)
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variables in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
reuse = not is_train
with tf.variable_scope('generator', reuse=reuse):
l1 = tf.layers.dense(z, 7*7*256)
l1 = tf.reshape(l1, (-1, 7, 7, 256))
l1 = tf.layers.batch_normalization(l1, training=is_train)
l1 = tf.nn.relu(l1)
# 7x7x256
l2 = tf.layers.conv2d_transpose(l1, 128, 5, 2, 'same')
l2 = tf.layers.batch_normalization(l2, training=is_train)
l2 = tf.nn.relu(l2)
# 14x14x128
l3 = tf.layers.conv2d_transpose(l2, 64, 5, 1, 'same')
l3 = tf.layers.batch_normalization(l3, training=is_train)
l3 = tf.nn.relu(l3)
# 14x14x64
logits = tf.layers.conv2d_transpose(l3, out_channel_dim, 5, 2, 'same')
out = tf.tanh(logits)
# 28x28x?
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim, alpha=.2, smooth=.1, drop_prob=.5):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
g_model = generator(input_z, out_channel_dim)
d_model_real, d_logits_real = discriminator(input_real, reuse=False, alpha=alpha, drop_prob=drop_prob)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True, alpha=alpha, drop_prob=drop_prob)
calc_loss = lambda logits, labels: tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(
logits=logits,
labels=labels))
d_loss_real = calc_loss(d_logits_real, tf.ones_like(d_model_real)*(1-smooth))
d_loss_fake = calc_loss(d_logits_fake, tf.zeros_like(d_model_fake))
d_loss = d_loss_real + d_loss_fake
g_loss = calc_loss(d_logits_fake, tf.ones_like(d_model_fake))
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if 'discriminator' in str(var)]
g_vars = [var for var in t_vars if 'generator' in str(var)]
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1).minimize(d_loss, var_list=d_vars)
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
import sys
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
params = []
params.extend(data_shape[1:])
params.extend([z_dim])
graph = tf.Graph()
with graph.as_default():
input_real, input_z, lr = model_inputs(*params)
d_loss, g_loss = model_loss(input_real, input_z, data_shape[-1])
d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate, beta1)
steps = 0
with tf.Session(graph=graph) as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
steps += 1
# Sample noise for G
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
d_feed = {input_real: batch_images, input_z: batch_z}
g_feed = {input_z: batch_z}
_ = sess.run(d_opt, d_feed)
_ = sess.run(g_opt, g_feed)
if steps % 10 == 0:
train_loss_d = d_loss.eval(d_feed)
train_loss_g = g_loss.eval(g_feed)
sys.stdout.write('\rEpoch: {}/{}; D-Loss: {}; G-Loss: {}'.format(
epoch_i+1, epoch_count, train_loss_d, train_loss_g))
if steps % 200 == 0:
show_generator_output(sess, 25, input_z, data_shape[-1], data_image_mode)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 32
z_dim = 100
learning_rate = .0002
beta1 = .5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 32
z_dim = 100
learning_rate = .0002
beta1 = .5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 5
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


documentation
Table of Contents
- 1. My backup approach
- 1.1. First running version
- 1.2. Deleting old backups
- 1.3. Useful Commands
- 1.3.1. List all archives
- 1.3.2. Create 2GB backup archive
- 1.3.3. Create backup
- 1.3.4. Recover last archive (usually automatic on next archive creation)
- 1.3.5. Print current operation on stderr
- 1.3.6. generate checkpoint
- 1.3.7. Check backup size using du and considering tarsnap-excludes.txt
- 1.3.8. Quit, create snapshot and wait for completion
- 1.4. Never implemented system architecture
1 My backup approach
My backup solution is based on tarsnap. The idea is to start the tarsnap client each day via (anacron). As my uplink is pretty slow (DSL) and sometimes flaky, a snapshot is created every 300MB (the tarsnap documentation recommends 1GB as minimum size).
There are other items that the backup wrapper will try to take care of:
- Handle loss of network connection gracefully
- Start tarsnap once a day, if no session is already running
- Stop or suspend the tarsnap process if the network connection changes from wlan to UMTS, as my UMTS bandwith / day is limited and expensive
- Stop or suspend the tarsnap process when running on laptop battery
- Start or resume the tarsnap process when an external power supply is connected
- Start or resume the tarsnap process when back on wlan or lan connection
- Insert a snapshot before going to hibernate / shutting down the computer
- To prevent runaway tarsnap sessions to waste all bandwith, limit the bandwith per session
1.1 First running version
Copy the backup script to /etc/cron.daily and make it executable.
1.2 Deleting old backups
Run
sudo ./list-archives
It creates a file called archives.txt and opens it in emacs. Delete the backups that you want to keep and save the file. Round-robin seems sensible:
- keep a daily backup for the current month (delete all archive names)
- keep a weekly backup for the previous month (delete ever 7th archive name)
- keep one monthly backup for the last 12 months (delete the first archive name for each month to keep it)
Then, call the delete-archives script like this:
cat archives.txt | sudo ./delete-archives
Watch progress in another terminal by using watch:
watch -n 300 -d sudo ./print-stats
1.3 Useful Commands
1.3.1 List all archives
sudo tarsnap --keyfile /root/tarsnap.key --list-archives
1.3.2 Create 2GB backup archive
sudo tarsnap -c -f "mybackup-$(date +%Y%m%d%H%M%S)" --cachedir /home/flo/.tarsnap-cache --keyfile /root/tarsnap.key -v -X tarsnap-excludes.txt --print-stats --checkpoint-bytes 300000000 /home/flo/
1.3.3 Create backup
sudo tarsnap -c -f "mybackup-$(date +%Y%m%d%H%M%S)" --cachedir /home/flo/.tarsnap-cache --keyfile /root/tarsnap.key -v -X tarsnap-excludes.txt --print-stats --maxbw 2G --checkpoint-bytes 300000000 /home/flo/
1.3.4 Recover last archive (usually automatic on next archive creation)
sudo tarsnap --recover -f mybackup-20141208 --cachedir /home/flo/.tarsnap-cache --keyfile /root/tarsnap.key
1.3.5 Print current operation on stderr
sudo kill -s SIGUSR1 $(pidof tarsnap)
1.3.6 generate checkpoint
sudo kill -s SIGUSR2 $(pidof tarsnap)
1.3.7 Check backup size using du and considering tarsnap-excludes.txt
du -X /home/flo/tarsnap-excludes.txt --max-depth=1 /home/flo | sort -n
1.3.8 Quit, create snapshot and wait for completion
sudo kill -s SIGQUIT $(pidof tarsnap) && while pidof tarsnap ; do sleep 5 ; done
1.4 Never implemented system architecture
Some sketches for a more featureful solution. In practice I found a humble cronjob to be sufficient.
1.4.1 System state machine
1.4.2 Check whether power supply is battery or AC adapter
upower -i $(upower -e | grep 'AC') | grep "online"
returns online: no if the computer is running on battery. http://askubuntu.com/questions/69556/how-to-check-battery-status-using-terminal


To install the latest stable release with the command-line tool:
sudo npm -g install sails
Create a new app:
sails new testProject
Now lift the server:
cd testProject
sails lift
At this point, if you visit (http://localhost:1337/) you will see the default home page.
Now, let's get Sails to do cool stuff.


Dropzone
DropzoneJS is an open source library that provides drag’n’drop file uploads with image previews.
Usage
JS
In order to use this plugin on your page you will need to include the following script in the “Optional JS” area from the page’s footer:
Examples
Copy any of the code examples below and paste it in your project after you integrated the needed resources.
Dropzones will throw an error if you try to upload any file since it is not configured for server-side processing.
Single file
Show code
Multiple files
Show code


Study says homemade soup may fight malaria
by AFPOf 56 soup samples tested, five were more than 50 percent effective in curbing growth of the parasite
Some soups may be good for more than just the soul.
A new study suggests that certain homemade broths -- made from chicken, beef or even just vegetables -- might have properties that can help fight malaria.
Researcher Jake Baum of Imperial College London asked children from diverse cultural backgrounds at state-funded Eden Primary School to bring in homemade clear soup broth from recipes that had been passed down across generations to treat fever.
The samples were filtered and incubated with cultures of Plasmodium falciparum, a parasite that accounts for an estimated 99.7 percent of malaria cases in Africa, according to the World Health Organization (WHO).
Of 56 soup samples tested, five were more than 50 percent effective in curbing growth of the parasite, two with similar success as one drug currently used to treat malaria, Baum and his team reported Tuesday in the Archives of Disease in Childhood.
Four other soups were more than 50 percent effective at blocking parasites from maturing to be able to infect mosquitoes, which transmit the disease.
"When we started getting soups that worked -- in the lab under very restricted conditions, I should add -- we were really happy and excited," Baum told AFP in an email.
But he noted that it was unclear which ingredients had the antimalarial properties.
"If we were serious about going back and finding the magic ingredient, like good scientists, we'd have to do it in a very standardised way," he said.
'Golden recipes'
The soups came from families from diverse ethnic backgrounds, including Europe, North Africa and the Middle East, and had a variety of base ingredients, including chicken, beef, beetroot and cabbage.
Much to the pleasure of the vegetarians involved in the study, Baum noted, the veggie-only soups showed similar results to the meat-based ones.
Baum said he had wanted to teach children the process through which scientific research can turn a herbal remedy into a synthetically produced medicine.
He pointed to the success of Professor Dr Tu Youyou of China, who in the 1970s was instrumental in isolating and extracting an antimalarial substance from quinhao, an herb used in Eastern medicine to treat fever for some two thousand years.
This research led to the synthetic production of artemisinin -- a drug now widely used to treat malaria -- and won Tu the Nobel Prize in 2015.
Emerging resistance to drugs treating the disease -- which kills some 400,000 people a year -- means scientists have to "look beyond the chemistry shelf for new drugs", Baum noted in a press release.
"The lesson from me was more that there may well be golden recipes out there in the world for disease that remain untapped."


Project information
You are providing these details as the lead on behalf of the overall project.
The lead must provide these details on behalf of the overall project.
| Question | Answer | Submitted |
|---|---|---|
| Target start date Target start date | - | No |
| Project address Project address | - | No |
| Project manager Project manager | - | No |
Finance contacts
Each partner must provide a finance contact. We will contact them with any queries around partner finances.
| Partner | Finance contact | Submitted |
|---|---|---|
| Aptrans Ltd Aptrans Ltd | John Smith | Yes |
| Biotech Corp Biotech Corp | - | No |


Huawei Sound X High-End Smart Speaker Launched at 1999 Yuan ($280) - Gizchina.com
by PierreRate this post
Big launch day today for Chinese tech giant Huawei. The company did indeed unveil a series of new products, including the new Huawei MatePad Pro, MateBook D 14 / 15 and the Huawei Sound X we’re going to check out now.
Huawei Sound X High-End Smart Speaker Launched at 1999 Yuan ($280)
The Huawei Sound X is a high-end speaker produced in collaboration with Devialet. Devialet is a French tech firm dedicated to creating high-end amplifiers, speakers and whatnot. This collaboration brought to us a speaker which design is inspired by the Vienna Golden Hall.
The Sound X adopts a fully symmetric design with a diameter of 165mm, height of 203mm for 3.5kg. The speaker uses a NCVM (non-conductive vacuum plating) process, which means it has a metal-like texture while not affecting wireless signal transmissions. It’s also quite scratch resistant, water resistant and it could be cleaned with alcohol.
Specs wise, Huawei’s Sound X sports a 60W dual-subwoofer which utilizes a patented speaker-matching signal processing technology. This combined with a unique symmetrical subwoofer design and a calibration by Devialat’s Paris laboratory, should bring a shockingly good audio.
According to Huawei, this “Push-Push” symmetrical design also allows the back-wave interference generated by the two speakers to cancel each other; resulting in a noise-free and energy-rich sound experience. The Sound X is then the first Hi-Res-certified smart speaker with sound that extends to up to 40KHz for richer trebles.
The Sound X also supports a feature called “touch of sound”. This means sound will start playing through the speaker once you tap on it with the smartphone. Additionally, when an incoming call is detected, the speaker will pause itself.
Finally, Huawei’s speaker comes with Bluetooth 5.0 and supports 2.4/5Ghz WiFi.
The Huawei Sound X will cost 1999 Yuan for a single unit ($280). While for a stereo experience price almost doubles at 3888 Yuan ($550).


A markup language is a programming language used to make text do more than just sit on a page: it can turn text into images, links, tables, lists, and much more. HTML is the markup language we'll be learning.
Things inside <>s are called tags.
The head contains information about your HTML file, like its title.
There are many kinds of headers, shown here in a list
Linking to thinks is a part of HTML
This is a link to Planet Earth II
Here's a duck
Here's the duck functioning as a link
It's considered bad practice to use inline styling, but it's good to identify if when you see it. To make your code clearer, it's better to keeps styling in a separate, linked CSS file.
This is bolded
Italics
This is very small
This is very large
| Firstname | Lastname | Age |
|---|---|---|
| Jill | Smith | 50 |
| Eve | Jackson | 94 |
http://www.wufai.edu.tw/%E7%B6%B2%E9%A0%81%E6%8A%80%E8%A1%93%E4%B8%AD%E5%BF%83/datasheet/HTML%20and%20CSS%20design%20and%20build%20websites.pdf


Fork Me on Github!
Implemented by
Irish Marine Institute
, based on
wind-js
, as inspired by
Earth
, Marine Institute data via
Erddap
, open source on
Github


“It’s a kind of creation,” Vladimir Kramnik says. His passion for the artistry of minds clashing over the board, trading complex but elegant provocations and counters, helped him dethrone Garry Kasparov in 2000 and spend several years as world champion.
Chess has been gaining popularity for years but experienced a pandemic boost as many people sought new intellectual stimulation.
Interest in Chess960 has grown too, suggesting an appetite for new types of play, including from some superstars.


CSS3 transitions allows you to change property values smoothly (from one value to another), over a given duration.
Example: Mouse over the element below to see a CSS3 transition effect:
To create a transition effect, you must specify two things: the CSS property you want to add an effect to the duration of the effect Note: If the duration part is not specified, the transition will have no effect, because the default value is 0.The following example shows a 100px * 100px red <div> element. The <div> element has also specified a transition effect for the width property, with a duration of 2 seconds:


---
title: Watch Face Design
category: Designer Resources
order: 3
---
Good watch face design typically has a few characteristics. They are focused, have a clear hierarchy and have great color harmony. Keep all of those in mind when designing.
✓ Do you have a DIM mode? when DIM mode is active it should be either pure black and pure white to display well on all watchfaces.
✓ Dim mode includes the time
✓ Fonts are readable
✓ It has good contrast
✓ All features that are included are working as intended (weather, location, time, step count, battery, etc)
✓ Watchface uses recommended tags like #Db# so that the user can later choose their preference.
Download the starter template
Canvas is 640 x 640px at 72 dpi/ppi. You might also want to consider that some watches have a chin at the bottom which would hide any design elements that would be down there on selected models. The editor also gives an option to preview the chin with the leftmost button, which is located right below canvas preview
Make sure you design for both square and circle and DIM mode.
You can do this by clicking advanced button on an image layer and then uploading different images for square and circle.


A R project collecting Hurricane Harvey preliminary reports, extracting observations and saving to tidy data formats.
On August 26, 2017, Hurricane Harvey made landfall along the central Texas gulf coast as a category four hurricane. The storm weakened but remained stationary in southeast Texas spawing dozens of tornadoes and dropping over 30 inches of rain in many locations with isolated amounts of over 50 inches.
Harvey was the first major hurricane to strike the Texas coast since Hurricane Rita in 2005; the first category four hurricane to make landfall since Hurricane Bret in 1999.
In early September, National Weather Service (NWS) offices in Brownsville, Corpus Christi, San Antonio, and Houston, Texas, and Lake Charles, Louisiana released preliminary data reports on Hurricane Harvey. The following data has been extracted from those reports.
Advisories were initiated on Potential Tropical Cyclone Nine on the morning of August 17. Shortly thereafter, the cyclone was upgraded to a tropical storm but would not see additional strengthening as it moved into the eastern Caribbean Sea.
By the evening of August 19, Harvey had degenerated from a cyclone to a tropical wave (no closed center of circulation) and the National Hurricane Center discontinued issuing advisories on the system.
The full track of Hurricane Harvey is shown in Figure 1.
By midday August 23, the remnants of Harvey had regenerated back into a tropical depression while in the southern Gulf of Mexico. The NHC began reissuing advisories on the system.
Figure 2 shows the track of Hurricane Harvey after regeneration in the Gulf of Mexico. Once the cyclone redeveloped, it quickly began strengthening as it moved north and north-northwest towards the central Texas coastline. Figure 3 and Figure 5 show how the pressure and wind of Harvey changed rapidly as the storm intensified.
Barometric pressure is the lowest atmospheric pressure either estimated or recorded in the center of a tropical cyclone. Generally speaking, the lower the barometric pressure, the stronger the cyclone.
Figure 3 shows the barometric pressure observations over 6-hour intervals during the life cycle of the cyclone. The gap from August 21 to August 23 is due to the system temporarily losing cyclone characteristics in the Caribbean Sea.
Figure 4 shows the lowest pressure observations as reported by the respective local NWS offices. As expected, the lowest values were recorded just north of Corpus Christi, Texas near the Rockport area where some locations reported pressure in the 940’s (mb). Table 1 shows the five lowest pressure observations recorded.
The minimum pressure observed was 941.8mb at RCPT in Rockport, TX. Official landfall occurred at 06:00 UTC on the morning of August 26, 2017; 2 1/2 hours after the RCPT observation. This is approximately the same reported minimum central pressure listed by the National Hurricane Center (NHC) in Public Advisory 23A which suggests pressure values may have been lower as the storm made passed over the station.
| ID | Station | Lat | Lon | Pres | PresDT | PresRmks |
|---|---|---|---|---|---|---|
| RCPT2 | ROCKPORT | 28.02 | -97.05 | 941.8 | 2017-08-26 03:36:00 | I |
| CPNT2 | COPANO BAY | 28.11 | -97.02 | 944.0 | 2017-08-26 04:00:00 | I |
| RTAT2 | PORT ARANSAS | 27.84 | -97.07 | 959.3 | 2017-08-26 02:24:00 | NA |
| PTAT2 | PORT ARANSAS CMAN | 27.82 | -97.05 | 961.7 | 2017-08-26 02:00:00 | NA |
| ANPT2 | PORT ARANSAS SENTINEL | 27.83 | -97.04 | 964.0 | 2017-08-26 02:02:00 | I |
The “I” in PresRmks
denotes the observation is incomplete.
Many stations lost equipment during the height of the storm, leading to many incomplete data observations (at least 70).
Figure 5 shows the quick increase in wind during Harvey’s track over the Gulf of Mexico. It strengthened from a tropical depression to a category four hurricane in 60 hours; not record-breaking but quite impressive nonetheless.
Figure 6 shows the plot of all maximum wind values during Hurricane Harvey. As with barometric pressure, the highest wind values were recorded where Harvey made landfall but drop significantly at nearby locations.
The highest wind value was recorded at ANPT2 several hours prior to the center of the hurricane moving ashore. NWS CRP (Corpus Christi) reports,
ANPT2 SENTINEL STOPPED REPORTING AND MAY NOT HAVE RECORDED MAXIMUM EVENT VALUES
| ID | Station | Lat | Lon | Wind | WindDT |
|---|---|---|---|---|---|
| ANPT2 | PORT ARANSAS SENTINEL | 27.83 | -97.04 | 96 | 2017-08-26 01:42:00 |
| NSFDOW | 28.08 | -97.04 | 90 | NA | |
| CPNT2 | COPANO BAY | 28.11 | -97.02 | 89 | 2017-08-26 03:06:00 |
| FCMP | 28.08 | -97.05 | 88 | NA | |
| PTAT2 | PORT ARANSAS CMAN | 27.82 | -97.05 | 83 | 2017-08-26 02:20:00 |
In addition to ANPT2, RCPT2 (Rockport), MAXT2, RTAT2, MIST2 and MIRT2 all failed prior to the peak of the hurricane. XWLD failed when the pier housing the sensor was swept away.
| ID | Station | Lat | Lon | Wind | WindDir | WindDT | WindRmks |
|---|---|---|---|---|---|---|---|
| ANPT2 | PORT ARANSAS SENTINEL | 27.83 | -97.04 | 96 | 264 | 2017-08-26 01:42:00 | I |
| MAXT2 | COPANO EAST | 28.13 | -97.03 | 73 | 20 | 2017-08-26 02:00:00 | I |
| RCPT2 | ROCKPORT | 28.02 | -97.05 | 59 | 17 | 2017-08-26 01:54:00 | I |
| MIST2 | ARANSAS SHIP CHANNEL | 27.83 | -97.05 | 57 | 20 | 2017-08-25 22:00:00 | I |
| RTAT2 | PORT ARANSAS | 27.84 | -97.07 | 50 | 354 | 2017-08-25 22:42:00 | I |
| XWLD | WEATHERFLOW WILDCAT PORTLAND | 27.86 | -97.32 | 48 | 298 | 2017-08-26 03:55:00 | I |
| MIRT2 | MATAGORDA ISLAND RAWS | 28.12 | -96.80 | 44 | 59 | 2017-08-25 23:12:00 | I |
The story of Hurricane Harvey will always center around the significant flooding that took place as the hurricane weakened and stalled in southeast Texas. Harvey dropped record rainfall amounts across broad areas of southeast Texas turning highways into rivers and neighborhoods into lakes.
Though the news focus of the flooding was centered in the Houston area (Harris County), the largest rainfall amounts were recorded in Chambers, Brazoria, Liberty and Jefferson counties.
| Location | County | Station | Rain | Lat | Lon |
|---|---|---|---|---|---|
| FRIENDSWOOD | GALVESTON | 56.00 | 29.50 | -95.20 | |
| 3 ENE SANTA FE | GALVESTON | 54.77 | 29.39 | -95.05 | |
| 2 W FRIENDSWOOD | GALVESTON | 54.00 | 29.51 | -95.22 | |
| 3 S LEAGUE CITY | GALVESTON | 52.87 | 29.43 | -95.11 | |
| 2 NW WEBSTER | HARRIS | 52.30 | 29.55 | -95.14 |
The text reports contain a Section D for Inland Flooding. Unfortunately at this time only the San Antonion/Austin NWS office have provided more info; generally river flooding and low water crossings.
There are 24 tornado observations for Hurricane Harvey. However, some observations may be for the same tornado. For example, there are two observations for a tornado in Fort Bend county with the same Lat
, Lat
and Date
value; only Details
is different.
Table 5 shows all tornado observations during the event from each of the NWS offices. Table Six identifies wind range values for Scale
.
| Location | CountY | Day | Time | Scale | Lat | Lon | Date | Details |
|---|---|---|---|---|---|---|---|---|
| 4 NNE SEADRIFT | CALHOUN | 25 | 2114 | EF0 | 28.43 | -96.67 | 2017-08-25 21:14:00 | FACEBOOK PHOTOS AND VIDEO SHOWED A BRIEF TORNADO TOUCHED DOWN ON GATES ROAD NEAR SEADRIFT. A SHED AND CARPORT WERE DESTROYED AND A FEW TREES WERE BLOWN DOWN. RATED EF0. |
| 9 NE GALVESTON | GALVESTON | 25 | 1923 | EF0 | 29.22 | -94.89 | 2017-08-25 19:23:00 | PUBLIC REPORTS A FUNNEL CLOUD AND A METAL FENCE DAMAGED NEAR FERRY RD IN GALVESTON |
| 2 W LIVERPOOL | BRAZORIA | 26 | 0428 | EF0 | 29.29 | -95.31 | 2017-08-26 04:28:00 | AN EF-0 TORNADO TOOK DOWN 4 POWER POLES ON HIGHWAY 35 ALONG WITH SEVERAL TREES NEAR THE GULF COAST SPEEDWAY. THE TORNADO THEN TRAVELED ACROSS GENERALLY OPEN FIELD BEFORE DAMAGING SOME BARNS AND OUTBUILDINGS AS WELL AS TREES ON COUNTY ROAD 511. |
| Scale | WindMPH | WindKTS |
|---|---|---|
| EF0 | 65-85 | 55-74 |
| EF1 | 86-110 | 75-96 |
| EF2 | 111-135 | 97-117 |
| EF3 | 136-165 | 118-143 |
| EF4 | 166-200 | 144-174 |
| EF5 | >200 | >175 |
| Version | Message | Date | Author |
|---|---|---|---|
| 4d41af3 | Rebuild website, Sun Jun 30 18:16:38 UTC 2019 [skip ci] | 2019-06-30 | Travis CI |
| 38a6edc | Rebuild website, Sun Jun 30 17:36:16 UTC 2019 [skip ci] | 2019-06-30 | Travis CI |
| 01fc4ae | Add children | 2019-06-30 | Tim Trice |
| 03a2e1e | Update Rmd yaml front matter | 2019-06-30 | Tim Trice |
| 0613f78 | Relocate analysis files | 2019-06-30 | Tim Trice |
| be170f1 | Add published docs | 2019-03-01 | Tim Trice |
setting value
version R version 3.6.0 (2017-01-27)
os Ubuntu 14.04.5 LTS
system x86_64, linux-gnu
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz UTC
date 2019-06-30
| Package | Version | Date | Source |
|---|---|---|---|
| dplyr | 0.8.2 | 2019-06-29 | CRAN (R 3.6.0) |
| forcats | 0.4.0 | 2019-02-17 | CRAN (R 3.6.0) |
| ggplot2 | 3.2.0 | 2019-06-16 | CRAN (R 3.6.0) |
| ggrepel | 0.8.1 | 2019-05-07 | CRAN (R 3.6.0) |
| glue | 1.3.1 | 2019-03-12 | CRAN (R 3.6.0) |
| knitr | 1.23 | 2019-05-18 | CRAN (R 3.6.0) |
| lubridate | 1.7.4 | 2018-04-11 | CRAN (R 3.6.0) |
| purrr | 0.3.2 | 2019-03-15 | CRAN (R 3.6.0) |
| readr | 1.3.1 | 2018-12-21 | CRAN (R 3.6.0) |
| rrricanes | 0.2.0-6 | 2019-06-30 | Github (ropensci/rrricanes@d631a32) |
| rrricanesdata | 0.2.0 | 2019-06-30 | Github (ropensci/rrricanesdata@83625e9) |
| stringr | 1.4.0 | 2019-02-10 | CRAN (R 3.6.0) |
| tibble | 2.1.3 | 2019-06-06 | CRAN (R 3.6.0) |
| tidyr | 0.8.3 | 2019-03-01 | CRAN (R 3.6.0) |
| tidyverse | 1.2.1 | 2017-11-14 | CRAN (R 3.6.0) |


6
6
4
8
3
6
3
10
2
Create a responsive table with alternating cell background color:
#
Name
Street
1
Anna Awesome
Broome Street
2
Debbie Dallas
Houston Street
3
John Doe
Madison Street


The GO DAG file format is used by gomo_highlight
and gomo
.
It is a quick parsing file, containing the structure and IDs from the Gene Ontology and can be
automatically generated from the
Gene Ontology's OBO format.
A GO DAG file is packaged with the gomo databases available on the MEME Suite website.
The file structure can be divided into 3 major parts.
The purpose of the header comments is to document the details of the OBO file that was used to generate it. Each line starts with a # symbol and the rest of the line can contain any content.
The purpose of the directed acyclic graph portion is to store the hierarchical structure of the Gene Ontology in a way that is quick to load into memory while still being compact in file size. The first line is the number of nodes in the DAG. Following that lines are in groups of 5 defining different attributes of the node. The group is on its own in the first line. The name is on the second line with the length coming first so memory can be preallocated for it. The node's position in the DAG is summarized in the third line with the total number of nodes above followed by the total number or nodes below. The fourth and fifth lines define the edges from the node to its parents and edges from the node to its children. Each line of edges starts with the edge count for that line which can be zero. Each edge is a number in the range zero to the node count minus 1 and is the index of the linked node. Values on the same line are tab separated. The order that the nodes are listed does not have any meaning other than providing a position to for the other nodes to link to.
The purpose of the graph labels is to allow lookup of a graph node. Each line in the graph labels section has a symbol indicating if the label is the primary (>) or alternate (+) label, followed by a tab, followed by the label, followed by a tab, followed by the position of the associated node (index plus 1) or zero if the label is obsolete. The labels are ordered alphabetically.
Suppose there were the nodes A, B, C, D with the alternate names G,E,H,F and an obsolete name Z all from the grouping 'example' which I will shorten to x.
| Node Name | Alternate Names | Parent Nodes | Child Nodes | Group | Nodes Above | Nodes Below |
|---|---|---|---|---|---|---|
| A | G | B, D | x | 0 | 3 | |
| B | E | A | C | x | 1 | 1 |
| C | H | B | x | 2 | 0 | |
| D | F | A | x | 1 | 0 |
So one possible output for this example would be as follows. Note that this example simulates tabs as tabs don't display properly in html.
If for some reason you can't source the GO DAG file from the MEME Suite website, then the tool obo2dag is provided in the scripts directory for the purpose of creating GO DAG files. It is an executable jar file with source packaged in the jar. As the OBO file format is still under active development we made use of a parser included with the OBO-Edit program which means our program is dependent on libraries from OBO-Edit. As this program is not likely to be needed by an end user we have not sought permission to include OBO-Edit's parser and so you will have to source the libraries yourself.
The tool obo2dag is dependent on the OBO-Edit classes:
org.obo.dataadapter.OBOParseEngine
org.obo.dataadapter.OBOParseException
org.obo.dataadapter.OBOParser
org.obo.dataadapter.ParseEngine
org.obo.datamodel.NestedValue
These classes have their own dependencies and it was discovered through a process of trial and error that the libraries needed from the OBO-Edit distribution are:
The current distributions of OBO-Edit seem to only include automated installers (no tar version) and so I recommend downloading the RPM version and using a program like 7-zip to extract the files you need. I found that the jar files were in the rpm at the location "/./opt/OBO-Edit2/runtime/". Once you have the jar files simply run obo2dag in the same folder.
As stated previously, obo2dag is an executable jar file and so if your system is setup correctly you can
run it like you would a program and it will bring up the graphical user interface. To run the GUI from the
command line type:
java -jar obo2dag.jar
If you need to run obo2dag in non-GUI mode then you must specify the class gomo.HierarchyParser
and pass it the path to the obo file and the path to the output GO DAG file. The command is:
java -cp obo2dag.jar gomo.DAGParser <GO OBO File> <Output File>


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Activity
{% if awaiting %}
Games awaiting your confirmation
{% for game in awaiting %}
{{ game }}
{% endfor %}
{% endif %}
{% if reported %}
Games awaiting opponent confirmation
{% for game in reported %}
{{ game }}
{% endfor %}
{% endif %}
{% if disputed %}
Games in disputed state
{% for game in disputed %}
{{ game }}
{% endfor %}
{% endif %}


Your browser doesn't support the HTML5 canvas element.
X
To load an image, type in a URL:
Right-click image to save


Item.
On the left edge of the machine, from back to front:
-
Micro USB power port
The BrailleNote Touch comes with a 6-foot micro USB cable and a wall charger. Plug the larger end of the USB cable into the wall charger and the small end of the cable into the power jack with the points facing down.
-
Concave-shaped Power/lock button
To start the BrailleNote Touch, hold down the Power button for about two seconds. You will see a Starting message in Braille, then a dot moving in a circular motion.
When the machine boots up, press space+U to unlock the screen.
You can lock or unlock the screen of the BrailleNote Touch by tapping the Power/lock button.
-
Volume Up and Volume down keys.
The volume controls offer a quick way to increase or decrease the volume.
They do the same thing as Enter+dot4 to increase volume, and Enter+dot1 to decrease volume.


It is more performant to access the class object directly by name.
Example:
Class<?> c = new Sample().getClass();
After the quick-fix is applied:
Class<?> c = Sample.class;


All Classes
App
Course
EnrolledSubject
IncompleteCourseException
InvalidArgumentException
NotFoundException
NullObjectException
School
Student
Subject
Vec3f


AirportRunway Contract Members
Namespace: SolutionNorSolutionPort.BusinessLogicLayer
Service name: CrudeAirportRunwayService
Contract name: CrudeAirportRunwayContract
Fetcher: FetchByAirportRunwayId
Id: AirportRunwayId, System.Guid
Create Read Update Delete (CRUD) members, operators for database table
Airport Runway Id
System.Guid
Airport Id
System.Guid
Direction
System.String
Dimensions
System.String
Surface
System.String
Instrument Landing System Type
System.String
User Id
System.Guid
Date Time
System.DateTime
Service Operations
CrudeAirportRunwayContract
FetchByAirportRunwayId
(System.Guid airportRunwayId);
List<CrudeAirportRunwayContract>
FetchByAirportId
(System.Guid airportId);
List<CrudeAirportRunwayContract>
FetchByUserId
(System.Guid userId);
List<CrudeAirportRunwayContract>
FetchWithFilter
(System.Guid airportRunwayId,System.Guid airportId,System.String direction,System.String dimensions,System.String surface,System.String instrumentLandingSystemType,System.Guid userId,System.DateTime dateTime);
List<CrudeAirportRunwayContract>
FetchAll
();
List<CrudeAirportRunwayContract>
FetchAllWithLimit
(System.Int32 limit);
List<CrudeAirportRunwayContract>
FetchAllWithLimitAndOffset
(System.Int32 limit,System.Int32 offset);
System.Int32
FetchAllCount
();
System.Void
Insert
(CrudeAirportRunwayContract contract);
System.Void
Update
(CrudeAirportRunwayContract contract);
System.Void
Delete
(System.Guid airportRunwayId);


{{ organization.name }}
{{ application.name }}
Warning: There is no OAuth Redirect setup for this application. Please enter it in the Settings tab.
Deleting an application cannot be undone. Any existing users of your application will break!. Here be dragons!
Click the button below to generate a new OAuth 2 Access Token.
The generated token will act on behalf of user
{{ user.username }}
|
{{ scopeInfo.description }}
|
- Client ID:
- Client Secret:
- {{ application.client_secret }}


AI Saturdays (affectionately known as AI6) is a
community-driven, non-profit and global movement across the globe
to make Artificial Intelligence education at the quality and rigor
of the world’s best universities accessible to everyone for free.
AI6 is a free-to-attend, structured study groups going through
materials used in universities like Stanford, Berkeley, and UCL,
covering cutting-edge techniques in AI and deep learning. These
study groups are held every Saturday and done in cycles. Each
cycle consists of a 14 weeks structured lesson plan targeted at
people with different skill levels.
AI Saturdays Port
Harcourt is an active learning community in Rivers State, Nigeria.
We organize structured study groups around core Artificial
Intelligence fields like Machine Learning, Computer Vision and
Natural Language Processing through the use of massive open online
courses (MOOCs) and courses from top universities across the
globe.
Contact us at -<EMAIL_ADDRESS>LinkedIn, Twitter - AI6ph
Our mission is to democratize Artificial Intelligence by creating a community to enable AI education, we believe that anyone can learn to code and build with Artificial Intelligence.
Our Goal is to democratize, diversify and demystify Artificial
Intelligence by creating a community where Artificial Intelligence
is accessible, distributed and simplified.
Our core values are Inclusiveness, Excellence, Diversity,
Leadership, Empathy, Collaboration


India’s Space Agency Wants to Explore Venus
by Dan RobitzskiHey Neighbor
The Indian Space Research Organization wants to launch a mission to Venus.
The ultimate goal is to use an orbiter to map the entire planet, as well as to scan and figure out what’s going on beneath the surface, according to Space.com. If the mission takes off, it could help give scientists a much better understanding of our planetary neighbor — including information about how its bizarre atmosphere behaves.
Closer Look
The space agency is currently awaiting the green light for the mission. If all goes to plan, it may launch as soon as 2023, Space.com reports.
Once it arrives, the orbiter would be able to create a map of Venus is just about a year, while also using scientific instruments to study the planet’s atmosphere, volcanic activity, and intense lightning storms.
India’s space program suffered a setback when its Moon lander crashed in September. But because the Venus mission wouldn’t involve actually touching down on the surface, it may have a brighter future.
READ MORE: India Has a New Planetary Target in Mind: Venus [Space.com]
More on Venus: NASA Scientists Imagine Studying Venus From A Floating Research Colony


An interactive map plugin for jQuery.
This is the main map canvas.
Random events are created on the map as example. You can use this feature to show real time events which contain latitude and longitude information.
Also see SonicMetrics as live example.
The size of each dot represents the amount of 'land' at this point on the world.
The 'night'-mode is active. So the part of the world, where everyone sleeps looks a bit darker. This is achieved by rendering the dots a little bit bigger.
Smallimap is currently in an early stage of development.
Follow us on github to stay updated.


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7:00 AM - 8:00 AM
Event title
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Event title that is long and overflows, testing multiline and overflow styles
7:30 AM - 9:00 AM
Hovered Recurring event
8:30 AM - 9:30 AM
Selected event
7:00 AM - 8:00 AM
Custom color event
8:00 AM - 9:00 AM
Drag hint
10:00 AM - 11:00 AM
Inverse Background
8:30 AM - 9:30 AM
Multi-Day event
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logs.xsl.
$Date: 2006/01/27 17:12:41 $
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